Author: a16z Podcast

  • The Olympics of Talent: France’s Tech Boom

    AI transcript
    0:00:06 There is a distinct advantage of building companies in France from dollar perspective.
    0:00:09 I think France is now on the map.
    0:00:14 We see a lot of folks who come from Europe or come from the US and decide to move to Paris
    0:00:20 and contribute to the startups in the same way that this happened with Silicon Valley 15, 20 years ago.
    0:00:25 That was the main feedback that all the entrepreneurs in the ecosystem heard for many years.
    0:00:28 You’re not being ambitious enough, you’re not being ambitious enough.
    0:00:33 The French founders that I’ve met often times the ambition isn’t that.
    0:00:39 Ambition isn’t even the Eurozone. Ambition is we’re going to build the biggest company in the world.
    0:00:43 It was dirty in France to say that a few years ago.
    0:00:47 That’s the one thing we need to crack.
    0:00:53 The Olympics returned to Paris this year, precisely 100 years since the city last hosted the event.
    0:00:59 Hopefully you’ve caught some of the highlights, like how the world’s fastest man was only a fraction of a second faster
    0:01:03 than the athlete who came fourth, just shy of the podium.
    0:01:10 Now, every game is filled with these incredible moments, as host nations use the event to show their strength as a country,
    0:01:15 while over 180 participating nations do the same with their athletic talent.
    0:01:21 But as the games do approach their close, it’s worth reflecting on the fact that in the 98% of the time
    0:01:26 when the Olympics aren’t happening, countries show their strength with their talent in other fields
    0:01:29 and increasingly in technology.
    0:01:33 So in this three-part series, we’ll be exploring those dynamics across three regions.
    0:01:36 France, the UK, and Latin America.
    0:01:39 So what makes these regions distinct?
    0:01:42 And what ingredients yield thriving startup ecosystems?
    0:01:46 Is it funding, risk tolerance, regulation, or lack thereof?
    0:01:51 As people increasingly ask the question of whether Silicon Valley can be recreated elsewhere,
    0:01:53 the answers may just be across the pond.
    0:01:59 There are nuanced conversations around visa programs, successful startup mafias, and local culture.
    0:02:03 In this episode around France, you’ll get to hear from Roxane Barza,
    0:02:07 long-time director of StationF, the world’s largest startup campus.
    0:02:13 Also, Antoine Martin, co-founder and CEO of Zenly, which was acquired by Snap in 2017,
    0:02:15 who is now working on Ammo.
    0:02:21 And Antoine was even referred to by Sifted as the “Godfather of France’s emerging social media” app scene.
    0:02:26 And finally, Brian Kim, a 16Z consumer partner who also happened to lead the round
    0:02:29 under recently acquired French startup BReal.
    0:02:32 Reflecting on the very startup scene that they helped build,
    0:02:36 let’s kick things off with Roxane, then Brian, then Antoine.
    0:02:41 As a reminder, the content here is for informational purposes only.
    0:02:44 Should not be taken as legal, business, tax, or investment advice,
    0:02:47 or be used to evaluate any investment or security,
    0:02:51 and is not directed at any investors or potential investors in any A16Z fund.
    0:02:57 Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast.
    0:03:03 For more details, including a link to our investments, please see a16z.com/disposures.
    0:03:12 My prism is very early stage founder.
    0:03:15 And I’ve seen this evolve quite a bit over the last few years.
    0:03:18 I feel like it’s become a lot more international.
    0:03:20 We’re seeing a lot more people from different geographies
    0:03:23 that now want to come build companies here, join companies here.
    0:03:26 And also, I think with the maturity of the ecosystem,
    0:03:31 we’re starting to see people who have previously been in a startup or a scale-up,
    0:03:33 or even founded companies before now building new companies.
    0:03:37 So these are things that we weren’t seeing as much of a few years ago.
    0:03:39 But I would say also with the AI boom,
    0:03:42 and I think it’s no secret for anyone that the technical talent here,
    0:03:47 especially because the math and data programs that we have here are so exceptional,
    0:03:50 that if you look in, I think any of the leading tech companies worldwide,
    0:03:54 their tech and data teams will usually have a lot of French people in them.
    0:03:57 When I think about the French tech ecosystem,
    0:04:00 typically have this three-pronged answer.
    0:04:05 I would start with the infra level, and I don’t mean infras and like bandwidth speed.
    0:04:08 It’s an infra for the startups, especially early-stage.
    0:04:12 And Roxanne, of course, runs one of the largest startup studios in the world.
    0:04:15 Then I view station F as being a critical piece of infrastructure.
    0:04:18 And there’s, of course, the amazing school like Polytechnique
    0:04:21 that are technical and you even have schools like School 42,
    0:04:27 where the infra is really, really good for creating the next batch of startup founders.
    0:04:32 The second ingredient I would say that France has that I haven’t really seen elsewhere
    0:04:35 is there’s such a strong sense of community,
    0:04:39 even the fact that there’s a group of French consumer founders
    0:04:42 that all know each other, all talk to each other,
    0:04:45 and are very keen on giving back to the community
    0:04:47 after having seen what they’ve gone through.
    0:04:54 Antoine is a perfect example of someone who sort of grew up in the French tech ecosystem
    0:04:56 and then is very determined to give back,
    0:05:00 whether it’s lessons, learning, angel investing, advising.
    0:05:04 And that loop, to me, is quite rare.
    0:05:08 And the last, I would also mention that there’s actually a lot of,
    0:05:10 I don’t want to say governmental support,
    0:05:15 but there is a lot of push for the startup ecosystem to do really well.
    0:05:21 Like there is a distinct advantage of building companies in France from dollar perspective,
    0:05:26 whether it’s like BPI loans or whether it’s actual GPUs.
    0:05:30 So when you combine all three, the infra, the community,
    0:05:32 and the support at a governmental scale,
    0:05:37 I think that makes for a very, very unique country to build companies in.
    0:05:40 Yeah, it is fascinating to see that the country last year published
    0:05:45 a national AI strategy dedicating 500 million euros to AI clusters.
    0:05:46 So we’ll get into that.
    0:05:48 But Antoine, I’d love to hear your perspective,
    0:05:52 especially since it’s been about seven years since your company Xenli was acquired.
    0:05:54 So you’ve been in this ecosystem for a while.
    0:05:57 I’d love to hear how you see it, but also how you’ve seen it change.
    0:06:01 I mean, at high level, I’ve doubled down on what Huxan and BK have said.
    0:06:07 There is this obvious underdog mentality, just because it’s a smaller ecosystem,
    0:06:11 which does create the bonds and the desire for folks to help each other.
    0:06:16 And so we discussed the last decade, if I go even a little further than that,
    0:06:19 Huxan managed an incubator before Station F.
    0:06:24 We had the most poor office you could have at this time.
    0:06:29 And we couldn’t host even 15 people in that consumer group you were talking about, BK.
    0:06:32 We needed a space to see each other at night.
    0:06:36 Huxan would lend us rooms in the incubator she managed back then.
    0:06:42 So the whole underdog/givebacks mentality is one of the things that today is getting dividends.
    0:06:47 We’re also seeing second-time founders, third-time founders for the first time.
    0:06:50 That coming was an ambition level and access to funding,
    0:06:57 and talent was in their initial teams that we couldn’t see 10 years ago when it was the first generation.
    0:07:01 You add the openness that France is coming towards,
    0:07:04 where it feels like a more open country than it was 10, 15 years ago.
    0:07:10 Yes, we had a lot of tourists, but it wasn’t depicted as the place where your quality of life was great
    0:07:12 and you’d be biking around the city.
    0:07:15 That is driving a lot of international talent.
    0:07:19 And we see a lot of folks who come from Europe or come from the U.S.
    0:07:22 and decide to move to Paris and contribute to the startups
    0:07:26 in the same way that this happened with Silicon Valley 15, 20 years ago.
    0:07:33 The top of mind example I have is DJ O’Horst was one of the founding designers, early designers at Flipboard,
    0:07:36 then at Mailbox, then led design at Uber,
    0:07:40 and now he’s helping Kung-Tul who’s on an IPO road track.
    0:07:43 And he moved back to France a couple of years ago
    0:07:47 and that generation of folks is helping us get to the next stage.
    0:07:48 That’s amazing.
    0:07:53 I know Roxane, you also just published the international component of Station F.
    0:07:57 Yeah, for the last seven years, because we just celebrated seven years,
    0:08:00 we’ve always been around one-third of our community international,
    0:08:05 but we found out this year that we have actually 65 nationalities on campus.
    0:08:06 I didn’t believe that.
    0:08:08 I wouldn’t have guessed that.
    0:08:10 And then when you actually look also at some of the nationalities,
    0:08:13 they’re countries that also aren’t the most obvious ones.
    0:08:16 There’s a lot of places that you would just imagine very pro-business
    0:08:18 and maybe they have ties to France,
    0:08:22 but also you have some very small countries that you cannot imagine
    0:08:25 that these people just picked up and came here to build a company.
    0:08:28 So yeah, it’s attracting people from everywhere now.
    0:08:31 And how many companies are now on campus?
    0:08:34 So we always have 1,000 that are based on campus.
    0:08:37 We’re refreshing minimum 700 companies per year.
    0:08:42 And so we’ve actually worked with more than 700 new companies per year,
    0:08:45 which takes us to over 7,000 since the beginning.
    0:08:48 My partners, Olivia and Justine, when they visited,
    0:08:50 the word for Station F in their eyes are,
    0:08:53 “It’s like a Disneyland for startups.”
    0:08:54 I’ve heard that before.
    0:08:56 Or when it works.
    0:08:58 So true, it is Disneyland.
    0:09:01 Sometimes it’s too cushy, maybe for our entrepreneurs.
    0:09:05 We got to give them a kick, but yes, it’s definitely Disneyland for startups.
    0:09:06 What a title.
    0:09:09 And I mean, I think when people think about the world’s largest startup campus,
    0:09:11 they expect that to be in Silicon Valley.
    0:09:13 It’s amazing that it’s in France.
    0:09:16 Roxanne, same question posed to Antoine.
    0:09:19 Seven years, what have you noticed?
    0:09:22 I mean, it’s been a 180 degree shift.
    0:09:24 When we started Station F,
    0:09:27 people didn’t know are there 1,000 companies in France.
    0:09:31 This was very clearly the underdog ecosystem that Antoine mentioned.
    0:09:34 And it’s funny because Brian, you mentioned community.
    0:09:36 I actually forget that.
    0:09:40 I think we’re so used to people here just helping each other and working together
    0:09:43 that we forget that it’s not like that in all the ecosystems.
    0:09:46 But I think what we’ve seen really change in the last few years
    0:09:51 is maybe also the international investors that are paying attention to this ecosystem.
    0:09:54 So we talked about international talent, but seven years ago,
    0:09:56 we didn’t have Andreessen coming out here.
    0:09:58 We didn’t have Sequoia coming out here.
    0:10:03 And I think today it makes up over 50% of the investment that’s going into this ecosystem
    0:10:06 and helping the startup scale on an international level.
    0:10:09 So, I mean, to just put that in short form,
    0:10:13 I think France is now on the map and very high up there.
    0:10:14 Absolutely true.
    0:10:16 Roxanne, that actually reminded me of something where
    0:10:20 one of the things that I love about French startups is
    0:10:24 a lot of times when you look at other geographies or communities or ecosystem,
    0:10:26 they’re building for their own ecosystem.
    0:10:30 They’re like, “Oh, I’m going to build this biggest company in Germany,
    0:10:32 your biggest company in Korea.”
    0:10:34 But the French founders that I’ve met,
    0:10:37 oftentimes the ambition isn’t that.
    0:10:39 Ambition isn’t even the Eurozone.
    0:10:43 Ambition is we’re going to build the biggest company in the world.
    0:10:46 And of course, US is one of the largest market.
    0:10:49 We’re going to go after it with zeal and thoughtfulness
    0:10:51 and design that actually works for those markets.
    0:10:54 And I think that attitude, confidence,
    0:10:57 and approach is actually fairly rare.
    0:11:01 Any thoughts on what makes that unique when it comes to France?
    0:11:03 High level, I think it’s new to be honest,
    0:11:05 because it wasn’t the case 10 years ago,
    0:11:09 and I’ve heard her say this many times to consumer founders
    0:11:11 or other founders we know in common.
    0:11:13 “Hey guys, France is great, but it’s 65 million people.
    0:11:16 You’re not going to make an extremely successful business
    0:11:18 if you focus on that.”
    0:11:20 And clearly today it’s not a topic anymore.
    0:11:21 It’s actually the opposite.
    0:11:23 There was a founder yesterday at 42,
    0:11:26 which is one of the earliest coding schools,
    0:11:31 asking me if he should focus on the US first or France first,
    0:11:34 because he was naturally going towards the US.
    0:11:37 And I was like, “Yeah, of course you need to succeed in the US,
    0:11:40 but maybe you need TMFs with 50 folks locally
    0:11:43 just to mature your product and test it.”
    0:11:47 And he was so so grown on the idea that US is the only way to succeed,
    0:11:50 that he was also forgetting that it also has to work locally.
    0:11:53 But that’s a change that wasn’t like this 10 years ago for sure.
    0:11:54 Totally agree with that.
    0:11:56 And I think it was very intentional.
    0:11:58 I mean, that was the main feedback
    0:12:01 that all the entrepreneurs in the ecosystem heard for many years.
    0:12:03 You’re not being ambitious enough.
    0:12:04 You’re not being ambitious enough.
    0:12:06 So I don’t know when the change happened.
    0:12:08 It was maybe like two or three years ago.
    0:12:10 It just really accelerated,
    0:12:13 and literally I have not heard that in several years.
    0:12:15 The messaging worked, and I mean,
    0:12:19 two industries that are inherently international,
    0:12:21 at least these days, AI and consumer, right?
    0:12:25 You often don’t think of like a country-based AI model
    0:12:27 or in some cases, consumer applications,
    0:12:30 but still the big ones obviously are international.
    0:12:31 So let’s talk about those
    0:12:34 because France has become a leader in some ways in both.
    0:12:38 And so starting with AI, we’re seeing companies like Mistral leading the charge.
    0:12:41 What do you think is yielding that kind of representation?
    0:12:44 This will be maybe a surface level observation,
    0:12:47 but I go back into what is AI?
    0:12:51 Ultimately, it’s numbers, it’s math.
    0:12:54 And I think there’s a little bit of difference between AI and consumer
    0:13:01 in that regard where consumer can be about culture, taste, UX, and design, aesthetics.
    0:13:04 AI is a little bit more around the technical prowess.
    0:13:08 You actually understand the math underlying it.
    0:13:11 And if you think back historically,
    0:13:16 I think France has been extremely strong at producing elite mathematicians.
    0:13:23 And the schools like Polytechnique are focused also on deepening that technical prowess
    0:13:27 and the sort of a arrival of LLM and chat GPT, et cetera,
    0:13:30 just coincides really with a talent and interest,
    0:13:33 which I think is not really a surprise to me
    0:13:36 that one of the biggest fair office was in Paris, right?
    0:13:38 And that the Mistral folks came out of that.
    0:13:40 In Yann LeCun, of course, as well.
    0:13:43 And then two, again, like we’re talking about last seven years,
    0:13:49 but the infra, the idea, the direction towards globally expanding,
    0:13:52 it’s all been set as a foundational piece.
    0:13:55 And then now you have this wave that’s happening.
    0:13:59 I think the underlying for AI is mass and numbers,
    0:14:01 where we do have strong technical talent.
    0:14:05 The underlying for consumer today might be taste.
    0:14:07 And if you look at the city we live in,
    0:14:13 it’s the epicenter of fashion, art, a lot of great brands.
    0:14:16 This is what we’re inspired by on a daily basis.
    0:14:21 I come out of this office and there is fashionistas in the street doing exhibitions.
    0:14:27 There’s an exhibition within 42’s on campus where there’s banksies on the wall.
    0:14:31 So we are emerged in that culture that I think needs to consumer,
    0:14:33 provokes great divine talent.
    0:14:35 You add awesome engineering to that.
    0:14:38 And the equation, it becomes really strong.
    0:14:41 And in the last five years, we’ve added funding,
    0:14:44 which was the one thing that was back in the day’s midst thing.
    0:14:49 In my own case, one of the reasons why it made sense back then to join SNAP,
    0:14:52 because if you wanted to do an IPO in an architecture,
    0:14:54 you would have to raise a billion, a billion and a half.
    0:14:57 The SNAP interest and others had done prior to us.
    0:15:00 And that seemed impossible with very few gross funds locally
    0:15:03 and with the level of ambition to enable that.
    0:15:05 This has changed. Thanks for having us on this podcast.
    0:15:07 This is the perfect example of that.
    0:15:09 I so agree with the culture piece.
    0:15:11 I think I told a couple of people,
    0:15:13 “What’s different for French consumer founders?”
    0:15:18 And my theory was, “Look, how many countries in the world export culture?”
    0:15:21 And if you think of consumer product as a cultural force,
    0:15:22 then honestly, think about it.
    0:15:25 How many companies can actually even export culture
    0:15:29 and is not a net importer of US Hollywood or French fashion?
    0:15:32 I think we are left with very few countries.
    0:15:34 And again, I do think you need the funding.
    0:15:36 I think you need the technical talent.
    0:15:40 But from that standpoint, there just aren’t that many countries in the world
    0:15:42 that can export culture.
    0:15:44 This is also the shift.
    0:15:46 Antoine, I’m sure when you guys were watching Zen,
    0:15:48 nobody was talking about consumer in France.
    0:15:50 You guys were the only ones.
    0:15:52 So what’s changed?
    0:15:54 Why are we good at consumer now?
    0:15:59 I think we’ve had the luck of seeing a few successful companies paving the way.
    0:16:02 And Zen is probably one of them.
    0:16:07 We’ve had MWM, Voodoo, we’re both massive publishers.
    0:16:10 Mindy was the origin of TikTok.
    0:16:13 The design was invented locally by art students.
    0:16:18 And so these companies have shown that it’s possible and have succeeded.
    0:16:21 No one yet was an ITO, so no home run.
    0:16:24 But some of us have gone to like first base, second base.
    0:16:28 And so there is everyone wanting to compete and go further than this,
    0:16:34 which leads to today where it seems possible to, by generation, the generation after.
    0:16:38 And so there’s more and more new, cool consumer products coming out.
    0:16:40 We’re talking about 10-10 a lot these days.
    0:16:45 And there’s more coming in the same direction with former team members from all of these companies.
    0:16:48 Excel, who leads back end, is a former Zen IT team members.
    0:16:52 And that enables the scale that was harder for Zen Lee back in the day.
    0:16:56 And we’re also seeing a little bit of mafia-ness, right?
    0:16:59 Only mafia, stupeflex mafia or photo room.
    0:17:00 Definitely.
    0:17:05 And so it’s just very interesting to see the concept of mafia.
    0:17:07 There are places where that doesn’t exist.
    0:17:10 In Korea, where I’m very familiar with, there’s no concept of mafia.
    0:17:12 There will be. One day.
    0:17:13 One day.
    0:17:18 Like a prerequisite for a lot of the founders wanting to build the next thing.
    0:17:20 Korea has produced great ones too.
    0:17:21 This is true.
    0:17:23 K.O.Talk, Naver, there’s a few good examples.
    0:17:24 Absolutely.
    0:17:30 Are you guys seeing people from those mafias go on and create consumer applications once more?
    0:17:35 Or if we’re seeing more integration, more of the crossover as founders go for round two?
    0:17:40 So we have a little over 50% of our founders that are repeat founders at StationF.
    0:17:43 It’s grown considerably in the last few years.
    0:17:50 And what I’ve noticed is second-time founders, they either go for something related to their first domain
    0:17:53 because they have better insights and experience and the connections.
    0:17:57 But I’m also seeing a lot of people really going more for impact.
    0:18:01 There’ll be a lot of people that will say, “My first company, we built this. It was great.”
    0:18:03 But now is my chance to really make a mark.
    0:18:09 And so there’s a lot more of these kind of experience profiles going for climate-related projects,
    0:18:12 health-related projects, education-related projects.
    0:18:14 Hey, it’s Steph.
    0:18:19 You might know that before my time at A16Z, I used to work at a company called The Hustle.
    0:18:23 And then we were acquired by HubSpot, where I helped build their podcast network.
    0:18:30 And while I’m not there anymore, I’m still a big fan of HubSpot podcasts, especially My First Million.
    0:18:34 In fact, I’ve listened to pretty much all 600 of their episodes.
    0:18:38 My First Million is perfect for those of you who are always trying to stay ahead of the curve
    0:18:43 or, in some cases, take matters into your own hands by building the future yourself.
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    0:19:19 [music]
    0:19:21 You know, people are quick to label, right?
    0:19:25 People think of Boston for healthcare, they think of New York for finance,
    0:19:29 but obviously every city, every country has a medley of things,
    0:19:33 and perhaps there are things that are more underground that folks who live there know,
    0:19:38 “Oh, actually, we’re not just good at consumer, we’re not just good at AI, we’re good at many other things.”
    0:19:42 Curious, if you’re seeing other things where France actually has a lot of strength,
    0:19:44 but other people may not know that quite yet.
    0:19:49 I don’t think station F represents the entire French ecosystem particularly well
    0:19:52 because we’re obviously attracting people based on the infrastructure we have,
    0:19:57 so we don’t have a ton of bio, but I think health is a space where France really shines
    0:20:02 and we’re seeing a lot of, even with regards to AI, a lot of really interesting things in the health space.
    0:20:06 Obviously, AI, we’re seeing just all sectors, all fields,
    0:20:09 B2B historically has been a very strong suit for France,
    0:20:11 so a ton of really interesting B2B applications.
    0:20:17 We also have decided that we want to double down on two sectors where we feel France is well positioned to lead,
    0:20:22 but I would say quantum computing, we have some excellent Nobel Prizes in France.
    0:20:26 I think this is an ecosystem, if you want to talk about community like that,
    0:20:28 it’s a really tight-knit community.
    0:20:31 You can count the quantum companies probably on both hands,
    0:20:33 but they all know each other, they all work together,
    0:20:37 so we have a quantum program on campus, probably the only one in Europe.
    0:20:43 Climate, because I feel like the regulation in Europe is very well positioned to accelerate these businesses,
    0:20:46 and we’re seeing a lot of really interesting climate-related innovations,
    0:20:52 female health solutions, things that are in the femtech space, more stuff in that area here.
    0:20:58 Plus one on that one, I think I would add, when you look at the panorama of scale labs and companies
    0:21:05 that really have a go at world domination at some point, with founders and teams that are ambitious enough to do that.
    0:21:11 In fintech, we have a squad of repeat founders that are so driven,
    0:21:16 have made significant exits the first time and started looking to do massive ones the second time
    0:21:18 or never actually exit.
    0:21:25 I think of Yvan first, I think of Memo Bank, I think of Kato, in the adjacent insurance space,
    0:21:29 I am an eternal believer in Jean-Charles and Charles from Allen,
    0:21:33 who I think have a go at one of the biggest companies in the world.
    0:21:39 They’re resaving insurance through AI, and this whole group is repeat founders who have succeeded once,
    0:21:45 are going at existing industries and are executing super well.
    0:21:48 Antoine, you mentioned Jean-Charles, and that actually reminded me of something.
    0:21:53 One thing that I always have a question on in regards to founders in France is,
    0:21:59 the balance between commerciality, i.e., I want to make money.
    0:22:02 I want to go public, I want to build this giant thing.
    0:22:07 Versus, oh, I want to have a great impact on the world, which is obviously noble and amazing
    0:22:11 and is a mission for a lot of folks, I want to build something beautiful.
    0:22:15 I want to build something that gives me joy and satisfaction when people use it.
    0:22:26 Those two are not necessarily at odds, of course, but I tend to see a little more folks focusing on impact, beauty,
    0:22:33 the satisfaction, the internal, oh, wow, I built something beautiful, versus less-going money.
    0:22:39 I do think there are few folks, and when you say Jean-Charles, that’s like, oh, he’s in that camp.
    0:22:42 What would you say to that?
    0:22:48 I mean, he’s also in the health camp, and the following story behind Alan is also his first, like,
    0:22:55 solving health in a country where a lot of its deficits and structural balance goes into solving health.
    0:23:00 If he takes, he can partially solve that, so it’s both noble and, yeah, definitely.
    0:23:02 He wants to build a massive business.
    0:23:06 He finishes his investor reports saying he wants to build the biggest company in the world,
    0:23:11 and he has the ambition and the courage to actually stay that, and he’s executing in that direction.
    0:23:18 So I think this is also something that changed where it was dirty in France to say that a few years ago.
    0:23:20 It still is in parts.
    0:23:28 I was very well-perceived by everyone until then he exited, and then suddenly I was a bad guy because we had made money.
    0:23:34 I think that’s changing, and there’s more respect for the way that can also be utilized for public good.
    0:23:41 And when you look at all of these stories, the tie-in between every single story which is discussed,
    0:23:50 whether it’s station F, 42, AI in France, then the capacity to be funded at the stage when no one else wanted to give money,
    0:23:55 is one entrepreneur, one founder, pushing in all directions.
    0:24:01 He was an elephant in the room that I was going to at some point talk about, so I’m glad you brought that.
    0:24:05 But I do think Antoine said something that’s definitely not to be ignored.
    0:24:10 There’s a cultural element to talking about money in France that’s not the same as in the US,
    0:24:18 and I think within the ecosystem it’s much more accepted to talk about raising money, going after money, making money.
    0:24:22 I don’t think within the entrepreneurial community it’s particularly taboo,
    0:24:27 but I think outside of this community, the general public, that is very much the case,
    0:24:34 which means that when people are talking about their businesses, openly they’re not going to be saying that as much.
    0:24:40 And that permeates who people’s role models are, what fields they go into, whether they’re willing to start businesses.
    0:24:47 But another key driver, in addition to talent, is of course the government strategy and what messages they’re sending as well.
    0:24:53 So maybe we can pivot to that. I mentioned a little bit earlier the country last year published a national AI strategy,
    0:25:01 but you also have private businesses, you have Microsoft, for example, announcing an additional $4 billion for data centers and other AI investment in France.
    0:25:10 But then you also have, for example, the EU reaching a deal on AI regulation that some people are debating may actually stifle that innovation.
    0:25:15 So I’d love to hear this group’s perspective on how regulation is playing a role here.
    0:25:22 As an outsider, I view recent policy towards the tech ecosystem as being very encouraging.
    0:25:24 They’re seeing the impact that these businesses can have.
    0:25:31 They’re seeing the impact that having these businesses on your shore and representing the country to some extent,
    0:25:38 what they can do to the national image of talent coming back to your country and building things and creating value within your borders,
    0:25:46 where we’re seeing it from the top. It’s almost as if somebody listened to like, “Oh, it’s time to build in the trans edition.”
    0:25:50 And so I get pretty excited about that and I’ve seen the concrete benefit.
    0:25:59 Like I mentioned the BPI loans, I do know that changes the calculus for initial funding for a lot of startup founders
    0:26:07 because it’s a non-diluted funding and it enables them to think through the initial inflow of funds a little differently from other ecosystems.
    0:26:16 I think that’s interesting. I also know that there’s a real concrete economic benefit for AI companies to relocate or build in France.
    0:26:18 You know, all these things are so connected.
    0:26:24 But on the launch of Station F, we had Solz and he enjoy snap a couple of months prior.
    0:26:32 And Roxane invites me to the private tour before the day of the launch with the president, which I met for the first time that day.
    0:26:38 We tell him doesn’t any story. He learns the word divots, which he uses in a speech an hour later.
    0:26:45 Along the way, one of his cabinet members who led Digital Strategy for France for maybe five years afterwards
    0:26:51 comes to me and says, “Hey, I worked with the president. I’d love to understand where we can do better.”
    0:26:54 We’ve been very lucky. We’ve had political momentum.
    0:26:58 We need to transform that into economic momentum and we need to deliver.
    0:27:04 These are his exact words that day. And he invited me over and a few other entrepreneurs to give feedback.
    0:27:08 And they did that continuously over the last seven, eight years.
    0:27:17 A lot of that led to reforms, led to encouragement, led to fixing a few things that made it harder to be an entrepreneur in France and elsewhere.
    0:27:27 Today, as a French founder, I don’t see a reason to build a company and a team elsewhere unless 100% of your market is in another location.
    0:27:37 But even then, the access to talent you have locally, the local encouragement, the support makes it a fairly easy equation to actually stay in France and build from here.
    0:27:45 I can’t help but agree with everything that’s been said, but I do think we have to make a distinction because we talked about also AI policy on a European level.
    0:27:51 So I think when you look at the French government specifically, I can pretty much only say positive things about what’s happened.
    0:27:55 And some of the groundwork was laid pre-Maconne, but I think he really came in.
    0:28:00 I mean, this story from what Antoine said, I remember that speech that he gave, and we’re like, oh my God, pivot.
    0:28:06 He heard that 10 minutes ago. But yeah, I think the thing is he really understood, he really connected, he grasped it.
    0:28:10 But he also pushed the government to be close to the entrepreneurs.
    0:28:18 I mean, we have at station F 30 government services, but I actually, my team shares a floor with 20, 30 people from the government.
    0:28:23 So anything that we need, someone’s visa is blocked, we’re having issues with public funding.
    0:28:26 They’re going to announce some kind of new thing for data protection.
    0:28:30 We can just go right next door and just ask these questions and get it solved.
    0:28:34 So I think that’s just something we never would have imagined prior.
    0:28:41 And I also think that with regards to the negotiations around AI Act, I mean, yes, I think it could have been better.
    0:28:48 And I’m hearing a lot of comments from AI founders today that are saying Europe is going to be behind because of what can be released here.
    0:28:53 But the fact of the matter is that when you look at what, well, France was playing in those negotiations.
    0:28:58 A lot of people are saying France was coming across as way more pro business than everyone else.
    0:29:00 So I think that’s also not something to be ignored.
    0:29:02 Maybe we could get into the specifics.
    0:29:13 I mean, I love that both of you mentioned that France seems to be a place that’s more profounder than just for the uninitiated who aren’t as familiar with what it’s like to be a founder there.
    0:29:23 How would you characterize, whether it’s the regulation or the community, what is actually different about being a founder in France, let’s say, compared to America?
    0:29:30 I see people coming over from all different countries, but actually the country that’s the best represented at station F after France is the U.S.
    0:29:32 And it’s been the U.S. from day one.
    0:29:34 We get a lot of Americans that come here.
    0:29:42 And I think in the past, maybe like 10 years ago, the conversations were around the cliches around hiring and firing.
    0:29:44 I don’t hear that at all anymore.
    0:29:46 That’s not a topic people are concerned about.
    0:29:53 Actually, people are pleasantly surprised by Brian, you mentioned it, the public funding, the grants you can get.
    0:29:57 In some cases, people qualify for unemployment, very generous unemployment.
    0:30:04 I mean, there’s money here and there’s public money here that is probably way, way more generous than what you have in the U.S.
    0:30:08 So I think that’s the first thing that a lot of people are talking about.
    0:30:12 And then obviously a lot of people who are coming from different countries are going through the visa scheme.
    0:30:21 The government did a massive overhaul of the visas, and I think it’s probably hands down the best entrepreneur or tech talent visa that exists in Europe.
    0:30:28 Plus one, I mean, if you look at AMOs, my current company, the majority of our hires come from abroad.
    0:30:37 It’s often faster to get them a visa and make them move in than notice periods in certain countries.
    0:30:41 The first nationality represented in terms of international hires is the U.S.
    0:30:49 We have, I don’t know, 9, 10 Americans in the team up to a point where I’m questioning the idea of making the C2 American and if we want to stay international.
    0:30:50 This is the reality.
    0:30:52 This was enabled through the French tech visa.
    0:30:56 There’s also a lot of things that were done around capital gain taxes.
    0:31:05 They were done very early on and barely changed since, which was also one of the asks from the entrepreneurs to stop changing these systems every year.
    0:31:08 They’ve been good at not doing that too often.
    0:31:11 They’ve improved the way we grant stock options.
    0:31:13 And this was one of the liabilities.
    0:31:17 It was harder here to do so to apply for market value and things like that.
    0:31:20 And it seems like it’s been changed and it’s now very competitive.
    0:31:27 So I have a few investments in Germany and in other countries where DocuSign is barely recognized.
    0:31:30 You need a notary to actually find a fundraise.
    0:31:35 It’s crazy how complex it is versus what it is today in France.
    0:31:36 That’s amazing.
    0:31:38 What I’m hearing is clarity as well.
    0:31:45 Obviously, it sounds like over the last decade a lot has changed for the positive, but I’d love to hear your take on where we go from here.
    0:31:51 What would you love to see, whether it’s from the government or from the startup ecosystem, as we look to, let’s say, the next decade?
    0:31:54 Imagine what we’re recording this in 2034.
    0:31:58 I would love to see a couple of 10 billion plus dollar IPOs.
    0:32:00 Thank you, plus one.
    0:32:12 I was going to say the same thing, and then probably some M&A on top, which, by the way, we had the very first local significant M&A in France ever within tech companies.
    0:32:16 You all know DRL, Anderson Horvitz was through BK and Investor.
    0:32:30 It was awesome for me as the early helper of that team and investor to see them sell to another local company that has a goal at that $10 billion IPO in the next two years.
    0:32:31 That’s very new.
    0:32:34 That opens up another market for VCEs.
    0:32:37 It qualifies the early stage space.
    0:32:39 It enables more business essentials.
    0:32:47 It enables teams who have made money through exit and are therefore telling us there is that stock options have value associated.
    0:32:49 That’s one of the things I’d love to see.
    0:32:51 It will come with the IPOs.
    0:32:52 100%.
    0:32:54 I think the only thing that I could think of is exits.
    0:32:56 That’s the one thing we need to crack.
    0:32:58 The government is very conscious of this.
    0:33:04 So what I think is really great is they’re often on the ground asking people what needs to change, what needs to happen, where can we act?
    0:33:06 They’ve been doing that also since COVID.
    0:33:16 And when the funding cycles started changing, 2022, 2023, on the ground again, especially close to people in the finance world.
    0:33:20 And the one topic that is always talked about is exits.
    0:33:23 So hopefully we’ll see some movement there.
    0:33:26 I wrote that when Steph asked the question.
    0:33:28 I literally exited and I circled it.
    0:33:37 And to your point of the government really asking for feedback, Macron is till this day the only head of states I ever met.
    0:33:39 And he asked the question, what can we do better?
    0:33:42 Like, why do you think this is an interesting market for you?
    0:33:48 And at the beginning of our podcast, talked about like the infra, the community and the policy, like I said, like exactly those three things.
    0:33:50 And he took notes.
    0:33:52 I’m like, what?
    0:33:56 I’m like an investor and you’re like taking notes.
    0:33:59 So that’s when I also sort of the third point, the policy.
    0:34:05 I’m like, oh, there’s actually a system here that thinks of the tech ecosystem as being priority.
    0:34:07 Totally. And Brian, I’d love to hear your just quick take.
    0:34:14 I mean, I know there’s probably limitations in what you can say, but just with the B Real acquisition, like what was that like to see that French company?
    0:34:16 You obviously invested on our side.
    0:34:17 Was that surprising at all?
    0:34:20 Or how does it feel to see that M&A get off the ground?
    0:34:21 It’s interesting.
    0:34:30 When you think about the exit ecosystem, we talked about the commerciality and what have you, like Voodoo is led by someone who I think is also very commercial.
    0:34:37 And he also was a fairly early investor in B Real himself through the angel sort of system.
    0:34:40 And I think he posted almost every day as well.
    0:34:43 I was friends with him on B Real, so I would see him post every day.
    0:34:59 And I think it’s very interesting when founders who understand the power of the product, the origin story, the design, eat those, the people behind the product intimately well to have that confidence, right?
    0:35:12 Like someone from far, far away may not be able to make the same decision because there’s so much wealth of knowledge and intimate relationship and understanding about what the product is.
    0:35:16 What the potential is to combine the forces together.
    0:35:19 So I think there is really something to be said about.
    0:35:33 I think this also is a power of the community where had it not been the group, the closeness and the intimacy within the community and the knows that all crisscross across like all the people.
    0:35:42 I think that would have been a different outcome, right? So like I think that’s an interesting case study of how the ecosystem actually can produce real exits.
    0:35:52 It is changing the ecosystem for sure because it’s also enabling visibility for these companies at a level that was not possible for a French company prior to now.
    0:36:02 One of the successes for Mistral is the quality of the model, the quality of their team, of course, but also the way they’re evangelizing it and how this whole community, it’s a million developers has been using it.
    0:36:13 This is only possible because French entrepreneurs now speak English and their teams are connected to the US and have all these French engineers living in Silicon Valley and evangelizing, etc.
    0:36:21 You do the same Mistral 10 years ago. I don’t think it could have had the reach it has today because of the maturity of the ecosystem.
    0:36:30 You’re right. This is the first time people are putting the world leader OpenAI and a French company back to back, which we haven’t had before.
    0:36:38 And also, what’s really funny is Mistral, we didn’t talk about this researcher movement before we didn’t see people leaving research to build companies.
    0:36:49 And we saw it with Mistral and then we saw it with H company and I think a couple of the corporations freaked out and came and made some announcements here to calm their research teams down.
    0:36:54 But I’m now hearing entrepreneurs on the ground here. That’s a new way to build a company.
    0:37:07 Now people are like, oh, I’m just going to go get some researchers, raise 200 million and build a company. That’s the new dream, which is really incredible to see that they’ve inspired this new level of ambition even further than what we had before.
    0:37:17 Well, this has been great. I have to cap things off with a final question. So Roxanne and Antoine, will you be swimming in the river this Olympics?
    0:37:21 Do you believe in French technology enough that you would swim in the river?
    0:37:26 No way. But I’m very happy the mayor did because she said she would.
    0:37:28 Oh, the mayor did?
    0:37:30 Oh, she did. She did.
    0:37:33 She’s a true woman of the people. Nobody can…
    0:37:36 She didn’t have a choice. She had to get in there.
    0:37:39 That’s amazing. She swims pretty well too, to be honest.
    0:37:41 Wow, amazing.
    0:37:43 Wow, respect.
    0:37:50 All right, that’s all for now. Stay tuned for two more episodes in the series where we cover the unique attributes that have shaped the UK.
    0:37:54 And Latin America, up to the forces that they are today.
    0:37:56 We’ll see you then.
    0:38:07 [Music]
    0:38:17 [BLANK_AUDIO]

    Once criticized for lacking ambition, French founders are now aiming to create the world’s largest companies. With a thriving ecosystem attracting talent from across Europe and the US, France is becoming a major player on the global stage.

    In this episode, we cover the unique advantages of building startups in France. Roxanne Varza, Director of Station F; Antoine Martin, co-founder of Amo and Zenly; and Brian Kim, a16z consumer partner, discuss the key factors driving this transformation, including infrastructure, community, and government support.

    Discover how international talent, a supportive community, and robust governmental backing are propelling France’s startup scene. This episode is filled with insights into why France is now an exciting place to build a startup.

    Resources:

    Find Roxanne on Twitter: https://x.com/roxannevarza

    Find Antoine on Twitter: https://x.com/an21m

    Find Bryan on Twitter: https://x.com/kirbyman01

    Learn more about Station F: https://stationf.co/

    Learn more about Amo: https://get.amo.co/en

    Stay Updated: 

    Let us know what you think: https://ratethispodcast.com/a16z

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    Follow our host: https://twitter.com/stephsmithio

    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • Building the World’s Most Trusted Driver

    AI transcript
    0:00:01 (upbeat music)
    0:00:02 – Hello, everyone.
    0:00:04 Welcome back to the A16Z podcast.
    0:00:05 This is Stuff.
    0:00:07 Now, one of my favorite podcasts we’ve recorded
    0:00:09 since I joined the team
    0:00:11 was just about this time last year.
    0:00:13 That episode was on autonomous vehicles,
    0:00:17 but it was actually also in an autonomous vehicle.
    0:00:20 That was my first ride in a self-driving car.
    0:00:21 And over the last year,
    0:00:23 I’ve seen so many others have their first
    0:00:25 as Waymo has expanded to the public
    0:00:27 in Phoenix and San Francisco,
    0:00:30 while also placing its roots in Austin and LA.
    0:00:32 In 2015, Waymo tested
    0:00:35 its first fully driverless ride on public roads.
    0:00:38 It then opened to the public in Phoenix in 2020,
    0:00:40 but it wasn’t until 2022
    0:00:43 that autonomous drives were offered in San Francisco.
    0:00:45 And by the end of 2023,
    0:00:48 it clocked in over 7 million driverless miles.
    0:00:51 Slowly, then all at once.
    0:00:53 So with this space moving so quickly,
    0:00:54 we wanted to give you an update
    0:00:57 on where this industry is today.
    0:01:00 Passing the baton to properly introduce this episode,
    0:01:02 here is our very own AI Revolution host
    0:01:06 and A16Z General Partner, Sarah Wang.
    0:01:08 As a reminder,
    0:01:11 the content here is for informational purposes only.
    0:01:13 Should not be taken as legal, business, tax
    0:01:14 or investment advice,
    0:01:16 or be used to evaluate any investment or security
    0:01:18 and is not directed at any investors
    0:01:21 or potential investors in any A16Z fund.
    0:01:23 Please note that A16Z and its affiliates
    0:01:24 may also maintain investments
    0:01:27 in the companies discussed in this podcast.
    0:01:28 For more details,
    0:01:29 including a link to our investments,
    0:01:33 please see A16Z.com/disclosures.
    0:01:35 (upbeat music)
    0:01:39 – Hey guys, I’m Sarah Wang,
    0:01:42 General Partner on the A16Z growth team.
    0:01:45 Welcome back to our AI Revolution series.
    0:01:46 In this series,
    0:01:48 we talk to the Gen AI builders
    0:01:50 who are transforming our world to understand,
    0:01:53 one, where we are, two, where we’re going
    0:01:56 and three, the big open questions in the field.
    0:01:59 Our guest this episode is Dmitry Dolgov,
    0:02:01 the co-CEO of Waymo.
    0:02:04 Dmitry has led Waymo to solve some of the biggest challenges
    0:02:06 and bringing AI to the real world.
    0:02:09 And after tens of millions of miles of testing,
    0:02:11 Waymo’s vehicles have shown themselves
    0:02:14 to be safer and more reliable than human drivers,
    0:02:16 myself included.
    0:02:18 Dmitry has a unique perspective,
    0:02:20 given that his work has spanned multiple AI ML development
    0:02:22 cycles across decades.
    0:02:25 He was an early pioneer in self-driving cars,
    0:02:28 working with Toyota and Stanford on DARPA’s grand challenge
    0:02:30 before joining Google’s self-driving car project,
    0:02:33 which then evolved into Waymo.
    0:02:35 In this conversation from a closed door event
    0:02:38 with A16Z General Partner, David George,
    0:02:41 Dmitry talks about the potential of embodied AI,
    0:02:43 the value of simulations and building training data,
    0:02:46 and his approach to leading a company focused on solving
    0:02:49 some of the world’s hardest problems.
    0:02:50 Without further ado,
    0:02:53 here’s Dmitry in conversation with David.
    0:02:56 (dramatic music)
    0:03:05 – Maybe to start, take us back to Stanford, if you will.
    0:03:07 And that was when you first started working
    0:03:09 on the DARPA project.
    0:03:12 And maybe give us a little bit of your history
    0:03:15 of how you ended up from there to here.
    0:03:18 – My introduction to autonomous vehicles
    0:03:21 was when I was doing a postdoc at Stanford,
    0:03:23 that you just mentioned, David.
    0:03:28 This was during, I got pretty lucky with the timing of it.
    0:03:30 This was when the DARPA grand challenges were happening.
    0:03:33 DARPA is the Defense Advanced Research Project Agency
    0:03:35 that started these competitions with the goal
    0:03:39 of boosting this field of autonomous vehicles.
    0:03:44 And the one that I got involved in was in 2007,
    0:03:46 that was called the DARPA Urban Challenge.
    0:03:50 So the setup there was, it’s kind of like a toy version
    0:03:53 of what we’ve been working on since then.
    0:03:55 It was kind of supposed to mimic the driving
    0:03:56 in urban environments.
    0:04:00 So they kind of created a fake city on an abandoned airbase
    0:04:03 and they populated it with a bunch of autonomous vehicles,
    0:04:04 a bunch of human drivers,
    0:04:07 and they had them do various tasks.
    0:04:12 So that was kind of my introduction to this whole field.
    0:04:14 And it was a bit of a, I think in a DARPA,
    0:04:16 these challenges are often by people in the industry
    0:04:19 considered kind of a foundational pivotal moment
    0:04:22 for this whole field.
    0:04:23 And it was definitely that for me.
    0:04:27 It was like a light bulb, light switch moment
    0:04:29 that really got me hooked.
    0:04:31 – What was like the hardware and software
    0:04:33 that you guys had at that point?
    0:04:35 Is this 2007?
    0:04:39 – Yeah, I know it’s a, at a very high level,
    0:04:41 not unlike what we talk about today.
    0:04:43 A car that has some instrumentation
    0:04:45 so you can tell it what to do
    0:04:47 and you get some feedback back.
    0:04:50 Then you have kind of what’s called a post system,
    0:04:54 a bunch of inertial measurement system accelerometers,
    0:04:55 gyroscopes that kind of tell you in GPS,
    0:04:57 tells you how you’re moving through space.
    0:05:00 And it has sensors, radars, lighters and cameras,
    0:05:02 those same stuff we still use today.
    0:05:06 And then there’s a computer that gets the sensor data in
    0:05:08 and then tells the car what to do.
    0:05:10 And a bunch of software and software head,
    0:05:13 perception components and decision-making planning
    0:05:15 components and some AI.
    0:05:17 But of course everything that we had,
    0:05:20 like each one of those things over that,
    0:05:21 how long has it been?
    0:05:23 Almost 18 years, more than that.
    0:05:24 It’s changed drastically, right?
    0:05:26 So when we talk about AI today versus AI,
    0:05:30 we had back in 2007, 2009, nothing in common.
    0:05:31 And similarly, everything else has changed.
    0:05:34 The sensors are not the same, computers are not the same.
    0:05:35 – Yeah, of course.
    0:05:37 So then, okay, so take us, so at that point,
    0:05:40 that was the pivotal, that was like the light bulb moment.
    0:05:43 And then at that point, you said, okay, I’m at Stanford,
    0:05:45 I wanna make this my career, right?
    0:05:47 Is that, and then it was Toyota,
    0:05:49 and then where did it go from there?
    0:05:51 – I don’t know if I thought about it in those terms.
    0:05:55 I was like, this is the future, I wanna make it happen.
    0:05:56 I wanna be building this thing, career.
    0:05:58 Okay, you know, they can wait.
    0:06:00 But it was, that was the next step.
    0:06:03 That was the next big step is a number of us
    0:06:06 from the DARPA Challenge competitions
    0:06:09 started the Google self-driving project.
    0:06:12 It was about a dozen of us, and then in 2009,
    0:06:14 came together at Google with support,
    0:06:16 an assignment from Larry and Sergey,
    0:06:19 to see if we can take it to the next step.
    0:06:24 And that then, we worked on it for a few years,
    0:06:26 and that project then became Waymo in 2016,
    0:06:29 and we’ve been on this path since then.
    0:06:31 – Okay, so we have this new big breakthrough
    0:06:33 in generative AI.
    0:06:34 Some would say it’s new,
    0:06:36 some would say it’s 70 years in the making.
    0:06:40 How do you think about layering advances
    0:06:43 that have come from generative AI
    0:06:46 to what many would describe as more traditional AI
    0:06:48 or machine learning techniques
    0:06:50 that were kind of the building blocks
    0:06:53 for self-driving technology up to that point?
    0:06:54 – Oh yeah, great question.
    0:06:56 So maybe generative AI is kind of a broad term.
    0:06:59 So maybe you can take a little bit of a step back
    0:07:02 and talk about the role that AI plays
    0:07:05 in autonomous vehicles and kind of how we saw
    0:07:07 the various breakthroughs in AI
    0:07:09 map to the space of our task, right?
    0:07:11 So like I mentioned,
    0:07:16 AI has been part of self-driving autonomous vehicles
    0:07:18 from the earliest days.
    0:07:20 Back when we started, it was a very different kind of AI,
    0:07:22 ML, kind of classical maintenance,
    0:07:24 decision trees, classical computer visions
    0:07:27 with kind of hand engineered features,
    0:07:28 kernels and so forth.
    0:07:34 And then one of the,
    0:07:37 first really important breakthroughs
    0:07:41 that happened in AI and computer vision
    0:07:44 but really was important for our task
    0:07:48 was the advancement in convolutional neural networks
    0:07:51 right around 2012, right?
    0:07:54 Many of you are probably familiar with AlexNet
    0:07:55 and the ImageNet competition.
    0:07:58 This is where AlexNet kind of blew away
    0:08:01 out of the water all other approaches.
    0:08:04 So that obviously has had very strong implications
    0:08:06 for our domain, like how you do computer vision
    0:08:07 and not just on cameras, right?
    0:08:11 How you can use ConvNets to interpret what’s around you
    0:08:13 and do kind of object detection and classification
    0:08:14 from camera data, from LiDAR data,
    0:08:16 from your imaging radars.
    0:08:18 So that was kind of a big boost
    0:08:22 around that 2012, 2013 timeframe.
    0:08:24 And then we played with those approaches
    0:08:27 and tried to extend the use of ConvNets to other domains,
    0:08:30 just beyond perception with some interesting
    0:08:32 but limited success.
    0:08:36 Then another big, very important breakthrough
    0:08:41 happened around 2017 when Transformers came around.
    0:08:43 It had a really huge impact on language,
    0:08:45 language understanding, language models,
    0:08:48 machine translation, so forth.
    0:08:52 And for us, it was a really important breakthrough
    0:08:54 that really allowed us to take a mel in AI
    0:08:58 to new areas well beyond perception.
    0:09:00 And so if you think about, you know,
    0:09:03 Transformers and the impact that they had on language,
    0:09:06 ConvNets, the intuition is that they’re good at understanding
    0:09:10 and predicting and generating sequences of words, right?
    0:09:14 And in our case, we think about, in our domain,
    0:09:17 about the tasks of understanding and predicting
    0:09:20 what people will do, like other actors in the scene,
    0:09:22 or the task of decision-making
    0:09:23 and planning your own trajectories
    0:09:26 or in simulation, generating generative AI,
    0:09:29 or our version of generating behaviors
    0:09:31 of how the world will evolve.
    0:09:34 That kind of these behavioral,
    0:09:37 like these sequences are not unlike sentences, right?
    0:09:39 You’re kind of operating the state of objects, right?
    0:09:40 And then there’s kind of local continuity,
    0:09:42 but then the global context of the scene really matters.
    0:09:44 So this is where we saw some really exciting breakthroughs
    0:09:48 in behavior prediction and decision-making and simulation.
    0:09:50 And then, you know, since then we’ve been on this trend
    0:09:52 of, you know, models getting bigger.
    0:09:56 People started building foundation models
    0:09:57 for multi-tasks.
    0:10:00 And most recently, all of the,
    0:10:01 can I use the last couple of years,
    0:10:04 all the breakthroughs in large language models.
    0:10:08 You know, modern state, modern-day generative AI,
    0:10:11 visual language models where you kind of align
    0:10:13 image understanding and language understanding.
    0:10:16 And there’s been, most recently,
    0:10:17 one thing I’m pretty excited about
    0:10:21 is kind of the intersection or combination of the two,
    0:10:24 so that that’s what we’ve been very focused on
    0:10:28 but Waymo most recently is taking kind of the AI backbone
    0:10:32 and all of the AI, the Waymo AI that is over the years
    0:10:35 we’ve built up that is really proficient
    0:10:37 at this task of autonomous driving
    0:10:41 and combining it with kind of the general world knowledge
    0:10:44 and understanding of these, you know, VLMs.
    0:10:45 – One of the things that you just mentioned
    0:10:50 is the role of simulation and how that has been,
    0:10:51 you guys have had major breakthroughs
    0:10:54 in the use of simulation.
    0:10:56 And this idea in, you know,
    0:10:59 the recent breakthroughs in generative AI
    0:11:02 around synthetic data and its usefulness
    0:11:04 is somewhat in question.
    0:11:06 I would say in your field,
    0:11:08 this idea of synthetic data and simulation
    0:11:11 is extremely useful and you’ve proven that.
    0:11:12 So maybe you could just talk about
    0:11:15 the simulation technology you guys have built,
    0:11:16 how it’s allowed you to scale,
    0:11:20 you know, build that real world understanding,
    0:11:24 you know, and maybe how it’s changed in the last few years.
    0:11:25 – Yeah, yeah, definitely.
    0:11:27 It is super important in our field.
    0:11:32 I mean, largely, if you think about this question
    0:11:36 of evaluating the driver, like, you know, is it good enough?
    0:11:38 It’s, you know, how do you answer that?
    0:11:39 There’s, you know, a lot of metrics
    0:11:43 and a lot of, you know, data sets you have to build up.
    0:11:46 And then, you know, you,
    0:11:49 how do you evaluate the latest version of your system?
    0:11:51 You can’t just, you know, throw it on the physical world
    0:11:54 and then, you know, see what happens.
    0:11:55 You have to do a simulation.
    0:11:59 But of course, the new system behaves differently
    0:12:03 from what might have happened in the world otherwise.
    0:12:05 So you have to have a realistic closed loop simulation
    0:12:08 to give you, you know, confidence and value.
    0:12:09 So that is one of the most important needs
    0:12:10 for the simulation.
    0:12:12 You’ve also mentioned synthetic data,
    0:12:15 as that’s another area where simulation allows you
    0:12:17 to have very high leverage.
    0:12:20 And you just got to explore the long tail of that, right?
    0:12:21 Maybe there’s something interesting
    0:12:23 that you have seen in the physical world.
    0:12:25 And, but, you know, you want to modify that scenario
    0:12:28 and you want to kind of turn one event into thousands
    0:12:30 or tens of thousands of variations of that scenario.
    0:12:31 You know, how do you do that?
    0:12:33 You know, this is where the simulation comes in.
    0:12:34 And then, you know, lastly,
    0:12:39 if you, you know, sometimes want to evaluate
    0:12:43 and train on things that you’ve never seen.
    0:12:47 You and I are very vast experience.
    0:12:49 So this is where purely synthetic simulations come in
    0:12:51 that are not based on anything that you have seen
    0:12:53 in the physical world.
    0:12:55 So in terms of technologies that go into play,
    0:12:58 I mean, it’s a lot.
    0:13:01 And that is like a huge generative AI problem.
    0:13:04 But what’s really important is that that simulator
    0:13:07 is realistic, right?
    0:13:10 It has to be realistic in terms of your, you know,
    0:13:12 sensor or perception realism, right?
    0:13:17 Because it has to be realistic in terms of the behaviors
    0:13:20 that you see from other dynamic actors, right?
    0:13:23 You have, you know, if there are other actors
    0:13:24 that are not behaving in an realistic way,
    0:13:26 like if, you know, pedestrians are not walking
    0:13:27 the way they do in the real world,
    0:13:31 you need to be able to quantify the kind of the,
    0:13:36 the scenarios that you create in simulation
    0:13:39 to the realism and the rate of occurrence
    0:13:40 in the physical world, right?
    0:13:42 It’s, you know, very crazy to sample something
    0:13:45 very, you know, easy to sample something totally crazy
    0:13:47 in simulator, but then, you know, what do you do with that?
    0:13:49 So I think that that brings me to the third point
    0:13:52 of, you know, realism is that it has to be kind of realistic
    0:13:54 and quantifiable at the macro level,
    0:13:55 at the statistical level.
    0:13:56 So there’s any, you can imagine,
    0:13:58 there’s a lot of work that goes into building a simulator
    0:14:01 that is, you know, large scale and has, you know,
    0:14:03 that level of realism across those categories.
    0:14:05 And if kind of intuitively you think about it, you know,
    0:14:08 to build a good driver, you need to have a very good simulator,
    0:14:09 but to have a good simulator,
    0:14:11 you actually have to build models
    0:14:13 of like realistic pedestrians and cyclists and drivers, right?
    0:14:15 So it’s, you know, it kind of do that iteratively.
    0:14:16 – Yeah, of course.
    0:14:19 And then by having this simulation software
    0:14:22 that is very good at mimicking real world
    0:14:25 and very usable in the sense that you can
    0:14:27 create variables in the scenes,
    0:14:30 you can actually give the driver
    0:14:32 multiples of the amount of experience
    0:14:33 that they have on the road.
    0:14:34 – That’s exactly right.
    0:14:36 – In real miles, is that right?
    0:14:36 – That’s exactly right.
    0:14:40 We’ve driven, you know, tens of millions of miles
    0:14:41 in the physical world.
    0:14:44 And at this point we’ve driven more than 15 million miles
    0:14:47 in full autonomy, we call it, you know, rider only mode.
    0:14:48 But we’ve driven, you know,
    0:14:49 tens of billions of miles of simulation.
    0:14:52 So you get, you know, orders of magnitude of an amplifier.
    0:14:56 – Speaking of multiples of miles driven,
    0:15:01 one of the hotly debated topics in the AI world today
    0:15:04 is this concept of scaling laws.
    0:15:06 So how do you think about scaling laws
    0:15:08 as it relates to autonomous driving?
    0:15:09 Is it miles driven?
    0:15:12 Is it certain experience had?
    0:15:13 Is it compute?
    0:15:15 Like, what are the ways that you think about that?
    0:15:19 – So model size matters.
    0:15:22 So we’re seeing, you know, scaling laws applied,
    0:15:26 a lot of typical, you know,
    0:15:29 old school models are severely under trained.
    0:15:31 And so if you have a bigger model,
    0:15:33 you have data that actually does help you.
    0:15:36 You just have more capacity that generalize better.
    0:15:39 So we are seeing the scaling laws apply there.
    0:15:41 Data, of course, usually matters, right?
    0:15:43 And, but it’s not just, you know,
    0:15:46 counting the miles, right, or hours.
    0:15:48 It has to be, you know,
    0:15:50 the right kind of data that, you know,
    0:15:53 teaches the models or trains the models to be, you know,
    0:15:56 good at the rare cases that you care about.
    0:15:58 And then, you know, there is a bit of a, you know,
    0:16:00 a wrinkle ’cause then you have to,
    0:16:02 you can build those very large models,
    0:16:04 but in our space, it has to run on board the car, right?
    0:16:07 So you are somewhat complicated, you have to distill it
    0:16:10 into your, you know, onboard system.
    0:16:13 But we do see trend, we just, you know,
    0:16:15 common trend and we see that play out in our space
    0:16:17 where you’re much better off training a huge model
    0:16:19 and then distilling it into a small model
    0:16:20 than just training small models.
    0:16:22 – Yeah, I’m gonna shift gears a little bit
    0:16:25 and I’m gonna do a sort of simplifying statement,
    0:16:27 which is probably gonna drive you crazy.
    0:16:32 But the DARPA School of Thought is, you know,
    0:16:35 there’s sort of a rules-based approach, right?
    0:16:39 A more traditional kind of AI-based approach
    0:16:43 with a massive amount of volume and you document edge cases
    0:16:46 and then the model then learns how to react to those.
    0:16:51 The more recent approaches from some other large players
    0:16:52 and startups would say,
    0:16:54 hey, we just have AI from the start,
    0:16:57 make all the decisions end to end.
    0:17:00 You don’t need to have sort of all that pattern recognition
    0:17:02 and learning, you know, like the end to end driving
    0:17:04 that is kind of a tagline out there.
    0:17:08 What is your interpretation of that approach
    0:17:12 and what elements of that approach have you taken
    0:17:14 and applied inside of Waymo?
    0:17:16 – Yeah, you know, I think it’s kind of, you know,
    0:17:19 sometimes it’s a, you know, the way people talk about it
    0:17:23 is kind of this weird dichotomy is this or that.
    0:17:24 – Yeah, of course.
    0:17:27 – But it’s not, it’s that and then some, right?
    0:17:30 So it is, you know, big models.
    0:17:32 It is end to end models.
    0:17:35 Yeah, it is a generative AI and combining, you know,
    0:17:37 these models with VLMs, right?
    0:17:41 But the problem is it’s not enough, right?
    0:17:43 So I mean, like we all know the limitations
    0:17:44 of those models, right?
    0:17:47 And that’s, and we’ve seen, you know, through the years,
    0:17:48 a lot of these breakthroughs in AI, right?
    0:17:50 You know, Continuous Transformers,
    0:17:52 you know, big end to end foundation models,
    0:17:53 they’re huge boosts to us.
    0:17:56 And you know, what we’ve been doing
    0:17:58 at Waymo through the history of our project
    0:18:03 is kind of constantly applying and pushing forward
    0:18:04 these state-of-the-art techniques ourselves
    0:18:06 in some cases, but then applying them to our domain.
    0:18:08 And what we’ve been learning is that they really
    0:18:11 give you a huge boost, but they’re just not enough, right?
    0:18:14 So in the kind of, the theme has always been
    0:18:16 that you can take, you know, your kind of latest
    0:18:19 and greatest technology of the day
    0:18:22 and it’s fairly easy to get started, right?
    0:18:24 Like, you know, like the curves always look like that.
    0:18:26 And they, like they’ve been kind of the curves
    0:18:27 in their shaping, but the really hard problems
    0:18:30 in that remaining point is 0.0001%.
    0:18:32 And there it’s not enough, right?
    0:18:34 So then you have to do stuff on top of that, right?
    0:18:36 So yes, you can take, you know, nowadays,
    0:18:38 you can take, you know, an end-to-end model,
    0:18:41 go from sensor to, you know, trajectories or actuation.
    0:18:42 You know, typically you don’t build them in one stage,
    0:18:43 you build them in stages, but you know,
    0:18:45 you can do, like, back prop through the whole thing.
    0:18:48 So, you know, the concept is very, very valid.
    0:18:50 You can, you know, combine it and, you know,
    0:18:52 with a VLM and then, you know,
    0:18:54 you add closed-loop simulations, some sort.
    0:18:56 And, you know, you’re off to the races.
    0:18:59 You can have a great demo, like, almost out of the box.
    0:19:03 You can have, you know, an ADESP, or a driver assist system,
    0:19:06 but that’s not enough to go all the way to full autonomy.
    0:19:08 So that’s where really a lot of the hard work happens.
    0:19:09 So I guess the question is, you know,
    0:19:11 not is it this or that, it’s, you know, this,
    0:19:14 and then what else do you need to take it all the way
    0:19:16 to have the confidence in, you know,
    0:19:18 so that you can actually remove the driver
    0:19:19 and go for full autonomy.
    0:19:20 And that’s a ton of work.
    0:19:23 That’s a ton of work through the entire, kind of,
    0:19:25 life cycle of these models and the entire system, right?
    0:19:27 So it starts with training.
    0:19:28 Like, how do you train?
    0:19:29 How do you architect these models?
    0:19:32 How do you, you know, evaluate them?
    0:19:34 Then, you know, if you put in a bigger system,
    0:19:35 the models themselves are not enough,
    0:19:36 so you have to do things around them.
    0:19:38 You have to, you know, they have,
    0:19:40 modern genera of AI is great,
    0:19:41 but there are some issues with, you know,
    0:19:43 hallucinations, there are issues with, like,
    0:19:45 – Explanability. – Exactly, exactly.
    0:19:46 So, you know, they have some weaknesses
    0:19:50 and kind of goal-oriented planning and policy-making
    0:19:52 and kind of understanding this, you know,
    0:19:55 3D space operating in this 3D spatial world, right?
    0:19:57 So you have to add something on top of that.
    0:19:58 We talked a little bit about the simulator.
    0:20:00 That’s a really hard problem, you know, itself.
    0:20:02 And then, you know, once you have something,
    0:20:03 you know, once you deploy it
    0:20:05 and you learn how do you feed that back.
    0:20:07 So I guess this is where all of the really,
    0:20:07 really hard work happens.
    0:20:09 So it’s not, like, end-to-end versus something else.
    0:20:12 It is end-to-end and, you know, big foundation models.
    0:20:14 And then, like, and then the hard work.
    0:20:15 – And then all the hard work.
    0:20:17 Yeah, that totally makes sense.
    0:20:19 That is a great segue into all of the progress
    0:20:21 that you guys have made, right?
    0:20:24 Writing in the Waymo for those who have done it
    0:20:26 is an extraordinary experience.
    0:20:28 It’s not to say that you have solved
    0:20:29 all of these complex tasks,
    0:20:31 but you’ve solved a lot of them.
    0:20:36 What are some of the biggest AI or data problems
    0:20:39 that you still feel like you’re facing today?
    0:20:42 – The short answer is going to be, you know,
    0:20:46 taking it to, you know, the next order of magnitude of scale.
    0:20:47 Multiple orders of magnitude of scale.
    0:20:49 And with that come, you know,
    0:20:50 additional improvements that we need
    0:20:53 to make it, you know, a great service, right?
    0:20:57 But, you know, just to level-set in terms of
    0:20:58 where we are today, you know,
    0:21:03 we are, you know, driving in all kinds of conditions.
    0:21:07 We’re driving, you know, 24/7 in San Francisco,
    0:21:09 in Phoenix, you know, a little bit,
    0:21:10 those are the most mature markets,
    0:21:12 but also in LA and in Austin.
    0:21:15 And, you know, all of the complexity that you see,
    0:21:17 you know, go drive around the city, right?
    0:21:18 All kinds of weather conditions,
    0:21:21 whether it’s, you know, fog or, you know, storms
    0:21:25 or dust storms or, you know, rainstorms down here,
    0:21:27 like all of that, all of those are conditions
    0:21:28 that we do operate in, right?
    0:21:30 So then I think about, you know,
    0:21:34 what makes it a great, you know, customer experience, right?
    0:21:35 Like what does it take if you, you know,
    0:21:39 grow by, you know, next, you know, orders of magnitude?
    0:21:40 There’s a lot of improvements that we want to make
    0:21:42 so that it becomes a better service for you
    0:21:44 to get from point A to point B, right?
    0:21:46 Like we asked for feedback from our writers.
    0:21:49 A lot of feedback we get is, you know,
    0:21:51 it has to do with the quality of your pickup
    0:21:52 and drop-off locations, right?
    0:21:53 So we’re learning from users.
    0:21:55 Like no matter what, we want to make it a magical,
    0:21:57 seamless, you know, delightful experience
    0:21:59 from the time you kind of, you know,
    0:22:00 start the app on your phone too,
    0:22:01 when you get on the destination.
    0:22:04 So that’s a lot of the work that we’re doing right now.
    0:22:06 – Yeah, pick up and drop-off for what it’s worth
    0:22:09 is an extraordinarily hard problem, right?
    0:22:13 Like do you kind of block a little bit of a driveway
    0:22:15 if you’re in an urban location
    0:22:16 and then have a sensor that says,
    0:22:19 oh, actually, I just saw somebody opening a garage door.
    0:22:22 I need to get out of the way, you know,
    0:22:24 how far down the street is acceptable to go pull.
    0:22:25 Or if you’re in a parking lot,
    0:22:27 where in the parking lot do you go?
    0:22:29 Like this is an extraordinarily hard problem,
    0:22:32 but to your point, it’s huge for user experience.
    0:22:33 – That’s exactly right, right?
    0:22:35 And just, you know, I think that’s a good example
    0:22:36 of like just, hey, just one thing,
    0:22:39 one of the many things that we have to build
    0:22:41 in order for this to be an awesome product, right?
    0:22:43 Not just like a technology demonstrator.
    0:22:44 And I think you just like, you know,
    0:22:49 hit exactly on a few things that make,
    0:22:53 you know, something that kind of at the face of it
    0:22:54 might seem fairly straightforward, right?
    0:22:56 Okay, you know, I know there’s a place on the map
    0:22:57 and I need to pull over.
    0:22:59 It’s like, how hard can it be, right?
    0:23:00 But really, if it’s a complicated, you know,
    0:23:02 dense urban environment,
    0:23:03 there’s a lot of these factors, right?
    0:23:05 Is there like, you know, another vehicle
    0:23:06 that you’re gonna be blocking?
    0:23:08 Is there a garage door that’s opening, right?
    0:23:10 Like, you know, what is the most convenient place
    0:23:11 for the user to pick up?
    0:23:14 What is, you know, so it really gets into this,
    0:23:17 you know, the depth and the subtlety of understanding
    0:23:21 the, you know, the semantics and the dynamic nature
    0:23:23 of this driving task and, you know, doing things
    0:23:25 that are, you know, safe, comfortable and predictable
    0:23:28 and lead to a nice, seamless, pleasant,
    0:23:30 delightful customer experience.
    0:23:32 – Of course, okay, so you’ve mentioned this stat,
    0:23:36 but 15 million miles, I know the number’s probably
    0:23:39 a little bit bigger than that, but you released it Tuesday.
    0:23:42 Yeah, it’s growing by the day.
    0:23:46 15 million autonomous miles driven, that’s incredible.
    0:23:49 Even more impressive, and you didn’t share this stat yet,
    0:23:54 it results in 3.5 times fewer accidents
    0:23:56 than human drivers, is that right?
    0:23:59 – And I think 3.5 acts as the reduction in injury,
    0:24:02 and it’s about 2x reduction in the police reportable
    0:24:03 kind of lower severity incidents.
    0:24:08 – This sort of comes to a question of both kind of
    0:24:12 regulatory and, you know, business or ethical judgment.
    0:24:15 What is the right level that you want to get to?
    0:24:17 Obviously you want to constantly get better,
    0:24:19 but is there a level at which you say,
    0:24:21 “Okay, we’re good enough,” and that’s acceptable
    0:24:22 to regulators?
    0:24:24 – Yeah, so there’s no, you know,
    0:24:28 simple, super simple short answer, right?
    0:24:29 I think it starts with that.
    0:24:31 It starts with those statistics that you just mentioned.
    0:24:33 I can then have the day what I care about
    0:24:35 is that roads are safer.
    0:24:36 So when you look at those numbers,
    0:24:38 yet, you know, when we operate today,
    0:24:40 and we have, you know, strong empirical evidence
    0:24:44 that our cars are in those areas safer than human drivers.
    0:24:47 So on balance, that means a reduction in, you know,
    0:24:49 collisions and harm.
    0:24:54 Then, actually on top of the numbers
    0:24:55 we’ve probably been publishing,
    0:24:57 this is you’re quoting the latest numbers that we’ve shared.
    0:24:58 – Yeah.
    0:24:59 – Consistently, you know,
    0:25:04 sharing numbers as our service scales up and grows.
    0:25:06 You can also bring in, you know,
    0:25:08 an additional lens of, you know,
    0:25:11 how much did you contribute to a collision?
    0:25:12 And we actually published, I think it was based
    0:25:14 on about 4 million miles, 3.8 million miles.
    0:25:17 We’ve published a joint study with Swiss ARRI,
    0:25:20 which is, I think, the largest global reinsurer
    0:25:20 in the world.
    0:25:22 And the way they look at it is, you know,
    0:25:24 who contributed to an event.
    0:25:27 And there we saw like the same theme,
    0:25:30 but the numbers were very strong.
    0:25:35 That new field was a 76% reduction in property damage
    0:25:39 collisions, and it was an 100% reduction
    0:25:42 in claims around bodily injury.
    0:25:43 So if you kind of bring in that lens,
    0:25:45 I think the story becomes even more compelling.
    0:25:46 – That is extremely compelling.
    0:25:48 – Right, but there are some collisions where, you know,
    0:25:51 we’d be, and that’s the bulk of the events that we see.
    0:25:52 We’d be stopped at a red light,
    0:25:54 and then somebody just plows into you, right?
    0:25:55 – Sure.
    0:25:58 – So, but then, like we, I think, you know,
    0:26:01 we do know it’s a new technology, it’s a new product,
    0:26:04 so it is held to a higher standard.
    0:26:07 So we, when we think about our safety
    0:26:09 and our readiness, you know, framing of methodology,
    0:26:10 we don’t stop at just the race, right?
    0:26:12 We build over the years as, you know,
    0:26:16 one of the huge areas of investment
    0:26:18 and experience over the years, like how, you know,
    0:26:19 what else do you need?
    0:26:20 So we have done, and we’ve done a number
    0:26:21 of the other different things.
    0:26:23 And we’ve published some of our methodologies,
    0:26:25 we’ve shared our readiness framework, you know,
    0:26:27 we do other things like we actually,
    0:26:30 not just statistically, but on specific events,
    0:26:34 we build models of an attentive, very good human driver,
    0:26:36 like not distracted human, you know,
    0:26:38 a good question whether such a driver exists, right?
    0:26:41 But that’s kind of what we compare our driver to, right?
    0:26:43 And it’s a model, like, it’s then it’s, you know,
    0:26:45 in particular scenario, we evaluate ourselves
    0:26:47 versus that model of a human driver,
    0:26:49 and we hold ourselves to the bar of, you know,
    0:26:51 doing well compared to that very high standard.
    0:26:53 And then, you know, you pursue other, you know,
    0:26:54 validation methodologies.
    0:26:58 So that’s my answer is that it’s the, you know,
    0:27:00 the aggregate of all of those methodologies
    0:27:03 that we look at to decide that, yes, you know,
    0:27:06 the system is ready enough to be deployed in scale.
    0:27:09 – I’d love for you to talk about what you think,
    0:27:10 maybe today and in the future,
    0:27:13 about market structure, competition,
    0:27:17 and what kind of role you envision Waymo playing.
    0:27:20 – So the way we think about, you know,
    0:27:22 Waymo and our company is that we are building
    0:27:25 a generalize of both driver.
    0:27:26 That’s the core of it.
    0:27:28 And that’s the core of the mission
    0:27:33 of making a transportation safe and accessible, right?
    0:27:38 And we’re talking about right hailing today.
    0:27:42 That’s our main, most mature primary application.
    0:27:43 But, you know, we envision a future
    0:27:46 where the Waymo driver will be deployed
    0:27:47 in other commercial applications, right?
    0:27:49 There’s deliveries, there’s trucking,
    0:27:52 there’s personally owned vehicles, right?
    0:27:54 So in all of those, you know,
    0:27:57 our guiding principle would be to think
    0:28:00 about the go-to-market strategy in a way
    0:28:04 that accelerates access to this technology
    0:28:08 and gets it deployed as, you know, broadly,
    0:28:11 you know, of course, doing it gradually
    0:28:12 and deliberately and safely, you know,
    0:28:16 as quickly and broadly as possible.
    0:28:18 So with that, as our guiding principle,
    0:28:22 we’re gonna explore different commercial structures,
    0:28:23 different partnership structures.
    0:28:25 For example, in Phoenix today,
    0:28:28 we have a partnership with Uber and Right Healing,
    0:28:30 both in Uber Right Healing and in Uber Eats,
    0:28:33 where, so in Phoenix, we have our own app.
    0:28:35 You can download the Waymo app and, you know,
    0:28:36 take a ride, an hour vehicle will show up
    0:28:39 and take you where you wanna go.
    0:28:41 That’s, you know, one way to experience our product.
    0:28:43 Another one is through the Uber app.
    0:28:45 We have a partnership where you can get through
    0:28:48 the Uber app matched with our product,
    0:28:49 the Waymo driver, the Waymo vehicle,
    0:28:51 and it’s the same experience, right?
    0:28:54 But this is another way for us to accelerate
    0:28:56 and give more people to experience full autonomy.
    0:28:59 And it gives us a chance to kind of, you know,
    0:29:02 think about the different go-to-market strategies, right?
    0:29:06 One is, you know, us having more of our own app.
    0:29:07 The other one is more of a, you know,
    0:29:09 driver-as-a-service for somebody else’s network.
    0:29:11 So we’ll, you know, still early days,
    0:29:13 but we will iterate and hold, you know,
    0:29:15 in service of that main principle.
    0:29:15 – That’s amazing.
    0:29:18 Yeah, that’s gonna be exciting.
    0:29:21 Maybe on back to the vehicle,
    0:29:23 what about the hardware stack that you use?
    0:29:24 You and I have talked a bunch about, you know,
    0:29:28 you said like, hey, going all the way back to DARPA,
    0:29:29 you know, it’s kind of the same stuff, right?
    0:29:32 It’s, you know, it’s sensor, they’ve advanced
    0:29:34 quite considerably, but, you know,
    0:29:37 you still use, you know, radars and LiDAR.
    0:29:41 Do you think that remains the future path
    0:29:42 for autonomous driving?
    0:29:43 LiDAR specifically?
    0:29:48 – Yeah, no, I mean, the sensors are physically different,
    0:29:53 right?
    0:29:55 They have each one cameras, LiDARs, radar,
    0:29:57 they have their, you know, benefits,
    0:29:59 each one brings their own benefits, right?
    0:30:00 You know, cameras obviously give you color
    0:30:03 and they give you high, you know, very high resolution.
    0:30:06 LiDARs kind of give you, you know,
    0:30:09 a direct 3D measurement of your environment
    0:30:11 and they’re an active sensor, right?
    0:30:12 So it kind of brings their own energy,
    0:30:15 pitch dark when there’s no, you know, external light source,
    0:30:18 you know, you still get the seat just as well
    0:30:20 as they do during the day, you know,
    0:30:21 better in some cases.
    0:30:24 And then, you know, radar is, you know,
    0:30:26 very good at like, punching through just, you know,
    0:30:28 different physics, different wavelengths, right?
    0:30:32 If you build an imaging radar, which we do ourselves,
    0:30:34 you know, it allows us to, you know,
    0:30:37 give you an additional redundancy layer
    0:30:39 and it has benefits, also an active sensor,
    0:30:40 it can directly measure, you know,
    0:30:42 through Doppler velocity of other objects
    0:30:46 and it can, you know, degrades differently
    0:30:48 and more gracefully in some other conditions.
    0:30:50 Like, you know, very dense fog, you know,
    0:30:52 or very dense rain.
    0:30:53 So, you know, they’ll have their benefits.
    0:30:58 So if you, you know, our approach has been to, you know,
    0:31:00 use all of them, right?
    0:31:02 And, you know, that’s how you have redundancy
    0:31:04 and that’s how you get an extra boost
    0:31:06 and capability of the system.
    0:31:09 And, you know, we are on, you know,
    0:31:11 today deployed in 5th and working to deploy
    0:31:13 the sixth generation of our sensors.
    0:31:15 And, you know, over those generations,
    0:31:18 we’ve improved, you know, reliability,
    0:31:20 we’ve improved, you know, capability and performance
    0:31:23 and we’ve brought down the cost very significantly, right?
    0:31:25 So, yeah, I think that the trend, you know,
    0:31:27 for us that will, you know, using all three modalities
    0:31:29 just makes a lot of sense.
    0:31:31 Again, you know, you might make different trade-offs
    0:31:33 if you are building a driver’s system
    0:31:35 versus a fully autonomous vehicle where, you know,
    0:31:38 that last 0.001% really, really matters.
    0:31:39 – Yeah, absolutely.
    0:31:44 One of the observations that we have
    0:31:48 from the very early days of this wave of LLMs
    0:31:53 is that there has been sort of already a massive
    0:31:56 race of like cost reduction.
    0:31:59 And many would argue that it’s sort of a process
    0:32:02 of commoditization already, even though it’s very early days.
    0:32:06 I would say the observation from autonomous driving
    0:32:10 over many, many years now is kind of the opposite thing.
    0:32:13 There’s been a thinning of the field, you know,
    0:32:16 it’s proven to be much, much harder than expected.
    0:32:19 Can you just talk about maybe why that’s the case?
    0:32:21 – You know, they always have this property
    0:32:22 that it’s very easy to get started,
    0:32:25 but it’s very insanely difficult to get it, you know,
    0:32:28 all the way, you know, to full autonomy
    0:32:30 so that you can remove the driver.
    0:32:34 And, you know, there’s maybe a few factors
    0:32:36 that contribute to that.
    0:32:40 One is, you know, compared to the LLMs and, you know,
    0:32:43 it’s kind of AI in the digital world,
    0:32:45 you have to operate in the physical world.
    0:32:49 The physical world is messy, it is noisy,
    0:32:50 and, you know, it can be quite humbling, right?
    0:32:53 There’s all kinds of, you know, uncertainty and noise
    0:32:57 that can kind of pull you out of distribution,
    0:32:58 if you will, right? – Right, sure.
    0:33:02 – So that’s one thing, that makes this very difficult.
    0:33:07 And secondly, it’s safety, right?
    0:33:09 – Sure.
    0:33:12 – These, you know, AI systems, you know, in some domain,
    0:33:16 you know, this is creativity, and it’s great.
    0:33:18 You know, our domain, the cost of mistakes,
    0:33:21 our lack of, you know, accuracy
    0:33:22 has very serious consequences, right?
    0:33:25 So that’s just the bar, very, very high.
    0:33:27 Right, and then the last thing is that
    0:33:30 it is, you know, you have to operate in real time.
    0:33:33 You’re putting these systems on fast-moving vehicles,
    0:33:35 and you have to, you know, milliseconds matter, right?
    0:33:37 You have to make the decisions very quickly.
    0:33:39 So I think it’s, you know, the combination of those factors
    0:33:43 that really, you know, together lead to, you know,
    0:33:45 the trend that you’ve been seeing is that,
    0:33:47 like, you know, it’s an and, right?
    0:33:48 You have to be excellent on this and this and this
    0:33:49 and then, right?
    0:33:50 It’s all of the bar.
    0:33:52 The bar is very, very high for, you know,
    0:33:54 every component of the system and how you put them together.
    0:33:56 But, you know, there’s big advances,
    0:33:57 and they, you know, boost you,
    0:33:59 and they profile the system forward,
    0:34:00 but there are no silver bullets, right?
    0:34:03 And there’s no shortcuts if you’re talking about full autonomy.
    0:34:06 And because of that lack of tolerance for errors,
    0:34:08 you have a very high bar for safety.
    0:34:12 You have a very high burden from regulators.
    0:34:16 You know, it’s very costly to go through all those processes.
    0:34:17 And so it makes sense.
    0:34:20 And I’m very grateful that you guys have seen it through,
    0:34:23 despite all the humbling experiences
    0:34:25 that you had along the way.
    0:34:29 It’s been a long journey, but it’s, you know,
    0:34:31 for me and the many people at Weymo,
    0:34:36 it is super exciting and very, very rewarding
    0:34:38 to finally see it become reality.
    0:34:41 Now, we talk about safety and AI in many contexts, right?
    0:34:42 That’s a big question, right?
    0:34:44 But, you know, here we are in this application of AI
    0:34:46 in the physical world.
    0:34:48 We have, you know, at this point a pretty robust
    0:34:50 and increasing body of evidence that, you know,
    0:34:53 we are seeing, like, tangible safety benefits.
    0:34:54 So that’s very exciting.
    0:34:56 Yeah, I always say to people,
    0:34:58 it was a long journey
    0:35:01 and very costly and expensive along the way.
    0:35:04 But this is probably the most powerful manifestation of AI
    0:35:08 that we have available to us in the world today.
    0:35:09 I mean, you can get in a car without a driver,
    0:35:11 and it’s safer than having a human.
    0:35:12 And that’s just remarkable.
    0:35:16 What were some of those humbling events along the way?
    0:35:16 And those are early days?
    0:35:17 Those are the first couple of years?
    0:35:19 Early days.
    0:35:24 Oh, I’m sorry, I remember one, there was one route.
    0:35:29 That we did, that started, I think it started in Montmaville,
    0:35:30 then went through Palo Alto,
    0:35:33 then went, you know, through the mountains to Highway 1.
    0:35:35 That took Highway 1 to San Francisco.
    0:35:38 And I think, you know, went around the city a little bit
    0:35:40 and, like, actually finished for Lombard Street.
    0:35:42 So, like, in 2009, 10 people.
    0:35:43 That is really complicated.
    0:35:45 100 miles to the beginning to end, right?
    0:35:47 I mean, as human drivers would fail at that task,
    0:35:48 I think, so, yeah, I keep…
    0:35:49 Yeah, yeah.
    0:35:51 So, you know, we’re doing it one day,
    0:35:52 and then we’re driving and kind of made it through
    0:35:54 the Montmaville-Palo Alto part.
    0:35:55 We’re driving through the mountains
    0:35:57 and it’s foggy, it’s early morning.
    0:36:00 And then we’re, like, seeing objects.
    0:36:03 And, you know, our objects seem like random stuff
    0:36:04 on the road in front of us.
    0:36:06 There’s, like, a bucket and, like, a shoe.
    0:36:08 And then there’s, like, at some point,
    0:36:10 we come across, like, a, you know, a rusty bicycle.
    0:36:12 Like, okay, what’s going on there?
    0:36:13 And then we catch, you know, eventually.
    0:36:16 And, like, the card, you know, doesn’t, you know,
    0:36:17 handles it okay.
    0:36:18 You know, maybe not super smoothly,
    0:36:21 but, you know, we get stuck and we catch up to, like,
    0:36:24 this dump truck that has all kind of stuff on it.
    0:36:26 And, you know, periodically losing things
    0:36:28 that person obstacles to the car.
    0:36:30 This is, like, a cartoon, you know,
    0:36:33 continuation of anomalies being thrown at you guys.
    0:36:36 That’s pretty cool.
    0:36:38 Okay, last question.
    0:36:40 I’m going to tee you up to do some recruiting, probably.
    0:36:45 But if you were in the shoes of the audience here
    0:36:50 and just kind of seeking your first job,
    0:36:52 I’m going to take something that you said, which is, like,
    0:36:54 I can see your passion and excitement
    0:36:56 for doing the start-up thing, right?
    0:36:59 And, like, you know, kind of longing back for those days
    0:37:01 is so cool.
    0:37:04 What advice would you have for these folks
    0:37:08 in where to go, whether it’s type of company,
    0:37:13 type of role, industry, or anything else?
    0:37:14 Way more?
    0:37:16 That’s what I’m saying.
    0:37:18 It’s the easiest to tee you right up.
    0:37:20 You know, it’s a fine —
    0:37:22 I mean, we’re talking about AI today,
    0:37:24 but it’s a fine problem that matters.
    0:37:26 You know, problem that matters to the world,
    0:37:28 problem that matters to you.
    0:37:31 Chances are it’s going to be a hard one.
    0:37:33 Yeah.
    0:37:37 Many things, you know, we’re doing have that property.
    0:37:41 So don’t get discouraged by, you know,
    0:37:43 the unknown by what others might tell you.
    0:37:46 And, you know, start building.
    0:37:49 And then, you know, keep building and don’t look back.
    0:37:52 Huge congratulations on all the progress you guys have made.
    0:37:56 And as a very happy customer, thank you for building it.
    0:37:59 And we really appreciate you being here.
    0:38:03 All right, that is all for today.
    0:38:06 If you did make it this far, first of all, thank you.
    0:38:08 We put a lot of thought into each of these episodes,
    0:38:10 whether it’s guests, the calendar touchers,
    0:38:12 the cycles with our amazing editor Tommy
    0:38:14 until the music is just right.
    0:38:16 So if you’d like what we put together,
    0:38:20 consider dropping us a line at ratethispodcast.com/a16z.
    0:38:23 And let us know what your favorite episode is.
    0:38:26 It’ll make my day, and I’m sure Tommy’s too.
    0:38:28 We’ll catch you on the flip side.
    0:38:31 (upbeat music)
    0:38:34 (crunching)
    0:38:36 (upbeat music)

    Waymo’s autonomous vehicles have driven over 20 million miles on public roads and billions more in simulation.

    In this episode, a16z General Partner David George sits down with Dmitri Dolgov, CTO at Waymo, to discuss the development of self-driving technology. Dmitri provides technical insights into the evolution of hardware and software, the impact of generative AI, and the safety standards that guide Waymo’s innovations.

    This footage is from AI Revolution, an event that a16z recently hosted in San Francisco. Watch the full event here:  a16z.com/dmitri-dolgov-waymo-ai

     

    Resources: 

    Find Dmitri on Twitter: https://x.com/dmitri_dolgov

    Find David George on Twitter: https://x.com/DavidGeorge83

    Learn more about Waymo: https://waymo.com/

     

    Stay Updated: 

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    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • From AI to Instant Replay: The Technology Behind the Olympics

    AI transcript
    0:00:05 – Sports is interesting because it’s the great aggregator.
    0:00:07 I talk to founders all the time,
    0:00:09 and one of the things I’m cautioning them about
    0:00:12 is how is what you’re doing making this better?
    0:00:14 It’s an extraordinary piece of technology
    0:00:16 because for the first time you understand the speed,
    0:00:20 you understand the ability of the athlete.
    0:00:22 A lot of people are sort of building technology
    0:00:24 without understanding how does this actually enhance
    0:00:26 the storytelling experience.
    0:00:28 This is incredible, this is amazing.
    0:00:30 I have absolutely no idea what the applicable value
    0:00:32 of this is.
    0:00:34 We’re seeing the purest version
    0:00:37 of the human experience of what can the human body
    0:00:38 actually accomplish?
    0:00:41 – Exactly one week ago,
    0:00:44 the 2024 Paris Summer Olympics kicked off,
    0:00:48 bringing in an estimated 10 million plus people to the city
    0:00:51 that of course included over 11,000 athletes
    0:00:54 who have begun competing across 32 sports,
    0:00:56 including four new additions,
    0:00:58 ranked dancing in its first games,
    0:00:59 plus skateboarding, sport climbing,
    0:01:03 and surfing, making their second appearance.
    0:01:04 And of course, there are a few events
    0:01:07 that bring the world together quite like the Olympics.
    0:01:08 So as we all watch in awe,
    0:01:10 there’s a reason why people are talking
    0:01:12 about the bunny hopping fencer
    0:01:15 or the 11 year old skateboarder or Kim Uji,
    0:01:18 the sharpshooter with a lot of swag.
    0:01:20 There’s also a reason why you might not recognize
    0:01:22 the name Nathan Adrian,
    0:01:25 but you almost certainly know the name Simone Biles.
    0:01:27 Even though they’re American Olympians
    0:01:29 who have earned the exact same medals
    0:01:30 in their Olympic careers,
    0:01:33 because the Olympics is as much about excellence
    0:01:35 as it is about story.
    0:01:37 And that’s precisely what we discussed today
    0:01:39 with Charlie Ebersole.
    0:01:41 Charlie has long been immersed in athletics,
    0:01:43 co-founding the Alliance of American Football
    0:01:44 and Infinite Athlete,
    0:01:45 where they’re building products
    0:01:47 ranging from AI injury detection
    0:01:50 to bespoke broadcasting technology.
    0:01:53 Charlie also happens to be the son of Dick Ebersole,
    0:01:55 the longtime chairman of NBC Sports,
    0:01:58 where he produced 19 Olympic Games
    0:01:59 and is also credited
    0:02:02 with the creation of NBC’s Sunday Night Football,
    0:02:04 which as of 2023,
    0:02:08 had over 20 million average viewers every single week.
    0:02:10 So as we welcome yet another games
    0:02:13 with a whole new wave of technologies being show boated,
    0:02:15 this episode is about dissecting
    0:02:16 which pieces of technology
    0:02:19 have truly moved the needle in athletics.
    0:02:20 And equally importantly,
    0:02:22 why other innovations have historically
    0:02:24 failed to make their dent.
    0:02:25 All right, let’s get into it.
    0:02:30 As a reminder,
    0:02:32 the content here is for informational purposes only,
    0:02:35 should not be taken as legal, business, tax,
    0:02:36 or investment advice,
    0:02:38 or be used to evaluate any investment or security,
    0:02:40 and is not directed at any investors
    0:02:42 or potential investors in any A16Z fund.
    0:02:45 Please note that A16Z and its affiliates
    0:02:46 may also maintain investments
    0:02:49 in the companies discussed in this podcast.
    0:02:51 For more details, including a link to our investments,
    0:02:54 please see a16z.com/disclosures.
    0:03:02 So Charlie, why don’t we actually start off
    0:03:03 with your background?
    0:03:06 You’ve got a pretty deep personal relationship
    0:03:06 to the Olympics.
    0:03:10 So maybe before we talk about what’s going on today,
    0:03:11 what actually led you here?
    0:03:15 – I had what some might call a very strange childhood.
    0:03:19 My dad was the chairman of NBC Sports for 25 years.
    0:03:22 When he retired in 2011,
    0:03:25 the New York Times wrote that he had produced
    0:03:29 nine of the 11 biggest events in the history of the world,
    0:03:30 most of which were Olympics,
    0:03:34 including like the 2008 Beijing Olympics
    0:03:36 and the ’92 Barcelona Olympics.
    0:03:40 He was the number two to the guy running all ABC production
    0:03:42 for the Munich Olympics
    0:03:45 when the Israeli athletes were kidnapped and killed.
    0:03:48 And there’s a crazy story about my father
    0:03:50 and his boss at the time, Runar Laj,
    0:03:54 standing outside the athlete’s pavilion,
    0:03:57 waiting, just looking up as a full moon, smoking cigarettes,
    0:03:58 having this beautiful moment.
    0:04:00 And eventually one said to the other,
    0:04:02 “You know, we should really go home.”
    0:04:05 And years later, when they did the security report,
    0:04:08 one of the terrorists said they had decided
    0:04:09 that they were just gonna kill
    0:04:11 the two guys smoking cigarettes out front
    0:04:14 and just go in because they’d been there so long
    0:04:17 and they were like slowing down the kidnapping.
    0:04:19 My very first job, 12 years old,
    0:04:21 was working at an Olympics as a runner,
    0:04:23 working for a producer telling stories.
    0:04:26 So yes, the Olympics were a big part of my life.
    0:04:28 – And I mean, that puts you in a unique position
    0:04:31 to observe for many years, right?
    0:04:34 Not just the latest Olympics and the Olympics in Paris.
    0:04:38 What did you learn from watching your father or your brother
    0:04:41 about what actually makes the game successful?
    0:04:45 – My dad was the very first runner in Olympic history.
    0:04:47 And what that means, that sounds funny,
    0:04:48 it sounds like he’s an Olympian.
    0:04:52 What that means is his job was, before the Olympics started,
    0:04:55 was to research the athletes,
    0:04:56 not just the American athletes,
    0:04:57 but the international athletes
    0:04:59 and learn their back stories.
    0:05:02 And then they would tell those stories before the games.
    0:05:04 And so people would engage with, you know,
    0:05:09 nobody’s following the 100 meter dash for three and a half
    0:05:10 years and then all of a sudden it’s like,
    0:05:12 oh, we all have to pay attention to Usain Bolt
    0:05:14 or Michael Johnson or whatever.
    0:05:16 In fact, oddly enough, the very first athlete
    0:05:19 he ever covered was an athlete
    0:05:22 who was accused of being transgender.
    0:05:25 And this is in the late 1960s, early 70s.
    0:05:27 It was the first athlete ever to sort of face that
    0:05:28 with blood testing and all this other stuff
    0:05:30 to try to figure it out.
    0:05:33 And it is probably the single most important thing
    0:05:35 about the Olympic success is that the Olympics,
    0:05:37 unlike all other professional sports,
    0:05:40 are a majority female audience.
    0:05:42 And they’ve done decades and decades of research.
    0:05:44 The reason they found out is because they created
    0:05:46 an emotional connection with the athletes
    0:05:47 through the storytelling.
    0:05:50 And so it’s really not the guy behind a football mask
    0:05:51 who you don’t really know doing this stuff.
    0:05:52 It’s someone you’ve gotten to know
    0:05:55 over the 16 weeks of the Olympics.
    0:05:57 And then there’s the patriotism of,
    0:05:58 I want to see America win.
    0:06:02 But my dad is largely credited with being
    0:06:07 the greatest storyteller in the history of sports.
    0:06:09 The people that he worked with were Jim McKay,
    0:06:11 originally, and then Bob Costas, and Al Michaels.
    0:06:13 We’re telling these stories.
    0:06:15 And I think what gets lost,
    0:06:19 often in the deluge of sports now,
    0:06:21 we are drawn as humans, I think,
    0:06:23 to the struggle of what got us there.
    0:06:25 There’s the famous line,
    0:06:27 the joy of victory and the agony of defeat.
    0:06:30 The idea that Sean White had three open heart surgeries
    0:06:33 before he was three years old and then went on to win,
    0:06:36 or Michael Phelps, his mom didn’t swim.
    0:06:37 He’d never been in a pool.
    0:06:39 And she was a single mom and an educator.
    0:06:41 This incredible American story.
    0:06:43 And he goes on to become,
    0:06:45 I mean, certainly the most decorated athlete
    0:06:46 in the history of the world,
    0:06:48 if not maybe the greatest athlete.
    0:06:50 And it’s the background that we care about.
    0:06:52 We learn to love these people and get to know them.
    0:06:54 We care about them so deeply.
    0:06:55 – Let’s dive into that idea of storytelling
    0:06:59 because the Olympics have been running for a long time.
    0:07:01 I mean, the original iteration of it,
    0:07:02 we’re talking thousands of years,
    0:07:04 but even in the last revival,
    0:07:07 we’re talking over 100 years of modern Olympics.
    0:07:08 That’s a lot of games.
    0:07:10 But when I originally reached out to you,
    0:07:11 I had this thesis.
    0:07:13 The last couple of years is all about AI.
    0:07:14 We’re going into this new Olympics.
    0:07:16 It’s gonna completely change the games,
    0:07:17 just like everyone’s saying,
    0:07:20 it’s gonna completely change everything.
    0:07:21 But when we chatted,
    0:07:24 you had a really interesting take that kind of took me back
    0:07:28 and made me reconsider the original thesis of this episode
    0:07:31 about how technology maybe in itself is not enough.
    0:07:34 What are the different technologies over,
    0:07:35 let’s say the last couple of decades,
    0:07:38 that have actually moved the needle in sports
    0:07:41 versus what I’d imagine are hundreds or thousands
    0:07:45 of other attempts to do the same that haven’t quite succeeded?
    0:07:46 – Sports is interesting
    0:07:49 because it’s the great aggregator, right?
    0:07:51 It’s what brings huge amounts of people together
    0:07:52 for a singular live event.
    0:07:54 We all watch it in unison,
    0:07:56 the Super Bowl being a great example,
    0:07:57 the World Cup, et cetera.
    0:07:59 And I think what gets lost,
    0:08:02 oftentimes in the storytelling of technology around sports,
    0:08:05 is that the technology has to actually move
    0:08:08 the experience of watching the sport forward
    0:08:10 in a way that makes it better,
    0:08:13 more accessible, more palatable, not just cool.
    0:08:15 I mean, there’s been a lot of really cool technology,
    0:08:17 but at the end of the day,
    0:08:19 when you talk about the most transformative technology
    0:08:20 in the mid ’60s,
    0:08:23 when my dad’s former boss, Ron Arledge,
    0:08:25 introduced instant replay, it was game changing
    0:08:28 because unless you are a professional athlete,
    0:08:30 you probably can’t see the nuances
    0:08:31 of what have just happened on this play.
    0:08:33 But now all of a sudden,
    0:08:35 if you’ve got Frank Gifford or Al Michaels
    0:08:38 or John Madden or Chris Collinsworth saying,
    0:08:39 no, look right there,
    0:08:42 see how he twisted on his right foot to do it,
    0:08:42 that’s incredible.
    0:08:44 Now all of a sudden you’re like, holy, that is incredible.
    0:08:45 It’s amazing, he did it.
    0:08:47 So there were four,
    0:08:49 and this is by no means the definitive list,
    0:08:52 but I think of four sort of transformative moments
    0:08:55 in terms of changing sport positively with technology,
    0:08:57 instant replay in the ’60s for sure.
    0:08:59 It was a massive change.
    0:09:02 In the early ’80s, the introduction of cable,
    0:09:04 so now all of a sudden, two things happened.
    0:09:07 One, sports basically became entirely live.
    0:09:08 People forget.
    0:09:11 The NBA finals until the early ’80s were on tape delay.
    0:09:13 People were not watching this stuff live,
    0:09:16 and then all of a sudden you get cable showing up
    0:09:17 and they’re telling you,
    0:09:19 look, this is all gonna be available all the time,
    0:09:21 and that cable ultimately became OTT,
    0:09:24 and so you’ve had this one great access point.
    0:09:26 And then in the mid ’90s,
    0:09:28 probably the most transformative piece of technology
    0:09:31 of our era, of our generation, is the yellow line.
    0:09:33 That for the first time,
    0:09:35 you could watch a football game
    0:09:37 and anyone could just walk in the room
    0:09:39 and instantaneously understand,
    0:09:41 oh, they’ve got this amount of distance to go
    0:09:44 to achieve their first down and be able to do this.
    0:09:46 And what’s interesting is you look at how much
    0:09:49 augmented reality has actually been brought into sports.
    0:09:52 Very little of it has been as effective.
    0:09:53 I mean, I think the shot tracer
    0:09:55 where you’re able to follow the golf ball
    0:09:57 or eagle eye with tennis,
    0:10:00 where it’s, okay, I can see if the ball was in or out,
    0:10:01 those technologies actually help
    0:10:03 the storytelling of the sport.
    0:10:07 And then I think probably in terms of just sheer engagement,
    0:10:09 other than Taylor Swift,
    0:10:12 fantasy is probably the single biggest thing
    0:10:14 that has affected sports in general,
    0:10:17 because all of a sudden you care about every single game.
    0:10:20 Like one of the challenges of baseball, football, et cetera,
    0:10:25 is I am a whatever, L.A. Rams fan.
    0:10:28 I don’t really care what’s going on with the dolphins
    0:10:29 unless it affects my standings.
    0:10:31 But now all of a sudden I’ve got fantasy
    0:10:35 and the quarterback for Miami Tua is on my fantasy team.
    0:10:37 Now I care about what’s happening in Miami games.
    0:10:39 So now all of a sudden you’ve got this engagement.
    0:10:40 I mean, let’s be honest,
    0:10:42 fantasy is basically a glorified Excel sheet.
    0:10:45 It’s technology that’s been around since the late ’80s,
    0:10:48 but inherently it enhances the storytelling.
    0:10:51 I talk to founders all the time.
    0:10:52 And one of the things I’m cautioning them about
    0:10:55 is how is what you’re doing making this better?
    0:10:58 Like gambling has become such a massive thing.
    0:11:00 So little of it is actually transformative
    0:11:03 because it’s not really enhancing the experience.
    0:11:06 And then you look at a company like, for example, prize picks,
    0:11:09 which has figured out how to really add drama
    0:11:11 and excitement around parlays.
    0:11:14 Like the technology is only there to enhance the storytelling,
    0:11:15 not the other way around.
    0:11:17 And I think the thing people constantly get lost is
    0:11:19 in the lead up to the Olympics, you’re seeing it already.
    0:11:21 They’re like AI Michaels
    0:11:22 and all these different things
    0:11:24 that they’re bringing to the game.
    0:11:27 Are you really gonna engage with the majority of those?
    0:11:28 I don’t know.
    0:11:31 The ones that actually make the game better,
    0:11:33 like the drop cam in the high dive,
    0:11:36 where the camera drops with the diver.
    0:11:38 It’s an extraordinary piece of technology
    0:11:39 because for the first time you understand the speed,
    0:11:43 you understand the ability of the athlete.
    0:11:45 There was a piece of tech a couple of years ago
    0:11:46 that they were trying out at the Olympics.
    0:11:50 It was like bullet time, like the matrix basically,
    0:11:51 where they line up a bunch of cameras
    0:11:53 in an arc around an athlete.
    0:11:55 And then they all take a picture at the same time.
    0:11:57 And then you stitch the frames together
    0:11:59 and it looks like you’re rotating around the athlete.
    0:12:00 Very cool, very cool.
    0:12:03 Basically never got used
    0:12:05 because fundamentally people didn’t engage
    0:12:08 with the technology because it wasn’t enhancing
    0:12:09 their understanding of the game.
    0:12:11 They used it in the home run derby
    0:12:13 at the all-star game baseball all-spot game this year.
    0:12:15 Again, really cool technology,
    0:12:16 but I don’t understand how it’s making
    0:12:19 my understanding of the game better.
    0:12:20 Whereas stat cast,
    0:12:22 where they’re explaining the launch angle of the ball,
    0:12:24 like we know this is a home run because of the launch angle
    0:12:27 before the ball ever travels far enough,
    0:12:29 that changed my understanding of the game.
    0:12:30 And I think that that’s a really hard thing
    0:12:33 for people to understand, particularly in technology,
    0:12:35 because they constantly lose track of the fact
    0:12:37 that just ’cause you, my mom used to say all the time,
    0:12:39 not her quote, someone else’s,
    0:12:42 but just ’cause you can do something doesn’t mean you should.
    0:12:44 A lot of people are sort of building technology
    0:12:45 without understanding like,
    0:12:47 how does this actually enhance the storytelling experience?
    0:12:49 – Let’s kind of roll through those.
    0:12:50 I mean, you mentioned yellow lines.
    0:12:53 That helps people understand the way football works.
    0:12:55 Instant replay also helps people understand
    0:12:58 what just happened and also hear from experts.
    0:13:01 Cable allows people to engage all together.
    0:13:03 And fantasy, like you said, kind of also expands the game,
    0:13:05 helps people get involved in other teams.
    0:13:08 So there’s a lot of really clear learnings there,
    0:13:09 but to your point,
    0:13:12 a lot of people are kind of just exuberantly excited
    0:13:14 about what’s on the horizon.
    0:13:15 Let’s use AI as an example.
    0:13:17 If you were a founder,
    0:13:19 having just heard all the things you shared
    0:13:20 about the few technologies
    0:13:22 that did actually move the needle in sports,
    0:13:24 and the reason that they did,
    0:13:26 how would you kind of coach them almost
    0:13:29 into adjusting their approach
    0:13:31 so that they can actually address a real problem
    0:13:32 per your point?
    0:13:35 – I’ll quote Chamath who is quoting someone else.
    0:13:37 When the refrigerator was invented,
    0:13:41 the guys that invented refrigeration did very well.
    0:13:44 But the people who did transformatively well was Coca-Cola.
    0:13:48 Like as soon as you figured out how to use the technology
    0:13:50 to then make another product,
    0:13:52 the reach was exponentially bigger.
    0:13:54 I’ll give you an example, sports betting.
    0:13:58 Sports betting is really not a good business.
    0:14:00 It’s usually four to 7% margin business.
    0:14:03 Parlays, in-game, multi-game, parlays, et cetera,
    0:14:05 they go to like a 27% margin business,
    0:14:07 but they’re only really possible because of technology
    0:14:10 ’cause you have to move so fast and sort of be adaptive.
    0:14:15 The beauty of sport is inherently it is this human endeavor
    0:14:18 where the rules are known, they’re very static,
    0:14:19 you’re not seeing a lot of change.
    0:14:22 So what can you do around that static component
    0:14:23 that can be really compelling?
    0:14:26 It’s like what AI was designed to do.
    0:14:30 And so I’m constantly finding myself talking to founders
    0:14:32 and saying there are 20 companies
    0:14:34 that are doing computer vision right now,
    0:14:36 like they’re all losing money,
    0:14:38 they’re all have cameras pointed at the field,
    0:14:40 they’re all basically doing the same thing.
    0:14:42 And it’s a race to the bottom
    0:14:44 because someone’s gonna commoditize it.
    0:14:46 And once we all sort of set the standard,
    0:14:48 a lot of those companies are gonna get killed.
    0:14:52 – And so if you can use AI to start to take the output
    0:14:55 of those technologies and start to build specific categories
    0:14:59 for players, coaches, betters, field technicians, et cetera,
    0:15:01 you’re gonna find businesses there
    0:15:02 because right now most of it’s still
    0:15:04 being done with pencil and paper.
    0:15:06 – Yeah, and just to double click on that,
    0:15:08 are there other technologies that you think
    0:15:11 we might see in this upcoming Olympics,
    0:15:14 whether it’s applied to actually making athletes better
    0:15:17 at performing, whether it’s in the distribution
    0:15:20 of the content or something else entirely?
    0:15:22 – I remember this is 16 years ago,
    0:15:25 but in the ’08 Olympics, the swimmers were allowed
    0:15:29 to wear suits, like full-body suits.
    0:15:34 And they were shaving like seconds off of world record times,
    0:15:36 which in sprinting is unheard of.
    0:15:39 I mean, even like Usain Bolt,
    0:15:40 I think over the course of his entire career,
    0:15:42 shaved a second off of his time,
    0:15:43 let alone doing it on every single race.
    0:15:45 And it was clear that the suit was doing,
    0:15:46 it was like a shark skin suit.
    0:15:48 It caused the water to move faster,
    0:15:50 like all this other stuff.
    0:15:53 And they changed the polyurethane or whatever
    0:15:57 the composite is for track and field a couple of years ago.
    0:15:58 And then all of a sudden, like world records
    0:16:01 were getting decimated because the rebound on the foot
    0:16:04 was so much higher, which is to say nothing
    0:16:07 of what Adidas and Nike and Puma are new balance,
    0:16:09 what they’re doing inside of a shoe,
    0:16:11 where someone can run a sub five minute
    0:16:14 or sub four minute mile or a two hour marathon.
    0:16:17 So what I’ll say is this,
    0:16:20 I think that if Michael Phelps had won 16 gold medals,
    0:16:22 but we didn’t know Michael Phelps’ story,
    0:16:25 his background, who he was, what was going on in his life,
    0:16:26 I don’t think people would remember it.
    0:16:28 I think the greatest athletes who ever lived
    0:16:30 are the athletes we have nostalgia for.
    0:16:32 Like we remember the story of Michael Jordan
    0:16:35 leaving for a year and coming back or LeBron leaving Cleveland
    0:16:37 only to come back and win it for Cleveland.
    0:16:39 Like we care more about that in a lot of cases
    0:16:41 than we do the stats, right?
    0:16:43 And so when I look at the technologies
    0:16:44 that I think are coming,
    0:16:46 AI Michaels is an awesome technology
    0:16:51 where they’re using AI and Al’s voice to be able to recap.
    0:16:53 And I think from a pure experience standpoint,
    0:16:55 you’re going to have a better experience
    0:16:57 because it’s not going to sound like Siri
    0:17:00 telling you what happened or seeing it in infographics.
    0:17:01 It’s going to feel like you’re getting a studio host
    0:17:03 telling you what’s going on.
    0:17:04 And the new camera technologies
    0:17:06 that they’re introducing around track and field
    0:17:09 and water polo are incredible.
    0:17:12 In reality, I think the technology
    0:17:16 that’s going to really change our experience
    0:17:21 is basic stuff that we take for granted, like Peacock.
    0:17:24 The fact that the streamer is set up in a way
    0:17:26 where you can create a bespoke experience of what you want.
    0:17:29 Like I tell people a lot of times all of the technology
    0:17:32 that really moves the needle in sports is super unsexy.
    0:17:33 Like I’ll give you an example.
    0:17:36 The yellow line, people are like, how do they do it?
    0:17:38 They isolate the players and they vote, no,
    0:17:41 they’re chroma keying the green on the field.
    0:17:42 It’s 50 year old technology.
    0:17:44 I’m not discounting what they did.
    0:17:45 What they did was incredible.
    0:17:46 Like the technology is amazing,
    0:17:48 but like the most difficult part,
    0:17:49 people had overthought for years
    0:17:52 ’cause oh, we have to create masks of every player.
    0:17:54 No, they had a green field.
    0:17:57 They’ve been working with green screens in Hollywood
    0:17:59 for a decade at that point.
    0:18:00 And they were just like,
    0:18:01 oh, what if we just take the green away?
    0:18:02 Boom, right?
    0:18:05 And so the thing I constantly go back to people with
    0:18:07 is like you have to be solving for the solution,
    0:18:10 not solving for the technology
    0:18:12 because people have shown me stuff in sports technology
    0:18:13 that is insane.
    0:18:15 It’s mind blowing.
    0:18:18 Somebody did a recreation of all the messy shots
    0:18:23 from messy’s perspective live in 3D in an Unreal Engine.
    0:18:25 I’m like, this is incredible.
    0:18:26 This is amazing.
    0:18:28 I have absolutely no idea what the applicable value of this is
    0:18:32 to a broadcast storytelling, but it’s really cool.
    0:18:33 You know what I mean?
    0:18:36 And I think people overestimate the value of cool
    0:18:39 over the value of how does this make the story better?
    0:18:42 And I go to all these sports conferences
    0:18:45 and they’re talking about like digital jerseys
    0:18:46 where you can change the number.
    0:18:48 Amazing, cool.
    0:18:49 – Not useful.
    0:18:50 – Yeah.
    0:18:51 – Yeah.
    0:18:52 Another example that you shared with me before
    0:18:54 is even just latency, right?
    0:18:55 We basically have the technology
    0:18:57 to have essentially no latency,
    0:18:59 but is that really necessary?
    0:19:01 I mean, there’s certainly a difference between
    0:19:04 zero seconds latency and a day latency, right?
    0:19:06 We’ve migrated from there.
    0:19:07 You want some immediacy,
    0:19:09 but do we really need to get to zero?
    0:19:10 Is one second too much?
    0:19:11 Is three?
    0:19:12 Is 12?
    0:19:13 Is 20?
    0:19:14 And I feel like there’s maybe a parallel there
    0:19:17 in asking that of any technology, right?
    0:19:19 Do we need precision or do we need something
    0:19:22 that to your prior points actually enhances the story?
    0:19:24 And so what is the right question there
    0:19:26 that people should be asking themselves
    0:19:29 if they’re evaluating like does a digital jersey
    0:19:32 that allows you to change your number help in some way?
    0:19:34 What’s the right question they should be posing?
    0:19:36 – Let’s use latency as an example.
    0:19:38 My company works inside of latency a lot
    0:19:41 because for certain things, it matters a lot.
    0:19:43 For officiating inside the NFL,
    0:19:46 they need to know instantaneously at sub-second latency,
    0:19:48 whether or not the ball was in or out
    0:19:50 and they’ve got to be able to look at it from every angle
    0:19:52 and they’ve got to be able to do that.
    0:19:55 Latency to the mass of people.
    0:19:56 Like I’ll give you an example.
    0:19:58 If you’re delivering video that people can bet against,
    0:20:00 you have to deliver it in sub two seconds of latency
    0:20:03 because the belief is somebody sitting in the stadium
    0:20:04 with a cell phone,
    0:20:06 if they have more than two seconds,
    0:20:08 could be like home run and you cheat the system.
    0:20:10 So the sort of general thesis is sub two seconds.
    0:20:13 And there is technology that allows you
    0:20:16 to deliver sub two seconds of latency to video,
    0:20:19 not at scale yet.
    0:20:21 There are a bunch of companies that say they can do it,
    0:20:24 but I mean, Amazon’s one of the three biggest companies
    0:20:25 in the world working on this.
    0:20:28 They are by far the fastest in delivering video
    0:20:31 from live sports and they’re still in double digit.
    0:20:32 But part of the argument is why?
    0:20:33 Like what do you need it for?
    0:20:34 If you want it for betting,
    0:20:35 when you look at the percentage of population
    0:20:38 that’s actually taking in-game bets still,
    0:20:40 I’m not saying they’re not going to, they clearly are.
    0:20:42 That’s clearly where we’re going.
    0:20:45 How we do that and why we do that is a question.
    0:20:50 I have had employees and partners and mentors
    0:20:54 and investors in this business and my last business
    0:20:58 who were fixated on these problems.
    0:21:00 And I found myself at odds with them a lot,
    0:21:02 just basically saying I don’t disagree
    0:21:03 that that’s where we’re going,
    0:21:06 but you want to be there when the adoptive part
    0:21:08 is going to occur and I think people forget that.
    0:21:10 And to your point, people forget.
    0:21:13 When you watch a game on cable television,
    0:21:15 it is a minimum of 30 seconds of latency.
    0:21:18 And if you’re watching it on someone’s streaming platform,
    0:21:20 I won’t name any of them for the risk of pissing people up,
    0:21:23 but you’re like at 90 seconds of latency.
    0:21:24 If I’m watching on my Android
    0:21:26 and you’re watching on your iPhone
    0:21:27 or I’m watching on my iPad
    0:21:28 and you’re watching on your Samsung or whatever,
    0:21:30 like they’re different codecs.
    0:21:31 There’s all this other stuff that’s going in.
    0:21:34 The latency is really significant.
    0:21:38 My dad used to take a ton of crap from reporters
    0:21:41 because they would tape delay a lot of the Olympics
    0:21:43 so that it would happen in prime time.
    0:21:45 So like the gold medal game for the dream team,
    0:21:47 they would hold the game and then air it live.
    0:21:48 So even if people knew results,
    0:21:52 they could watch it live at eight o’clock at night
    0:21:54 when everyone is home and they’re not at work
    0:21:56 like trying to watch it on their screen.
    0:21:57 So they did this study.
    0:21:59 First of all, at the time they did the study,
    0:22:03 which was like 20 years ago,
    0:22:06 less than 18% of the population in the United States
    0:22:07 live west of the Mississippi
    0:22:09 and they were already getting it taped late
    0:22:11 ’cause people will forget that almost everything
    0:22:14 appears on the West Coast later than the East Coast,
    0:22:16 meaning they’d delay it three hours.
    0:22:20 The ratings were always higher on the West Coast
    0:22:21 than the East Coast.
    0:22:22 So even if the East Coast got it live
    0:22:24 and the West Coast got it taped,
    0:22:25 the ratings were higher on the West Coast
    0:22:27 because the West Coast, even if they knew the results,
    0:22:29 they wanted to see the storytelling,
    0:22:30 they were engaged with the athlete
    0:22:33 and they wanted to see the event actually occur.
    0:22:35 You know, if you talk to sports reporters,
    0:22:37 they’ll be like, it’s very important
    0:22:39 that the Premier League, the World Cup game
    0:22:42 or the UEFA game or whatever match has to be live
    0:22:43 in America, like at four a.m.
    0:22:47 Those people are gonna figure out how to watch it.
    0:22:48 They’re gonna VPN it, they’re gonna whatever.
    0:22:49 That is not your audience.
    0:22:54 Your target audience is Bill and Sue who live in Colorado
    0:22:56 and who have three kids
    0:22:58 and they wanna get their kids down and have dinner
    0:22:58 and then they wanna sit down
    0:23:00 and they wanna watch the thing together.
    0:23:02 They’re not getting up at four a.m. to watch this.
    0:23:04 They wanna have a produced experience.
    0:23:06 The other technology that we talked about
    0:23:07 a couple of weeks ago,
    0:23:10 but I think it’s really important to drill down on this.
    0:23:13 For the last 30 plus years, actually,
    0:23:17 this goes back to ’96, giving users the ability
    0:23:20 to pick what camera angles to watch the game.
    0:23:21 So there’s a guy named Freddie Gidelly.
    0:23:24 He’s arguably, if he’s not the best,
    0:23:28 he’s one of the three best live sports producers
    0:23:29 who’s ever lived, right?
    0:23:32 I mean, he did zillions of Super Bowls.
    0:23:35 He basically did all of a sudden in a football forever.
    0:23:37 He launched Amazon’s Thursday Night Football.
    0:23:40 Freddie is a transformative figure in sports.
    0:23:43 Freddie has spent every day
    0:23:44 since he was in his early 20s,
    0:23:46 perfecting the art of understanding
    0:23:48 that you gotta go from camera one to camera four
    0:23:50 to camera 16 to camera 11, go to the audience.
    0:23:53 I wanna see the crying mom reacting to,
    0:23:54 okay, come back to Michael Phelps
    0:23:55 ’cause this is really beautiful.
    0:23:56 Okay, now come wide.
    0:23:59 I wanna see the expanse of 60,000 people sharing ’em on.
    0:24:01 Okay, now come tight to his opponent.
    0:24:02 Oh, the agony of defeat.
    0:24:03 Now come back wide.
    0:24:04 He’s gonna get the flowers from his sister
    0:24:06 who recovered from cancer.
    0:24:07 That’s storytelling, right?
    0:24:08 – Yes.
    0:24:12 – Joe Blow on his couch does not wanna do that.
    0:24:14 And every single time anyone has introduced you get
    0:24:17 to pick your angle thing, it never works.
    0:24:20 There’s never, they put all these BS numbers
    0:24:21 about engagement.
    0:24:24 Now, if someone built an AI platform
    0:24:26 that knew who you were and knew that you hated
    0:24:28 seeing the audience shots, you wanted to stay
    0:24:30 on the tight shot of Steph Curry
    0:24:31 because you care about Steph.
    0:24:34 You don’t care about random people or whatever.
    0:24:36 If AI knew that and had all the access
    0:24:37 to the cameras and all the other stuff,
    0:24:39 and AI Michaels is a great start.
    0:24:41 But if someone could actually produce the version
    0:24:43 of sports that I wanna watch that’s tailored to me,
    0:24:45 while you are also watching your version,
    0:24:48 ’cause as dark as this is,
    0:24:53 the Democrats on Instagram are seeing the chat
    0:24:54 that they wanna see in the comments
    0:24:56 on the same video that the Republicans
    0:24:59 are seeing bespoke experiences.
    0:25:00 AI is gonna be able to do that
    0:25:02 and deliver experiences that are worthwhile.
    0:25:05 But it takes understanding the expertise
    0:25:07 that goes into doing it that brings it to life.
    0:25:09 And right now there’s very little.
    0:25:10 I’m shocked, by the way,
    0:25:14 I’m shocked when I look at tech companies and sports.
    0:25:16 They’ll have either no people
    0:25:20 from the creative production sports world involved
    0:25:23 or really old executives or nobody.
    0:25:24 I’m always blown away by that.
    0:25:25 And I go back.
    0:25:27 The last time there was this sort of
    0:25:30 massive transformation in technology.
    0:25:31 You gotta go to the early ’90s
    0:25:33 with computer-generated imagery,
    0:25:35 with SGI boxes, Silicon Graphics boxes,
    0:25:38 and electric image in these technologies.
    0:25:40 The reason that you can watch Jurassic Park,
    0:25:43 the original, the 1993 original movie today,
    0:25:45 and still be like, God,
    0:25:46 that really does look like a real dinosaur.
    0:25:49 Like, it really looks like that Brachiosaurus
    0:25:52 is walking behind Laura Dern
    0:25:55 is because they took the guys who had spent 30 years
    0:25:59 as clay modelers making the Stan Winston monsters.
    0:26:01 And they brought them in and then they were like,
    0:26:03 no, no, no, you don’t understand lighting.
    0:26:04 You think lighting is here,
    0:26:06 but actually there’s 700 points of light
    0:26:08 that are making this shading work
    0:26:10 because when it comes through the leaf,
    0:26:11 it actually reflects off the leaf.
    0:26:13 And then you now watch movies
    0:26:15 that are produced today on Netflix.
    0:26:18 And you’re like, I don’t understand.
    0:26:21 This movie is 31 years after Jurassic Park came out
    0:26:23 and the graphics look like garbage.
    0:26:25 Meanwhile, Jurassic Park still holds up.
    0:26:28 It’s because they went to expertise.
    0:26:30 And if storytelling is the only thing that matters,
    0:26:32 go get the storytellers who understand
    0:26:34 how to use what you’re replacing to do this
    0:26:37 and make them a part of the team and make it great.
    0:26:39 – And I mean, we see this in basically all industries.
    0:26:41 Tech is applied everywhere now, right?
    0:26:43 So whether it’s financial services
    0:26:45 or real estate or healthcare,
    0:26:47 I think that’s a learning that you can’t necessarily
    0:26:50 just reshape these industries without the help
    0:26:51 of people within those industries.
    0:26:52 And it goes vice versa, right?
    0:26:54 There’s a reason some of these industries
    0:26:57 are still on pen and paper, like you mentioned before,
    0:27:00 that could benefit from some of these newer technologies.
    0:27:03 But I guess to flip that on its head, what you just shared,
    0:27:05 we already know that there’s a bunch of technologists
    0:27:07 who have created new things
    0:27:09 that maybe aren’t being applied effectively
    0:27:10 to the sports world,
    0:27:13 but are there things that you actually wish
    0:27:15 could exist within athletics,
    0:27:18 within the Olympics, for example,
    0:27:20 that you haven’t seen people address
    0:27:23 because the sports people know it’s a problem,
    0:27:25 but the technologists have no idea
    0:27:26 they’re over here in their corner
    0:27:27 building things that aren’t gonna work.
    0:27:29 – 30 minutes before we started this podcast,
    0:27:32 I was making my lunch, I was scrolling Instagram
    0:27:37 and there was somebody had taken a clip
    0:27:39 of Babe Ruth hitting a home run and using AI,
    0:27:42 they created frames that didn’t exist
    0:27:44 so they could show his swing in slow motion.
    0:27:48 One of the things that I think people don’t fully appreciate
    0:27:50 is I’ll use Secretariat as an example.
    0:27:53 Secretariat was not just a triple crown winner.
    0:27:56 Secretariat is still, someone will tell me I’m wrong,
    0:27:58 but I’m fairly certain Secretariat still holds
    0:28:02 the track records at two of the three triple crown fields
    0:28:06 and not by like a nose, by like horse lengths.
    0:28:07 When Secretariat won,
    0:28:09 Secretariat won by 14 horse lengths
    0:28:10 and he would beat almost every horse
    0:28:13 ever on the track again by that much.
    0:28:16 I would love to watch the Kentucky Derby
    0:28:18 with Secretariat on the field running.
    0:28:21 Like I love this one thing during the Olympics
    0:28:24 where they show like Lindsey Vaughn is skiing the track
    0:28:27 and they show her versus the Swedish girl
    0:28:28 who she’s competing against
    0:28:30 and they overlay the one girl.
    0:28:33 So now I can see when Lindsey’s ahead and she’s behind
    0:28:34 but they’re on the same course in the same thing.
    0:28:37 I’m like, okay, I now understand how close this is,
    0:28:38 not just a little clock on the side.
    0:28:41 And by the way, I would love to see the average human
    0:28:42 on that as well.
    0:28:43 – Well, yeah.
    0:28:43 – You can just see them like,
    0:28:45 they’re just completely off screen.
    0:28:46 – They’d be dead.
    0:28:48 – Yeah, having skied a couple of those courses
    0:28:50 and I’ve been skiing since I was two,
    0:28:53 I assure you it’s the equivalent of ice skating
    0:28:57 down a sheer mountain for miles.
    0:28:59 And they’re doing it at 100 and whatever.
    0:29:01 I mean, it’s like the first time
    0:29:03 someone took me out in an Indy car.
    0:29:05 They had like a two-seater and they put me in the front seat
    0:29:07 and Al Unser Jr. who’s one of the greatest
    0:29:09 Indy car racers of all time.
    0:29:12 And they let me drive like the first one
    0:29:14 and I’m like, I’m going fast.
    0:29:16 And then he drove it.
    0:29:19 And I went from, oh, this track isn’t that bad to,
    0:29:22 oh my God, like he’s a quarter of an inch off the wall
    0:29:24 going 215 miles an hour around the corner.
    0:29:27 Like incomprehensibly fast
    0:29:29 and you’re this high off the ground.
    0:29:30 To answer your question though,
    0:29:33 context is really, really difficult in sport
    0:29:35 to understand like the significance.
    0:29:38 Like we use words, but we’ve moved beyond words.
    0:29:41 And what I would like to really see is technology
    0:29:44 makes sport even more accessible and storytelling
    0:29:47 because the thing is, is to paraphrase Mark,
    0:29:49 the software eats the world.
    0:29:52 The one thing that I think we can probably feel
    0:29:55 pretty confident about live human sport
    0:29:58 is going to remain incredibly important
    0:29:59 because it is the last bathroom work.
    0:30:03 We’re not going to let LeBron start wearing animatronic legs
    0:30:05 that are allowing him to jump 60 feet in the air.
    0:30:07 Like that’s not really the tradition of the sport.
    0:30:09 Like if you see how baseball has sort of come back,
    0:30:11 it’s actually the things we used to joke about in baseball.
    0:30:13 Oh, it’s so slow, it’s so boring.
    0:30:15 Now there’s actually something to be said
    0:30:20 for the anticipation and the lack of like instant delivery
    0:30:20 that matters.
    0:30:23 And I think technology making that more available
    0:30:25 without interfering with it is going to be huge.
    0:30:27 I had a bunch of conversations with the team
    0:30:29 that’s doing the enhanced games.
    0:30:32 And I’m fascinated by how traditional as sports people
    0:30:34 have come back and I’m like, this is wrong.
    0:30:37 I’m like, well, have you actually talked to him?
    0:30:39 ‘Cause first of all, it sounds like what they’re doing
    0:30:41 is what you guys always should have been doing,
    0:30:43 which is like, if the FDA allows it,
    0:30:45 it should be allowed everywhere.
    0:30:48 But more importantly, you allowed swimming suits,
    0:30:50 you allowed rubberized sneakers.
    0:30:52 Like Phil Knight is a massive billionaire
    0:30:54 because he figured out that if you put rubber
    0:30:56 on the bottom of a sneaker that had grips on it,
    0:30:59 people would run faster than if they didn’t.
    0:31:01 It’s like, to your point, the guys who were competing
    0:31:05 in the Parthenon 400 years ago, 500 years ago,
    0:31:09 1,000 years ago, clearly weren’t doing it
    0:31:12 where the dirt had been brought in and chemically altered
    0:31:14 so that it had the exact padding
    0:31:15 for the friction of the grass.
    0:31:18 Like all of this stuff wasn’t taken account.
    0:31:20 And so technology’s made a lot of things better,
    0:31:22 but I think people just skate by the need for it
    0:31:25 to be great storytelling.
    0:31:29 – Yeah, to that point, I think people also miss attribute
    0:31:30 what is technology, right?
    0:31:34 Who is to say that an injectable is so different
    0:31:35 from a different type of shoe,
    0:31:37 which is so different from a software
    0:31:39 that allows you to review your footage in a different way?
    0:31:42 Like all of that is a form of technology.
    0:31:44 And it’s just different lines that people have drawn
    0:31:46 around what is and isn’t acceptable.
    0:31:47 And I guess it’s interesting at the very least
    0:31:50 to see people challenging those lines.
    0:31:52 And I think just to close things out,
    0:31:55 since you have been a student of the games,
    0:31:57 you’ve watched your father create
    0:31:58 the modern day version of them.
    0:32:01 What are you excited about this year?
    0:32:03 – One thing that has happened in the last 20 years
    0:32:05 is the amount of parody in sports
    0:32:08 that have traditionally been owned by Americans
    0:32:10 is eye-opening.
    0:32:12 I mean, I don’t know when this is gonna air,
    0:32:15 but last night, team USA basketball team came
    0:32:18 within one point of losing to an African nation
    0:32:23 that had never played in international basketball before.
    0:32:25 And I think that’s a function of technology.
    0:32:28 I would venture a guess that things like Starlink
    0:32:32 have actually allowed for people to consume training videos
    0:32:33 in YouTube and all those other stuff
    0:32:35 and learn how to play that game.
    0:32:39 And then you add to it that the ubiquity of technology
    0:32:42 and the quality of shoes and all those other stuff.
    0:32:45 So I think that that’s gonna be a huge part of it.
    0:32:47 I also think, and this is gonna be a weird thing to say
    0:32:50 on a podcast that is entirely about technology,
    0:32:53 I think the thing that is gonna be the most popular
    0:32:55 about this Olympics is gonna be the things
    0:32:57 that technology really isn’t touching.
    0:33:02 Like, obviously Simone Biles is this transformative
    0:33:05 freak of nature that comes along once in a generation
    0:33:09 that defies all we know about are genetics
    0:33:11 and HV and everything else.
    0:33:13 And I think that seeing her compete,
    0:33:15 particularly in the context of four years ago
    0:33:17 when she really bravely said,
    0:33:20 “I can’t do this ’cause I have a mental block.”
    0:33:22 And then overcame that.
    0:33:25 I think that we’re all rooting for this experience
    0:33:27 of watching her collectively as a group.
    0:33:29 When the Olympics is at its best,
    0:33:32 the thing the Olympics does that is beautiful
    0:33:36 is it brings us together, humanity,
    0:33:40 in a singular moment to celebrate excellence.
    0:33:43 And I do think that we do all hold excellence
    0:33:47 at the highest levels of our respect as humans.
    0:33:50 And that’s really what sport and the Olympics is about.
    0:33:51 The Olympics are run by what’s called
    0:33:52 the International Olympic Committee
    0:33:54 and it has representatives from every country
    0:33:56 that’s part of the IOC and they vote on what country
    0:33:57 it’s going to.
    0:34:00 And in a lot of cases, the people who are at the IOC
    0:34:03 are politicians, former military guys,
    0:34:05 like men and women who have served their country
    0:34:07 in different ways and get elected to this non-deplace.
    0:34:09 And so you’d think there’d be tension,
    0:34:13 but because it was about sport, there wasn’t.
    0:34:15 And yet they would talk a ton of smack
    0:34:16 about how they were gonna beat each other
    0:34:19 in some arbitrary sport that weren’t even on our radar.
    0:34:22 And my mom said the Olympics has the ability
    0:34:24 to replace war in many places
    0:34:26 where war would have happened.
    0:34:29 Not all war, obviously, but like the fact
    0:34:31 that these two people might want to fight each other,
    0:34:35 but because they’re given the FIFA World Cup
    0:34:38 or the Club World Cup or the Olympics or whatever,
    0:34:40 they have this opportunity to do it in a way
    0:34:42 that is actually team building,
    0:34:45 like people coming together, even though they’re competitors.
    0:34:47 And I think that that’s the thing
    0:34:48 that we can’t lose sight of with the Olympics
    0:34:51 is you’re gonna get inundated with all the cool technology
    0:34:53 and everyone will have it.
    0:34:55 Johnson and Johnson will have some cool way
    0:34:57 that you can pick your shampoo
    0:34:59 based on whatever Simone Biles does.
    0:35:02 But all of that is in the context of the fact
    0:35:06 that we’re showing up because we’re seeing the purest version
    0:35:09 of the human experience of what can the human body
    0:35:10 actually accomplish?
    0:35:11 And then what does that look like
    0:35:13 when it’s head to head with someone else
    0:35:16 who’s pushed themselves that hard?
    0:35:18 All of the garbage that we all watch on Instagram
    0:35:19 about the like, it’s inside of you,
    0:35:21 you just have to get up at 430 in the morning
    0:35:22 and eat your blah, blah, blah and all those other stuff.
    0:35:24 Like these people actually did that stuff.
    0:35:27 And now let’s see what they can actually do when they did it.
    0:35:28 – Yeah, and to your point,
    0:35:30 it’s a culmination of not just them being there,
    0:35:34 it’s their whole life being dedicated to that sport.
    0:35:36 And it’s just the most human thing.
    0:35:38 There’s been so many takeaways in this podcast,
    0:35:40 but I think to your point about whether it’s like concerts
    0:35:43 or live sports as technology continues
    0:35:45 to accelerate and eat the world,
    0:35:48 it’s become super clear that people are just craving
    0:35:50 these super human experiences.
    0:35:51 And I guess the Olympics is where
    0:35:53 the most super human of humans show up.
    0:35:56 So thank you for sharing both your past,
    0:35:58 but also your experience today.
    0:36:00 – Thank you for having me, I really appreciate it.
    0:36:04 – All right, if you made it this far,
    0:36:05 make sure you’re subscribed
    0:36:07 because we have several Olympic themed episodes
    0:36:09 dropping in the next two weeks.
    0:36:11 And if you enjoyed this episode,
    0:36:14 drop us a line at ratethispodcast.com/A16Z.
    0:36:16 We would love to hear from listeners
    0:36:19 as we work our way up to the podcast podium.
    0:36:20 We’ll see you next time.
    0:36:22 (upbeat music)
    0:36:26 (upbeat music)
    0:36:29 (upbeat music)

    The Olympics features over 11,000 athletes competing in 32 sports, attracting an audience of more than 10 million.

    In this episode, Charlie Ebersol, co-founder of the Alliance of American Football and Infinite Athlete, explores how new innovations like AI and bespoke broadcasting technologies are shaping the future of sports.

    Charlie also reflects on the storytelling legacy of his father, Dick Ebersol, a legendary sports producer who transformed how we experience the Olympics. We discuss the importance of making sports more accessible and engaging through technology that enhances, rather than distracts from, the human stories at the heart of the games.

    Whether you’re a tech enthusiast or a sports fan, this episode offers a unique look at the convergence of these two worlds.

    Resources: 

    Find Charlie on Twitter: https://x.com/CharlieEbersol

    Learn more more about Infinite Athlete: https://infiniteathlete.ai/

    Stay Updated: 

    Let us know what you think: https://ratethispodcast.com/a16z

    Find a16z on Twitter: https://twitter.com/a16z

    Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

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    Follow our host: https://twitter.com/stephsmithio

    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • When AI Meets Art

    AI transcript
    0:00:02 (upbeat music)
    0:00:06 On June 27th, our team headed to New York City.
    0:00:08 We are at the A16Z office
    0:00:11 for the first ever AI artist retreat.
    0:00:15 That was A16Z consumer partner, Justine Moore.
    0:00:16 Justine was one of many partners
    0:00:18 who attended this retreat,
    0:00:19 which brought together the builders
    0:00:22 behind some of the most popular AI creative tools
    0:00:23 in existence.
    0:00:28 That is, 11 labs, Korea, FIGL, Udio, ideogram, and civet.
    0:00:31 All together with 15 top artists.
    0:00:34 These are the folks who are often
    0:00:36 doing the coolest things with these sorts of tools.
    0:00:38 They’re kind of pushing the boundaries
    0:00:40 of what the tools can create.
    0:00:43 Today, you’ll get to hear from many of these AI founders,
    0:00:45 who together with these artists
    0:00:48 are advancing what it means to be creative.
    0:00:50 Art is going to get better than ever.
    0:00:53 The average art output is going to improve,
    0:00:55 but so is the ceiling.
    0:00:57 It also is a higher participation rate.
    0:00:59 Everyone who’s interested in creativity
    0:01:01 can be creative and express themselves,
    0:01:02 which is just so cool.
    0:01:04 That was Anish Acharya,
    0:01:06 general partner on the consumer team,
    0:01:08 but that’s not all.
    0:01:09 I’ve been a founder twice.
    0:01:12 I’ve been spinning records as a DJ for 25 years,
    0:01:14 and I’m all about AI and art.
    0:01:17 So what happens when you put all these investors,
    0:01:20 leading artists and creative tool founders,
    0:01:21 all into the same room?
    0:01:24 I mean, the vibes have been immaculate.
    0:01:25 And I think that the thing that’s the most surprising
    0:01:27 is how much everyone has in common.
    0:01:29 Like the founders are more creative,
    0:01:33 and the creatives and artists are more technical.
    0:01:33 I think the other thing
    0:01:36 has just been how interdisciplinary it all is.
    0:01:37 People making video,
    0:01:39 want to play with generative audio,
    0:01:40 people making music,
    0:01:42 want to play with sound effects.
    0:01:44 It’s just incredible to see.
    0:01:45 One of the coolest things was
    0:01:48 a lot of the founders had recognized people
    0:01:50 by their online screen names or knew,
    0:01:52 “Oh my gosh, you used my tool
    0:01:55 to create this incredible song that went super viral.”
    0:01:57 Or, “You used my product to make this
    0:01:59 kind of amazing video animation
    0:02:01 that our whole team was talking about for a week.”
    0:02:03 These are people who have been interacting with each other
    0:02:08 often daily online for the past six, 12, 18 months,
    0:02:09 sometimes even two years,
    0:02:13 but didn’t even know what each other looked like in person.
    0:02:16 Now today, you get a behind the scenes look into this event,
    0:02:19 including the origin stories behind many of these tools,
    0:02:22 which by the way, some have never been shared publicly,
    0:02:24 and have these tools,
    0:02:26 which have all gone through their own viral moments,
    0:02:28 are navigating this AI wave,
    0:02:30 and what they see on the horizon.
    0:02:31 Let’s get started.
    0:02:35 As a reminder,
    0:02:38 the content here is for informational purposes only,
    0:02:40 should not be taken as legal, business, tax,
    0:02:41 or investment advice,
    0:02:43 or be used to evaluate any investment or security,
    0:02:46 and is not directed at any investors or potential investors
    0:02:48 in any A16Z fund.
    0:02:50 Please note that A16Z and its affiliates
    0:02:51 may also maintain investments
    0:02:54 in the companies discussed in this podcast.
    0:02:56 For more details, including a link to our investments,
    0:02:59 please see a16z.com/disclosures.
    0:03:06 Here we are in 2024.
    0:03:08 We’re at an exciting inflection
    0:03:10 where your creativity is being unbounded
    0:03:12 by the tools available.
    0:03:15 – I mean, we’re early, but there’s more people
    0:03:17 making more art and more people making more tools
    0:03:20 to make art than ever before.
    0:03:23 And if you kinda look at the history of technology and art,
    0:03:25 every single time there’s been a new technology,
    0:03:28 the amount of art has dramatically increased.
    0:03:31 People worry that drum machines would compete with drummers,
    0:03:33 and instead there’s more people making more music
    0:03:35 with both drummers and drum machines than ever before,
    0:03:37 so I think there’s a sort of equivalent moment
    0:03:39 here in technology and art,
    0:03:42 where we’re at the beginning of everybody
    0:03:45 who has taste and interest in art being able to make it.
    0:03:48 – Many have drawn parallels to prior computing waves,
    0:03:50 but is this any different?
    0:03:51 – Well, what’s different is for the first time
    0:03:53 we’re creating these sort of left brain things.
    0:03:54 You know what I mean?
    0:03:56 Computers and computing platforms
    0:03:58 have really been in the business of precision,
    0:04:00 and now we’re creating products
    0:04:03 that are intentionally imprecise, beautifully imprecise,
    0:04:06 so it just feels like a whole different flavor
    0:04:09 for products and product design than we’ve ever seen before.
    0:04:11 – So let’s introduce you to some of the people
    0:04:12 behind those products.
    0:04:14 – We have companies here covering basically
    0:04:18 every sort of creative modality, image, video, music,
    0:04:20 3D speech, all those sorts of things.
    0:04:21 – That includes–
    0:04:23 – Connor, I’m a co-founder at UDO.
    0:04:24 – And–
    0:04:26 – Omar, I’m the head of design at Love & Labs.
    0:04:28 – Both companies are focused on audio,
    0:04:30 with UDO focused on music,
    0:04:32 while Love & Labs is tackling everything
    0:04:34 from voice to sound effects.
    0:04:35 Meanwhile, founders like–
    0:04:39 – Mohammed, I’m the co-founder CEO at Ideogram.
    0:04:40 – Victor and–
    0:04:41 – Diego.
    0:04:42 – Who are the co-founders of–
    0:04:42 – Greya.
    0:04:43 – And–
    0:04:45 – Hong, I’m working on VEGLE.
    0:04:46 – These founders are building
    0:04:48 at the increasingly sophisticated world
    0:04:51 of 2D imagery and video, plus 3D.
    0:04:54 Ideogram, for example, lets you generate AI imagery
    0:04:56 with accurate text embedded,
    0:04:59 a surprisingly difficult technical feat.
    0:05:00 VEGLE, on the other hand, is building
    0:05:03 at the intersection of video and 3D.
    0:05:06 Meanwhile, Greya’s come up with a suite of AI tools,
    0:05:08 like upscalers and real-time generation.
    0:05:12 Or, in the case of Civit, a new breed of marketplace.
    0:05:14 – My name’s Maxwell Holker.
    0:05:17 I am COO at Civiti and co-founder.
    0:05:18 – Yes, and I’m Justin Mayer.
    0:05:21 I’m the COO and co-founder of Civit as well.
    0:05:22 – And CPO and CTO and–
    0:05:24 – Lots of things, the joys of a startup.
    0:05:26 We are a massive community of people
    0:05:29 making tons and tons of AI creations,
    0:05:33 using community-made models with community-made patches
    0:05:35 to those models called LORAS.
    0:05:37 We give people the ability to either train
    0:05:40 on a few specific models, so a model focused on anime,
    0:05:42 or a model focused on being semi-realistic.
    0:05:44 Or they can select their own custom model
    0:05:46 to train on top of.
    0:05:48 – With AI moving so quickly, it’s clear
    0:05:50 that we no longer live in a world
    0:05:52 of just chat GBT and mid-journey.
    0:05:55 Numerous companies have springboarded into the zeitgeist
    0:05:57 and grown at unprecedented rates.
    0:06:00 So we thought it was fitting to take a step back
    0:06:02 and document this whirlwind of a journey.
    0:06:04 While many of these founders have been quietly working
    0:06:08 in research for years, their origin story often started
    0:06:10 from scratching their own itch.
    0:06:11 Muhammad from I8Gram.
    0:06:15 – I guess part of it is that there is this thesis
    0:06:19 that everybody has an innate desire to create.
    0:06:24 And as humans, we have this inner creative child.
    0:06:28 The education system sometimes kills
    0:06:30 this creative child, unfortunately.
    0:06:34 And what’s finally possible with technology and AI
    0:06:38 is to help people express themselves visually
    0:06:39 and creatively.
    0:06:40 So that’s the interesting part.
    0:06:45 When you think of using image for communication,
    0:06:48 then you can communicate much more effectively
    0:06:51 if you have image and text together.
    0:06:54 – For Muhammad, it really was this unique combination
    0:06:56 of text and imagery.
    0:06:59 – For me, image and video is dear to my heart
    0:07:01 and very personal.
    0:07:03 – But for Connor, it was his connection to music.
    0:07:06 – Music for me, I think, is very special medium.
    0:07:07 It’s everywhere at all times.
    0:07:09 Like it’s in the background when you’re at a restaurant
    0:07:11 or a cafe, you’re listening to your headphones
    0:07:12 and you’re going to work in the morning.
    0:07:15 It really has an emotional resonance with people.
    0:07:17 And for me, making that abundance,
    0:07:19 like the kind of promise of generative modeling
    0:07:21 is that a lot of this can be far more abundant
    0:07:23 than it ever was before.
    0:07:24 – And for Victor, it was his discovery
    0:07:27 that programming itself was the creative gateway.
    0:07:29 – When I discovered about programming,
    0:07:32 that was great to me because I realized that through coding,
    0:07:33 you can also be super creative.
    0:07:37 But the moment where I discovered about early gen AI models
    0:07:40 like DCGan and later on, StyleGan,
    0:07:41 that’s when my mind was blown.
    0:07:45 And when I realized about the creative potential
    0:07:46 that this technology had,
    0:07:48 and that’s when I fell into the rabbit hole.
    0:07:49 And I feel like Korea, to me,
    0:07:52 it’s been kind of the snowball that it has started
    0:07:55 with me realizing that you can use artificial intelligence
    0:07:57 in a creative way.
    0:07:59 – But for Omar, it was building his own side projects
    0:08:01 and a desire to share what he was learning
    0:08:04 that actually propelled him into his role at 11 Labs.
    0:08:07 – It’s really funny, actually.
    0:08:10 I, over the last maybe couple of years,
    0:08:13 started diving into AI tools when ChatGBT came out
    0:08:15 and started making things on the side for fun.
    0:08:17 One of those was a children’s book
    0:08:19 that ended up accidentally going viral.
    0:08:22 And that kind of was my journey into AI.
    0:08:23 Through that and making that book,
    0:08:25 I started exploring other AI tools.
    0:08:29 And what I really enjoyed was sharing what I was doing
    0:08:30 and how I made it.
    0:08:33 So I discovered 11 Labs and made a podcast with 11 Labs
    0:08:36 where I was talking to a fictional figure
    0:08:38 and we were having a back and forth conversation
    0:08:40 that also kind of did the numbers on Twitter.
    0:08:42 And then I was like, I love using this tool.
    0:08:45 I’m gonna make my own AI short movie.
    0:08:46 Actually, Justine and I are friends.
    0:08:48 And so I showed it to her and I was like,
    0:08:51 I kind of need free credits because this movie
    0:08:53 is using up all the credits on 11 Labs.
    0:08:55 And she’s like, you should meet the founder, Maddie.
    0:08:57 We met, we really hit it off.
    0:08:59 And Maddie, in classic Maddie fashion,
    0:09:02 was very direct and at the end of the call was like,
    0:09:05 hey, we’re actually looking to hire someone to lead design.
    0:09:06 Are you interested?
    0:09:09 And then to work on a product that I’d used for over a year.
    0:09:10 That experience also gave Amar
    0:09:13 a taste of just how quickly this space moves
    0:09:15 and also a hit of virality.
    0:09:18 It happened because a friend of mine had their first kid
    0:09:21 and I read her children’s book actually.
    0:09:21 I was reading it and I was like,
    0:09:23 this story kind of makes no sense.
    0:09:25 So, so I went back home.
    0:09:26 I’d been using the journey a lot,
    0:09:28 chat to you two weeks old,
    0:09:30 combine the two to create that book.
    0:09:33 And then I was like, how do I get this published?
    0:09:35 And Amazon has this amazing publishing service.
    0:09:37 You can get a book out within 48 hours.
    0:09:41 I had a paper back in my hand in 72 hours, so fast.
    0:09:44 And it’s really interesting because writing a book
    0:09:46 and publishing on Amazon is like,
    0:09:48 it was almost like iterating on software.
    0:09:49 If I discovered a type or whatever,
    0:09:51 I just updated the PDF and the new book was out
    0:09:53 and a new publishing line was out.
    0:09:56 And so, yeah, I put it out there,
    0:09:57 got a ton of virality from that.
    0:10:01 And yeah, that was a really interesting experience.
    0:10:04 – Pre-AI, we were in this era of consumer
    0:10:07 where it was just really hard to get people’s attention,
    0:10:09 really hard to get them to download a new app
    0:10:10 or try a new tool.
    0:10:13 You had to spend a lot of money on customer acquisition.
    0:10:16 Now, just with the real excitement around AI,
    0:10:18 if you make a cool product,
    0:10:20 you can get it into the hands of people
    0:10:22 and get them using and talking about it.
    0:10:25 – This was the case for Victor and Diego at Cria,
    0:10:28 who eventually met their own viral moment,
    0:10:29 although it didn’t come easy.
    0:10:32 – First of all, it was called Geniverse,
    0:10:36 coming from Generative Universe, best name ever.
    0:10:38 And essentially, it was like two things.
    0:10:40 It was on the one side, an open source library
    0:10:43 that it was kind of integrating all the cool stuff
    0:10:45 that it was available at that moment.
    0:10:47 And on the other side, it was a creative tool.
    0:10:49 And the way how it looked, it was like super experimental.
    0:10:52 Like, we didn’t really know how to do UI design
    0:10:53 or any of that.
    0:10:56 Like, the background really had stars and everything.
    0:10:59 So it was like a galaxy, like the Generative Universe, right?
    0:11:03 And then you could put text, you could put images,
    0:11:05 and you had a few things that you could tweak
    0:11:06 and you could generate images.
    0:11:09 And you would see like the image evolving in real time.
    0:11:12 And the images that you liked, you could keep them.
    0:11:14 And they were added to this kind of universe.
    0:11:17 And essentially, you ended up with a ton of images
    0:11:18 in this interactive space.
    0:11:22 So for us, it was always with the same idea in mind,
    0:11:24 on the one side, controllability.
    0:11:26 And on the other side, intuitiveness.
    0:11:30 Like, how do we make tools that doesn’t look daunting?
    0:11:32 Because AI, in the end, is like a new creative medium.
    0:11:34 A lot of people are using it for the first time.
    0:11:37 And we want them to have the inexperience
    0:11:39 where the AI does what you expect to do.
    0:11:42 And you don’t need to learn about crazy prom and generings
    0:11:46 and all these tweaks up to get good results.
    0:11:47 And on the other side is controllability
    0:11:49 because we are dealing with creatives.
    0:11:52 We are dealing with folks who are not just OK
    0:11:54 with having a beautiful image.
    0:11:55 They want that beautiful image.
    0:11:59 So these are the two core principles that we had since then.
    0:12:03 And we built kind of a Figma-ish interface for AI.
    0:12:07 And we had every single utility that you had at that point
    0:12:08 with the stable diffusion in there.
    0:12:11 We had like thousands of AI models that you could use.
    0:12:13 We had every single technique, like every control net.
    0:12:15 Everything was in there.
    0:12:16 But you know, it was not working.
    0:12:18 It was like a learning curve that some people
    0:12:20 were just not willing to take.
    0:12:24 So then we have the first kind of virality moment
    0:12:27 when we ship this thing that it was almost like an equivalent
    0:12:28 to a meme generator.
    0:12:31 I remember that we were seeing all of these images on Twitter
    0:12:33 with the spirals, right?
    0:12:35 So we were like, well, what’s going on with these spirals?
    0:12:36 Like, we can do it.
    0:12:38 This is like one day of work.
    0:12:40 And I remember at that point, Diego was like,
    0:12:41 we should do something with this.
    0:12:43 We should do something with this.
    0:12:44 It’s getting so viral.
    0:12:45 And I was more like in the mood of, like,
    0:12:48 we need to ship this whatever feature we were working on.
    0:12:50 At that moment, until at one point, we were like,
    0:12:51 OK, let’s fucking do it.
    0:12:53 And we did it like in the sketchiest way possible,
    0:12:55 like in one or two days.
    0:12:57 And we shipped it in Twitter and it got viral.
    0:13:01 It was like the first time that we
    0:13:04 lived something that I had read about in terms of,
    0:13:06 this is what PMF looks like.
    0:13:09 That’s the first time I was like, oh, Jesus Christ.
    0:13:11 OK, this is how it looks.
    0:13:16 OK, I see you go to sleep and I can feel the heartbeat.
    0:13:17 And then you sleep three hours.
    0:13:21 You wake up because you know that there’s stuff broken.
    0:13:23 The email starts to get flooded.
    0:13:24 Twitter starts to go in there.
    0:13:28 Suddenly, literally, every day was like crazier than the one
    0:13:29 before.
    0:13:31 I was like, oh, my God, 1,000 people.
    0:13:32 Oh, my God, 10,000 people.
    0:13:34 And there’s like, oh, my God, like,
    0:13:36 Football Club Barcelona, like number one soccer club just
    0:13:37 used us.
    0:13:37 What?
    0:13:40 And why isn’t like, how many followers they have?
    0:13:42 Oh, my God, 100 plus million followers on Instagram.
    0:13:46 OK, I feel like it was actually hard in the sense
    0:13:52 of as a founder, you’re like, I’ve put multi amounts of years
    0:13:54 into like many things.
    0:13:56 And then the thing that we literally are like,
    0:13:59 it’s not important gives you all the success.
    0:14:01 So it’s a moment of reflection.
    0:14:07 You’re like, sometimes like the world throws truths at you.
    0:14:11 But those years of work were not all for nothing.
    0:14:14 And I don’t think like the years that we’ve been working on
    0:14:14 was like a waste.
    0:14:15 No, it actually is.
    0:14:18 Oh, that’s how you learn on the technical level, how it works.
    0:14:20 I mean, because it was so much failure,
    0:14:23 we learn about, OK, how do you communicate with your co-founder?
    0:14:26 I think that’s something important to note about those times
    0:14:30 is that we were very, very aware that this was a trend
    0:14:35 and that this was not the end product that we were building.
    0:14:38 It was like almost like a marketing engine
    0:14:41 that we were using to get better branding and to get known.
    0:14:43 They were finding us because of one reason,
    0:14:45 but they were staying because of another one,
    0:14:47 which was like this other product that we were working on.
    0:14:51 Even when we knew that, I think that the core learning
    0:14:56 that we got from this experience is that the AI field
    0:14:59 changes constantly, like every month or every two months.
    0:15:03 There are new breakthroughs, new techniques, new ways
    0:15:04 of doing things.
    0:15:07 And the tool that we were building,
    0:15:09 it was like already starting to get too complex
    0:15:12 because we were trying to put everything in a single tool.
    0:15:14 And I think that what we learned with the experience
    0:15:18 of the spiral virality is that there’s a lot of value
    0:15:23 on simplifying super niche and simple use cases.
    0:15:29 And that was the case again when LCMs were released.
    0:15:32 We saw this technology, and at that moment,
    0:15:35 we used all the experience that we got from the first virality
    0:15:36 to engine the second one.
    0:15:39 And the second one, we knew that it was not a trend.
    0:15:41 It was something extremely valuable.
    0:15:44 We were like finally being able to get that interaction
    0:15:46 that we were looking for for almost years, right?
    0:15:49 Like we can generate images in real time
    0:15:51 and have full control of the colors, the composition,
    0:15:52 the shapes, everything.
    0:15:55 That was almost like a dream come true.
    0:15:58 Victor and Diego have now hit virality several times over,
    0:16:00 but can you engineer that momentum?
    0:16:04 In some cases, it’s all about having a single critical feature
    0:16:05 not offered elsewhere.
    0:16:07 Mohamed from IDU Grimm.
    0:16:12 So basically, it was the version 0.1, as we called it.
    0:16:17 And this is back then in September of 2023.
    0:16:19 And it was a model that was working.
    0:16:26 It wasn’t perfect, but we felt like it’s already good enough
    0:16:27 to give it to users.
    0:16:30 And it was the first model that could put legible text
    0:16:31 into images.
    0:16:35 So it kind of went viral because of the unique capability
    0:16:40 of the model, somehow the ability to put text into images
    0:16:42 felt needed.
    0:16:46 But in other cases, it’s about cleverly enabling the masses,
    0:16:49 or in this case, the memesters, by drastically reducing
    0:16:51 the barrier to participate.
    0:16:54 Here’s hung with fake old story.
    0:16:55 It went pretty viral, right?
    0:16:58 What was that like experiencing to put a product
    0:17:01 in the hands of so many users and also see that kind
    0:17:02 of spread on its own?
    0:17:06 Yeah, it was– we didn’t anticipate that for sure.
    0:17:09 In the very beginning, we were thinking most targeting content
    0:17:10 creators.
    0:17:14 But somehow the meme makers and memesters stayed catch up on it.
    0:17:16 And that’s how it got pretty viral.
    0:17:19 And also, thanks to some of the templates,
    0:17:22 we spent so much time discussing why this is the case.
    0:17:25 There was this template, the Joker Lil Yachty coming
    0:17:26 on the stage.
    0:17:28 And there’s a Joker character that
    0:17:29 we placed down on the video.
    0:17:33 And we’ve seen millions of different characters
    0:17:35 just remixing the same moment.
    0:17:38 And we realized that the main reason was used to use.
    0:17:42 It’s so easy to– basically, you can upload one image.
    0:17:44 And then one click, choose that template.
    0:17:47 And then in just a matter of seconds,
    0:17:51 you’ll have yourself basically in that same moment.
    0:17:54 Maybe one other aspect of the virality is, as you said,
    0:17:56 the meme makers got ahold of it.
    0:17:59 There’s this kind of fun, maybe even silly, aspect to it.
    0:18:00 How have you thought about that?
    0:18:03 Well, I think that speaks to the entertainment value.
    0:18:07 And for anything to have real entertaining value,
    0:18:07 it has to work.
    0:18:09 It has to work well.
    0:18:12 And that actually requires a lot of rigorous in the research
    0:18:13 side.
    0:18:16 So we are pretty serious about being silly.
    0:18:20 And it takes quite a bit of rigorous research to do that.
    0:18:22 And the second thing is, you have
    0:18:25 to have a tool that provides precise control.
    0:18:28 And then because people are getting what they want,
    0:18:31 they can have all kind of a variety of fun with it.
    0:18:33 You’ve mentioned characters and templates a few times.
    0:18:35 What are some of your favorite examples
    0:18:37 of those generated on the platform?
    0:18:40 One is the Joker/Kamiyanthus state template.
    0:18:42 That one is basically the moment we realize,
    0:18:45 well, actually, people want to remix.
    0:18:48 And there is this virality and memes aspect of it.
    0:18:53 And the second one is, there has been one Rakuten advertising
    0:18:53 song.
    0:18:55 And people are dancing with this.
    0:18:57 And we’re also seeing millions of people remixing
    0:18:59 that same template.
    0:19:02 And this is interesting for us, because you make us realize
    0:19:06 that as long as there is this fun elements to it,
    0:19:08 people actually don’t mind this content
    0:19:10 having a little bit of a brand message.
    0:19:11 When you think about applications,
    0:19:14 and I know it’s early days, but have there
    0:19:16 been any that have surprised you about the ways
    0:19:19 that Vigil has been applied every time a founder creates
    0:19:20 a product?
    0:19:22 They have applications that they envision.
    0:19:24 And then the best products are often
    0:19:27 people are using them in alternate ways that surprise them.
    0:19:30 Yeah, that was exactly the case for us.
    0:19:32 In the very beginning, we were mainly thinking
    0:19:34 of movie makers, game makers, using–
    0:19:37 this might be a quick animation,
    0:19:38 pre-visualization tool for them.
    0:19:40 It’s actually pretty useful for that.
    0:19:43 And we’ve also seen the early users adopting to that.
    0:19:46 But then we never anticipated the meme search.
    0:19:50 So since that, we’ll be also providing those templates.
    0:19:53 So we’ve been keeping track of the latest trendy dance moves,
    0:19:55 sports events, et cetera.
    0:19:59 And we’ve also seen content creators hopping on to this.
    0:20:01 They are actually reaching out to us,
    0:20:04 say, can you feature our dance, our song, on your platform?
    0:20:07 And then can we collaborate on promoting
    0:20:10 some of those that’s been really interesting?
    0:20:13 We ask Connor the same question around what he’s learning
    0:20:16 by seeing how the masses are using UTO.
    0:20:19 The model we originally launched was a model which
    0:20:20 generated 32-second clips.
    0:20:22 And so to make it kind of a full track,
    0:20:24 you would extend that in various directions.
    0:20:27 You would add an intro, add maybe a chorus and an outro
    0:20:28 and stuff.
    0:20:29 And you would build a song like this.
    0:20:31 And you would start with these chunks.
    0:20:33 And I suppose we’ve actually come to realize quite quickly
    0:20:36 that people’s experience with music when they ask for, say,
    0:20:38 a song is actually a lot more focused on that.
    0:20:41 So they kind of want a song that begins at the beginning,
    0:20:42 maybe ends at the end.
    0:20:44 It’s maybe– it doesn’t have to be long.
    0:20:45 It could be like a short two-minute clip.
    0:20:47 But it has a verse and a chorus and a verse.
    0:20:48 And there’s a structure to it.
    0:20:52 And so I suppose we actually underestimated just how important
    0:20:52 that was.
    0:20:54 And so that’s something we were making steps to where
    0:20:55 it’s rectifying recently.
    0:20:59 11 Labs was also no stranger to the surprising and inspiring
    0:21:00 user behavior.
    0:21:03 Yeah, I think one of the most surprising ones
    0:21:05 was people who had lost their voices
    0:21:09 and then had used 11 Labs to bring their voices back to life
    0:21:11 and then do the thing they loved doing.
    0:21:13 So we had Lori Cohen, who was a lawyer.
    0:21:15 She lost her voice one morning.
    0:21:18 And a friend of hers helped her replicate her voice
    0:21:19 with 11 Labs.
    0:21:21 And then she was back in the courtroom delivering arguments.
    0:21:24 And that, to me, is just such an incredible moment
    0:21:26 because you don’t expect that.
    0:21:28 And I think our idea was like, hey,
    0:21:29 we’re going to give ideas of voice
    0:21:31 with our product and our tools.
    0:21:33 But this gave someone their own voice back.
    0:21:35 And I think that was such an amazing thing to see.
    0:21:38 And we saw that again with a climate activist, Bill
    0:21:41 Wheel, who was delivering his award speech.
    0:21:43 He suffered from ALS, unfortunately,
    0:21:45 but, again, was able to replicate his voice
    0:21:46 and then deliver that award speech.
    0:21:49 So I think those kinds of things are just like–
    0:21:51 you’re like, wow, technology being used in a way
    0:21:51 we didn’t see it.
    0:21:54 And now we want to lean into that and, of course, help others.
    0:21:54 Yeah.
    0:21:56 Maybe in the opposite sense, have there
    0:21:58 been any applications that you’ve actually
    0:22:00 built or designed for where you’re like, everyone’s
    0:22:02 going to use it for this, obviously.
    0:22:04 Or that’s actually not been the case?
    0:22:04 It’s interesting.
    0:22:07 When we launched dubbing and automated dubbing,
    0:22:08 we thought, yeah, this is it.
    0:22:10 Like, everyone’s just going to use automated dubbing.
    0:22:10 It’s going to be great.
    0:22:13 And of course, with dubbing, one of the most important things
    0:22:14 is accuracy, right?
    0:22:16 And so automated dubbing, we realized,
    0:22:19 people still want a lot of creative control on that.
    0:22:22 And so we ended up having to build dubbing studio, which
    0:22:26 allowed people to go really fine tune that dub and change
    0:22:27 a lot of the content.
    0:22:29 And then we also introduced 11 Studios,
    0:22:31 which was basically creative teams
    0:22:34 that help you dub your content with professionals.
    0:22:35 We’re really good at that.
    0:22:37 And so we realized that actually was
    0:22:40 what people needed more of and not just automate everything
    0:22:41 and all the things, right?
    0:22:43 And then it actually picked up again.
    0:22:45 And this is something even when I was working at Palantir,
    0:22:47 you learn, which is like the temptation
    0:22:49 to try to automate everything or to use intelligence
    0:22:50 for everything.
    0:22:52 But actually, there’s so much value
    0:22:54 in having someone in the middle and still having
    0:22:57 that human touch to take it to that final step with something
    0:22:59 we learned with dubbing.
    0:23:02 And as these companies get all this new data,
    0:23:03 it’s not always easy to figure out
    0:23:06 who they should be catering to.
    0:23:09 So how do you think about what you build and for who?
    0:23:11 Your TAM is everyone, in theory.
    0:23:14 I think what we acknowledge is that we probably
    0:23:17 have different types of users, like distinctly different types
    0:23:19 of users, at the very top being, does someone
    0:23:23 in a studio who’s making an album at the very top level?
    0:23:26 And then at the end of the scale is maybe someone
    0:23:28 on their phone who wants, in a minute,
    0:23:31 they want just a funny song to send to their friend.
    0:23:34 And those are two very different experiences
    0:23:38 and somewhat similar to the kind of output
    0:23:41 you can get from just an instrument in general.
    0:23:42 Someone can have a guitar at home
    0:23:44 that they play just to have fun from time to time.
    0:23:46 It’s like a totally personal thing.
    0:23:47 It’s not anything necessarily serious.
    0:23:50 It’s just a way to express yourself with it musically.
    0:23:52 And the same way someone can take that same guitar
    0:23:55 and a professional can take it into a studio
    0:23:57 and make it part of something fantastic,
    0:24:00 we like the technology to basically enable
    0:24:02 all ends of the oil parts of that spectrum.
    0:24:05 Several are unsprisingly using their flywheel of new users
    0:24:08 to inform their decisions.
    0:24:11 Yeah, we kind of use our user base
    0:24:14 and the prompts that they enter into the system
    0:24:18 to decide how to evaluate the quality of the model
    0:24:20 and what to prioritize.
    0:24:23 What’s interesting is our users used ideogram
    0:24:25 to tell us what they want.
    0:24:27 So they were like, we want image upload,
    0:24:30 we want comment, we want more servers.
    0:24:34 So I guess the good news is we already have this flywheel
    0:24:36 of users coming and using it.
    0:24:38 Some are paid, some are free.
    0:24:40 And that sets the vision for us.
    0:24:43 Hung from Vigol has actually used these new learnings
    0:24:46 to expand who they’re building for.
    0:24:49 How are you thinking about who you now build for, right?
    0:24:51 Are you pivoting or adjusting
    0:24:53 to incorporate these new use cases?
    0:24:57 So we are broaden our target audience in this sense.
    0:25:01 So we are seeing this as eventually we’re going towards
    0:25:04 the direction of a new type of AI power content platform.
    0:25:06 And the content platform is really important
    0:25:08 to have all these creators.
    0:25:11 And those are still the content creators, the artists,
    0:25:13 the movie makers, the game makers,
    0:25:14 the demo game designers.
    0:25:18 They are the sources for all those new ideas,
    0:25:20 all those new templates.
    0:25:23 And then we’re broaden this into content consumers.
    0:25:27 Basically Vigol is a new way to consume content.
    0:25:29 Before AI, it was mainly like,
    0:25:33 if I like the moment I will share it, I will like it.
    0:25:35 But there’s a deeper engagement
    0:25:36 you can have with that moment.
    0:25:39 I can basically, I love this moment so much
    0:25:42 that I want to put my own avatar in it.
    0:25:43 It’s almost like in a parallel universe,
    0:25:47 I want to see how this looks really if that moment myself.
    0:25:49 So this is a new kind of content consumption.
    0:25:53 And that’s actually one of the most important aspect.
    0:25:58 The variety actually comes from all those creative ideas.
    0:26:00 So for us, it’s all about empowering
    0:26:02 those creative community first,
    0:26:03 making sure they have what they want.
    0:26:04 They have the best tool.
    0:26:07 They have early access to new features.
    0:26:09 They have almost private channels.
    0:26:12 They have almost unlimited access.
    0:26:13 The team at Krea, on the other hand,
    0:26:16 is more focused than ever on experimentation
    0:26:18 and their signal for success.
    0:26:22 When your users are better at using your tool than yourself.
    0:26:25 How I think about it is that every tool that we launch
    0:26:27 follows a similar process.
    0:26:30 And I think that it all starts with a hypothesis.
    0:26:32 And I think that this initial hypothesis
    0:26:33 needs to come from the founder
    0:26:35 and needs to come from your own intuition.
    0:26:38 But we are wrong a lot of times
    0:26:40 in the way how we validate these ideas.
    0:26:43 And when we are wrong, it’s through listening to the community,
    0:26:45 seeing what they do with the tools.
    0:26:47 And I think that a good rule of thumb
    0:26:50 or something that I found that is a good north star
    0:26:52 to realize when something is good or not,
    0:26:56 is when your users are better at using your tool than yourself.
    0:26:59 And that has been key to me, because with the real time,
    0:27:01 I was seeing things that I was like, how the fuck?
    0:27:02 Did they create that?
    0:27:04 And same thing with the video tool.
    0:27:06 Like with the video tool, I was trying to do a demo,
    0:27:08 like trying to showcase cool stuff.
    0:27:10 And I was trying things, and I was not getting there.
    0:27:12 And I was looking at Twitter at all the things
    0:27:14 that our users were creating with our product.
    0:27:16 And I couldn’t get to that quality.
    0:27:18 I couldn’t get to those results.
    0:27:20 So I think that every time that your users are using
    0:27:23 your product better than what you are, that’s a good sign.
    0:27:26 – Meanwhile, Justin and Maxis of it are charting new ground,
    0:27:29 but also figuring out new limits.
    0:27:31 – Stable diffusion allowed you to make anything.
    0:27:34 And so when we launched, I wanted to make sure
    0:27:37 that we could continue to support that community.
    0:27:38 But it was so diverse.
    0:27:42 And there’s running meme of things you can make
    0:27:43 with stable diffusion.
    0:27:45 And in the front is like somebody making funny memes.
    0:27:48 And then there’s a train coming that’s porn, right?
    0:27:50 Sure, people know that you can make all of this stuff.
    0:27:53 I mean, that’s the point of this tech, make anything, right?
    0:27:55 And so it was important for us to say,
    0:27:58 hey, we want to be able to support this tech as it develops.
    0:28:00 It means that we need to embrace all of it.
    0:28:01 And that’s not easy.
    0:28:06 It’s been incredibly difficult to set up policies
    0:28:08 that allow the creation of all things
    0:28:13 in a way that’s not going to hurt people
    0:28:16 and to also do it in a way that makes it so that people
    0:28:18 still have the level of control that they need
    0:28:22 to prevent the creation of content that can’t be there.
    0:28:23 – In the beginning, our policies were very straightforward.
    0:28:26 They were kind of just like, look, as long as it’s not illegal
    0:28:29 and as long as it’s not just ethically, completely debased,
    0:28:31 then we’ll let it on the platform.
    0:28:35 And we were okay when we had the small enough user group
    0:28:37 with kind of leaving it even like that vague.
    0:28:40 We found over time that we’ve had to really kind of specify
    0:28:42 ’cause it turns out that there are just like subsections
    0:28:44 of the internet that are into just the absolute strangest
    0:28:46 things you’ve never heard of at all,
    0:28:48 which can be really funny, which can be really cool.
    0:28:49 And some of that is really interesting.
    0:28:51 And some of it is just, oh my gosh.
    0:28:54 And it’s like a balancing act of figuring out, okay,
    0:28:56 what are, you almost have to grow as a person.
    0:28:59 And we created like a council of moderators around here
    0:29:01 to on our platform to really kind of like get together
    0:29:04 and look at when these new things pop up and be like,
    0:29:05 how do we feel about this?
    0:29:06 One of the things that really blew my mind
    0:29:08 when we were getting into the whole moderation aspect was,
    0:29:10 like, oh, we’ll just do what other platforms do.
    0:29:11 We’ll do what Imager does, we’ll do what Reddit does.
    0:29:13 We’ll just copy kind of like what they’re doing.
    0:29:16 And as we kind of dug into what they do,
    0:29:19 is they don’t define any of this.
    0:29:20 None of this is defined.
    0:29:22 We had to come up with terms of how do you define
    0:29:23 what a child is?
    0:29:25 How do you define what is photorealistic?
    0:29:27 How do you define what is and isn’t all of these terms?
    0:29:31 But before, really didn’t have any really set definition.
    0:29:32 – Perhaps it shouldn’t be surprising
    0:29:34 that there are new moderation challenges
    0:29:36 since this industry is so fresh
    0:29:39 with new ideas coming from a new breed of creatives.
    0:29:41 In fact, we heard about this range
    0:29:43 in both prosumers and professionals
    0:29:45 from most of the founders we spoke with.
    0:29:46 Here’s Victor from Korea.
    0:29:50 – The range of creatives is quite wide.
    0:29:52 Like the kind of people that use Korea
    0:29:56 can come from having 20 years of working
    0:29:58 in the creative industry and being like,
    0:30:00 I don’t know, three the artist
    0:30:02 or people doing graphic design
    0:30:05 or even photographers or these kind of people.
    0:30:07 But we also find a lot of folks
    0:30:10 who don’t have a professional creative background.
    0:30:11 For the professional ones,
    0:30:14 you can find them doing a lot of prototyping.
    0:30:17 Like for example, when they start working on a new project,
    0:30:21 they may go to Korea to really quickly brainstorm
    0:30:22 some ideas that they have
    0:30:24 and they would use the real time tool
    0:30:26 that we have for that.
    0:30:29 And they can do like a very simple sketch
    0:30:30 add a text from
    0:30:32 and have something that looks super realistic
    0:30:34 and that can either give them ideas
    0:30:37 and maybe even serve as a final deliverable
    0:30:38 depending on what they’re doing.
    0:30:41 And when we’re talking about like a less professional creative,
    0:30:43 it’s honestly more about having fun.
    0:30:46 And they are using Korea for everything that you can imagine
    0:30:51 from imagining new walls to creating paintings
    0:30:54 to creating like characters or all sorts of things.
    0:30:55 – And as more participate,
    0:30:57 these new platforms generate new talent
    0:31:02 but also new expectations like expectations in speed.
    0:31:06 – And on the meantime, what we’re doing is building community
    0:31:09 and bringing to the community what they want now,
    0:31:11 just focusing on what can we do now
    0:31:13 with the technology that is out there.
    0:31:17 We are very deep into AI communities
    0:31:20 and every time that there’s something
    0:31:22 that we think that is valuable from a creative point of view,
    0:31:24 we go ahead and we execute it very, very fast.
    0:31:27 So the way how we’re working is almost like a video game company
    0:31:30 where instead of video games, we are building tools
    0:31:33 and every six months or so, there’s a new tool
    0:31:35 because the space just happened to evolve in a way
    0:31:38 that every six months, there’s a new technology
    0:31:40 that you can use in order to make a new tool.
    0:31:42 And that’s gonna keep being like that until we get to these
    0:31:44 like real-time multimodal systems
    0:31:47 that allow us to do something way more interesting.
    0:31:51 – This new wave has also shifted people’s willingness to pay.
    0:31:53 Back to Anish.
    0:31:54 I think the willingness to pay
    0:31:57 and the amount that consumers are willing to pay is really high.
    0:31:59 And that’s really interesting because for so long,
    0:32:02 we’ve had these sort of patronage models
    0:32:03 for how to fund the arts.
    0:32:05 And there’s been this belief
    0:32:08 that there’s a sort of decreasing interest in paying for art.
    0:32:09 And instead, we’re seeing the exact opposite.
    0:32:12 People want to pay for art and pay for tools to make art
    0:32:13 and pay a lot.
    0:32:17 So that’s a really, really exciting development to me.
    0:32:18 – And this willingness to pay
    0:32:21 is also unlocking new business models.
    0:32:22 – People make so many things
    0:32:24 because it’s a tool for creating anything.
    0:32:27 And to see the things that people can create,
    0:32:29 whether that’s assets for a game
    0:32:31 or videos of flowers that are dancing,
    0:32:32 it’s just endless.
    0:32:33 The possibilities are endless.
    0:32:35 And it’s inspiring to see how people
    0:32:36 are kind of pulling it to do new things.
    0:32:38 – That was Justin from Civet,
    0:32:40 which is also working on a new way
    0:32:43 to reward AI artists for their contributions.
    0:32:45 – When we were getting this going
    0:32:47 and we were really like realizing this could be a business,
    0:32:49 was we interacted with a lot of the people
    0:32:49 who are doing this creation.
    0:32:51 And it’s a lot of time and it’s a lot of money.
    0:32:52 That’s a lot of like technical skill
    0:32:54 that goes into making these things well.
    0:32:55 And people were doing it,
    0:32:56 thousands of people were doing it,
    0:32:57 just for the love of the game.
    0:32:59 Like they just really enjoyed the clout
    0:33:01 and the entertainment factor.
    0:33:02 They got their position on the leaderboard.
    0:33:05 – The leaderboard, oh my God, the leaderboard.
    0:33:07 And it became pretty clear that,
    0:33:09 look, this is almost like a whole new creator economy
    0:33:09 that can come out of this
    0:33:11 because it’s a group of people who are putting effort
    0:33:14 and love into something that could very easily
    0:33:15 become livelihoods for them
    0:33:17 if they had even the smallest way to monetize it
    0:33:18 based on the number of eyes they’re getting
    0:33:19 and uses they’re getting.
    0:33:21 So yeah, a very clear goal
    0:33:22 from the very beginning was like,
    0:33:24 let’s figure out how we can keep the creators monetized
    0:33:26 while maintaining the open source ethos.
    0:33:28 – We actually just announced something
    0:33:30 that we’re hoping to roll out over the next six weeks.
    0:33:31 Let me give you a little bit of history.
    0:33:33 So we launched a creators program four months ago
    0:33:35 and we opened it to a small cohort
    0:33:37 of essentially 50 creators.
    0:33:39 We opened applications and took essentially people
    0:33:41 that met certain criteria
    0:33:43 and have been experimenting with ways
    0:33:45 that we can help them monetize their work.
    0:33:48 What we’ve landed on for this next generation
    0:33:50 that we’re hoping to open up in these next six weeks
    0:33:53 is making it so that people can earn for the generation
    0:33:55 that people are doing on our site.
    0:33:56 So if they make a resource
    0:33:59 that’s intended to produce a new character,
    0:34:01 like a consistent character that they’ve made
    0:34:03 and somebody chooses to use that in the generator,
    0:34:05 then they’re gonna get their share of 25%
    0:34:07 of what we charge for that generation.
    0:34:10 So the aim is to make it so that these people have a way
    0:34:14 to get essentially paid for allowing the convenience
    0:34:15 of using their resource on our site.
    0:34:17 – One of the main things that we saw right away
    0:34:19 before we had the time to be able to implement
    0:34:21 any real monetization stuff for creators was,
    0:34:23 we put in a DM system simply because we knew
    0:34:25 that there’s a lot of people who are contacting creators
    0:34:26 for work outside of the platform.
    0:34:28 And because of that, I mean,
    0:34:30 we just get untold number of people contacting us
    0:34:31 being like, “Thank you so much as platform.”
    0:34:32 Because of that, I was able to get hooked up
    0:34:34 with Hugo Boss or Hyundai
    0:34:35 or some of these other people
    0:34:36 who are suddenly using this technology.
    0:34:38 And it’s completely changed my life
    0:34:40 before I was making $30,000 a year as a waiter or whatever.
    0:34:44 And now I’m making six figures doing this whole new thing
    0:34:45 that’s a passion for me.
    0:34:46 And I have lost count
    0:34:48 on the number of people who’ve contacted me about that.
    0:34:49 So it’s really cool to see.
    0:34:51 So from a services side, we want to kind of enable that
    0:34:53 and make it even easier for people to be able to sell
    0:34:55 their services, their expertise,
    0:34:57 directly to businesses from the system.
    0:34:58 – It’s not alone here.
    0:35:02 11Labs is also building a marketplace for voices.
    0:35:06 – I know you guys are building kind of a marketplace of sorts.
    0:35:08 So people can upload voices
    0:35:10 or they can use voices that others have uploaded.
    0:35:12 – Yeah, I think it’s a really exciting way
    0:35:15 to give folks a way to earn passive income as well.
    0:35:16 Maybe you were a voice actor
    0:35:18 and you weren’t getting the gigs you wanted,
    0:35:20 but now you can put your voice out there
    0:35:21 and you might become extremely popular.
    0:35:25 And we’ve seen people earn quite well on our platform.
    0:35:28 And so the library is just a great way
    0:35:30 to one, put your content out there.
    0:35:32 And we want to partner with more voice actors, honestly,
    0:35:34 to have more expressive voices
    0:35:37 and then give people great voices to create content with.
    0:35:39 So two-way street.
    0:35:41 – But it’s not just the marketplace.
    0:35:43 It’s also the interface.
    0:35:46 – I think we’ve always had the dream of voice interactions
    0:35:47 with all our products.
    0:35:49 If you think about Star Trek
    0:35:51 and Knight Rider talking to his car kit,
    0:35:52 it’s something that’s been a part
    0:35:53 of pop culture history forever,
    0:35:57 but I don’t think we’ve had the quality and the sound
    0:36:00 and for it to feel as natural as it should have been.
    0:36:02 And so I think we’re getting to that point
    0:36:04 where the interactions between large language models
    0:36:08 using voice interfaces is becoming incredibly natural
    0:36:10 and feels like talking to a person.
    0:36:11 And so I do totally see a future
    0:36:14 where a lot of this physical interface
    0:36:16 that you’re tapping around with is going to just fade away
    0:36:18 and you’re going to be able to ask the questions
    0:36:21 you want to ask and have the conversations you want to have.
    0:36:24 I know her is the hot topic movie of the AI space,
    0:36:25 but I think there was one thing in that movie
    0:36:28 that stuck with me more than just the interactions
    0:36:29 he was having with her,
    0:36:31 which was there was this scene in the movie
    0:36:34 where everyone was down looking at their phones
    0:36:35 and kind of scrolling.
    0:36:37 And there’s this inflection point somewhere later
    0:36:39 in the movie where actually everyone’s kind of talking
    0:36:41 to something in their ear.
    0:36:44 And I think that is a very precious take that they had.
    0:36:46 And I think we’re going to see more of that.
    0:36:48 It’s just going to be natural conversations
    0:36:51 we’ll be having with this AI or any interface.
    0:36:53 – Yeah, it reminds me of my husband’s grandmother,
    0:36:55 says that the first time she ever heard someone talking
    0:36:58 on a phone in the grocery store,
    0:37:00 she thought they were talking to themselves.
    0:37:02 Because all of these new interactions, right?
    0:37:03 You’re just not used to,
    0:37:05 or the people who go to prison and come out
    0:37:07 and 10 years later, they’re like,
    0:37:09 why is everyone looking down?
    0:37:11 And then I realize that we have these crazy computers
    0:37:11 in our pockets.
    0:37:12 – Totally.
    0:37:14 The thing that I love about AI in particular
    0:37:16 and all these AI creative tools is
    0:37:19 the magic is you had an idea
    0:37:20 and now you can imagine it, right?
    0:37:22 You can imagine the image that you wanted
    0:37:24 and that was in your head and the dream you had.
    0:37:26 And now we’re saying you can imagine the sound
    0:37:27 that you’re probably hearing in your head
    0:37:29 that no one else can hear yet.
    0:37:31 – But it’s not just a new UI.
    0:37:34 Perhaps it’s a new approach to modeling the world itself.
    0:37:36 Hang from Viggo.
    0:37:38 – One thing I really look forward to is,
    0:37:40 like I said, the next generation of the model.
    0:37:44 So we are really hoping to extend this character model
    0:37:48 to more the rest of the world, like objects and the scenes.
    0:37:52 And so I think those are two general passes
    0:37:54 towards modeling the real world.
    0:37:58 One is more on, we’ve seen this pixel level approach.
    0:38:00 So diffusion models are really good at that.
    0:38:02 But it has this drawback of,
    0:38:04 it’s really hard to manipulate pixels.
    0:38:08 And the real world is essentially, is really, is physical.
    0:38:11 So pixel is not really a efficient representation for it.
    0:38:14 But it has the advantage of you can train with any video
    0:38:16 and it generates anything.
    0:38:20 And the hope there is, if we scale it up to a certain extent,
    0:38:22 a controllability will kind of emerge.
    0:38:25 But we’re taking another kind of different path
    0:38:28 in that we want to nail down better the first,
    0:38:32 making sure it’s just as precise, as controllable,
    0:38:35 as a graphics engine, and then we scale up from there.
    0:38:39 So I think this, how those two passes evolve
    0:38:44 and how actually they can be combined into one immersive experience.
    0:38:46 As we close out this episode, it’s hard to understate
    0:38:50 just how much these tools are shifting, what it means to be creative.
    0:38:54 To both existing artists and to those who never would have called themselves artists before.
    0:38:56 Connor from UDO.
    0:39:00 The threshold for someone going into a studio and recording something like that
    0:39:01 was way too high.
    0:39:04 Whereas now, the promise of the technology is that
    0:39:06 it brings an order of magnitude or two orders of magnitude,
    0:39:09 more people into the creative kind of experience, right?
    0:39:13 Like, people can express themselves in this way,
    0:39:16 but kind of even more concretely, as moments happen in the world,
    0:39:19 different cultural moments, you can attach music to them now.
    0:39:23 Because it can be dynamically attached to these things in interesting ways.
    0:39:24 And this is super compelling.
    0:39:27 This is a kind of a market that didn’t really exist before
    0:39:30 just because it wasn’t actually possible to explore this way.
    0:39:33 I think as well as that, we’ve been fascinated with how
    0:39:37 at the top level, say with the existing artists or existing producers,
    0:39:40 how this can basically work as an ideation machine,
    0:39:45 like a kind of well of infinite creativity that you can just pull from for ideas.
    0:39:47 Maybe you have the beginning of a track, you have a riff, you have a beat.
    0:39:50 You want to see where could this go from here?
    0:39:52 If I remix this a bit, what are variations on this?
    0:39:54 And that’s a super compelling thing to do as well.
    0:39:58 Again, because it’s something that before took a lot of time.
    0:40:02 And so it just accelerates the creative experience for professionals like that as well.
    0:40:05 I have yet to meet an artist who’s actually used the products
    0:40:07 that is worried about the products competing with them.
    0:40:11 The biggest worry that I hear over and over is that somebody is going to take them away.
    0:40:16 Diego from Korea with a great reminder of just how monumental this shift is.
    0:40:21 I was a creative myself doing graphic design, photography.
    0:40:25 I even tried to make video games in flash, motion graphics in After Effects,
    0:40:30 digital sculpture in Zbrush, 3D modeling for architecture visualization.
    0:40:35 And I was like, it’s almost like I felt the fear of,
    0:40:38 “Hey, what’s the point if this thing can’t do everything,” right?
    0:40:40 But I don’t think that’s the case.
    0:40:49 What I think is happening is that we’re just giving so much power to creatives
    0:40:56 that things that were like a job in a way like now you don’t even think about them.
    0:40:58 That’s what technology does, right?
    0:41:03 Like one day it is a lifetime work to move from the east coast of the US
    0:41:06 to the west coast and people die on the process.
    0:41:11 So now you’re like, “Oh, it took me like 20 minutes at the line to get to the airport thing.”
    0:41:15 And you don’t even think about the fact that you flew like a great god through the planes.
    0:41:17 Instead, you’re just thinking at a higher level.
    0:41:23 You’re just, I don’t know, flying between coasts to make like bigger things, right?
    0:41:26 So I feel like the same is going to happen.
    0:41:31 Suddenly like coloring 3D models through texture things and all these repetitive things
    0:41:37 like sketching and whatever like you will save so much time like of your life.
    0:41:42 Because of not having to do that, you can focus on having even better and crazier ideas.
    0:41:49 So I’m really, really, really excited to see what the creatives are going to be able to do.
    0:41:51 All right, that’s all for now.
    0:41:55 The demos shared during the day were followed by a gallery party at night
    0:41:59 showcasing many of the artist’s work of the broader New York City creative community.
    0:42:02 So if you want to get up close and personal with these tools,
    0:42:07 head on over to a16z.com/aiart to check out their demos and more.
    0:42:10 We’ll leave you with a little sneak peek.
    0:42:17 Ladies and gentlemen, I am thrilled to be here at the a16z artist retreat.
    0:42:19 Yeah, it gets you pumped.
    0:42:20 So pumped.
    0:42:21 So pumped.
    0:42:24 You can generate whatever you want.
    0:42:25 That was amazing.
    0:42:28 Yes, so it’s a whole body swap.
    0:42:29 Wow, this is so good.
    0:42:33 We’re also working on a new type of memes.
    0:42:36 Actually, I think that is better if we see it in slow motion.
    0:42:37 All right, you should come see this.
    0:42:40 This changes from being deterministic to being totally random.
    0:42:42 Remix.
    0:42:49 If you liked this episode, if you made it this far, help us grow the show.
    0:42:52 Share with a friend or if you’re feeling really ambitious,
    0:42:58 you can leave us a review at ratethespodcast.com/a16z.
    0:43:03 You know, candidly producing a podcast can sometimes feel like you’re just talking into a void.
    0:43:07 And so if you did like this episode, if you like any of our episodes,
    0:43:08 please let us know.
    0:43:18 We’ll see you next time.
    0:43:27 [BLANK_AUDIO]

    On June 27th, the a16z team headed to New York City for the first-ever AI Artist Retreat at their office. This event brought together the builders behind some of the most popular AI creative tools, along with 16 artists, filmmakers, and designers who are exploring the capabilities of AI in their work.

    In this episode, we hear from the innovators pushing the boundaries of AI creativity. Joined by Anish Acharya, General Partner, and Justine Moore, Partner on the Consumer team, we feature insights from:

    • Ammaar Reshi – Head of Design, ElevenLabs
    • Justin Maier – Cofounder & CEO, Civitai
    • Maxfield Hulker – Cofounder & COO, Civitai
    • Diego Rodriguez – Cofounder & CTO, Krea
    • Victor Perez – Cofounder & CEO, Krea
    • Mohammad Norouzi – Cofounder & CEO, Ideogram
    • Hang Chu – Cofounder & CEO, Viggle
    • Conor Durkan – Cofounder, Udio

    These leaders highlight the surprising commonalities between founders and artists, and the interdisciplinary nature of their work. The episode covers the origin stories behind these innovative tools, their viral moments, and their future visions. You’ll also hear about the exciting potential for AI in various creative modalities, including image, video, music, 3D, and speech.

    Keep an eye out for more in our series highlighting the founders building groundbreaking foundation models and AI applications for video, audio, photography, animation, and more.

    Learn more and see videos on artists leveraging AI at: 

    a16z.com/aiart

     

    Find Ammaar on Twitter: https://x.com/ammaar

    Learn more about ElevenLabs: https://elevenlabs.io

    Find Justin on Twitter: https://x.com/justmaier

    Find Max on LinkedIn: https://www.linkedin.com/in/maxfield-hulker-5222aa230/
    Learn more about Civitai: https://civitai.com

    Find Diego on Twitter: https://x.com/asciidiego?lang=en

    Find Victor on Twitter: https://x.com/viccpoes

    Learn more about Krea: https://www.krea.ai/home

    Find Mohammed on Twitter: https://x.com/mo_norouzi

    Learn more about Ideogram: https://ideogram.ai/t/explore

    Find Conor on Twitter: https://x.com/conormdurkan

    Learn more about Udio: https://www.udio.com/home

    Find Hang on Twitter: https://x.com/chuhang1122

    Learn more about Viggle: https://viggle.ai/

     

    Stay Updated: 

    Let us know what you think: https://ratethispodcast.com/a16z

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    Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

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    Follow our host: https://twitter.com/stephsmithio

    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

     

     

  • Founders Playbook: Lessons from Riot, Discord, & More

    AI transcript
    0:00:02 Right now, we’re in the soccer-cathode
    0:00:04 in the beginning of a gaming Renaissance.
    0:00:06 We’ll see gaming ultimately dominate
    0:00:09 and become the primary entertainment media for the future.
    0:00:14 I love the intersection of tech and art and psychology
    0:00:20 and design and how they interact.
    0:00:22 It’s just the coolest industry in the world.
    0:00:25 Over the past few decades,
    0:00:28 gaming has undergone a radical transformation.
    0:00:31 From one-off experiences that came on a disk
    0:00:32 to viral mobile games
    0:00:36 to now intricate, seemingly never-ending online universes
    0:00:38 that actually feel like they have more in common
    0:00:40 with movies or social media
    0:00:43 than the video games we might remember from the ’90s.
    0:00:45 Esports tournaments fill stadiums,
    0:00:48 games inspire major TV series,
    0:00:50 and the money spent on gaming content alone
    0:00:54 is five times what is spent on the movie “Box Office.”
    0:00:56 So with all that said,
    0:01:00 leveling up as a game company should be a breeze, right?
    0:01:02 Well, it’s not that easy.
    0:01:04 With intense competition, distribution challenges,
    0:01:06 and high production costs,
    0:01:09 gaming startups are used to playing on hard mode,
    0:01:11 but they’re also pioneers of innovation,
    0:01:13 leading the pack when it comes to the adoption
    0:01:16 of everything from smartphones to virtual reality.
    0:01:19 And these hard-won lessons offer insights
    0:01:21 that can help startups across the tech industry
    0:01:25 to power up and advance to the next level.
    0:01:27 So that’s why we brought in some of the titans
    0:01:29 of the game industry.
    0:01:31 And today, you’ll hear them discuss everything
    0:01:33 from the state of the gaming industry today,
    0:01:35 how to survive a bare market,
    0:01:37 the strategies that startups can leverage
    0:01:39 to build and market products that stand out
    0:01:43 in a busy crowd, and the potential impact of AI.
    0:01:46 These conversations were all recorded during Speedrun,
    0:01:49 A16Z’s extensive games accelerator.
    0:01:52 So ready, set, game on.
    0:01:55 As a reminder, the content here
    0:01:57 is for informational purposes only,
    0:01:59 should not be taken as legal, business, tax,
    0:02:00 or investment advice,
    0:02:03 or be used to evaluate any investment or security,
    0:02:04 and is not directed at any investors
    0:02:07 or potential investors in any A16Z fund.
    0:02:09 Please note that A16Z and its affiliates
    0:02:11 may also maintain investments
    0:02:13 in the companies discussed in this podcast.
    0:02:16 For more details, including a link to our investments,
    0:02:19 please see a16z.com/disclosures.
    0:02:22 (upbeat music)
    0:02:28 – I’m very excited because I legitimately believe
    0:02:30 that right now we’re in the suck with the third inning
    0:02:31 of a game in Renaissance.
    0:02:34 – That was Jonathan Lai,
    0:02:38 general partner and founding investor of A16Z Games.
    0:02:40 John previously worked at Riot Games,
    0:02:42 where he shipped the Riot Games API
    0:02:44 before the company was acquired by Tencent.
    0:02:46 You might also recognize Riot
    0:02:48 as the creators of League of Legends,
    0:02:50 a game which sees 15 million players
    0:02:52 on average every day.
    0:02:55 – If you’re starting a game company,
    0:02:58 there’s never been more tools and new technology
    0:03:00 to help you build games.
    0:03:03 There’s never been more sources of funding,
    0:03:06 and there’s more players of games today than ever before.
    0:03:08 There’s three founding gamers around the world,
    0:03:10 like Southeast Asia, Africa, India,
    0:03:13 all of these emerging markets are coming online.
    0:03:13 At the same time,
    0:03:15 like we have more distribution platforms
    0:03:17 that are hungry for content,
    0:03:19 where Netflix is getting into games.
    0:03:21 I just heard that Walmart and Verizon last month
    0:03:23 are like really excited about games.
    0:03:26 Apple Arcade, Steam is at all time highs.
    0:03:30 There’s just never been more demand for great content.
    0:03:33 – Gaming has long been overlooked as an industry,
    0:03:35 but it continues to evolve.
    0:03:36 One of its next phase shifts
    0:03:39 has been its influence on Hollywood.
    0:03:40 Here’s Andrew Chen,
    0:03:43 also general partner at A16Z Games.
    0:03:47 – A lot of Hollywood are intensely interested
    0:03:47 in the games industry,
    0:03:50 because they’ve just seen in the last year,
    0:03:51 not just the Mario movie,
    0:03:53 not just what’s happened with Hogwarts Legacy,
    0:03:55 Last of Us.
    0:03:57 I’ve had a ton of meetings with everyone
    0:03:59 from the team around JJ Abrams,
    0:04:00 the bad robot people,
    0:04:04 the Eisner family who ran Disney for many years,
    0:04:05 the folks around Ridley Scott,
    0:04:09 and Riot has obviously been pushing from the gaming side.
    0:04:12 And it really feels like there’s a tremendous boom
    0:04:15 that’s happened in the same way that Marvel
    0:04:18 and the superhero franchises sort of became the core IP
    0:04:21 that then unlocked basically the last,
    0:04:23 I don’t know, 10 years of films.
    0:04:24 What you’re really seeing
    0:04:27 is just an aging out of the population
    0:04:30 of folks that grew up watching two-hour movies
    0:04:33 and that’s their primary method of entertainment.
    0:04:34 And as that group ages out,
    0:04:37 I think what we’ll see is we’ll see gaming ultimately dominate
    0:04:40 and become the primary entertainment medium for the future.
    0:04:44 And it’s inevitable just based on consumer watch time
    0:04:45 and engagement time,
    0:04:47 if you just measure it in minutes and hours
    0:04:48 and monetization.
    0:04:50 I think the folks on the business side
    0:04:53 are starting to really understand
    0:04:57 that gaming is actually larger than film, TV, books,
    0:04:59 magazines, radio, combines.
    0:05:03 And you can actually build and monetize your IP
    0:05:04 and have daily interaction
    0:05:07 in a way that you wouldn’t otherwise.
    0:05:11 And it’s not just Hollywood that’s taking notice.
    0:05:12 It started at Fortnum,
    0:05:14 a smash hit that everyone in the globe
    0:05:16 was talking about for years.
    0:05:18 Right after Fortnite, you had a My Guest,
    0:05:20 which almost made the pandemic livable.
    0:05:22 Then you had games like Elden Green,
    0:05:24 followed by Hogwarts Legacy,
    0:05:26 followed by now Power World.
    0:05:28 And so now it feels like every year
    0:05:29 you’ll have like one or two games
    0:05:32 that just like curses like the cultural fabric.
    0:05:34 It just becomes this thing that everyone talks about,
    0:05:37 which I find is like really amazing
    0:05:40 and the sign that games has come into its own right
    0:05:42 as a piece of culture.
    0:05:43 If you need any convincing,
    0:05:46 remember that viral dance move, Flossing?
    0:05:49 Well, part of its popularity came from the ability
    0:05:52 to buy it as an emote for your character in Fortnite.
    0:05:54 And while this pop culture breakthrough
    0:05:56 is great news for the industry,
    0:05:59 every quest still has its challenges.
    0:06:01 Like much of the technology sector,
    0:06:03 games industry investment stalled last year,
    0:06:07 following to less than a quarter of its post-pandemic peak.
    0:06:09 But at least according to one industry veteran,
    0:06:12 a bear market can bring its own advantages.
    0:06:16 – When we were pitching what we codenamed Fellowship,
    0:06:18 this open world co-op free to play game,
    0:06:20 there were a lot of people who were telling us
    0:06:23 like there are dozens of these, they’re so expensive,
    0:06:24 no one’s going to want to fund this,
    0:06:26 it’s going to be ridiculous.
    0:06:28 And I think if you look at the market two years ago,
    0:06:30 all that pushback was totally right.
    0:06:32 – That was Steven Snow,
    0:06:34 a four-time gaming studio founder
    0:06:37 and one of the creators behind games like League of Legends,
    0:06:41 Degen Siege and Total Annihilation.
    0:06:43 – I think when you look at the market today,
    0:06:46 there’s less than 10 of these product pitches still live.
    0:06:49 Meaning like as the economy’s kind of gotten more condensed,
    0:06:51 and I heard everybody talking earlier today
    0:06:53 about how there are founders who prefer to operate
    0:06:55 in a more financially constrained market
    0:06:57 because it makes it kind of easier
    0:06:59 to ignore a lot of the riffraff and the noise.
    0:07:00 I don’t disagree with that.
    0:07:03 In fact, I would say that we now find ourselves
    0:07:06 in a very interesting situation where we’re one of a few,
    0:07:08 whereas if three years ago we were one of so many,
    0:07:10 it wasn’t worth doing.
    0:07:11 – The current economic climate offers
    0:07:14 another potential advantage to gaming startups
    0:07:16 in the form of talent.
    0:07:19 As margins narrow, we’ve seen a wave of mass layoffs
    0:07:22 from major gaming studios.
    0:07:23 – What’s happened to us
    0:07:25 in our overall applicant pipelines
    0:07:28 over the last 60 days is we are flooded.
    0:07:31 We are seeing heads of studios apply
    0:07:34 for like base tier leadership jobs.
    0:07:36 Trust me, if you guys are not checking
    0:07:38 your email inboxes right now,
    0:07:39 you’re making a huge mistake.
    0:07:42 Everybody’s emailing everyone trying to find a job,
    0:07:43 and some of these people don’t need to.
    0:07:45 They’re just looking to get out of the studio
    0:07:48 that handled their, I won’t name any names,
    0:07:50 but they handled their folks very poorly.
    0:07:51 And so if you have cash,
    0:07:54 just figure out how you wanna focus
    0:07:57 because there’ll be so many people who are trying to get in.
    0:08:02 – But even a market full of big name talent
    0:08:04 can present its own challenges.
    0:08:07 – The mistake I see so many startups make
    0:08:09 is go hire that person from EA.
    0:08:13 You know, go hire that person from Xbox.
    0:08:17 Like they get really rude by the resume at the early stage.
    0:08:19 – Aerosource Meany is an angel investor
    0:08:22 and former CMO at Discord.
    0:08:24 – And there are some amazing people at those two companies.
    0:08:26 Don’t get me wrong, they really are,
    0:08:28 but the resume alone is not what is actually gonna help you
    0:08:30 be successful as a startup.
    0:08:33 And you can waste a lot of time, a lot of money.
    0:08:35 These people are expensive often.
    0:08:39 Sometimes they’re seeking the same salary they got of Xbox.
    0:08:41 And the thing is they’re probably really great
    0:08:43 in those environments,
    0:08:46 but when you’re a team of 10 or less, 20 or less,
    0:08:49 50 or less, it’s a completely different ball game.
    0:08:51 So all that amazing experience,
    0:08:52 all the knowledge that they have,
    0:08:54 all the skills that they have,
    0:08:57 don’t necessarily apply to the early stage.
    0:09:00 – Now this is just one of the ways
    0:09:01 that companies are trying to stand out
    0:09:04 in this sea of stiff competition.
    0:09:06 And it’s truly a worldwide game.
    0:09:07 Here is Jonathan Lai.
    0:09:11 – Competition is seeding up in games,
    0:09:14 even beyond the competition that we see here in the West.
    0:09:16 Most of the Asian game companies
    0:09:19 call it Meharier, Tencent, NetEase,
    0:09:22 they’re actually all moving West.
    0:09:24 And this has been an effort that has been going on
    0:09:27 for some time, but I think it’s really accelerated recently.
    0:09:31 The crackdown that China’s had in gacha boxes
    0:09:34 and regulatory playtime and so on and so forth.
    0:09:35 Just using the example of Meharier,
    0:09:38 I think it’s opening three or four offices,
    0:09:39 like hearing the West cares for my own
    0:09:41 and hiring up a massive number of people.
    0:09:43 And so something to think about
    0:09:46 is if you are starting a game studio today
    0:09:49 and having the potential to compete against developers
    0:09:51 that can feel massive workforces
    0:09:53 that are working around the clock
    0:09:55 and have very, very deep understanding
    0:10:00 of monetization, how to run free-to-play economies and so on,
    0:10:03 I think it’s hard to compete with one of these larger guys,
    0:10:05 just purely on our content production.
    0:10:08 So the treadmill, what are the levers that you can pull
    0:10:12 to basically compete against an incumbent in your space?
    0:10:14 – So let’s dive into exactly that.
    0:10:16 The tools and strategies that gaming companies
    0:10:18 are putting into action
    0:10:20 to get their products onto the leaderboard.
    0:10:23 Starting with listening to fans.
    0:10:25 It used to be that back in the day,
    0:10:30 marketing was this combination of PR conferences and events
    0:10:32 and building case studies with your customers
    0:10:34 and doing field marketing.
    0:10:37 And it was sort of this like very repeatable playbook,
    0:10:40 like the whole industry is getting foundationally disrupted.
    0:10:42 It’s shifting really towards the idea
    0:10:45 of a lot of B2B founders actually,
    0:10:48 instead talking directly to their audience,
    0:10:50 building direct channels with their customers,
    0:10:51 building in public,
    0:10:55 building a sense of a buzz around the work that you’re doing.
    0:10:57 And we certainly see that a ton in AI
    0:11:02 where the primary hunting ground for acquiring customers,
    0:11:04 for attracting funding, for recruiting employees,
    0:11:08 actually has been Twitter and LinkedIn and Discord
    0:11:10 and some of these other platforms.
    0:11:11 And I would certainly encourage anybody
    0:11:13 that’s kind of working in a B2B context
    0:11:15 to really consider the same.
    0:11:17 – Steven Snow learned the power of this approach
    0:11:21 when him and his team at Riot stepped away from their screens
    0:11:24 and set up a stall at the gaming industry’s largest convention.
    0:11:28 – When League of Legends made its big announce,
    0:11:31 we went to E3 and I had a booth
    0:11:36 at the end of the end of a row in Kentia Hall.
    0:11:37 We told our community,
    0:11:39 if you want to do resume reviews, come by.
    0:11:42 All we had was our community and no one knew who we were.
    0:11:45 We were a 45 person studio at the time,
    0:11:47 but everybody else thought we were three idiots
    0:11:48 in a garage, right?
    0:11:50 The day started super sad.
    0:11:53 It was just me and a couple others in the booth
    0:11:55 and within a few minutes, people are showing up.
    0:11:57 They usually just wanted to talk about the game
    0:11:58 and I was like, I’ll talk to you about the game,
    0:12:01 but I have one commitment.
    0:12:02 Before I talk to you about the game,
    0:12:04 you have to tell me something
    0:12:07 that completely sucks about League of Legends.
    0:12:08 And it’s a qualitative question.
    0:12:10 It doesn’t matter what their answer is,
    0:12:12 I’m just gonna source with them like,
    0:12:14 oh, is it a friction related to matchmaking?
    0:12:15 And they might say like, oh, it takes me forever
    0:12:16 to find a friend.
    0:12:18 It’s like, okay, cool, is that a matchmaking problem?
    0:12:19 Is that like a friend’s list problem?
    0:12:21 But I’d go through and pull it all out.
    0:12:26 I did it for three days straight and it was horrible.
    0:12:28 And they’re just eviscerating the product right there, right?
    0:12:30 Like just right in front of everybody.
    0:12:31 And the whole thing I just kept doing
    0:12:33 was writing down their feedback, writing it down.
    0:12:35 And by the time I got back to the office
    0:12:38 after that Ken Tia Hall debacle,
    0:12:41 I had a punch list that was more effective
    0:12:43 for the overall trajectory of League of Legends
    0:12:46 than if I’d tried to sit in a room with our top designers.
    0:12:48 At the end of the day, it’s not personal.
    0:12:51 They are as angry and as furious
    0:12:56 about the state of the game because they care.
    0:12:59 Right, like that is the secret sauce right there.
    0:13:01 It got to the point on League of Legends release notes,
    0:13:04 I was putting in parentheses next to the big beats
    0:13:07 and we would give them credit for giving us the feedback.
    0:13:11 There’s another detail that’s gonna sound completely insane,
    0:13:13 but when we had about 50,
    0:13:18 all the way up until about 250,000 monthly active players,
    0:13:21 I would meet with the top tier players
    0:13:24 and it was first come, first serve in a ventrilo server.
    0:13:26 It was capped at 200.
    0:13:29 And I would just go every Sunday starting at 4 p.m.
    0:13:33 I would just go down the line of the 199 other people
    0:13:34 and ask them what sucked.
    0:13:37 And that was what fed the release notes.
    0:13:39 Direct user engagement can be a game changer
    0:13:41 for any technology product.
    0:13:44 And the team at Riot takes their player-focused approach
    0:13:46 a step further by putting players
    0:13:48 at the heart of everything they do.
    0:13:51 Here’s Michael Chow, Steven’s former colleague at Riot.
    0:13:55 – The holy grail is the customer
    0:13:57 and you just obsess about the customer.
    0:13:59 And when I showed up at Riot,
    0:14:03 I used to call our customers users
    0:14:05 because that’s what everybody in consumer technology
    0:14:08 calls users, they call them users.
    0:14:12 I didn’t realize how much I hated that
    0:14:14 until I started calling them players.
    0:14:15 And when you think of them that way
    0:14:18 and you start using language like that
    0:14:19 and you envision what they do
    0:14:22 with the thing that you’re trying to give them,
    0:14:23 it just changes everything
    0:14:26 about how you can make great products.
    0:14:27 And so that for me was like,
    0:14:29 that was a huge inflection point,
    0:14:33 is just becoming really explicitly customer obsessed.
    0:14:35 You don’t make your dream game,
    0:14:37 you make players dream game.
    0:14:40 And I think that is a very helpful way of thinking about it.
    0:14:42 I think there are basically two kinds
    0:14:44 of game developers in the world.
    0:14:47 There are people who are the consumer tech companies
    0:14:49 who got into games.
    0:14:51 Mark Pincus, who was here yesterday, was my boss.
    0:14:52 I love him deeply.
    0:14:53 He has passion for the gaming space,
    0:14:56 but he’s not a game developer by trade.
    0:15:00 He is a consumer internet technology product developer.
    0:15:01 So that’s one kind.
    0:15:04 And then the other kind is what I would call real games.
    0:15:06 These are real game developers.
    0:15:08 Both are actually really important.
    0:15:10 But I think the highest level feedback
    0:15:12 or suggestion I give to any of you
    0:15:14 is figure out which of those two things you are
    0:15:16 and then just do the other thing.
    0:15:19 If you consider yourself a consumer internet tech person,
    0:15:21 you think more about what is the market saying
    0:15:23 and you’re thinking about the customer,
    0:15:25 which is nice actually, that’s good.
    0:15:28 You really need to tap into the internal part of you
    0:15:31 that has very strong sense of inspiration and taste making.
    0:15:33 Whatever is the product that you’re making
    0:15:35 really immerse yourself in it.
    0:15:37 Conversely, if you are a game developer
    0:15:41 and don’t think of yourself at all as the consumer tech person,
    0:15:44 you mostly go inside out from your own inspiration
    0:15:47 and intuition into shipping it out into the world.
    0:15:51 This is like Hideo Kojima is my least favorite example
    0:15:53 of this kind of developer.
    0:15:55 All he wants to do is make what he wants.
    0:15:57 And if you like it, then great, but it doesn’t matter.
    0:15:58 It’s about him.
    0:16:00 That’s also a noble way of being,
    0:16:02 but if that’s your way, do the other thing.
    0:16:06 Learn to be obsessive about the customer and the market
    0:16:08 and work backwards from their needs
    0:16:10 rather than your own inspiration.
    0:16:12 Over at Discord, Eros and his team
    0:16:15 are focused on talking directly to their users as well.
    0:16:17 But in their early growth stages,
    0:16:19 they paid extra special attention
    0:16:22 to an important subset of fans.
    0:16:24 Now you’re in a world where you’ve got your first
    0:16:28 100,000, 10,000, 50,000 user.
    0:16:29 The question you have to ask yourselves is,
    0:16:31 within those groups, who are your super fans
    0:16:34 and what are you doing to encourage their behavior?
    0:16:37 That’s the thing I actually think works best for growth.
    0:16:40 Something we did phenomenally well at Discord.
    0:16:44 If you were a Discord super fan and we saw you,
    0:16:46 you knew that we saw you.
    0:16:47 You just knew it.
    0:16:49 You could tell that we were loving you right back.
    0:16:51 And I remember Stan would always say,
    0:16:52 “So Stan’s the CTO of Discord.”
    0:16:54 Stan would always say,
    0:16:58 “My favorite thing to do is to get out of writing code
    0:17:00 “and go to PAX and talk to the people
    0:17:01 “about the code I’m writing.”
    0:17:04 And he loved it and he would always insist on being there
    0:17:06 and ask questions and take feedback.
    0:17:09 And he would whip out his phone and show some new feature
    0:17:10 he was thinking about and get feedback
    0:17:12 and he just really got into that.
    0:17:16 And then of course, on Twitter, you know, same day,
    0:17:18 someone was like, “I just spoke to Stan at Discord
    0:17:20 “and he’d like show me this cool thing.”
    0:17:21 And like, there was a social love
    0:17:23 and then our social team would be like,
    0:17:24 “Thank you so much for hanging out with us.”
    0:17:28 And it was just like, just effusive sort of love feel.
    0:17:30 And so the reason I say this, the reason why,
    0:17:34 those people are your most important asset
    0:17:37 from day zero to the end of year one,
    0:17:39 your most important asset.
    0:17:40 They’re the ones that are gonna tell you
    0:17:43 what you’re doing right and what you’re doing wrong.
    0:17:45 Probably before the world sees it
    0:17:47 ’cause they’re using the product so much,
    0:17:50 so intently, so passionately,
    0:17:53 that they’ll know bugs that you don’t know about.
    0:17:54 So embrace them.
    0:17:58 – Now, there is another way to reach your super fans.
    0:18:01 There’s some of the most influential people
    0:18:03 in the gaming world, streamers.
    0:18:08 – What we noticed was a number of streamers
    0:18:09 on Twitch trying to figure out
    0:18:11 how to better manage their communities.
    0:18:14 It was very clear that there wasn’t a great tool for them.
    0:18:15 They were patching it together
    0:18:18 with everything from Ventrilo to TeamSpeak
    0:18:22 to other sort of pseudo Discord-like solutions.
    0:18:25 And we decided after we saw some sort of small uptick
    0:18:27 from some smaller streamers,
    0:18:28 to just invest in that a little bit.
    0:18:30 We thought, hey, if we could show them
    0:18:34 that our tool is really good at what it does,
    0:18:35 we could provide them with some stuff
    0:18:38 that is streamer-specific, creator-specific.
    0:18:41 And we could get them to use Discord
    0:18:43 while they’re gaming with their friends.
    0:18:44 It will literally show the world
    0:18:46 what our product is intended to do.
    0:18:48 Discord was really intended for you and your 10 friends
    0:18:49 to hang out.
    0:18:50 It was never intended to have
    0:18:51 hundreds of thousands of people on it,
    0:18:53 even though that happens now.
    0:18:54 The original attempt was like,
    0:18:57 bring people together through games, hang out,
    0:18:58 build your small community.
    0:19:01 So we built a few things.
    0:19:05 We helped them link their subscriber sort of status
    0:19:07 to special roles in Discord automatically.
    0:19:09 We handled some of the payment gateway pieces
    0:19:10 related to that.
    0:19:13 We just sort of made Discord a better tool for them.
    0:19:15 And anyone who sort of watched Discord grow up
    0:19:18 and was also watching Twitch at the time could see it.
    0:19:20 It was obvious, like all the big streamers were using it.
    0:19:23 And the funny thing is the first few
    0:19:26 that talked about Discord, we didn’t pay them.
    0:19:27 So when we met Lyric at like a TwitchCon
    0:19:29 and we were just like, hey, here’s our really cool thing.
    0:19:32 And like we can’t pay you, we don’t have money,
    0:19:33 but we think we’ve built something cool
    0:19:35 and we love just to get your feedback on our product.
    0:19:36 That was the conversation.
    0:19:40 A week later, he gets on stream and says,
    0:19:42 this is the best built piece of software
    0:19:45 for what I do that I’ve ever seen.
    0:19:48 And you can just see the Lyric spike, boom, right?
    0:19:52 And that was a nice way to sort of validate
    0:19:54 that we should ride the Twitch rig.
    0:19:56 ‘Cause there are people on that platform
    0:19:57 that think the way we do,
    0:19:59 which is like, let’s make great products
    0:20:01 and let them speak for themselves.
    0:20:04 – Clearly, player feedback is a cheat code
    0:20:05 for identifying opportunities,
    0:20:08 building great products and finding customers.
    0:20:11 But a focus on player preferences is also key
    0:20:13 to tackling one of the biggest challenges
    0:20:16 in the industry, distribution.
    0:20:17 Here is Michael.
    0:20:20 – The industry is in a tremendous amount of flux
    0:20:23 about channels for receiving your content
    0:20:25 and channels for paying for your games.
    0:20:27 I don’t think we know how it’s going to resolve,
    0:20:29 specifically the regulatory environment.
    0:20:32 The diaspora of platforms right now is pretty frustrating.
    0:20:35 Like if you wanna watch a television show right now,
    0:20:37 it’s your guess as to whether or not
    0:20:40 it’s on Netflix or Prime or Hulu or Disney Plus,
    0:20:42 which is now kind of Hulu, but not yet Hulu
    0:20:46 or Crunchyroll or Peacock or whatever.
    0:20:49 And I think that players don’t really want that in their games.
    0:20:51 I think they’re much more discerning as players in games
    0:20:53 and they’re also more religious,
    0:20:55 which is why you see the divide between Steam
    0:20:56 and the Epic Games Store.
    0:20:59 And I think that you gotta rewind backwards
    0:21:00 from what the players want.
    0:21:03 – Despite players being siloed in their chosen platforms
    0:21:06 and floods of content being available,
    0:21:10 there may just be one major wave that could disrupt it all,
    0:21:12 artificial intelligence.
    0:21:14 AI is already capable of helping us write stories,
    0:21:16 create artwork and build software,
    0:21:19 some of the core components of game development.
    0:21:22 But it also presents a host of new opportunities,
    0:21:25 like more personalized narratives and custom virtual goods
    0:21:27 or AI players that can help test games
    0:21:30 and even tools for analyzing player activity.
    0:21:31 Here is John’s take.
    0:21:34 – The way we think about AI in games
    0:21:37 that there’s going to be sort of two waves of innovation.
    0:21:40 And so the first wave is making the same games
    0:21:43 that we have today, but just faster, cheaper,
    0:21:46 like at greater scale than before.
    0:21:47 And I think there will be valuable companies
    0:21:50 that do that and do that well.
    0:21:52 But I think long-term, the incumbents
    0:21:54 are actually the most likely to capture value
    0:21:56 from the sort of faster, better, cheaper,
    0:21:58 well, the game development.
    0:21:59 And then sort of the second wave,
    0:22:01 which we are even more excited about,
    0:22:05 is the potential for AI to create entirely new markets.
    0:22:07 And so this is like new types of gameplay experiences,
    0:22:09 new social experiences involved in the agents,
    0:22:11 new types of genres that use AI
    0:22:14 as part of its core game that we haven’t seen yet.
    0:22:16 And I think ultimately, like you can create
    0:22:18 the most value here because if you’re successful,
    0:22:21 you’re bringing in net new players, right?
    0:22:23 Like you’re not trying to cannibalize call of duty
    0:22:24 or leave legends and say,
    0:22:26 “Hey, like come over here and play this game instead.”
    0:22:28 You’re actually appealing potentially
    0:22:31 to the people who don’t self-identify as gamers today,
    0:22:34 but they might see something, say character AI,
    0:22:37 say, “Hey, that’s actually really compelling.”
    0:22:38 And so I think that’s the long-term promise
    0:22:41 of AI and gaming that we’re very excited about.
    0:22:42 – And we probably have no conception
    0:22:44 of the innovation that’s on our doorstep.
    0:22:48 – People often talk about how if you knew
    0:22:51 that cars were gonna be invented,
    0:22:54 you could extrapolate that gas stations would be a thing,
    0:22:56 right, because that’s kind of the first order.
    0:22:58 And by the way, you know, in a world of like horses,
    0:23:00 like, yeah, you need stopping stations for your horse
    0:23:01 to have water or whatever, so you’re like,
    0:23:03 “Okay, well, a car is kind of like that.”
    0:23:06 It is really, really hard to go from that
    0:23:09 and saying, you know, Walmart can exist because of the car.
    0:23:11 You know, where a city like LA can exist
    0:23:13 because it really is something that the urban sprawl
    0:23:16 kind of requires, you know, the invention of a car to support.
    0:23:20 That’s the second degree aspect I think is really difficult.
    0:23:23 I think that is why a lot of what we can imagine
    0:23:26 is just taking things that exist today
    0:23:28 and just doing it a little bit better.
    0:23:30 But the reality is I think we’re gonna see people compete
    0:23:32 in a bunch of different avenues
    0:23:34 that they wouldn’t have previously.
    0:23:37 You know, maybe when it turns out that we decide
    0:23:40 as a country we’re gonna have Trump be Biden again,
    0:23:43 somebody that evening is gonna spin up like a meme game
    0:23:45 and people are gonna play it for like 30 minutes
    0:23:47 that evening and then they’re gonna throw it away.
    0:23:49 But it was instantly easy to build.
    0:23:50 Today you talk about markets.
    0:23:53 You say, “Oh, well, I’m gonna build this experience.”
    0:23:57 And it’s got to address a market of millions of gamers
    0:23:59 and that’s the only way we would possibly do it.
    0:24:01 Well, you know, again, if it’s super easy,
    0:24:03 the same way that you would make a little meme
    0:24:05 to make fun of someone in your office
    0:24:06 or whatever not that we’d ever do that,
    0:24:09 then maybe you would build a little game
    0:24:11 that’s for an audience of 20 people
    0:24:14 that’s just a free-for-all, you know, like thing
    0:24:16 of what the A16Z partners, like, you know,
    0:24:19 shooting at each other, maybe that would be fun.
    0:24:21 – When it comes to AI and gaming,
    0:24:23 there’s still a lot of uncertainty,
    0:24:25 but the gaming community has always been quick
    0:24:28 to embrace new tools and new technologies.
    0:24:30 So given his track record, other industries
    0:24:32 would be smart to learn from these pioneers.
    0:24:38 – The game industry is this really special force within tech
    0:24:43 because you look at how the PC came into the consumer
    0:24:47 household, how GPUs came to be, how 3D came to be,
    0:24:49 how VR is happening right now.
    0:24:52 The games industry has really been this sort of like
    0:24:56 alpha nerd, kind of early adopter set of technologies
    0:24:59 that then comes to actually ultimately revolutionize
    0:25:01 the rest of the tech industry.
    0:25:05 – All right, that’s all for now.
    0:25:07 Whether you’re building directly in games or not,
    0:25:09 I’ll be quick to remind you that the industry
    0:25:11 has long been on the frontier.
    0:25:12 And we hope this gives you a glimpse
    0:25:15 into how they’re solving some universal challenges
    0:25:17 and progressing to the next level.
    0:25:22 If you liked this episode, if you made it this far,
    0:25:25 help us grow the show, share with a friend,
    0:25:27 or if you’re feeling really ambitious,
    0:25:32 you can leave us a review at ratethispodcast.com/asiccisi.
    0:25:35 You know, candidly producing a podcast
    0:25:38 can sometimes feel like you’re just talking into a void.
    0:25:39 And so if you did like this episode,
    0:25:41 if you liked any of our episodes,
    0:25:44 please let us know, we’ll see you next time.
    0:25:47 (upbeat music)
    0:25:50 (upbeat music)
    0:25:54 (upbeat music)
    0:26:02 [BLANK_AUDIO]

    Gaming is not just entertainment—it’s a revolution reshaping our culture, technology, and economy. 

    a16z’s Jonathan Lai and Andrew Chen dive into the current gaming renaissance and its future impact. Joining them are Michael Chow, CEO and Steven Snow, CPO of The Believer Company, and Eros Resmini, Founder and Managing Partner of The Mini Fund.

    They explore the intersection of tech, art, psychology, and design in gaming, discussing how startups can navigate intense competition, distribution challenges, and high production costs. With insights from these industry leaders, this episode covers the transformative potential of AI, the importance of player feedback, and strategies to stand out in a crowded market.

    Recorded during Speedrun, a16z’s extensive games accelerator, this episode offers a glimpse into the strategies and innovations driving the gaming industry forward.

     

    Resources: 

    Find Steven on Twitter: https://twitter.com/StevenSnow

    Find Michael on LinkedIn: https://www.linkedin.com/in/believer-paladin/

    Find Eros on Twitter: https://twitter.com/erosresmini

    Find Jonathan on Twitter: https://twitter.com/Tocelot

    Find Andrew on Twitter: https://twitter.com/andrewchen

    Learn more about Speedrun: https://a16z.com/games/speedrun/

     

    Stay Updated: 

    Let us know what you think: https://ratethispodcast.com/a16z

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    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • Transitioning From Gymnast to Investor with Aly Raisman

    AI transcript
    0:00:04 and you’re competing at the Olympics if I’m jet lag or if I don’t feel well it’s
    0:00:10 not like the judges care. So at eight years old it started to get really intense
    0:00:14 and I would spend six days in the gym I had Sundays off and I would train
    0:00:19 somewhere between four to seven hours a day. When I was training for the Olympics
    0:00:23 like if I was tired I felt like almost my coach was harder on me on the days
    0:00:28 where I didn’t sleep well. It took me so long to get diagnosed because doctors
    0:00:32 would say to me well you just have anxiety and depression and I’d say well
    0:00:35 I didn’t mention anything to you about anxiety or depression why do you say
    0:00:39 that and they say well you know I’ve read your story in the news. What if you
    0:00:42 have an underlying issue that could have been fixed what if there’s an
    0:00:47 underlying issue that’s been a problem for 10 years. Building a successful
    0:00:51 business can feel like landing a backflip on a balance beam which
    0:00:56 impressively enough some humans have figured out. One foot wrong and it all
    0:01:02 comes tumbling down but get it right and you might just see gold. With the
    0:01:06 greatest event in sports just weeks away we’re sharing an episode that bridges
    0:01:11 these two worlds of elite athletics and elite entrepreneurship straight from a
    0:01:16 two-time Olympic athlete herself. This episode originally published on our
    0:01:21 sister podcast Raising Health features the one and only Allie Raceman. Allie
    0:01:26 has six Olympic medals under her belt and she’s recently pivoted her pursuit
    0:01:30 of excellence towards health in the many forms of it from women’s health and
    0:01:35 fertility to mental health. Here Allie also discusses with a 16z general partner
    0:01:40 Julie Yu and investing partner Daisy Wolfe the parallels of being a founder
    0:01:45 and an Olympian both requiring consistent performance at an elite level but
    0:01:49 also the intensity of being judged against the best in the world and
    0:01:53 equally what is like to transition from that lifestyle to investing so that she
    0:01:58 can scale her impact. Now for more episodes just like this don’t forget to
    0:02:02 search Raising Health wherever you get your podcasts and be sure to look out
    0:02:06 for future Olympic themed episodes in the weeks to come right here on the a 16z
    0:02:13 podcast. But for now we bring you two-time Olympian Allie Raceman.
    0:02:19 Hello and welcome to Raising Health where we explore the real challenges and
    0:02:22 enormous opportunities facing entrepreneurs for building the future of
    0:02:28 health.
    0:02:33 I’m Olivia and I’m Chris. Today’s episode is with Allie Raceman a two-time
    0:02:38 Olympic gymnast investor and part of a 16z cultural leadership fund. She is
    0:02:43 joined by Julie Yu and Daisy Wolfe of a 16z bio and health. Allie chats about her
    0:02:46 background how she thinks about health and fitness now that she is no longer
    0:02:50 competing and a few of her passion projects including financial literacy.
    0:02:54 Allie also talks about her latest forays into investing in how she appreciates
    0:02:58 and empathizes with founders tunnel vision and work ethic. And I just really
    0:03:02 respect founders because they’re working so hard and I can’t imagine how
    0:03:06 stressful it is and I think it’s cool that they’re seeing something that’s
    0:03:09 lacking or seeing something they want to do differently and they’re solving a
    0:03:14 problem and fixing it. You’re listening to Raising Health from a 16z bio and
    0:03:21 health. Allie Raceman no introduction needed obviously you are a total star
    0:03:26 and everyone obviously knows you as being one of the most decorated American
    0:03:31 Olympic gymnasts of all time. And I personally believe that gymnastics is
    0:03:36 just the extreme elite of elite of all professional sports. So first and foremost
    0:03:39 congratulations on an amazing career and just inspiring so many folks including
    0:03:43 ourselves and thank you for being with us here today. Well thank you so
    0:03:47 much that’s so sweet. I am so excited to be here with both of you and thank you
    0:03:52 both also for all of your support. You’ve been so helpful in my new
    0:03:57 investing journeys. Absolutely you have really been campaigning for many many
    0:04:01 things amongst which is health and you’ve been really a strong advocate for
    0:04:06 everything from from mental health to physical health and body positivity for
    0:04:11 women improving health care overall as a system and even something that’s near
    0:04:15 and dear to our heart which is financial health for all consumers. And so what
    0:04:18 we’re hoping to do today is just walk through some of these areas and really
    0:04:22 just hear your perspective on all of these different flavors of health. Let’s
    0:04:26 start with physical health. Allie as an Olympic athlete you’ve spent a lot of
    0:04:32 time thinking about how to stay healthy and maintaining a sense of well-being and
    0:04:36 we’re curious just how this carries over into your life now. What are wellness
    0:04:42 strategies that you employ in your post gymnastics life. Yeah so I’ve learned a
    0:04:47 lot in the last several years about my own mental health and also just my own
    0:04:53 physical health. I think that mental health is much more of a conversation now
    0:04:59 than it was when I was training and I was competing in gymnastics. However even
    0:05:02 so there’s still such a stigma and there’s still so many people that are
    0:05:07 suffering in silence. I do reflect a lot and wish that a lot of the tools that
    0:05:12 I’ve learned now and I’m still learning I wish I had when I was younger. It’s
    0:05:15 really interesting because when I was training and competing you know for
    0:05:20 example if I had an ankle injury I would do whatever I could to heal my ankle I
    0:05:25 would do recovery I would I said heat it whatever I needed and I also did a lot
    0:05:29 of physical therapy for it but there just wasn’t that same emphasis on the
    0:05:33 mental health aspect of it which I think was a huge problem and I didn’t know
    0:05:38 that at the time but you know competing at such a high level I was obviously so
    0:05:42 nervous and so stressed and it’s kind of crazy to look back I didn’t really have
    0:05:49 any tools to help me calm down in those moments so I have been on this journey of
    0:05:54 just really trying to figure out how to just be calm. I kind of let go of this
    0:05:58 idea of like one day I’m gonna feel perfect I’m gonna feel happy all the
    0:06:01 time I think that’s extremely unrealistic there’s so many things in life
    0:06:05 that can happen and so I guess the way that I take care of my mental and
    0:06:09 physical health today is that I see a therapist weekly which has been super
    0:06:15 helpful and I plan to do that for a long time it’s so fascinating to me because
    0:06:21 when I really take care of my nutrition and I feel like my mental health is so
    0:06:24 much better even if something my friends make fun of me even if something
    0:06:27 tastes disgusting but it’s really good for me it makes me feel good I’m gonna
    0:06:31 eat it and I do wish that I had this when I was competing and when I was
    0:06:36 training. What kind of exercise do you do in your post gymnastics life? I get asked
    0:06:39 this a lot and I think people would be really shocked I think people think I’m
    0:06:44 being like modest or I’m kidding but I honestly don’t work out that much so
    0:06:49 first of all I spent most of my life in a gym I started gymnastics and I was two
    0:06:54 years old and at the age of eight I was so busy with my gymnastics career that
    0:06:57 my coach has said that if you want to go to the next level and you want to get
    0:07:01 better you have to stop everything out so I eight years old it started to get
    0:07:07 really intense and I would spend six days in the gym I had Sundays off and I
    0:07:11 would train somewhere between four to seven hours a day and it was like really
    0:07:15 intensely training I still feel like I’m recovering from it because it was
    0:07:20 exhausting so part of it is it’s nice now to be in control and to not have to
    0:07:25 go to the gym every single day I will also say that I believe that working out
    0:07:30 can be really good for our mental health so I’ve kind of had to learn how to
    0:07:35 like re-enjoy working out because I feel like for so long it was so just intense
    0:07:41 I did the same thing every single day and I felt like no matter what I did there
    0:07:44 was always something that needed improvement which it never got boring
    0:07:50 but it was just a lot of pressure my workouts mostly consist of walking a
    0:07:54 lot and people always laugh when I speak at events because I say I walk on the
    0:07:57 treadmill on an incline and people think that’s so funny because I think people
    0:08:04 expect me to do more however I experience like such major burnout when I
    0:08:08 finish competing you know I don’t have a goal of like looking a certain way when
    0:08:13 I work out I just want to feel good and that was also challenging for me going
    0:08:17 from working out seven hours to actually working on the mental side of that and
    0:08:22 being okay with okay today I just walked for 20 minutes but I’m doing the best
    0:08:25 that I can. Hey I think it’s super fun that we just learned that Allie Reisman
    0:08:30 walks uphill on a treadmill so now that now when I go do that at the gym I’m
    0:08:32 just gonna call that the Allie Reisman workout and we’re gonna make that a
    0:08:36 thing so thank you for normalizing that. You mentioned you know the kind of the
    0:08:39 change that from like being in such a high-pressure environment from a workout
    0:08:42 perspective and then sort of the opposite of that the other thing we
    0:08:46 sometimes hear from athletes after they retire is that the kind of motion of
    0:08:50 having a day-to-day coaching regimen as well of just having so much structure in
    0:08:53 your life and then going into an environment where you don’t have that
    0:08:56 do you feel like there’s this void in your life of someone who is gonna you
    0:08:59 know every day when you wake up tell you okay here are the ten things you need to
    0:09:02 do. So it’s so funny it’s like if I’m in a yoga class like I don’t want the
    0:09:06 teacher to tell me anything like I’ve had enough coaching in my life where I
    0:09:13 think that it depends on what the coaching is when it comes to working out
    0:09:17 like I don’t want any coaching if I’m like doing a cycling class or if I’m
    0:09:21 doing yoga or something and the teacher corrects me or they try to push me I’m
    0:09:26 like I’ve had enough of that in my life I love being able to just go to a class
    0:09:31 and if I just feel tired or I don’t feel well I can just like sit there and
    0:09:36 relax because when I was training for the Olympics like if I was tired I felt
    0:09:40 like almost my coach was harder on me on the days where I didn’t sleep well he’d
    0:09:43 be like okay well too bad if you don’t sleep well the night before the Olympics
    0:09:47 we need to push you more today so that you feel more prepared because when
    0:09:51 you’re competing at the Olympics if I’m jet lagged or if I don’t feel well it’s
    0:09:55 not like the judges care if I’m like hey can I do this tomorrow instead it’s not
    0:10:00 an option you’ve got you know your one opportunity so I actually feel the
    0:10:04 opposite where I love sort of having the flexibility and I love being in
    0:10:09 control of doing what feels right for my body yeah and what’s also so inspiring
    0:10:12 hearing you talk Ali is that you could have done anything with your time once
    0:10:15 you retired from gymnastics the fact that you’re putting so much energy into
    0:10:18 multiple ways to make an impact at different levels is really incredible
    0:10:23 and the fact that you also have time to invest is even more incredible because
    0:10:26 we know how much work that is as well we all do investing for different reasons
    0:10:30 folks like Daisy and myself we’ve been builders and companies before in a past
    0:10:35 life and after building one company for a long period of time I think many of us
    0:10:38 recognize that there’s this sort of horizontal opportunity to really build a
    0:10:42 portfolio of opportunities to make an impact at the industry level versus that
    0:10:45 just as one individual company can you share with us what was your inspiration
    0:10:49 what’s the why behind your time that you’re spending on the investing side
    0:10:53 and and what’s it been like it’s been so fun and I really love the experience of
    0:10:58 learning about investing and meeting with founders I became really passionate
    0:11:02 about financial literacy I think that financial literacy and mental health are
    0:11:07 very correlated because I feel like I don’t know if I know anyone who like
    0:11:12 doesn’t feel stressed about finances some capacity and our system is kind of set
    0:11:18 up to make it really confusing and hard to understand I’m very very passionate
    0:11:23 about pushing that conversation because I think that in schools as early as kids
    0:11:28 can really understand I think that they should be taught about like finances and
    0:11:31 the importance of speaking up and asking questions and I know sometimes when
    0:11:34 you’re in a classroom it can be intimidating to ask questions and I
    0:11:37 kind of just told myself that I’m gonna get into this like financial world or
    0:11:42 this investing world I’m just gonna make a pact with myself that I’m not going to
    0:11:45 be afraid to ask questions but I think that I found out really quickly when I
    0:11:49 started to learn about my own finances I felt like I was like being put in this
    0:11:55 box of a dumb athlete and so I just felt very overwhelmed and I also realized how
    0:11:59 much anxiety it was giving me not understanding and I really believe that
    0:12:03 like knowledge is power and I think why I say it’s correlated to mental health
    0:12:07 because the more that I learned about finances the more confident I became
    0:12:12 and there’s so much shame around talking about money and so I just became
    0:12:15 really interested in that idea of like why is it so hard to talk about and if
    0:12:20 it was more normalized would more people be able to understand how to better
    0:12:24 save their money and if people felt less shame around asking questions I think
    0:12:29 it could really make a big difference and I’ve been fortunate since I was about
    0:12:33 17 years old getting to work with a lot of different companies and so it got me
    0:12:36 really interested in learning more about like the behind the scenes of how these
    0:12:41 companies operate and then I got excited about this idea of meeting with founders
    0:12:44 where they’re seeing something that’s lacking or seeing something they want to
    0:12:48 do differently and they’re solving a problem and fixing it. Similarly with my
    0:12:52 gymnastics career it was like the same thing all the time you’re so focused you
    0:12:56 have this like tunnel vision and I just really respect founders because they’re
    0:13:00 working so hard and I can’t imagine how stressful it is and just like the whole
    0:13:05 process of raising money and there’s probably so many different stressors
    0:13:08 that I don’t even know the first thing about but I just really admire and
    0:13:11 respect their work ethic and their passion. I’m sure the founders who are
    0:13:14 listening to this will absolutely appreciate your last comments there and
    0:13:18 perhaps on a future podcast we can debate whether it’s harder to raise
    0:13:22 capital in this market or win a gold medal at the Olympic gymnastics
    0:13:25 competition but actually that is what we hope to achieve with our health care
    0:13:30 system at some point but we all know that the system fails every day in many
    0:13:34 many ways to achieve anything close to that so curious what are some of the
    0:13:39 areas that do inspire you to invest in from a health care lens? Yeah well it’s
    0:13:44 interesting I mean I’m obviously a patient and so I have you know seen a
    0:13:48 lot of different doctors over the years a couple of years ago one of my best
    0:13:55 friends Abby had stage 4 cancer and she thankfully is in remission and she has a
    0:13:59 beautiful healthy baby so I’m so thankful and just forever grateful to her
    0:14:04 doctors for truly saving her life but her and I we’ve had a lot of
    0:14:10 conversations around just watching her go through that horrific experience and
    0:14:15 just the anxiety, the mental health side of having cancer and she talks about how
    0:14:19 there are some doctors who are amazing and then there’s some that are not
    0:14:22 amazing and you know when she was in the hospital she told me that there are
    0:14:26 certain instances where like she could hear the doctors or nurses like making
    0:14:32 fun of patients when she’s resting and laying in bed and I think that the
    0:14:36 patient experience should be more front and center for doctors because you know
    0:14:42 I obviously have the utmost respect for doctors but as a patient a lot of people
    0:14:45 I don’t think are comfortable speaking up for themselves or advocating for
    0:14:49 themselves and so you know while I talked about mental health a lot and how
    0:14:54 it’s more normalized and there’s still a stigma I actually found it took me so
    0:14:57 long to get diagnosed because doctors would say to me well you just have
    0:15:02 anxiety and depression and I’d say well I didn’t mention anything to you about
    0:15:05 anxiety or depression what why do you say that and they say well you know I’ve
    0:15:08 read your story in the news and I’m like okay well now I feel like you’re not
    0:15:13 really paying attention to me as the patient and you’re like making an
    0:15:16 assumption based off of what you saw in the news and so that was really
    0:15:20 challenging for me and I find that incredibly unprofessional and even if
    0:15:24 somebody is you know they are feeling sick from mental health I feel like the
    0:15:28 doctors are just like oh just go to a therapist like see you next year but
    0:15:33 there’s like no step to help somebody get the therapist but back to your
    0:15:37 question about what I’m really interested in I find myself at the age of
    0:15:42 29 I’m really interested in women’s health but particularly the fertility
    0:15:46 space and at the age where some of my friends I’ve had babies some of them are
    0:15:49 pregnant some of them are freezing their eggs we’re all kind of all in
    0:15:55 different stages and I just find it very odd that so many women we don’t
    0:15:59 realize if we’re gonna have trouble getting pregnant until we actually want
    0:16:03 to start getting pregnant and I just think like if there was something that
    0:16:08 when whatever age doctors think is appropriate whether it’s in your early
    0:16:12 20s or in your late teenagers I don’t know I’m not a doctor but I think that
    0:16:16 this idea of just what if you have an underlying issue that could have been
    0:16:19 fixed what if there’s an underlying issue that’s been a problem for 10 years
    0:16:24 and if you fix it 10 years ago from a blood test or something then it wouldn’t
    0:16:28 have affected you and I think in this world where miscarriages and infertility
    0:16:32 is so common and postpartum there’s so many things that women suffer and go
    0:16:37 through and there’s just not good solutions and then also we get our
    0:16:42 period every single month and I know a lot of women that like at least one day
    0:16:46 to multiple days of the month we feel terrible I just don’t think there is
    0:16:50 enough conversation and research into women’s health and I don’t think it’s
    0:16:54 acceptable that it’s normalized that so many women have postpartum and there’s
    0:16:59 not a solution to help women as they’re navigating that huge change in their
    0:17:04 life yeah that’s incredible I mean you touched on like access issues referral
    0:17:08 issues variants and care delivery across doctors and so much of you know when
    0:17:12 you described as kind of the challenges of health care I’ll also boil down to be
    0:17:15 payment model and kind of the payment incentive that drive all these are
    0:17:19 rational behaviors that we we think are completely insane but are sort of like
    0:17:23 the way the system was designed and so I would just say that you know we know
    0:17:26 that the future is bright we get to meet with these amazing entrepreneurs who
    0:17:29 are challenging the status quo every single day and so I think there’s a lot
    0:17:32 to be excited about I had the chance to do a clinical rotation during grad school
    0:17:36 and happen to get matched to the breast cancer radiology clinic at one of the
    0:17:40 major hospitals in Boston and as I was doing my rotation saw all these
    0:17:44 procedures being done a mammogram a biopsy etc we had to write a report
    0:17:49 afterwards as kind of a thesis and mine was effectively it’s very clear that all
    0:17:53 of these devices and machines were designed by men and not taking into
    0:17:57 account at all what that user experience is as a female being subject to these
    0:18:01 procedures so and there’s a ton of opportunity there yeah I’ve done a lot
    0:18:04 of calls and worked with a lot of companies over the years where it might
    0:18:08 be like a company that’s around women’s health but then a lot of the execs are
    0:18:12 men and men are welcome I think there’s so many amazing men in my life and I’m
    0:18:16 really grateful for that but if you’re doing a product that’s for women it’s
    0:18:20 really important to also talk to women and have them be a huge part of the
    0:18:25 conversation to make sure you’re making a product that is helpful and feels good
    0:18:30 for them amen okay this is amazing Ellie because with my past entrepreneur hat on
    0:18:32 and thinking about like you as a potential investor in my company you’ve
    0:18:36 already shown that like you’re a patient and you can bring that perspective
    0:18:39 you’re a survivor you can bring that perspective you’re a start athlete and
    0:18:43 you can bring sort of that brand and start power to the table as well what
    0:18:47 do you want entrepreneurs to know about your unique value proposition and and
    0:18:49 maybe the broader set of value propositions that professional athletes
    0:18:54 can bring to entrepreneurs when they invest in their companies yeah well
    0:18:58 thank you sometimes my perspective as like being a survivor of abuse and how
    0:19:04 that might be like less triggering or easier for someone to use I have sort
    0:19:07 of brought that perspective if it’s in the health care space and then of course
    0:19:12 as an athlete I’m very fortunate to have the platform that I have so I think
    0:19:17 where it makes sense most of the companies I invest in I do it privately
    0:19:20 but there are some that we decide together it makes sense to do a
    0:19:25 partnership and to promote it the campaigns that I do publicly that are
    0:19:30 just like pushing a product that don’t talk about like something philanthropic
    0:19:35 whether it’s a beast prevention for me or mental health they don’t really do
    0:19:38 well and I honestly frankly don’t do that anymore where it’s just like a
    0:19:45 specific product like we always try to make it more of a conversation and how
    0:19:48 is it authentic to me is it something that I really use is it something that
    0:19:54 really aligns and fits in with my values and I’ve seen firsthand how my most
    0:19:58 successful campaigns I’ve actually been able to be a part of the marketing side
    0:20:03 of it where I can like meet with like the CMO or the CEO and there’s been many
    0:20:06 campaigns I’ve been a part of where I’ve actually been able to be a part of
    0:20:10 those like brainstorming marketing conversations which is just so fun this
    0:20:14 generation really votes for their dollar and people really want to support
    0:20:19 companies that they believe in that are doing good and aren’t just like trying
    0:20:23 to sell a product they also have found the more honest I’ve been I’ve been so
    0:20:28 surprised so many people can actually relate to what I’ve experienced well
    0:20:31 Ali you are to use the technical term freaking amazing thank you so much for
    0:20:35 spending your time with us today you’re a truly inspiration to everyone and on
    0:20:38 behalf of everyone in health care we are just incredibly grateful that you are
    0:20:41 bringing your energy to our space because we we definitely need it thank you
    0:20:44 so much thank you both
    0:20:53 thank you for listening to Raising Health Raising Health is hosted and
    0:20:57 produced by me Chris Tatiosian and me Olivia Webb with the help of the bio
    0:21:02 and health team at A16Z the show is edited by Phil Hegseth if you want to
    0:21:06 suggest topics for future shows you can reach us at raisinghealth@a16z.com
    0:21:12 finally please rate and subscribe to our show the content here is for
    0:21:16 informational purposes only should not be taken as legal business tax or
    0:21:20 investment advice or be used to evaluate any investment or security and is not
    0:21:25 directed at any investors or potential investors in any A16Z fund please
    0:21:28 note that A16Z and its affiliates may maintain investments in the companies
    0:21:32 discussed in this podcast for more details including a link to our
    0:21:37 investments please see A16Z.com/disclosures
    0:21:47 [BLANK_AUDIO]

    Former gymnast and current investor Aly Raisman joins general partner Julie Yoo and investment partner Daisy Wolf of a16z Bio + Health.

    In this episode, Aly Raisman shares her quest for healthier living—physically, mentally, and financially—on her journey from gymnast to a business investor. Having transitioned from an intensely structured routine, Aly emphasizes the need for more open conversations about mental health and financial literacy. She speaks passionately about the gap in women’s health solutions and hopes to inspire entrepreneurs to create impactful businesses. Aly’s experiences as a patient, survivor, and global figure adds a unique dimension to her perspective as an investor. This candid conversation with Aly and Julie Yoo sheds light on Aly’s passion for more education within the investment space, offering invaluable insights for entrepreneurs, particularly in biotech and healthcare.

     

    Resources: 

    Find Aly on Twitter: https://x.com/aly_raisman

    Find Julie on Twitter: https://x.com/julesyoo

    Find Daisy on Twitter: https://x.com/daisydwolf

     

    Stay Updated: 

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    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • Live at Tech Week: Delivering AI Products to Millions

    AI transcript
    0:00:01 (upbeat music)
    0:00:03 – We’ve existed for about three years
    0:00:04 and we’ve passed everybody in revenue
    0:00:06 in like literally a year and a half.
    0:00:09 Usage is important, but that does not define
    0:00:12 the long-term success of an actual customer.
    0:00:14 – I think that daily active use
    0:00:19 is a pretty terrible metric to uncover customer value.
    0:00:21 – There have been companies built in the past
    0:00:22 on just great design.
    0:00:25 There’s no reason that they can’t be built on the AI side.
    0:00:27 – In upgrading all of these multiple layers,
    0:00:29 they’ll essentially end up building your core
    0:00:31 defensibility in the market.
    0:00:34 – Retention problems are just activation problems
    0:00:35 in disguise.
    0:00:37 – Between June 3rd and June 9th,
    0:00:41 A16Z ran its second annual New York Tech Week.
    0:00:43 Now this week had thousands of people attend
    0:00:46 a record-breaking 700 plus events,
    0:00:49 including one event run by our podcast team.
    0:00:51 Now this A16Z live recording
    0:00:53 is exactly what you’re about to hear,
    0:00:57 but first let’s take a quick trip to memory lane.
    0:00:59 When ChatGPT was launched in November, 2022,
    0:01:03 it quickly became the fastest growing consumer application
    0:01:07 in history, but TechSpace AI was just the beginning.
    0:01:08 In the next 500 days,
    0:01:12 a flurry of AI models launched that spanned new modalities,
    0:01:15 from images to video to audio to 3D,
    0:01:18 that all yielded an entire ecosystem of applications
    0:01:20 that have upended, quite frankly,
    0:01:23 the way we work, learn, create, and even play.
    0:01:27 Now here in mid-2024, competition is fierce,
    0:01:29 but I don’t think I have to convince you of that.
    0:01:30 So for this live recording,
    0:01:33 we brought in key leaders at three AI companies
    0:01:35 to discuss how they’ve managed to stand out
    0:01:36 amongst the noise,
    0:01:40 because they have products that reach millions of users.
    0:01:41 So in this conversation,
    0:01:43 you’ll hear from Gora Misra,
    0:01:45 co-founder and CEO of Captions,
    0:01:46 Karla Sarena,
    0:01:48 chief revenue officer of 11 Labs,
    0:01:52 and Laura Birkhauser, VP of product at Descript.
    0:01:55 Together, we explore what ladders up to AI products
    0:01:57 that people actually use,
    0:01:59 including what features really matter
    0:02:03 when AI is necessary or distracting,
    0:02:04 whether you need to own your models,
    0:02:07 designing for retention in international expansion,
    0:02:10 and of course, where we all go from here.
    0:02:13 I hope you enjoy this recording as much as I did.
    0:02:17 As a reminder, the content here
    0:02:19 is for informational purposes only,
    0:02:21 should not be taken as legal, business, tax,
    0:02:22 or investment advice,
    0:02:25 or be used to evaluate any investment or security,
    0:02:26 and is not directed at any investors
    0:02:29 or potential investors in any A16Z fund.
    0:02:31 Please note that A16Z and its affiliates
    0:02:33 may also maintain investments
    0:02:35 in the companies discussed in this podcast.
    0:02:36 For more details,
    0:02:37 including a link to our investments,
    0:02:41 please see a16z.com/disclosures.
    0:02:48 And so we’re actually less than two years since that,
    0:02:51 but a lot of people are familiar with text-to-text,
    0:02:53 but all three of the products here
    0:02:55 go into several other modalities, right?
    0:02:57 We’ve got audio, we’ve got video, imagery.
    0:02:59 So I think that’s really exciting,
    0:03:02 but maybe we could actually just start with the why now,
    0:03:05 and specifically maybe the unlock that we’ve seen
    0:03:07 with unstructured data, right,
    0:03:09 before we use databases and everything needed
    0:03:10 to be really structured
    0:03:12 in order for us to make sense of it.
    0:03:13 Today, that’s not quite the case.
    0:03:14 So Gaurav, maybe we start with you,
    0:03:17 and what do you see really today as the why now?
    0:03:19 – Yeah, I mean, I think it’s a really exciting time,
    0:03:21 generally, just because obviously there’s been
    0:03:22 a couple of key breakthroughs,
    0:03:25 just in terms of technology with transformers
    0:03:28 and diffusion models and so on and so forth.
    0:03:31 But I think the key here is we’re able to use a lot more data
    0:03:33 to train these models now than ever before, right?
    0:03:35 And there’s a bunch of things happening,
    0:03:38 both on the hardware side, the software side, right?
    0:03:40 And the data side to enable that to happen.
    0:03:42 And that’s why we’re seeing amazing results, right?
    0:03:44 If you look at a lot of what the key players
    0:03:46 in this industry are doing,
    0:03:47 they’re just training these models
    0:03:50 with more and more and more data every iteration, right?
    0:03:52 And that’s able to produce reliably better
    0:03:53 and better and better results,
    0:03:55 which is pretty amazing to see.
    0:03:57 And it’s not in sight so far.
    0:03:58 – Carlos, maybe we’ll go to you
    0:04:00 before we talk about description in a second.
    0:04:00 – I think it’s correct.
    0:04:02 The key message for us is experimentation
    0:04:04 for 11 lamps has been like,
    0:04:05 if you put garbage in, garbage out, right?
    0:04:07 If the quality of the data that you put in
    0:04:09 is not that great,
    0:04:10 then essentially what you end up producing
    0:04:13 is half-baked with lots of mistakes and things like that, right?
    0:04:15 And we can see that with Whisper,
    0:04:16 how many of you have tried Whisper
    0:04:17 and it comes out that like,
    0:04:19 subscribe, subscribe, subscribe,
    0:04:20 and things like that, right?
    0:04:21 All the time.
    0:04:24 That’s true, we’ve seen it all the time.
    0:04:25 But so I think like for us,
    0:04:27 like there’s been a layer and initially we trained it
    0:04:29 with a lot of data and then over time,
    0:04:30 we ended up curating the data
    0:04:33 to make sure that like it is very high quality.
    0:04:34 Otherwise you’re not able to achieve the results
    0:04:36 that you are expecting or that your consumers
    0:04:38 or your businesses would need, right?
    0:04:39 But that’s a fundamental change
    0:04:41 that has happened in the market.
    0:04:43 Amounts of data being used with transformers
    0:04:46 and alarms to generate this like human content generated,
    0:04:49 like whether that’s speech or text or anything else, right?
    0:04:51 – Yeah, 3D models, we’re seeing all types of stuff.
    0:04:54 So the reason I wanted to wait to talk to you, Laura,
    0:04:57 is because I don’t know how many of you have used Descript,
    0:05:00 but any guesses on when Descript started?
    0:05:03 We talked about Chat GPT, November 2022.
    0:05:06 So Descript has been around since 2017.
    0:05:07 The reason I wanted to frame that
    0:05:09 is because obviously the last couple of years,
    0:05:12 very exciting, but machine learning, AI,
    0:05:13 in the ’50s is when this really got going.
    0:05:15 And obviously there have been unlocks,
    0:05:17 but I want to get your pulse, Laura,
    0:05:20 on the importance of putting AI at the forefront.
    0:05:22 A lot of AI is embedded in the applications
    0:05:25 that probably people in the room are building as well,
    0:05:27 but Descript long-used machine learning
    0:05:28 before really saying, “Hey,
    0:05:30 you’re using machine learning, AI,” et cetera.
    0:05:32 So what are your thoughts?
    0:05:33 – That’s right.
    0:05:36 So Descript is software that lets you edit video
    0:05:37 just like a text document.
    0:05:41 So if you can edit a Google document, congratulations.
    0:05:43 You’re also a video editor.
    0:05:44 If you can just download Descript,
    0:05:46 and now you can edit video.
    0:05:47 And it turns out that the technology
    0:05:50 that sort of undergirds that is in fact AI,
    0:05:52 but we haven’t traditionally come forward
    0:05:55 and said, “We’re an AI video editor.”
    0:05:57 A, there wasn’t like this huge reward
    0:05:58 in the hype cycle for saying that.
    0:06:00 So we didn’t have marketers saying it,
    0:06:03 but also what we found is that customers didn’t care, right?
    0:06:05 They don’t care what is the technology
    0:06:07 that is creating this value for me.
    0:06:09 What they care about is there is value here.
    0:06:10 This is helpful for me.
    0:06:14 And so that was long hour way of designing software,
    0:06:16 and it probably would have continued that way forever,
    0:06:19 except that actually when I think about the thing
    0:06:20 that is making us change our minds,
    0:06:23 in addition to some of these cool models that are coming out,
    0:06:26 it is that the way that humans and computers
    0:06:27 are interacting is totally different.
    0:06:28 So you can talk to your computer now.
    0:06:31 You can use human language to communicate
    0:06:33 more subtle intentionalities that you have
    0:06:36 for how you wanna edit your video or create your video.
    0:06:40 So as this technology has gotten better, we thought,
    0:06:42 well, gosh, do we actually wanna design AI
    0:06:43 and the product differently?
    0:06:45 And if so, how?
    0:06:46 And so with our latest release,
    0:06:48 we’re actually bringing all of the AI features
    0:06:51 that we’ve long had in the product into the same space
    0:06:53 and adding a ton of new ones.
    0:06:55 And we had a big discussion with our design team
    0:06:56 about how do we do this?
    0:06:57 And one of the big discussions we had is,
    0:07:01 is AI a magic bond or is it an entity?
    0:07:04 And one of the big decisions you have to make there
    0:07:06 is that traditional creators are much more used
    0:07:08 to interacting with Pro Tools software
    0:07:11 or creative software in a point and click way.
    0:07:12 And so they want a magic wand.
    0:07:15 But you have this whole new wave of people
    0:07:18 that are now generating and editing video and audio
    0:07:20 and they’re used to using kind of more
    0:07:22 of this entity interaction.
    0:07:24 They want an entity.
    0:07:26 Then you start talking about an entity, right?
    0:07:28 And you get into internal discussions like,
    0:07:31 I don’t know if it’s an entity that might be a bad idea
    0:07:33 because what about our robot overlords
    0:07:35 are inevitable robot overlords, right?
    0:07:37 That’s kind of like one side of the debate.
    0:07:39 And then hilariously, you have the other side
    0:07:41 of the debate that I don’t want an entity
    0:07:43 because actually it turns out this technology
    0:07:44 is really stupid sometimes.
    0:07:47 And if you make it an entity, you said like,
    0:07:49 hey, welcome, this is like your co-editor.
    0:07:51 And it turns out your co-editor is like a total moron
    0:07:53 that makes horrible suggestions sometimes
    0:07:54 because it’s hallucinating.
    0:07:57 And so we’re like, okay, how do we deal with that?
    0:07:59 So what we decided to do with this newest release
    0:08:02 is we’re actually, we’re calling it underlord.
    0:08:06 And it’s a nod to the potentially apocalyptic future of AI.
    0:08:07 Well, also admitting that right now,
    0:08:10 this thing is kind of like a very eager,
    0:08:12 like somewhat competent intern
    0:08:15 that does a really great job at the first pass
    0:08:17 of the worst parts of your workflow.
    0:08:18 So that’s some of the story
    0:08:20 about how we’ve thought about designing with AI over the years.
    0:08:22 – I’d love to get both of your posts.
    0:08:24 Like, how do you think about that same question?
    0:08:27 What part of AI do I put at the forefront?
    0:08:29 Or do I just use this really powerful technology
    0:08:31 and kind of give my users what they want
    0:08:34 but not really sell this AI thing too much?
    0:08:36 – So I’d say, at the end of the day,
    0:08:37 you have to solve customer problems.
    0:08:39 That’s what we’re trying to do, right?
    0:08:41 I think the biggest mistake that can be made is to say,
    0:08:43 hey, here’s the technology.
    0:08:45 You can have technology, do whatever you want.
    0:08:47 People can’t just take that and be like, okay,
    0:08:49 I know what to do with this, right?
    0:08:50 I think you have to mold it into a product
    0:08:52 that solves a problem at the end of the day.
    0:08:53 So I think that’s like traditional.
    0:08:54 Nothing’s changed there, right?
    0:08:56 It’s exactly the same as before.
    0:08:57 And if you’re not doing that,
    0:08:59 then essentially you’re gonna see retention problems.
    0:09:01 Where you’re gonna see people coming in,
    0:09:02 trying out the thing,
    0:09:03 not knowing exactly what to do with it,
    0:09:06 not working perfectly for their use case.
    0:09:07 And then they’ll leave, right?
    0:09:09 Kind of tourism is what we’re calling it, right?
    0:09:11 But I think at the same time on the marketing side,
    0:09:13 like stepping away from product for a second,
    0:09:17 there is something to be said about sort of having AI
    0:09:19 in your message on the marketing side.
    0:09:20 Here’s why.
    0:09:23 If I just say, I have a better product,
    0:09:25 it’s so much better, you won’t believe it.
    0:09:26 I’ll be saying the same thing
    0:09:30 that people have been saying for literally 100 years
    0:09:31 about every product, right?
    0:09:33 Like, yeah, trust me, it’s better, right?
    0:09:34 Trust me, come on and try it out.
    0:09:37 This is every single product that exists, right?
    0:09:40 But putting in that AI term in there,
    0:09:42 just from the marketing side, this is just tactical,
    0:09:44 actually lets people understand,
    0:09:47 oh wait, this is gonna be a step change, right?
    0:09:48 Of course, if you don’t meet that expectation
    0:09:51 when they land in the product, you’re gonna have a problem.
    0:09:53 But if you’re able to meet that expectation,
    0:09:55 putting that in kind of does inform people about like,
    0:09:58 okay, this is not gonna be sort of like the better product,
    0:10:00 it’s gonna be a step change
    0:10:01 compared to everything else we’ve seen.
    0:10:03 So that’s the general guide.
    0:10:04 I do feel like a lot of people
    0:10:06 are just throwing in the AI term in the marketing side now
    0:10:08 just to kind of get the eyeballs there.
    0:10:11 And maybe that message will kind of get lost a little bit.
    0:10:14 But so far, the innovation has just been so strong
    0:10:16 that the message has kind of remained strong.
    0:10:17 And if it continues this way,
    0:10:19 the marketing side can continue as well.
    0:10:23 But at some point, it might get muddled, we’ll see.
    0:10:25 – Maybe just I can add on a modifier for you
    0:10:28 because I think not only do you have to market the product,
    0:10:30 but if you use this bucket term of AI, right?
    0:10:31 That means many different things.
    0:10:32 Do you own your models, build your own models?
    0:10:34 Are you an API wrapper?
    0:10:35 And so I would love to hear from you, Carlos,
    0:10:37 at 11 Labs in particular,
    0:10:40 like in building your own models as well,
    0:10:42 like how does that play into it?
    0:10:43 Is it a whole marketing packaging
    0:10:45 thinking about what you share and what you don’t?
    0:10:46 – Yeah, we need to be open.
    0:10:48 Like we are an AI company, sorry guys.
    0:10:49 And we say it all the time, like we say,
    0:10:52 like we do AI voices, we do AI sound effects,
    0:10:54 we’re gonna be doing AI music in many ways.
    0:10:57 So for us, like it’s all about the audio sphere, right?
    0:10:59 So it’s like that layer infrastructure
    0:11:01 that allows you to create high quality engaging content,
    0:11:05 whether that is like with voice, with like audio overall.
    0:11:06 And the way we thought is, well, actually,
    0:11:10 there wasn’t really a good quality text-to-speech available
    0:11:12 before we invented our own site.
    0:11:14 So we were fundraising initially.
    0:11:16 It was difficult because the market is not there,
    0:11:18 like how are you gonna be getting customers and so on.
    0:11:21 So it was like, it was really tough in the early days.
    0:11:23 But we thought, look, if you’re able to deliver quality
    0:11:25 that voices that sound engaging,
    0:11:27 the applications on top of it,
    0:11:30 then you end up having market that is just fully on top, right?
    0:11:33 So how do you do that? AI voices, simple and plain, right?
    0:11:34 And that worked really well.
    0:11:37 So we started with like the LLM pure like API play
    0:11:40 with a very simple UI that was end of January last year
    0:11:42 when we launched the product.
    0:11:43 And we thought, well, actually,
    0:11:45 there’s gonna be like some pieces of like some content creators
    0:11:47 that might want to use the UI,
    0:11:50 but we expect on the API side, it’s gonna be quite big purely
    0:11:53 because like people might want to build their own applications
    0:11:53 on top of it.
    0:11:55 And it worked really well.
    0:11:57 And since then, what we also realized, like,
    0:11:59 well, you cannot expect all of the business
    0:12:01 to have the capabilities, build their own application.
    0:12:04 So what if we end up going full end to end
    0:12:05 and we build our own applications
    0:12:08 for areas where we really care about?
    0:12:10 And that’s how we end up creating like projects
    0:12:13 or audio native or like the dubbing product
    0:12:14 and a bunch of other pieces, right?
    0:12:16 So it’s been very interesting for us.
    0:12:19 And of course, we always say that it’s AI driven
    0:12:21 because at the end of the day, we’re a foundational model
    0:12:24 that happens to also build applications on top of it.
    0:12:26 But I think like the beauty of it
    0:12:30 is that anyone can build anything they fancy on top of the API.
    0:12:32 And today we power quite a lot of different companies,
    0:12:35 more than 41% of Fortune 500 companies use 11 Labs.
    0:12:37 We power a lot of startups
    0:12:39 and we are very proud to help all of these companies
    0:12:40 like succeed as well, right?
    0:12:42 So it’s been very interesting,
    0:12:44 like having both sides, both motions,
    0:12:46 like the pure API play and the application layer
    0:12:48 on top of it, it’s challenging as well.
    0:12:50 Because then you and I’m having two different profiles
    0:12:52 in terms of like on the product side,
    0:12:53 on the engineering side and everything, right?
    0:12:55 So you always need to balance it.
    0:12:57 – Absolutely, maybe we can actually jump straight
    0:12:58 to that question of competition.
    0:13:00 I feel like if there’s one question
    0:13:02 that comes up on this podcast the most,
    0:13:03 everyone’s excited about AI and they’re like,
    0:13:06 okay, well, where does differentiation come up?
    0:13:08 Where do moats arise?
    0:13:10 I’d love to prove all three of you on that.
    0:13:11 I know we’re early,
    0:13:12 but where do you think you can stand out?
    0:13:15 Do you really need to be building at the model layer?
    0:13:17 You talked about the infrastructure layer,
    0:13:19 or can you really just build a really great UI
    0:13:20 and capture the app layer?
    0:13:22 What do you think about that?
    0:13:24 – Maybe I’ll start here by saying,
    0:13:26 again, not much has changed in terms of like,
    0:13:28 there have been companies built in the past
    0:13:29 on just great design.
    0:13:31 So I think there’s no reason
    0:13:33 that they can’t be built on the AI side.
    0:13:36 But at this point of the journey,
    0:13:39 there’s so much to innovate on and so much to build on.
    0:13:41 It does help to have models
    0:13:43 that are foundational and built in-house
    0:13:46 because it does give you that extra differentiation
    0:13:46 and that extra step.
    0:13:50 It is a competitive field and the deeper you can go
    0:13:54 and the more you can build from the ground up really,
    0:13:56 connecting these different layers together, right?
    0:13:59 You can deliver super fast fees on your models.
    0:14:02 You can deliver the highest quality that anyone’s seen, right?
    0:14:04 And you can deliver a great user experience
    0:14:06 that solves a real problem.
    0:14:07 Then you have an advantage there.
    0:14:10 So I would say though for consumer companies,
    0:14:11 which we’re a consumer company, right?
    0:14:14 Like we’re used by literally millions and millions
    0:14:15 of people around the world
    0:14:17 and people make over a hundred thousand videos a day
    0:14:19 published through our platform.
    0:14:21 For a consumer company,
    0:14:24 it does matter a lot to have that differentiation
    0:14:25 at this stage.
    0:14:26 I think in the longest term,
    0:14:29 if you think about what differentiates a consumer company
    0:14:32 in the longest of terms, it’s probably just brand, right?
    0:14:35 And that’s kind of what you’re building over a period of time.
    0:14:38 And the only way a brand dies is like with a generation.
    0:14:40 It also takes a generation to build a brand too, right?
    0:14:43 So I think that’s kind of the ultimate goal
    0:14:44 of where you want to get to.
    0:14:45 But I think in the meantime,
    0:14:48 there’s many modes that last like different lengths of time,
    0:14:51 whether that’s the data mode or a model or like,
    0:14:54 whether it’s a UI, UX mode, whatever it might be.
    0:14:57 – So at Descript, I would say that we are a horizontal editor
    0:14:59 and we’re a very powerful human editor,
    0:15:02 which is something that I think a lot of kind of newer
    0:15:04 just started in the age of AI,
    0:15:06 in the second chapter of AI companies can’t say
    0:15:07 because it takes a long time
    0:15:09 to build a really powerful,
    0:15:11 horizontal human driven editor.
    0:15:14 So you can do like really complex editing jobs with Descript.
    0:15:17 If you already are like an expert who’s great at this work
    0:15:21 and you can do it really quickly with low barriers to entry.
    0:15:22 If you’re new to it.
    0:15:24 So that reason, I think the application layer
    0:15:25 is especially important to us.
    0:15:27 And I almost see it as a mirror
    0:15:29 to kind of what 11 Labs was saying,
    0:15:31 where I think like in general,
    0:15:35 we have a may the best model win sort of mentality
    0:15:37 when it comes to all of the different models
    0:15:39 that we use in our application layer.
    0:15:41 And that’s because we’re trying to do everything,
    0:15:44 not just AI voices, but things like eye contact,
    0:15:48 things like avatars, things like AI speech, transcription,
    0:15:50 editing video with text.
    0:15:53 If there’s like a cool thing happening in AI
    0:15:55 when video generation, when Thora comes out,
    0:15:57 that will be in Descript, we’re gonna have it.
    0:16:00 And so I think like generally we have an attitude
    0:16:02 that is may the best model win,
    0:16:04 we wanna give our customers the absolute best experience.
    0:16:08 If we don’t see interesting enough work happening
    0:16:11 in a space that we wanna be in, we’ll build that model.
    0:16:14 And I think there are real places for Descript to differentiate
    0:16:16 because we own so much of the editing workflow
    0:16:19 and have really great editing workflow data
    0:16:20 that like that may be a place
    0:16:23 where our models become differentiated.
    0:16:25 But in general, if you’re trying to provide
    0:16:27 a ton of different services to customers
    0:16:29 across a ton of different workflows,
    0:16:32 it can really make sense to not try to build
    0:16:34 every single one of those in-house,
    0:16:36 but instead to be like very thoughtful
    0:16:39 about where it makes sense to own versus buy or borrow.
    0:16:42 – I think like there’s an element here on,
    0:16:45 if you think about purely about differentiation in these days,
    0:16:47 like ’cause the market has bought a lot
    0:16:49 from purely foundational picks and shovels.
    0:16:52 And now the transition towards the app side,
    0:16:53 what you end up thinking about
    0:16:56 or how I think about defensibility is fear about your users,
    0:16:58 your consumers or your businesses.
    0:17:00 That’s essentially what will drive defensibility
    0:17:01 over the long term.
    0:17:03 And if you think about Instagram or Meta
    0:17:05 or like a Facebook in the early days,
    0:17:06 what was their defensibility?
    0:17:08 There was literally nothing out there,
    0:17:10 but they were able to fast grow,
    0:17:12 outpace everyone in terms of growth, deliver value.
    0:17:15 And then the UI was not even that great, right?
    0:17:17 But it was actually like you were feeling
    0:17:18 there was part of the community
    0:17:20 and it was like the experience that you were getting, right?
    0:17:22 So defensibility was coming from the actual users
    0:17:24 versus the product itself.
    0:17:26 And I think like the transition that we’ve seen today
    0:17:30 from the foundational models sort of like app side,
    0:17:31 it’s actually very interesting
    0:17:33 because then you’re able to engage different type
    0:17:35 of generations or different type of users
    0:17:37 that like if you retain them
    0:17:39 and you give them the best experience possible,
    0:17:41 they will stay there for the coming year, right?
    0:17:43 Whether that is because they’re building their own applications
    0:17:45 on top of that because they’re essentially like,
    0:17:47 “Well, I want to use your app overall.”
    0:17:49 And the way we also think about this at 11 apps
    0:17:51 is like layers, right?
    0:17:53 So having the foundational layer,
    0:17:55 which is like the research that we provide, right?
    0:17:58 We do LMS and essentially we provide the best text to speech
    0:18:01 and AI voices in the market, fantastic.
    0:18:02 What else do you have on top of it?
    0:18:05 The data that we’ve acquired that we’ve licensed from partners,
    0:18:07 the products end-to-end products that we’re building,
    0:18:10 the partnerships that we have, the customers that we have.
    0:18:12 So you end up creating all of these multiple layers
    0:18:13 that essentially end up building
    0:18:16 your core defensibility in the market
    0:18:19 that hopefully will sustain us for the coming years, right?
    0:18:20 As the market changes,
    0:18:22 if one of the layers like ends up getting replaced,
    0:18:24 absolutely fine because then essentially you have
    0:18:25 all of the other ones that will back you
    0:18:27 over the long term, right?
    0:18:28 – Yeah, and something you spoke to here
    0:18:30 is just like this new generation.
    0:18:32 And I think we’re all kind of trying to figure out
    0:18:34 what can now be done with AI
    0:18:37 when you talked about UX even or designing a new UI.
    0:18:39 Voice is now in the mix in ways that it wasn’t before,
    0:18:41 but then you also have this question of,
    0:18:43 “Do I want to completely reinvent the wheel?
    0:18:45 “Show someone a very powerful UI
    0:18:47 “that they’re maybe just not familiar with
    0:18:48 “and that you don’t retain them.”
    0:18:50 So Gaurav, I’d love to probe you on retention.
    0:18:52 I mean, even just from the perspective of desktop
    0:18:54 versus mobile, you do have a mobile app.
    0:18:56 How do you think about designing for that?
    0:18:59 Because we’ve seen over over the last, let’s say two years,
    0:19:01 there’s this extreme willingness to try,
    0:19:03 but then I think someone internally
    0:19:05 and coin this like AI tourist phenomena, right?
    0:19:08 It’s people try and then a lot of them do leave.
    0:19:09 So how do you think about that?
    0:19:11 – Yeah, I mean, it’s something we think about a lot
    0:19:12 because at the end of the day,
    0:19:14 I think you can kind of go by metrics
    0:19:15 and you can really worry about like,
    0:19:18 “Oh, there’s retention number, it should be at that number.”
    0:19:20 And you can kind of get caught up in that a little too much
    0:19:23 when the reality is like those micro optimizations
    0:19:25 are not going to solve whatever retention problem
    0:19:27 or any other metric problem that you might have, right?
    0:19:29 At the end of the day, it’s about the user experiences.
    0:19:31 It’s about solving a real problem.
    0:19:35 I think generally, if you want a complete hit end to end,
    0:19:37 you need to have a breakthrough technology
    0:19:40 that’s applied to solve a very specific problem
    0:19:42 that a user actually has, right?
    0:19:43 And then you need to have an engine
    0:19:45 that can deliver that solution
    0:19:47 to people who have that problem
    0:19:49 as quickly as possible across the world, right?
    0:19:51 If you have all those pieces,
    0:19:53 then you won’t have a retention problem
    0:19:54 or an acquisition problem
    0:19:56 or any other problem basically, right?
    0:19:58 Now, the cool thing about this time right now
    0:19:59 is the technologies are being developed
    0:20:02 and there’s actually a crazy number of technologies out there,
    0:20:02 right?
    0:20:04 I think it’s a very unique time from that perspective, right?
    0:20:07 And for product people, the main problem is,
    0:20:09 “Hey, like how do we actually solve problems, right?”
    0:20:11 Actually solve real problems that people have, right?
    0:20:13 And not just sell the technology as technology, right?
    0:20:16 Like, “Hey, we have technology, just that, right?”
    0:20:19 But actually convert it into a real value delivery
    0:20:20 for users for a specific use case,
    0:20:21 even an issue’s case, right?
    0:20:23 Whatever it might be, right?
    0:20:24 And then I think for marketers,
    0:20:26 the problem is how do we actually educate people
    0:20:28 that there’s a new way to solve these problems, right?
    0:20:30 Like people may not think the first thing,
    0:20:31 “Oh, you know what?
    0:20:33 “I’m gonna Google AI for this, right?”
    0:20:35 That might not be the first thing that people think about, right?
    0:20:36 They might be searching for just
    0:20:37 whatever they were normally doing, right?
    0:20:39 Which may be something that takes a long time.
    0:20:41 And, or they might be like not aware
    0:20:43 that there’s new solutions available
    0:20:44 for these problems, right?
    0:20:46 So I think that’s sort of the end-to-end.
    0:20:49 I think if you focus on that at that level,
    0:20:51 like all the other numbers sort of follow on their own,
    0:20:53 and that’s kind of what we’ve seen,
    0:20:56 both across our desktop app and our mobile apps as well.
    0:20:57 And we’re in the consumer space,
    0:21:01 so retention is definitely a very hard game to crack
    0:21:03 compared to, say, B2B businesses.
    0:21:05 But we’ve been able to do it really well.
    0:21:08 And like, I think it’s because of that high-level focus
    0:21:11 across technology, product, and marketing.
    0:21:13 – Yeah, maybe Laura, you used to work at Twitter.
    0:21:15 What are you learning in terms of products
    0:21:17 that reach so many people?
    0:21:19 We’re talking daily active users.
    0:21:20 What have you learned from that space
    0:21:22 that you can apply to AI
    0:21:25 when you are trying to fix this retention problem?
    0:21:28 – I will say that I am so glad to be out of the game
    0:21:31 of trying to optimize for MDAU
    0:21:33 for monetized daily active users.
    0:21:34 I think that daily active use
    0:21:38 is like a pretty terrible metric
    0:21:40 to uncover customer value, right?
    0:21:42 And so one of the things that I just love most
    0:21:43 about working at Descript
    0:21:46 is being able to identify alternative metrics
    0:21:49 to think about how they’re done right by the customer.
    0:21:51 Two that I really like to think about
    0:21:53 that are a bit in tension with each other.
    0:21:54 They act as guardrails,
    0:21:57 it’s time to expression and editing richness.
    0:22:00 So I think if Descript is doing its job really well,
    0:22:03 the amount of time it takes you from starting a project
    0:22:05 to getting it into a shareable state,
    0:22:06 whether you’re a marketer
    0:22:09 who is like trying to repurpose a webinar into clips
    0:22:12 or someone who is more of a creator,
    0:22:14 trying to make your latest YouTube review
    0:22:16 or you’re someone in learning development,
    0:22:18 trying to create a training.
    0:22:20 I want the amount of time it takes you to create that
    0:22:22 to go down and down.
    0:22:25 And so you’re able to just create more and more of the content.
    0:22:26 Is anyone here a creator in any way
    0:22:29 have a YouTube channel or a marketer?
    0:22:31 Do you know about just like the gaping maw
    0:22:35 that can never be fully fed or stated for content
    0:22:37 that I find so many of our customers
    0:22:39 are just staring into with despair?
    0:22:42 And so getting kind of their time to expression down
    0:22:43 is really important.
    0:22:45 But one of the ways you do that is just like
    0:22:47 by creating worse and worse content
    0:22:49 that it’s just a role with an iPhone
    0:22:50 and you slap some captions on it,
    0:22:53 which is great for some use cases,
    0:22:56 but for others just like a missed opportunity,
    0:22:57 like you could have done so much more
    0:23:00 to create really high quality video content.
    0:23:02 And so if Descript is also winning on increasing
    0:23:04 the editing richness,
    0:23:06 the number of jobs that you’re able to do with us
    0:23:08 and the number of things you’re able to do
    0:23:10 to transform your media and make it really high quality,
    0:23:12 the interaction of those two metrics
    0:23:15 is such a great way to drive towards customer value.
    0:23:17 I will say that like what Gorav said
    0:23:20 around just like good product fundamentals
    0:23:23 with retention totally resonates with me.
    0:23:24 My attitudes for the tourists
    0:23:27 is you’ve got to triage the tourists.
    0:23:29 Some component of them just don’t have a use case
    0:23:30 for your software.
    0:23:32 They want to create a voice clone.
    0:23:33 They want to see it.
    0:23:34 They’re like, oh, that looks cool,
    0:23:36 but they don’t have anything to do with that voice clone.
    0:23:38 And it’s like, great, let’s let them do that.
    0:23:39 That’s awesome.
    0:23:41 Maybe one day you’ll think about Descript
    0:23:43 or 11 Labs and come back.
    0:23:45 But then who are these tourists
    0:23:48 who actually have a legitimate use case
    0:23:49 and they just don’t know it yet.
    0:23:50 They could be using video
    0:23:52 to communicate within their company.
    0:23:54 They could be using text-based video editing
    0:23:56 to create all of their marketing clips
    0:23:57 and they don’t know that yet.
    0:24:01 And how can I create software that activates really well,
    0:24:03 that displays all of our use cases
    0:24:05 and lets them have a good first time?
    0:24:08 And I find that like often retention problems
    0:24:11 or just activation problems in disguise in a trench coat.
    0:24:13 And so what I really try to focus on
    0:24:18 to improve retention is just like the activation experience.
    0:24:20 – Just having come from a social media background
    0:24:23 as well at Snap, such a good point about just DAU
    0:24:25 and like how that can be such a trap.
    0:24:28 – I think social media companies obviously optimized DAU
    0:24:31 for a reason because money’s coming from a different source.
    0:24:33 And so actually it’s good to be out of that game.
    0:24:36 And really interestingly with the generative AI space,
    0:24:38 it seems like it’s kind of having the opposite effect
    0:24:40 on what it’s trying to achieve.
    0:24:42 Like social media on one end is using AI as well,
    0:24:46 but really to consume time from people as much as possible.
    0:24:49 Consume as much of your time and it’s succeeding.
    0:24:51 And on the other hand, generative AI is actually kind of
    0:24:54 giving back time to people so they can actually do more.
    0:24:55 So pretty cool.
    0:24:57 – Yeah, we talked about this on a recent episode,
    0:25:00 how some tools, I’m sure people would resonate with this.
    0:25:03 If you had one excellent session,
    0:25:06 it could have saved you four hours of work in five minutes.
    0:25:07 That’s actually more valuable
    0:25:09 than spending 20 minutes every day in an app.
    0:25:11 And you don’t see that in the same metrics, right?
    0:25:13 So I love that you brought up different metrics
    0:25:15 that you’re paying attention to, Laura.
    0:25:18 Charles, is there anything that jumps to mind there for you
    0:25:21 in terms of how you might rethink a business model
    0:25:23 in terms of what metrics you’re paying attention to,
    0:25:25 or the way that you’re monetizing a product
    0:25:28 that might be different because the willingness to pay
    0:25:30 we’ve also seen is there, even if it is just,
    0:25:33 I’m using this once a month, once every two months even.
    0:25:36 – Yeah, and I think it’s a really good point, right?
    0:25:39 Some consumers actually feel that if they need to do something
    0:25:42 twice, the product is not working well, right?
    0:25:44 It’s that element that we’ve gone from one side
    0:25:45 to the other side.
    0:25:47 So probably like someone in the middle
    0:25:48 is what it fits well.
    0:25:50 I was actually like in a meeting with a customer
    0:25:52 and we presented a C level last week.
    0:25:54 And the question they came back with was like,
    0:25:56 okay, so how much time am I gonna save?
    0:25:58 And I was like, well, you’re gonna save anywhere
    0:25:59 between 50 to 60 times the time.
    0:26:01 Like it’s gonna be like 50 to 60,
    0:26:03 like it’s slashed by 50 to 60.
    0:26:04 And they were like, no, that’s not possible.
    0:26:06 And I was like, let’s do the math right now.
    0:26:07 And we did the math.
    0:26:08 And it was very interesting.
    0:26:11 So I think there is an emphasis on that side.
    0:26:14 But I think like sometimes we try to overemphasize
    0:26:16 the effects of like the efficiency
    0:26:18 that you’re getting with Genitive AI
    0:26:20 when in fact, Genitive AI is not perfect, right?
    0:26:22 I think like that’s one of the main reasons
    0:26:25 why the AI tourists are there and they’re very big.
    0:26:28 It’s because everyone comes with like such a big expectation
    0:26:30 that he’s gonna be solving all of my problems
    0:26:32 and it’s gonna be cooking dinner for me tonight as well.
    0:26:34 And unfortunately it’s not gonna cook dinner for you.
    0:26:36 It’s just never gonna solve all of your problems.
    0:26:38 But it’s gonna help you quite a lot
    0:26:40 either because you can do a lot of more modernization
    0:26:41 with your customers,
    0:26:43 with like you can reach new markets
    0:26:45 or you can actually do it much quicker, right?
    0:26:47 But I think like framing it on actually
    0:26:50 what is valuable for you as a business
    0:26:52 or as an individual is much more important.
    0:26:54 So like initially our metrics were like beautiful,
    0:26:55 like usage, right?
    0:26:56 And over the past month,
    0:26:59 we’ve ended up like switching to like usage is important,
    0:27:02 but that does not define like the long-term success
    0:27:04 of an actual customer for us, right?
    0:27:06 It’s one of our like, yeah, activation side
    0:27:09 is about actually what’s the use case that you have
    0:27:11 and how do we measure that of the long-term
    0:27:13 and how do we understand, try to insert the use case
    0:27:16 based on the way you’re using the product, right?
    0:27:17 So that we can offer you the best tools
    0:27:19 and the best tips and all that stuff.
    0:27:21 For us that that’s essentially those are the key metrics
    0:27:22 to the best like usage.
    0:27:24 Usage is still super important,
    0:27:27 but I don’t really mind if someone uses the product today
    0:27:30 and then doesn’t do it for like a week or two weeks
    0:27:32 because I know that like if we’ve nailed it,
    0:27:34 they’re gonna come back two weeks later, right?
    0:27:35 I think that’s how we are thinking about it.
    0:27:37 – You don’t have those social notifications
    0:27:38 that are like a friend of a friend
    0:27:42 maybe posted something, please come to our app.
    0:27:43 All right, well, so we’re gonna open up
    0:27:44 to questions very soon.
    0:27:47 So if you have any questions start thinking about them,
    0:27:48 but I wanna do rapid fire one or two more.
    0:27:52 So the importance of optimizing an application
    0:27:54 for a specific role or someone’s use case,
    0:27:56 who are you, what are you trying to do?
    0:27:59 So each of you actually comes from different backgrounds,
    0:28:00 right?
    0:28:01 So Gora, you’ve done design and development,
    0:28:02 you’ve been an engineer,
    0:28:04 Laura, you’ve been immersed in product,
    0:28:05 carless operations.
    0:28:07 And so those are roles where there’s a gosh,
    0:28:11 I don’t know how many other people who fit that subset.
    0:28:13 So I’d just love to hear your perspective,
    0:28:15 independent of your company,
    0:28:17 how do you think of AI as let’s say the next five years?
    0:28:20 What does an AI-powered engineer look like
    0:28:21 in your case, Gora,
    0:28:23 or like an AI-powered operations person?
    0:28:24 What do you need, what’s missing?
    0:28:25 Are there products out there
    0:28:28 that actually fit that use case and are doing it well?
    0:28:30 – Yeah, I mean, thinking about it
    0:28:32 from an engineering perspective
    0:28:34 or even from a design perspective,
    0:28:37 I think maybe the closest on the engineering side
    0:28:39 would be like a tech lead manager,
    0:28:42 someone who’s actually setting up the overall architecture
    0:28:44 of whatever’s being built, right?
    0:28:45 But a lot of the work’s been done by AI
    0:28:47 and they’re coming in, they’re making edits.
    0:28:48 They’re like, maybe we need to change this,
    0:28:49 reviewing stuff, right?
    0:28:50 Same on design, right?
    0:28:52 Like kind of giving high level instructions
    0:28:54 and like, let’s have this,
    0:28:56 let’s maybe use this style over here,
    0:28:57 let’s change these components, right?
    0:28:59 And getting that output back
    0:29:01 and kind of reviewing it, leaving comments
    0:29:03 the same way that a manager might, right?
    0:29:06 And being able to produce hopefully a lot more value
    0:29:07 and output.
    0:29:10 So that means that companies can be going
    0:29:12 to a much larger revenue scales with way fewer people,
    0:29:14 which is gonna be interesting.
    0:29:15 – Yeah, I think a lot about this.
    0:29:17 What is the AI product manager?
    0:29:19 The paradigm that I use is more like,
    0:29:22 how do I wanna interact with AI to do my job better?
    0:29:24 One of the use cases I’m excited about
    0:29:27 is a rubber duck who talked back.
    0:29:28 You guys hear about like rubber ducking
    0:29:29 where you keep a rubber duck on your desk
    0:29:32 and you talk through difficult problems with that rubber duck.
    0:29:35 And I think like, I’m never going to cede control
    0:29:39 of the creativity and the genius to like the entity.
    0:29:41 Like clearly, have you met me?
    0:29:42 I’m in charge of that.
    0:29:45 But I think like it can be fun to toss the ball around
    0:29:47 with someone and I think I’m excited to see
    0:29:51 how AI continues to develop to be like a fun thing
    0:29:55 to toss the ball around and then can take all of the stuff
    0:29:58 that you’re just like spewing out all of the kind of word
    0:30:02 garbage and turn it into something crisp and readable
    0:30:04 and easy to understand.
    0:30:07 So that’s a use case that I’m excited about.
    0:30:08 – I think it’s from an operation side,
    0:30:10 it’s like even more complex, right?
    0:30:12 Because like there’s so many like things that you need to do.
    0:30:13 Like how do you automate
    0:30:16 or how do you get someone to help you on that front, right?
    0:30:18 So ideally you end up having a product
    0:30:22 that helps you to twice as much in the same amount of time.
    0:30:23 Not because I’m thinking about it
    0:30:24 from an efficiency perspective,
    0:30:27 but much more of how I can potentially generate
    0:30:28 more revenue for the business, right?
    0:30:30 I think that’s where potentially
    0:30:32 and hopefully like the market is going to be going.
    0:30:34 I like on the sales side, it’s much easier
    0:30:37 because you end up having AISDRs these days.
    0:30:39 We’ll end up having AISDSMs in all of those pieces.
    0:30:42 Like that can be already there in many cases, right?
    0:30:44 But purely on the operation side,
    0:30:45 there’s a lot more complex.
    0:30:46 Chagivity is your friend for sure, right?
    0:30:49 Or on topic if you use it, or like any of those tools
    0:30:51 that will help you generate quite a lot of different things
    0:30:52 on a day-to-day basis.
    0:30:54 Is that giving you a 2X?
    0:30:55 Not yet, right?
    0:30:58 So I’m not sure, like I still haven’t found the right product
    0:31:00 that like would help anyone optimize
    0:31:02 and become like 2X themselves.
    0:31:03 – Maybe someone will build it in the room.
    0:31:04 I guess final question.
    0:31:06 Does anyone feel free to jump in?
    0:31:08 All three of your products have a lot of customers.
    0:31:09 People are using it.
    0:31:12 Seems like maybe for the retention problem,
    0:31:13 what challenges are you facing?
    0:31:17 Whether it’s like regulation or not having the right models
    0:31:19 or hoping that the open source models catch up
    0:31:21 or just curious if anything jumps out
    0:31:22 where just calling out a challenge
    0:31:24 that you’d like to be solved in the next few years.
    0:31:26 – Yeah, I’d say for us, it’s hiring actually.
    0:31:28 It’s very traditional, right?
    0:31:29 But I think hiring the right people
    0:31:30 to solve the particular problems
    0:31:31 that we’re having in our company.
    0:31:33 And problems go really quickly,
    0:31:35 or the company’s going really quickly, right?
    0:31:36 And you have to kind of keep an eye on
    0:31:38 all the different things that are happening,
    0:31:39 where new needs might come up,
    0:31:41 especially with a company like ours,
    0:31:43 where we’ve existed for about three years
    0:31:44 and there’s video companies that have been around
    0:31:46 for a long time.
    0:31:47 We’ve passed everybody in revenue
    0:31:49 in like literally a year and a half.
    0:31:51 And with growth at that scale,
    0:31:53 you just have to constantly be thinking about
    0:31:55 what are the new problems that are coming up
    0:31:57 and who can we hire solve those problems, right?
    0:32:00 So I think that’s like a very traditional answer.
    0:32:01 And maybe there’s some AI recruiters out there,
    0:32:02 but we have a great team.
    0:32:04 So I don’t think we need them, at least not yet.
    0:32:05 – Maybe AI can help with that.
    0:32:09 I think it’s just that we’re in the middle
    0:32:10 of a paradigm shift, right?
    0:32:12 Like we haven’t gotten to the end of it.
    0:32:13 We’re in the middle now.
    0:32:14 And what I can tell you is that the way
    0:32:18 that we’re going to edit video and audio in a year
    0:32:22 or in two years is going to look completely different
    0:32:24 than how we’re doing it right now.
    0:32:27 But we don’t know how yet.
    0:32:29 And on one hand, like that’s why I’m here.
    0:32:32 That’s like why I’m doing this job,
    0:32:34 because this is a place where the next generation
    0:32:37 of like product managers and designers
    0:32:38 we’re going to reinvent the way
    0:32:41 that humans and computers interact with each other.
    0:32:42 Someone’s going to figure it out.
    0:32:44 And God, I hope it’s like me
    0:32:46 or that I’m part of it in some small way.
    0:32:50 But that’s also just like a very fragile moment, right?
    0:32:52 Like it’s both a challenge and an opportunity.
    0:32:54 And I think it’s like the challenge
    0:32:56 of our industry right now.
    0:32:59 – I think for us, it’s like there’s two sides of it.
    0:33:02 What is definitely hiding, I can relate a lot on that.
    0:33:03 It’s difficult.
    0:33:06 We’ve gone from like zero to like tens and tens of millions
    0:33:08 in months, not even years, in months.
    0:33:10 And it’s really difficult to find people
    0:33:12 that have experienced that previously,
    0:33:13 also because like the market has evolved
    0:33:15 very quickly in such a timeframe.
    0:33:16 So that’s one side.
    0:33:18 So there’s a lot of commitment that like we expect
    0:33:19 from people at the company
    0:33:23 and we need to be able to actually keep growing at this stage.
    0:33:24 And on the research side,
    0:33:26 it’s extremely difficult to find the right researchers
    0:33:28 on the engineering side, on the operation side,
    0:33:31 on sales, even support like across the board, right?
    0:33:33 But that’s one side of the equation.
    0:33:36 The other side of the equation is preventing misuse, right?
    0:33:37 And I think realistically,
    0:33:38 that is something that we have
    0:33:39 an entire team dedicated to that
    0:33:41 a day and night in the fourth, seven.
    0:33:43 But every time that we put together something
    0:33:45 that is windy or the different things
    0:33:47 that like people make up to try to game it.
    0:33:49 And it is similar to fraud,
    0:33:51 where like you’re always like two steps behind
    0:33:53 and it’s really difficult to cut and like keep fighting it.
    0:33:55 So I think like about those two elements
    0:33:56 are like the biggest challenges
    0:33:58 that we constantly facing as a company.
    0:34:00 Like we’re winning, but still it’s just a matter
    0:34:02 of making sure that you’re constantly innovating
    0:34:05 and having resources for something that it is important.
    0:34:07 Otherwise like regulators come
    0:34:08 or like consumers don’t blame
    0:34:11 and things like that and people complain, right?
    0:34:12 – Yeah, you need unprecedented people
    0:34:14 for an unprecedented pace.
    0:34:16 Quick question is Laura,
    0:34:18 who’s our wonderful producer at the A16Z podcast
    0:34:19 is gonna go around.
    0:34:22 So if anyone does have a question, just raise your hand
    0:34:24 and she’ll come find you.
    0:34:28 – I’m curious how are we thinking about internationalization
    0:34:32 or serving users of like various levels of digital literacy?
    0:34:34 – We’ve had an international audience from the beginning,
    0:34:36 including every country and every region
    0:34:37 you could possibly imagine.
    0:34:40 So I think it’s been a high priority from the beginning,
    0:34:41 right?
    0:34:44 Because the interesting thing is a lot of the development
    0:34:48 that AI is bringing is not just things that are usable
    0:34:50 in like, oh, it’s just an English thing
    0:34:53 or oh, it’s just like a US thing or something.
    0:34:56 It actually brings change in workflows
    0:34:57 across almost every country
    0:34:59 and every culture you can imagine.
    0:35:00 And it actually works, right?
    0:35:03 Like I think we’ve gone and launched new markets
    0:35:04 where we’ve had zero users
    0:35:08 and overnight had an explosion of users in that market.
    0:35:10 But then we learned something about that particular market
    0:35:13 where, oh, they don’t like this particular thing
    0:35:15 or if you think about, for example, the Middle East, right?
    0:35:17 Text is written in the opposite way.
    0:35:19 And so that changes a lot about the UI
    0:35:21 and changes a lot about the user experience, right?
    0:35:23 And we’ve done a lot of work to make that good
    0:35:26 and make that as usable and as amazing of an experience
    0:35:28 as it is in any other language.
    0:35:30 So those are the types of efforts
    0:35:32 we’ve made high priority from the beginning.
    0:35:34 – Would you say that other countries or regions
    0:35:37 are actually more readily adopting the products
    0:35:38 because I’m just thinking through,
    0:35:40 well, actually maybe they can’t hire the software engineer
    0:35:42 or maybe they can’t pay for the traditional video editor
    0:35:44 or those thousands of dollars.
    0:35:48 So they’re actually more readily adopting these technologies
    0:35:49 ’cause they’re bringing the cost down.
    0:35:50 – Absolutely.
    0:35:52 I mean, I think around the world people are super open
    0:35:53 to trying something new
    0:35:55 to see if they can change their workflow, right?
    0:35:56 I think as long as you can provide something
    0:35:58 that is once you try it,
    0:36:00 you can’t go back to what you were doing before.
    0:36:01 That’s it.
    0:36:02 That’s the difference, right?
    0:36:05 If you can provide that experience in any language,
    0:36:06 any culture, any country,
    0:36:08 people will use the product.
    0:36:10 – I mean, I think for us internationalization
    0:36:11 has been like since day one there.
    0:36:13 We have a fully international team,
    0:36:14 everyone is fully remote.
    0:36:16 So that actually, there’s a very strong correlation,
    0:36:19 funny enough between the actual employee profile
    0:36:21 and the fact that we are multiple countries,
    0:36:22 everyone can be based whatever they wanted
    0:36:24 and traveling and all of that stuff.
    0:36:26 And the actual user type that we’ve got it, right?
    0:36:28 So yes, in the initial days,
    0:36:31 like a lot of our growth came from North America
    0:36:32 and European markets.
    0:36:34 But actually these days, when you look at the entire pie,
    0:36:37 it’s like super spread out across the world.
    0:36:39 I can relate to that purely on the fact
    0:36:41 that people want the best tools
    0:36:43 that will help them on a day-to-day basis, right?
    0:36:45 And you don’t really need to spend these days,
    0:36:48 like thousands of dollars or like hundreds of dollars
    0:36:51 to actually produce a video or to produce a podcast
    0:36:52 or produce something, right?
    0:36:55 You could do it much cheaper using tools.
    0:36:56 And that’s beauty of it.
    0:36:59 So by default, like anyone that truly wants to have
    0:37:01 a cost efficient solution will end up like using
    0:37:04 any of the tools, script, captions or labs
    0:37:06 or anything else that you have out there.
    0:37:08 So by default, you end up having the strategy
    0:37:09 that is about international markets,
    0:37:11 with doing well content,
    0:37:14 like trying to engage your audiences like that’s where they are
    0:37:17 and trying to personalize it to them anyway.
    0:37:20 Otherwise, I think like you end up like having a problem
    0:37:22 of being very skewed towards a market,
    0:37:23 traditionally it’s been always that,
    0:37:25 oh, you go one market, you conquer it
    0:37:27 and then you expand to another one.
    0:37:28 And this day it’s just not,
    0:37:31 it’s just that it worked quite well enough.
    0:37:34 – Yep, it’s time for maybe one, maybe two more.
    0:37:35 I see one at the back.
    0:37:38 – I’m just wondering what barriers or stop gaps
    0:37:40 you might be putting in place for people
    0:37:43 who may be using your products for nefarious purposes
    0:37:46 and thinking about trust and safety.
    0:37:48 – I think like from 11, we invest like millions
    0:37:51 every single year on actually like preventing misuse, right?
    0:37:53 And we will start somebody to implement
    0:37:54 like a fingerprinting system
    0:37:56 for any content that gets generated.
    0:37:58 So since we launched the fingerprinting has been in place,
    0:38:01 we then opened up the API and the UI,
    0:38:02 make sure that anyone can check
    0:38:05 whether something was generated by us or not.
    0:38:07 And since then we’ve also essentially engaged
    0:38:10 on monitoring the content that our users generate.
    0:38:12 So that essentially if someone is generating things
    0:38:14 that they shouldn’t, then essentially we block them.
    0:38:17 We’ve gone as far as to build the Nogo Voices,
    0:38:20 which is a model that will prevent anyone
    0:38:23 that tries to clone a celebrity voice for instance, right?
    0:38:25 We’re constantly adding all of these layers
    0:38:27 to try to make sure that we stay ahead of the curve.
    0:38:28 But as I was saying earlier,
    0:38:31 like it’s an uphill battle overall, right?
    0:38:33 There is always ways in which you can game it.
    0:38:35 But at the same time, like you have open source tools, right?
    0:38:38 So we can try to do our side of the equation,
    0:38:40 like anything that is open source
    0:38:43 and to some extent you don’t really have that much
    0:38:45 like control over those tools, right?
    0:38:47 But I think it’s important as a company,
    0:38:49 we will keep investing like millions every single year
    0:38:52 and we can increase it as the market grows as well.
    0:38:55 – I have to just quickly ask because it’s very timely
    0:38:57 and I’m sure people in the audience are wondering
    0:38:59 with some of the recent news around AI voices,
    0:39:01 let’s just leave it at that and celebrities.
    0:39:05 Are you finding there to be a bunch of false positives?
    0:39:07 ‘Cause I feel like that’s maybe something
    0:39:09 that people wonder, you hear a celebrity’s voice,
    0:39:12 but how unique can a voice be?
    0:39:15 And so if you’re trying to filter out certain people’s voices,
    0:39:19 are you finding that actually like our voices maybe aren’t
    0:39:20 that unique?
    0:39:22 – That’s a really good question, right?
    0:39:24 The voices are not as unique as everyone thinks,
    0:39:25 but however they quite unique.
    0:39:28 So you end up having like false positives for sure,
    0:39:30 but we end up thinking like, if it’s a false positive,
    0:39:31 if it tells you like, oh,
    0:39:32 you don’t have permission for this voice,
    0:39:34 automatically it tells you like, oh,
    0:39:36 but you can still pass the voice structure
    0:39:38 and it would show you the voice structure.
    0:39:40 So if you pass it because it is your voice,
    0:39:43 then you’re able to actually like use your own voice, right?
    0:39:46 I have a twin brother for the ones that don’t know.
    0:39:48 We do sound exactly the same.
    0:39:49 And even my parents actually,
    0:39:51 they sometimes they made mistakes, right?
    0:39:52 So truly like, I could be talking,
    0:39:54 but you could be thinking that it’s my twin brother.
    0:39:56 We have exactly the same voice.
    0:39:58 And that is a challenge that as a company we have
    0:40:00 and a society we have, right?
    0:40:01 But I think like the end of building layers
    0:40:04 as a product from a product perspectives
    0:40:06 to help filter those false positives.
    0:40:07 I think like people understand that like,
    0:40:10 you’re trying to go from like everything is free for all
    0:40:11 and then you can misuse as much as you wanted.
    0:40:13 There was like, let’s put some controls
    0:40:15 and even if there’s some false positives,
    0:40:17 people understand it online.
    0:40:19 – Something about the product side of this too,
    0:40:21 which I do think is super important
    0:40:23 to sort of like build the safety features
    0:40:25 from the product, from the ground up,
    0:40:26 like in the product from the ground up.
    0:40:27 And that’s kind of the difference
    0:40:28 between offering a technology versus offering a product.
    0:40:31 If you just say, hey, come to our website,
    0:40:31 make deep fakes, right?
    0:40:33 That’s offering a technology.
    0:40:35 And some people might be out there doing that, right?
    0:40:36 I don’t know, right?
    0:40:38 But I think if you build that into a product,
    0:40:41 like for example, we have the language translation feature,
    0:40:43 right, which can translate whatever you’re speaking
    0:40:45 to a different language, change your lip movements as well.
    0:40:48 And yes, that’s using the same technology,
    0:40:49 but in a very opinionative way
    0:40:51 that you can’t change what was said,
    0:40:53 but you can change what language it was set in, right?
    0:40:55 And so that limits the scope of abuse
    0:40:57 immediately, quite a bit, right?
    0:40:59 And then all the traditional methods
    0:41:01 can be used on top of that as well.
    0:41:02 – Bri, I mean, with these group,
    0:41:04 you can create a voice clone of yourself
    0:41:06 and sort of like intermingle.
    0:41:08 We have this thing called Overdub,
    0:41:09 where if I say the wrong word,
    0:41:11 I can go back in with the text,
    0:41:13 say the word that I actually meant to say,
    0:41:14 and then it will with my voice clone,
    0:41:15 kind of create that.
    0:41:18 But obviously there are a lot of misuses there.
    0:41:20 And so whenever we launch a product,
    0:41:22 we launch it with protections in place
    0:41:26 and do a bunch of testing and hire outside people
    0:41:28 to try to crack it and try to make sure
    0:41:30 that we do our very best to make sure that it’s ungamable.
    0:41:35 But like you said, if people are extremely determined
    0:41:36 to crack through security,
    0:41:38 like they will always find new ways to do it.
    0:41:40 And this was the case when I was in social media too,
    0:41:42 where like you do all kinds of things
    0:41:44 to try to protect your platform.
    0:41:47 And bad actors, they get up every morning
    0:41:49 and grind just as hard as you do.
    0:41:52 And so you’re just sort of in the eternal struggle.
    0:41:54 And I think like every single tech product
    0:41:55 should be thinking about like,
    0:41:57 how are people going to misuse us
    0:42:00 and making sure that they’re responsibly providing
    0:42:02 a bunch of resources to stay in the fight.
    0:42:06 – So as VP of Revenue at 11,
    0:42:09 how do you view the role of open source?
    0:42:11 Because as a developer myself,
    0:42:13 I would rather use, for example, Falcon 70B,
    0:42:15 which is a dollar in dollar out per million tokens,
    0:42:18 as opposed to GPT-4, which is 30 and 50 out.
    0:42:21 So do you think that open source is a threat to your business,
    0:42:23 especially as companies like Meta
    0:42:24 are kind of taking a scorched earth approach
    0:42:26 to releasing models?
    0:42:29 – I mean, I think it’s complementary actually.
    0:42:31 You always end up having like businesses
    0:42:34 or like people that like can go and use open source
    0:42:35 and they have the means and the tools
    0:42:37 and the knowledge to make that work.
    0:42:39 And then you’re having quite a lot of different people
    0:42:42 that like don’t really have those means or knowledge, right?
    0:42:45 So it just ends up becoming like different sides
    0:42:47 of the business or different sides of the market, right?
    0:42:49 However you want to segment it.
    0:42:50 When I think about voices,
    0:42:52 we’ve been talking to each other as humans
    0:42:54 for the past 50,000 years, right?
    0:42:56 And there wasn’t really a good technology
    0:42:58 that was able to replicate how we talk as humans.
    0:43:02 So the fact that like as a platform or like even open source,
    0:43:05 you’re able to actually replicate people’s voices
    0:43:08 with their permission, make it sound natural, engaging,
    0:43:10 and then power a new type of communication
    0:43:12 and like platform and experience.
    0:43:13 The market is massive.
    0:43:16 So by default, you need to have both sides
    0:43:18 to be able to actually like counterbalance each other
    0:43:20 and push each other.
    0:43:23 But it comes also the open source at a cost,
    0:43:25 which is like the number of features that you will have
    0:43:27 is like more limited, right?
    0:43:30 So you will end up also having like less voices.
    0:43:31 So what’s your preference?
    0:43:32 Like you don’t have the UI.
    0:43:35 So what’s your preference as a business or as an individual?
    0:43:37 Is it purely building on top of it?
    0:43:39 Then maybe open source is a good way.
    0:43:41 Like today, the quality is not there yet.
    0:43:43 But I’m sure that within the next three years,
    0:43:45 the quality is going to be like matching anything
    0:43:46 that is like private, right?
    0:43:48 So it’s going to be more about like the actual system
    0:43:52 that you build around it to make sure that like people start
    0:43:55 like using it in a much easier way and then embed it anyway.
    0:43:57 But I actually think it’s like complimentary.
    0:43:59 Like without one, we can not have the other one purely
    0:44:02 because the market like needs both sides.
    0:44:05 – So just a follow-up, would you say that’s important for,
    0:44:08 I guess, picks and shovels, companies,
    0:44:10 closed source to build an application layer on top
    0:44:12 to stay competitive?
    0:44:17 – I don’t think anyone has actually built a pool like LLM.
    0:44:20 If they’re not able to build applications on top of it,
    0:44:23 to make life easier for consumers and businesses,
    0:44:25 you will end up struggling down the line.
    0:44:26 Whether that is in six months time
    0:44:28 and that is in 18 months time, you will struggle.
    0:44:29 Because at the end of the day,
    0:44:31 like I want to launch my own application
    0:44:34 like my product to use the product like this immediately,
    0:44:35 right?
    0:44:37 And if I need to spend the next like like coding
    0:44:39 and building the UIs and everything
    0:44:41 might give up and go somewhere else.
    0:44:43 Even if it’s more expensive,
    0:44:44 especially if I don’t even know
    0:44:46 where they have product market fit.
    0:44:48 And product market fit, like we always think about like
    0:44:50 actual startups, but like big corporates
    0:44:52 might not have even product market fit.
    0:44:54 So if you want to iterate quickly
    0:44:57 and then go to market as quickly as possible,
    0:44:59 then you might want to have a stack
    0:45:01 that is like truly readily available for you.
    0:45:03 But once you’re ready and you’ve tested it
    0:45:06 and the technology fits good enough with other LMS
    0:45:07 or like open source,
    0:45:09 then you might end up looking to switch.
    0:45:11 And we’ve seen that with OpenAI,
    0:45:13 like the big migration that like from developers
    0:45:15 like that started using OpenAI,
    0:45:18 such as GPT, APIs and GPT 3.5.
    0:45:20 And then now they’re migrating towards like Anthropic
    0:45:22 and like Mithral or Lama.
    0:45:24 That’s been happening for the past six months.
    0:45:25 It will continue happening, right?
    0:45:28 So you start to validate that everything goes well
    0:45:30 and then you figure out whether there is alternatives
    0:45:32 or that is like really negotiating pricing
    0:45:33 or like open source.
    0:45:35 (upbeat music)
    0:45:39 If you liked this episode, if you made it this far,
    0:45:40 help us grow the show,
    0:45:43 share with a friend or if you’re feeling really ambitious,
    0:45:48 you can leave us a review at ratethisfodcast.com/asixz.
    0:45:51 You know, candidly producing a podcast
    0:45:54 can sometimes feel like you’re just talking into a void.
    0:45:55 And so if you did like this episode,
    0:45:58 if you liked any of our episodes, please let us know.
    0:46:01 I’ll see you next time.
    0:46:03 (upbeat music)
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    Less than two years since the breakthrough of text-based AI, we now see incredible developments in multimodal AI models and their impact on millions of users.

    As part of New York Tech Week, we brought together a live audience and three leaders from standout companies delivering AI-driven products to millions. Gaurav Misra, Cofounder and CEO of Captions, Carles Reina, Chief Revenue Officer of ElevenLabs, and Laura Burkhauser, VP of Product at Descript discuss the challenges and opportunities of designing AI-driven products, solving real customer problems, and effective marketing.

    From the critical need for preventing AI misuse to ensuring international accessibility, they cover essential insights for the future of AI technology.

     

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  • Marc Andreessen on Building Netscape & the Birth of the Browser

    AI transcript
    0:00:03 – It was this invitation to basically do anything.
    0:00:05 It was this kind of great moment where you just kind of
    0:00:07 felt like the future was like in front of you.
    0:00:09 It’s very important to know that at this point
    0:00:11 and all the way up until really 1994,
    0:00:13 the overwhelming uniform universal expectation
    0:00:15 was the internet would never be a business.
    0:00:18 I at the time completely lacked the skill set
    0:00:20 and the perspective to navigate, I would say,
    0:00:23 interpersonal and in particular bureaucratic situations.
    0:00:25 I had no clue how to do any of it.
    0:00:26 So much of computer science at that point
    0:00:28 was about optimizing scarce resources
    0:00:30 because that was all you had at that time.
    0:00:31 And they had spent decades figuring out how to do that
    0:00:34 and we collectively decided to just break that rule.
    0:00:38 – You’ve probably heard of the browser.
    0:00:40 In fact, billions of people use browsers
    0:00:42 as their gateway to the internet.
    0:00:44 And you might even be using one right now
    0:00:47 to access this very podcast recording.
    0:00:50 Now in today’s episode from the Ben and Mark show,
    0:00:52 Mark Andreessen and Ben Horowitz share the real story
    0:00:54 behind the creation of Netscape,
    0:00:56 a web browser co-created by Mark
    0:00:58 that revolutionized the internet
    0:01:01 and quite frankly, changed the world.
    0:01:03 As Ben notes up top, until today,
    0:01:05 this story has never been fully told
    0:01:08 either in its entirety or accurately.
    0:01:09 In this one-on-one conversation,
    0:01:11 Mark and Ben discussed Mark’s early life
    0:01:13 and how it shaped his journey into technology,
    0:01:16 the pivotal moments at the University of Illinois
    0:01:18 that led to the development of Mosaic,
    0:01:20 a renegade browser that Mark developed as an undergrad,
    0:01:23 which is widely referenced as the first widely used browser
    0:01:26 and the fierce competition and legal battles
    0:01:29 that ensued as Netscape rose to prominence.
    0:01:31 Ben and Mark also reflect on the broader implications
    0:01:34 of Netscape’s success, the importance of an open internet,
    0:01:36 and the lessons that still resonate
    0:01:40 in today’s tech landscape, especially with AI.
    0:01:42 That and so much more.
    0:01:43 I hope you enjoy.
    0:01:49 – Who will decide the future of the internet?
    0:01:52 Read Right On, a book by A6NZ General Partner
    0:01:53 and author Chris Dixon,
    0:01:55 takes on one of the most consequential questions
    0:01:57 of our time, which is also the key
    0:01:59 to unlocking more entrepreneurship,
    0:02:02 more creativity, and more innovation.
    0:02:06 From AI that compensates artists to social networks
    0:02:08 that reward you for participating,
    0:02:09 Read Right On shares a playbook
    0:02:12 for building the next era of the internet.
    0:02:14 Learn more at readrighton.com.
    0:02:19 – Okay, you idiot, like this giant commercial opportunity
    0:02:20 is staring you in the face.
    0:02:22 You literally have like inbound sales leads,
    0:02:23 like coming out of your ears,
    0:02:25 like why don’t you go raise venture capital
    0:02:26 and start a company?
    0:02:28 And of course the answer was because I had no idea
    0:02:29 that there was such a thing as venture capital.
    0:02:31 – Yeah, venture capital.
    0:02:34 – I literally, you know what a tractor was.
    0:02:36 – Yes, exactly.
    0:02:38 The content here is for informational purposes only,
    0:02:41 should not be taken as legal, business, tax,
    0:02:43 or investment advice, or be used to evaluate
    0:02:45 any investment or security,
    0:02:47 and is not directed at any investor
    0:02:51 or potential investors in any A16Z fund.
    0:02:53 Please note that A16Z and its affiliates
    0:02:55 may maintain investments in the companies
    0:02:56 discussed in this podcast.
    0:02:59 For more details, including a link to our investments,
    0:03:02 please see A16Z.com/disclosures.
    0:03:04 – Welcome to the Mark Inventio.
    0:03:06 Today is a super special episode
    0:03:10 because we are going to talk about the origin
    0:03:13 of the web browser and the invention of the web browser.
    0:03:15 And we have one of the co-inventors
    0:03:17 with us right here in Mark.
    0:03:18 So it’s exciting.
    0:03:21 It’s also exciting because this story’s never
    0:03:25 really been told either in its entirety or accurately.
    0:03:28 And so we’re gonna get a chance to do that.
    0:03:30 For those of you who are so young
    0:03:33 that you’re not quite sure what a web browser is anymore,
    0:03:36 it is kind of how most people experience the internet.
    0:03:38 So you might call it the internet.
    0:03:39 It’s a thing, Chrome.
    0:03:42 Let’s start at the very beginning
    0:03:46 because one of the things that is kind of
    0:03:49 one of the largest disinformation campaigns going
    0:03:52 is this whole idea that people, entrepreneurs
    0:03:55 and people who invent things are kind of born
    0:03:57 with a silver spoon in their mouth.
    0:03:59 And almost none of the successful entrepreneurs
    0:04:02 we work with is that the case for.
    0:04:04 They all come from, you know,
    0:04:08 somewhere between like refugee and middle class backgrounds.
    0:04:10 And you certainly were not born
    0:04:11 with the silver spoon in your mouth.
    0:04:14 So tell us a little bit about where you grew up.
    0:04:15 You didn’t grow up in a big city.
    0:04:17 You grew up in quite a small town.
    0:04:18 What was that like?
    0:04:21 And then what is it like growing up in?
    0:04:23 How did you first encounter the internet?
    0:04:25 – Yeah, so let me, if I could start our session today
    0:04:28 with two disclaimers, which maybe relate to your question.
    0:04:30 So disclaimer number one is we’re gonna be talking
    0:04:31 about events that happened over 30 years ago.
    0:04:33 – Little memory problems.
    0:04:34 – Yeah, so, you know, I’m gonna tell the truth
    0:04:36 as I remember it, I may get things wrong
    0:04:37 or other people may have different recollections.
    0:04:39 And so I have to disclaim that.
    0:04:41 It’s ’cause I can’t swear to the factual accuracy
    0:04:42 of stuff that was that long ago,
    0:04:43 but I’ll tell the stories, I understand it.
    0:04:45 And then I’d say the other story is
    0:04:46 there are twists and turns along the way
    0:04:48 where I would just characterize it as
    0:04:50 at the time I was irritated at other people
    0:04:51 for things that happened.
    0:04:52 I think in the fullness of time,
    0:04:54 what I realized is that I just at the time
    0:04:56 completely lack the skillset and the perspective
    0:04:58 to navigate, I would say interpersonal
    0:05:00 and in particular bureaucratic situations.
    0:05:02 I had no clue how to do any of it.
    0:05:04 – Yeah, well, and so, I think when you get
    0:05:07 into your background, people will kind of understand.
    0:05:09 – I sometimes describe myself, I was feral
    0:05:10 at this point in my life.
    0:05:11 And so it’s always this thing,
    0:05:13 if you could rerun prior events,
    0:05:14 like with the skillset I have today,
    0:05:16 I could have navigated it much better
    0:05:17 and a bunch of things could have turned out different,
    0:05:20 but I certainly did not have the skillset at the time.
    0:05:22 So anyway, if it sounds like I’m criticizing other people,
    0:05:23 it’s actually not what I intend.
    0:05:26 It’s gonna be more ultimately criticizing myself
    0:05:27 in the sense of whatever happened that I didn’t like
    0:05:29 at the time, I think I was at least partly,
    0:05:30 if not wholly responsible for.
    0:05:31 – Yeah.
    0:05:32 – ‘Cause I-
    0:05:34 – You know, growing men can be like that
    0:05:35 from time to time, you know?
    0:05:38 – Yes, I would say I was raw aggression at that point
    0:05:40 with very little, and yes, you’ve been, of course,
    0:05:41 remembers this ’cause he met me shortly
    0:05:42 after the events we were about to talk about.
    0:05:45 So, first of all, the modern cliche is,
    0:05:47 Elon Musk’s father had an emerald mind.
    0:05:50 – Right, when he showed up in the U.S. with $2,000,
    0:05:52 is the actual story, yeah.
    0:05:53 – Yeah, exactly.
    0:05:54 So there’s all these kind of fake histories
    0:05:56 that are kind of retconned into people who grew up,
    0:05:58 and in some cases, pretty tough backgrounds, yeah.
    0:06:00 So I grew up in the American Midwest and rural Wisconsin,
    0:06:03 and for people who haven’t spent time in Wisconsin,
    0:06:04 there’s basically three Wisconsin’s.
    0:06:05 They’re sort of the big city of Milwaukee,
    0:06:07 which is like a, you know, kind of like a big,
    0:06:09 almost like a Chicago kind of thing.
    0:06:10 That’s its own world.
    0:06:10 And then there’s Madison,
    0:06:13 which is like a very kind of hippie college town
    0:06:15 that was actually kind of a core of activity
    0:06:17 in the ’60s, and then there’s the rest of Wisconsin,
    0:06:20 which is completely disconnected from those two cities,
    0:06:23 which has nothing to do and has no interface
    0:06:24 into those two places at all,
    0:06:26 and is sort of the rural Midwest,
    0:06:28 which is basically a farming country.
    0:06:28 And so–
    0:06:30 – Probably one of the more grants, actually,
    0:06:31 as I understand it.
    0:06:32 – Yeah, I think that’s right.
    0:06:34 If you get 10 minutes outside of either
    0:06:35 Milwaukee or Madison,
    0:06:38 you get into a real, real rural territory in a hurry, right?
    0:06:40 And so, there were people in the farming world
    0:06:41 in the Midwest, out through the 1970s,
    0:06:43 that still didn’t have indoor plumbing.
    0:06:44 I have memories of outhouses.
    0:06:46 – Well, for a while, you didn’t have gas heat,
    0:06:47 so you weren’t that far.
    0:06:49 – There’s also that, exactly.
    0:06:51 So, yeah, see, if you wanna heat your house,
    0:06:52 you cut down some wood.
    0:06:55 And so, look, it’s up north and it’s very close to Canada,
    0:06:57 so it’s extremely cold.
    0:06:58 And so, it’s actually ’cause it’s this amazing thing
    0:07:00 where it’s sort of frozen tundra for nine months,
    0:07:01 and then three months of summer.
    0:07:03 You know, but mostly farming, you know,
    0:07:06 a lot of dairy farming, a lot of corn to feed the cows,
    0:07:07 so corn and cows.
    0:07:11 And then, I would say, light manufacturing, light tourism,
    0:07:12 a lot of Illinois people vacation up there,
    0:07:14 go hunting, fishing, or whatever.
    0:07:16 So, a little bit of that, but mostly agricultural.
    0:07:18 My town was sort of the sign of the outside of town
    0:07:21 forever, population, 1300 and nine.
    0:07:22 The sign never changed.
    0:07:23 – (indistinct)
    0:07:25 whether you had 1308 or 1310.
    0:07:27 – Yeah, I don’t think it actually moved around that much.
    0:07:29 So, it’s probably more or less accurate the whole time.
    0:07:31 And then, of course, the running joke was that’s 1300 and nine,
    0:07:32 including the cows.
    0:07:34 So, yeah, so very small town environment,
    0:07:36 kind of lower middle class context,
    0:07:38 and public eight through 12 school.
    0:07:40 My school was very small, 25 kids in a class.
    0:07:42 So, I feel like, whatever, 300 kids in the whole school.
    0:07:45 – So, a lot of people don’t have school choice today.
    0:07:46 You didn’t have teacher choice either.
    0:07:48 ‘Cause here’s, I guess, one teacher for every subject.
    0:07:50 – No, no, exactly.
    0:07:52 And then, look, this is the 70s and then the 80s.
    0:07:54 And so, this not only predates the internet,
    0:07:56 but this also predates cable TV.
    0:07:57 We had no cable TV.
    0:07:59 Long distance phone calls were still a dollar a minute.
    0:08:01 We saw actually my neighborhood growing up, actually.
    0:08:03 We had a party phone line for the entire neighborhood.
    0:08:04 – That’s interesting.
    0:08:05 – Which is actually quite an adventure.
    0:08:07 And so, there’s a single phone number for the neighborhood.
    0:08:08 And so, when your phone rings,
    0:08:10 everybody in the neighborhood picks up the phone.
    0:08:12 This is true, this is true.
    0:08:14 And then, there’s an arbitration process,
    0:08:17 a verbal arbitration process for who the call’s actually for.
    0:08:19 And then, the expectation is that everybody else hangs up.
    0:08:21 But, you know, they don’t have to.
    0:08:23 – Well, they say there are no secrets in the small town.
    0:08:24 – This is one of the reasons why.
    0:08:26 So, yeah, so it’s sort of, I don’t know,
    0:08:29 it’s halfway between the 1930s and the 1980s or something.
    0:08:31 It just is one of those places where, you know,
    0:08:33 a lot of the country was like that at that point,
    0:08:34 which is it hadn’t fully adapted to,
    0:08:36 certainly the things that we all now take for granted.
    0:08:38 And then, you asked me how to discover the internet.
    0:08:40 So, I had no idea the internet even existed
    0:08:41 until I went to college.
    0:08:42 So, the thing I knew that existed,
    0:08:43 and this is where I kind of got lucky
    0:08:46 in terms of when I grew up and when I came of age,
    0:08:47 is I came of age sort of precisely at the moment
    0:08:49 when the PC happened.
    0:08:51 And so, I was aware of, you know,
    0:08:53 there were all these just amazing stories.
    0:08:55 This is when Steve Jobs was on the cover of Time Magazine,
    0:08:56 and you know, so there was this moment
    0:08:57 when the person on the computer
    0:08:58 hit the popular consciousness.
    0:09:00 It was sort of built in the late ’70s,
    0:09:02 and then it sort of catalyzed hard in the early ’80s,
    0:09:03 especially around ’82.
    0:09:04 And then, you know, our school,
    0:09:05 even though it was very small,
    0:09:07 started to get a handful of early computers.
    0:09:09 And then, there were a wave of consumer computers
    0:09:12 at that time that were actually quite inexpensive.
    0:09:13 And so, there were computers at that time
    0:09:16 as cheap as $200 in currency at that point, which–
    0:09:18 – And this is our floppy disk.
    0:09:20 So, this is pre-hard drive or post-hard drive
    0:09:22 when you got your first computer.
    0:09:24 – Pre-floppy disk.
    0:09:25 – And tape.
    0:09:27 – Cassette tape, exactly, yes.
    0:09:28 – It’s a slow loader, bro.
    0:09:30 You can power it a load again.
    0:09:31 I remember that era.
    0:09:32 – Yeah, so, for people who don’t remember,
    0:09:33 but before floppy disks,
    0:09:35 you would literally hook up a cassette tape player.
    0:09:37 And the thing with a cassette tape player
    0:09:39 is it didn’t have any kind of seek capability, right?
    0:09:41 And so, the way that you loaded the program was,
    0:09:42 you had to fast-forward by hand
    0:09:44 at the right point in the tape, right?
    0:09:45 And then, you were always at risk.
    0:09:46 You were gonna write to the tape.
    0:09:48 You wrote a program, you wanted to write it out of the tape.
    0:09:49 You just ran the risk.
    0:09:52 You were gonna overwrite something in the past.
    0:09:53 And then, there was this really fundamental trade-off.
    0:09:54 If you didn’t have a lot of money,
    0:09:55 it’s this very fundamental trade-off,
    0:09:57 which is you could buy a short cassette tape
    0:10:00 that was high quality or a small amount of stuff,
    0:10:01 or you could buy, same price,
    0:10:03 you could buy a cassette tape that was much longer
    0:10:06 and could record a lot more, but at much lower quality.
    0:10:08 And that mattered because the lower quality tapes frequently,
    0:10:10 you would not be able to read back what you had written.
    0:10:12 And so, there was a real quality-quantity trade-off.
    0:10:15 – Yeah, this is a gambling exercise.
    0:10:16 – Exactly.
    0:10:17 And then, so we didn’t have the internet,
    0:10:18 but we had no exposure to the internet.
    0:10:20 We’ll talk about the internet prehistory in a little bit,
    0:10:21 but we didn’t have that.
    0:10:23 What was happening at that time was what were called BBSs,
    0:10:26 which was acronym for Bullition Board Systems.
    0:10:27 And the thing about these is,
    0:10:30 BBSs were kind of pre-social networks in a way,
    0:10:31 and pre-internet.
    0:10:33 And so, the way this would work is the host of the BBS
    0:10:36 would literally set up a set of modems
    0:10:38 in their house or apartment,
    0:10:39 often like eight or 12 or 20 or something,
    0:10:43 to take incoming calls from people with remote computers.
    0:10:45 And then, in theory, you could dial into BBSs,
    0:10:46 and you just literally used a modem
    0:10:49 and you dialed into the phone number for the BBS.
    0:10:50 And then, if you got to the BBS, it was really cool
    0:10:53 because you had access to early versions of email
    0:10:55 and social networking and user profiles
    0:10:58 and Bullition Boards and classified ads
    0:11:00 and downloading games and playing games and so forth.
    0:11:02 And so, it’s kind of pre-internet, pre-AOL,
    0:11:03 kind of versions of these things.
    0:11:05 The problem that I had was, again,
    0:11:07 rural Wisconsin, longest as phone calls are a dollar a minute.
    0:11:09 There are no BBSs in my town.
    0:11:10 And so, I read about BBSs.
    0:11:11 I actually don’t, to this day,
    0:11:13 I think I never actually used one
    0:11:14 ’cause I couldn’t afford it.
    0:11:16 And by the way, also, this is also pre-day broadband.
    0:11:18 And so, when I first started on this stuff,
    0:11:20 this was actually pre-modem, as we understand it today.
    0:11:22 So, the form of the modem at the time
    0:11:24 was what’s called an acoustic coupler.
    0:11:26 And so, you take your old-fashioned telephone handset
    0:11:28 and you literally put it in these two…
    0:11:31 – Yeah, no, I remember those, yeah, right.
    0:11:32 – In the two rubber cups.
    0:11:34 And then, it’s literally using your handheld phone
    0:11:36 as the receive transmit for the audio signals.
    0:11:39 And so, the acoustic coupler modems were 300 bod,
    0:11:41 300 bits per second.
    0:11:45 – Yes, and very noisy, 300 bod, yeah.
    0:11:46 – Yeah, very noisy, exactly.
    0:11:47 So, yeah, very slow.
    0:11:49 So, you could kind of get a glimpse.
    0:11:51 I would say the romance of the personal computer
    0:11:53 at that point was very clear.
    0:11:54 And that’s what really got me was,
    0:11:56 and basically, the way that you’d bought a computer,
    0:11:57 you plugged it into your TV set in those days.
    0:11:59 And what happened was, you literally,
    0:12:01 you got injected into the basic programming language
    0:12:02 interpreter, and what that showed up as
    0:12:04 is that literally, the screen would say ready,
    0:12:06 and then there was a cursor.
    0:12:07 And for kind of kids of my age,
    0:12:10 it was this invitation to basically do anything, right?
    0:12:11 And so, it was this kind of great moment
    0:12:13 where you just kind of felt like
    0:12:14 the future was like in front of you.
    0:12:15 And then, there were all these,
    0:12:16 this became a pop kind of culture thing.
    0:12:18 And so, there were all these books and magazines
    0:12:19 that you could buy or subscribe to that,
    0:12:21 you literally subscribed, you know,
    0:12:22 hobbyist magazine for what kind of computer you had.
    0:12:24 And it would literally have printouts
    0:12:26 in the magazine of programs that you could actually sit
    0:12:27 and type into your computer,
    0:12:29 type into the basic prompt and make work.
    0:12:31 And so, there was this incredible sense of adventure
    0:12:33 for what you could do on a computer.
    0:12:35 And then, there was this additional thing out there,
    0:12:36 which was, wow, if you could afford it,
    0:12:38 you could be on BBSs and you could talk to other people.
    0:12:39 And so, they kind of had that network thing
    0:12:40 from the beginning.
    0:12:42 It’s just the economics at the time was not feasible
    0:12:44 to have it be a mass marketing thing.
    0:12:46 – Yeah, yeah, interesting, interesting.
    0:12:50 Okay, so then, you get the University of Illinois.
    0:12:52 And why did you go there?
    0:12:56 Why not Madison or MIT or what have you?
    0:12:58 – Financially, the state schools were the options.
    0:12:59 And then, Illinois turns out to,
    0:13:01 then and now is a great engineering school.
    0:13:03 And so, Madison’s very good,
    0:13:04 but Champaign-Hurban was one of the top
    0:13:05 engineering schools in the country.
    0:13:07 And so, it was just, it was a nice coincidence
    0:13:09 that that was kind of close enough and inexpensive enough.
    0:13:11 – And also having to have national computing,
    0:13:13 super computing.
    0:13:15 – Yeah, so this is where I got really lucky.
    0:13:17 So, I dropped into Illinois as a new student,
    0:13:19 started out in double E and then decided
    0:13:21 I did not care at all about electrical engineering
    0:13:22 and switched into computer science,
    0:13:23 which was a much better fit.
    0:13:25 But, you know, I showed up as a CS student.
    0:13:27 And basically, this was my big stroke of luck was,
    0:13:31 this was Illinois, University of Illinois in 1989.
    0:13:34 So, this was four years into two federal programs
    0:13:36 that basically created the precondition
    0:13:37 for everything that followed with the internet.
    0:13:39 And the two programs were something,
    0:13:41 I think it was called the National Supercomputing Act,
    0:13:44 and it was basically this effort to basically fund,
    0:13:46 it was funded for what were called
    0:13:48 National Supercomputing Centers at four universities,
    0:13:50 one of which was Illinois.
    0:13:51 And so, the campus as the federal government
    0:13:52 just dropped in a ton of money
    0:13:54 to basically buy state-of-the-art computers,
    0:13:56 including at the time, really big computers
    0:13:58 like these big Cray and thinking machines computers
    0:14:01 that cost like $25 million at the time
    0:14:02 and filled up entire rooms.
    0:14:04 The supercomputers in those days were so big
    0:14:06 that in some cases you’d actually build a building for them
    0:14:08 and you’d build the building,
    0:14:09 but you wouldn’t close the roof
    0:14:11 and you would lower the computer by a crane
    0:14:13 down through the roof into the center of the building
    0:14:14 and then you would just use the roof.
    0:14:16 And so, the big iron.
    0:14:19 Exactly, some very esoteric, expensive, powerful systems.
    0:14:20 So, we had those.
    0:14:23 And then the other federal program was a program
    0:14:25 to build what was called the NSF net.
    0:14:27 The NSF there being short for National Science Foundation,
    0:14:29 which is the government agency that all the money came through.
    0:14:32 And the NSF net basically was the first internet backbone
    0:14:33 as we understand it today.
    0:14:34 And those programs were joined
    0:14:36 because the original purpose of the NSF net
    0:14:38 was to connect together these supercomputing centers
    0:14:41 and then to allow researchers, scientists
    0:14:43 in many other colleges, universities across the country
    0:14:45 to be able to remotely access
    0:14:47 these large centralized supercomputers.
    0:14:49 I want to take a moment here to kind of pay credit to Al Gore
    0:14:52 on this who famously gets just like endless shit
    0:14:54 for people kind of saying that he said
    0:14:54 that he invented the internet.
    0:14:56 And so, just to defend Al’s honor for a moment.
    0:14:58 A, he never actually said he invented the internet.
    0:15:00 What he said is he took the lead in the Senate
    0:15:01 in creating the internet.
    0:15:03 And what he meant by that was not that he sat down
    0:15:04 and wrote the code for it.
    0:15:06 What he meant was he was one of the real leaders,
    0:15:07 one of the main forces in the Senate
    0:15:09 to actually fund these two programs.
    0:15:10 And these two programs led directly to the internet
    0:15:11 as we know it today.
    0:15:13 And so, he and his colleagues at that time
    0:15:15 really stepped up at a pivotal moment.
    0:15:16 And I think that’s actually very relevant
    0:15:18 to kind of what’s happening today with AI.
    0:15:19 Like, I think that’s actually the same thing
    0:15:21 that needs to happen with AI today.
    0:15:23 Well, it’s kind of the opposite of what’s happening
    0:15:26 with AI in universities today,
    0:15:29 which is they’re not only underfunded to do AI,
    0:15:32 but there’s a push among the big tech companies
    0:15:36 to enact legislation that would essentially outlaw AI
    0:15:38 and universities by eliminating open source.
    0:15:42 So, full credit to Al Gore for doing the right thing.
    0:15:44 ‘Cause it’s clear that that wasn’t obvious.
    0:15:45 Yeah, that’s right.
    0:15:47 We’ve been spending a lot of time in Washington lately.
    0:15:48 And I’ve actually been telling the story
    0:15:49 to a lot of current senators
    0:15:52 and encouraging them to basically do the same thing.
    0:15:52 Yeah.
    0:15:54 Democrats love it ’cause it rehabilitates Al Gore.
    0:15:56 The Republicans, I gotta get them through the Gore part,
    0:15:57 but–
    0:15:58 Everything partisan in 2020.
    0:16:00 But they also seem to think it’s a good idea.
    0:16:01 So, I hope that will happen.
    0:16:04 So, basically my great luck was I showed up at Illinois in ’89
    0:16:06 and basically four years into these federal programs.
    0:16:09 And so, I showed up basically just got blasted
    0:16:10 into the future in one step.
    0:16:11 ‘Cause when I showed up there,
    0:16:13 there was, University of Illinois was actually wired.
    0:16:16 It was one of the hub nodes of the internet backbone.
    0:16:18 And the campus was getting wired for broadband.
    0:16:20 And there were computers and computer labs
    0:16:21 with state of the art equipment
    0:16:23 all the way up to these giant Craig supercomputers
    0:16:26 that the computer science department had access to.
    0:16:26 It was just there.
    0:16:28 It was like being beamed into the future.
    0:16:31 Now, the twist on that is the assumption in those days
    0:16:34 was you would use this stuff while you’re in school.
    0:16:36 And so, they had started to give out email addresses
    0:16:38 to undergrads and things like that.
    0:16:40 But the assumption was that you would use these systems
    0:16:41 while you were in school.
    0:16:43 And then if you stayed and became a faculty member
    0:16:45 or something, you would use these systems
    0:16:45 for your research.
    0:16:47 But if you graduated and just went out
    0:16:48 and went into the real world,
    0:16:49 you would leave it all behind.
    0:16:50 – Right, there’s access to the internet, right?
    0:16:52 There’s not access to the internet chains, right?
    0:16:57 Maybe you could kind of describe what the internet was
    0:16:59 at that point.
    0:17:00 ‘Cause when we say internet,
    0:17:01 people imagine a lot of things,
    0:17:03 but that’s not what it was then
    0:17:06 in terms of a user experience.
    0:17:07 – Yeah, that’s right.
    0:17:07 And so a couple of things.
    0:17:09 So one is it’s very important to know
    0:17:11 that at this point and all the way up until really 1994,
    0:17:14 the overwhelming uniform universal expectation
    0:17:16 was the internet would never be a business.
    0:17:17 There would never be a business.
    0:17:18 There would never be an industry.
    0:17:20 There was never going to be money to be made.
    0:17:21 There was never going to be a commerce.
    0:17:22 There was never going to be streaming video.
    0:17:25 There was never going to be stores, any of the stuff.
    0:17:27 By the way, even the idea of having like newspapers online
    0:17:28 was considered bizarre.
    0:17:29 It wasn’t even going to be that.
    0:17:31 It was supposed to be like scientific research papers
    0:17:33 and experimental data and things like that.
    0:17:34 And so it was very much not viewed
    0:17:35 as like a commercial opportunity.
    0:17:37 It was viewed very much not that way.
    0:17:38 And basically, I think, correct me if I’m wrong,
    0:17:40 it had been up until like ’94.
    0:17:42 I think zero of the big tech companies of that era
    0:17:43 took it seriously.
    0:17:44 – Yeah, zero.
    0:17:46 And in fact, well, in fact, the opposite,
    0:17:49 they were building kind of parallel systems to the internet,
    0:17:52 often referred to as the information superhighway.
    0:17:55 Bill Gates was a huge kind of champion
    0:17:57 of the information superhighway
    0:17:59 and specifically not the internet.
    0:18:02 So yeah, and he was kind of the biggest figure
    0:18:04 and for sure in software
    0:18:06 and probably in the industry at the time.
    0:18:07 – Yes, so the big computer companies
    0:18:08 wanted to build proprietary networks
    0:18:09 and they were doing that.
    0:18:11 And by the way, AOL was up and running by ’94.
    0:18:13 AOL kind of got going around ’89,
    0:18:14 kind of the same time I showed up at Illinois,
    0:18:16 but it really kind of hit critical mass.
    0:18:19 AOL basically was a consumer-scaled version
    0:18:20 of the BBS idea that we described.
    0:18:23 And then in ’93, it famously interconnected itself
    0:18:24 with the internet.
    0:18:26 And so all of a sudden, all the AOL subscribers
    0:18:26 became internet users.
    0:18:27 And so there was that,
    0:18:29 but that didn’t even happen until ’93.
    0:18:30 There was certainly no vision for that,
    0:18:32 I think in the late ’80s
    0:18:33 and there were no consumer ISPs
    0:18:36 and then there were no normal businesses online.
    0:18:38 And in fact, the internet up until 1993,
    0:18:40 what was the NSF net, which then turned into the internet,
    0:18:42 the operator under something that the federal government
    0:18:44 dictated called the acceptable use policy,
    0:18:48 the AUP and because the NSF net was federally funded,
    0:18:51 commercial activity on the internet was actually banned.
    0:18:52 ‘Cause it was viewed as a certain inappropriate use
    0:18:54 of federal research dollars.
    0:18:55 And so it actually would not have been legal
    0:18:56 to engage in commercial activity.
    0:18:58 And so there basically was none.
    0:19:00 And then yeah, and then the big phone companies
    0:19:01 and the big media companies at that time
    0:19:04 didn’t even want to build like BBSs or anything,
    0:19:05 internet-related.
    0:19:06 What they wanted to do was basically,
    0:19:08 what we now know as streaming,
    0:19:09 they wanted to do what they called
    0:19:10 at the time, interactive television.
    0:19:12 And the big killer app for internet television
    0:19:13 was called video on demand.
    0:19:16 And so sort of the revolutionary idea at that time
    0:19:18 that instead of watching whatever was on a TV channel
    0:19:19 at that moment, you could watch whatever you want
    0:19:22 by clicking a button and then maybe you could order a pizza.
    0:19:25 – Interestingly, there is a small minor bandwidth problem
    0:19:27 with that idea, if I recall it correctly.
    0:19:28 – Yeah, it was actually an idea
    0:19:29 that was ahead of its time, right?
    0:19:31 Streaming video didn’t really work
    0:19:32 in the way that we understand it today
    0:19:34 until probably 15 years later, right?
    0:19:36 – Yeah, yeah, yeah, definitely.
    0:19:38 I mean, well really when Netflix made the cutover
    0:19:43 from CDs to streaming, which was the late 2000s, right?
    0:19:45 – Yeah, I remember meeting with Reed Hastings in,
    0:19:47 I think 2004 and Netflix was up and running
    0:19:50 and it was very successful doing DVD rental by mail
    0:19:51 and Reed’s a technical genius
    0:19:52 in addition to being a business genius.
    0:19:55 And he said, “I’m thinking about doing streaming.”
    0:19:57 And my first reaction was that’s crazy, it’ll never work
    0:19:59 because even in 2004, like most people on the internet,
    0:20:01 they didn’t have broadband connections fast enough
    0:20:03 to do like TV quality.
    0:20:04 So the video at that point
    0:20:07 was actually these little postage stamp size videos.
    0:20:08 And I was like, oh, I don’t understand
    0:20:09 who’s gonna wanna sit there
    0:20:10 and watch a little postage stamp size thing.
    0:20:12 And Reed had correctly extrapolated
    0:20:14 that the broadband wave in the 2000s
    0:20:15 was gonna result in streaming working.
    0:20:18 But just give you a sense of the delay there, right?
    0:20:20 So even a decade later, even a decade after the founding
    0:20:21 of Netscape, development of Mosaic,
    0:20:23 and founding of Netscape in a decade later,
    0:20:25 it was still considered weird and bizarre
    0:20:26 to turn to stream videos.
    0:20:27 Yeah, so the media companies in the early 90s
    0:20:29 were not being run by technologists.
    0:20:31 And so they had a hard time, I think mapping.
    0:20:33 There was a famous interactive television
    0:20:36 information super highway trial in the early 90s
    0:20:38 around this time, which was to do this video on demand.
    0:20:40 So to do this thing where you’d have a remote
    0:20:41 and you could press a button and watch
    0:20:42 whatever movie you wanted.
    0:20:43 And I remember it was a trial.
    0:20:44 They were trying to figure out if there would be
    0:20:45 consumer demand for this.
    0:20:47 And so one of these companies,
    0:20:49 they wired a neighborhood to do the streaming of a video,
    0:20:52 but it wasn’t digital switched, it was analog switched.
    0:20:54 And so they had a dedicated long,
    0:20:57 basically analog line wired to each house.
    0:20:59 And then in the back office, they had a bank of ECRs,
    0:21:02 video tape players, and they had a videotape player
    0:21:03 for each house.
    0:21:05 And then they had a wall of video cassettes
    0:21:06 with all the movies that were optioned.
    0:21:08 And then they had a guy on roller skates.
    0:21:11 – Yeah, roller skates to get to them quickly.
    0:21:12 – To get there quick enough.
    0:21:14 Cause the user expectation was you click the button,
    0:21:16 you watch the movie.
    0:21:18 And so the guy on roller skates had to like shoot over
    0:21:20 to the wall of video tapes, pull down the right tape
    0:21:22 and then shoot down the hall to the right VCR
    0:21:24 and get the tape and the VCR and press play
    0:21:26 before the couch potato was like giving up
    0:21:28 cause the stream business started.
    0:21:29 – Oh my God.
    0:21:31 – And so yeah, that idea was a bit early.
    0:21:33 But on the University of Illinois campus,
    0:21:35 like broadband existed, like I said, email existed.
    0:21:37 You asked how do people use the internet in those days?
    0:21:39 So sort of pre-web, it was mostly,
    0:21:41 well, there was the leading apps at that point.
    0:21:43 There was an app called Telnet that you would use
    0:21:45 to basically log into another computer on the network.
    0:21:46 And that was actually very important
    0:21:49 cause that’s how the scientists would use the super computers.
    0:21:51 And actually the group I was in at Illinois
    0:21:53 actually built one of the main Telnet apps.
    0:21:54 There was an app called FTP
    0:21:55 that was a file downloading app.
    0:21:57 And so you could upload and download files.
    0:21:59 There was early email.
    0:21:59 So that worked.
    0:22:01 There was early what were called news groups,
    0:22:03 which is like basically forums,
    0:22:04 kind of early social networking.
    0:22:06 But I think at the time those were probably the four
    0:22:08 main things that people did.
    0:22:10 – And it was all scientists
    0:22:14 and computer science majors on the internet, if I recall.
    0:22:16 I mean, there was really nobody else.
    0:22:18 – Yeah, so this is at the time 89.
    0:22:20 I’m gonna guess there were somewhere between 500,000
    0:22:21 to a million people total online.
    0:22:23 And yeah, it was basically the,
    0:22:25 it was basically the faculty, staff and students
    0:22:27 at these four supercomputing centers.
    0:22:28 It was the remote users.
    0:22:30 And then it was like the defense contractors
    0:22:31 got wired up early.
    0:22:33 And then there were branches of the government
    0:22:34 that got wired up early.
    0:22:36 And then there was like the national labs.
    0:22:38 And there were, and then a handful of hobbyists
    0:22:40 would figure out a way to get online.
    0:22:43 And so yeah, so basically it was,
    0:22:45 first of all, it was like 100% people in the West,
    0:22:47 overwhelmingly the US and Europe.
    0:22:49 It was very heavily obviously English dominated
    0:22:50 from the very beginning.
    0:22:53 It was extremely technical scientific oriented.
    0:22:57 Almost everybody on it had a scientific or technical degree.
    0:22:59 It was also very, as a consequence of all that,
    0:23:01 the, it was this incredible, brilliant,
    0:23:03 this is like a million of the smartest people on the planet.
    0:23:05 So the caliber of the people
    0:23:07 and the quality of the discussions was like sky high.
    0:23:09 – Oh yeah, I remember being,
    0:23:13 the old news groups were unbelievable.
    0:23:18 I remember like, if there was like a bug in a compiler,
    0:23:20 like you could find out about it
    0:23:22 and you know, there would be workarounds
    0:23:25 and like the level of expertise on those things
    0:23:26 was absolutely astounding.
    0:23:28 – And look, many of the smartest people
    0:23:29 in the scientific and technical world at that point
    0:23:31 were in there and they would talk to you
    0:23:32 if you had something interesting to say.
    0:23:33 And so if you posted on a news group,
    0:23:35 they would respond.
    0:23:37 And so it was like this distributed community
    0:23:38 of like, you know,
    0:23:39 the smartest scientific technical minds in the planet.
    0:23:40 It was really special.
    0:23:43 And then also because there was no money,
    0:23:44 you know, there was, there were no ads,
    0:23:46 you know, there were, there were no scams.
    0:23:46 There was no fraud.
    0:23:48 There was no spam, you know, they’re like,
    0:23:50 I remember there was actually a scandal
    0:23:52 that there was a guy who figured out
    0:23:53 that this was like a ripe for, you know,
    0:23:54 basically scam, you know, kind of thing.
    0:23:56 And he started, did the first spam emails
    0:23:57 and news group messages.
    0:23:59 And it was like a big scandal at the time
    0:24:01 that somebody would actually do that.
    0:24:03 Cause like a guy just literally started to do that, right?
    0:24:05 And, but you know, it had run for years
    0:24:07 without anybody even trying that.
    0:24:08 Yeah, that’s what a community.
    0:24:10 That’s a true meaning of community, right?
    0:24:14 Like you have all people of the same culture in one place.
    0:24:17 That scale, that’s amazing.
    0:24:18 Yeah. So people who were on that at the time
    0:24:20 kind of always look back at that and they miss it
    0:24:23 because that has never been reconstituted.
    0:24:24 You know, like a lot, a lot of the,
    0:24:25 a lot of those people in their equivalents today
    0:24:27 are like on X or they’re on the other social platforms,
    0:24:28 but they’re, you know,
    0:24:29 they’re a minority population
    0:24:32 in a much larger, you know, context everywhere now.
    0:24:34 Whereas at the time they were the entire population.
    0:24:36 Yeah. So that, that, that was a super magical thing.
    0:24:37 But, but yeah, I mean, look,
    0:24:40 the actual functional use cases were quite limited.
    0:24:42 And yeah, so yeah, that’s, that’s sort of,
    0:24:43 that’s sort of what I saw when I got there.
    0:24:45 Maybe it’d be helpful just cause I think it’s really relevant
    0:24:47 both to the, the, the, what followed,
    0:24:48 but also the AI discussion.
    0:24:50 Maybe if I could, maybe I could go back in history now
    0:24:52 to kind of where the internet came from.
    0:24:55 Yeah. Yeah. Go back to like the late sixties.
    0:24:58 Yeah. So, so the idea of the internet was sort of famously
    0:25:01 this idea of what was called a packet switch network, right?
    0:25:02 So the, the reason the internet works
    0:25:04 is because it’s this peer to peer system in which computer,
    0:25:06 you know, anybody can kind of plug a computer
    0:25:08 into the internet and then you kind of have messages
    0:25:10 that are able to go around and, and, and route.
    0:25:12 And so, you know, famously this is an idea
    0:25:13 that actually was developed originally
    0:25:17 by the Defense Department in the 1960s called packet switching.
    0:25:19 And, and in particular, there’s a guy, Paul Baran,
    0:25:20 who’s kind of the original, you know,
    0:25:21 kind of true founding father, you know,
    0:25:24 godfather of the, of this idea.
    0:25:26 And actually he’s a great, he’s a great story on this,
    0:25:27 going back to your silver spoon thing.
    0:25:30 So he was born, he’s a, he was a Jewish,
    0:25:32 Jewish Polish immigrant to the US.
    0:25:35 And so his parents came, brought him as a small child
    0:25:38 of the US in the 1920s, sort of classic American
    0:25:38 immigrant success story.
    0:25:41 His father opened a grocery store
    0:25:42 and then was able to make enough money
    0:25:44 to send his kid to college.
    0:25:45 Baran, you know, was a super genius.
    0:25:46 He got an engineering degree.
    0:25:48 And then he actually went to your alma mater.
    0:25:50 He went to UCLA for a master’s degree,
    0:25:53 which he got in 1959 in computer science.
    0:25:55 By the way, his master’s degree in 1959
    0:25:57 in computer science was on character recognition.
    0:26:00 – How amazing, AI.
    0:26:03 – And so he was actually, so it’s like,
    0:26:06 he tried to do AI first and, you know,
    0:26:07 he was early on that.
    0:26:09 Yeah, you know, he got part way there,
    0:26:11 but you know, he was already at that point trying to do AI.
    0:26:13 And then he went, he went to work for the Rand Corporation,
    0:26:15 which did a lot of work for the Defense Department
    0:26:18 on military, you know, kind of strategy topics.
    0:26:20 And there was a huge, this is the height of the Cold War.
    0:26:23 So this is in the early 60s, Cuban Missile Crisis,
    0:26:24 you know, where there was a real feeling that, you know,
    0:26:26 there might be nuclear war at any moment.
    0:26:27 And one of the big concerns
    0:26:30 the Defense Department had was in a nuclear strike,
    0:26:31 the way telecom systems worked at that point
    0:26:33 is if you took out the central office,
    0:26:35 you took out an entire telecom network.
    0:26:38 And so the fear of the Defense Department was the Soviets
    0:26:40 presumably knew where the central switching offices were
    0:26:41 for like the AT&T network.
    0:26:43 And so they would bomb those, you know,
    0:26:44 in a nuclear strike.
    0:26:46 And then basically what would happen is the US
    0:26:49 would lose command and control of its nuclear weapons.
    0:26:51 And so basically it was a way,
    0:26:52 the fear was it was a way for the Soviets
    0:26:54 to do a decapitation strike.
    0:26:56 They take out the central switching office from AT&T
    0:26:58 and then the US can’t retaliate.
    0:27:00 Literally the US would not be able to fight,
    0:27:01 you know, to fire its nukes
    0:27:02 ’cause they couldn’t send the commands
    0:27:03 to actually fire the nukes.
    0:27:06 And so it was this existential kind of thing at the moment.
    0:27:08 And so this guy, Paul Baran said,
    0:27:09 well, what if we build a network
    0:27:11 that basically is designed for packet switch
    0:27:12 instead of being circuit switch
    0:27:13 or everything’s going through a central place
    0:27:15 for packet switch where the packets can flow around.
    0:27:17 And if part of the network gets bombed or destroyed
    0:27:20 or taken offline or, you know, power cut or whatever,
    0:27:22 you know, the network kind of reallocates.
    0:27:23 And the significance of this idea
    0:27:25 is not just that it led to the internet.
    0:27:27 The other significance is AT&T thought
    0:27:29 it was the craziest idea they’d ever heard.
    0:27:30 Yeah, yeah, right.
    0:27:32 ‘Cause you need control.
    0:27:33 You need control.
    0:27:35 Control, there’s a central control.
    0:27:36 Yeah, yeah.
    0:27:37 And I was reading just before this,
    0:27:38 I was refreshing myself
    0:27:40 when I read Paul Baran’s obituary in the New York Times
    0:27:42 and Vince Turf has quoted in the obituary saying that,
    0:27:45 you know, Paul Baran was basically a laughed out of AT&T
    0:27:46 when he proposed this idea, right?
    0:27:48 Because it was such a heretical idea.
    0:27:50 So anyway, so the point being is the internet
    0:27:52 was a heretical idea from the very beginning.
    0:27:56 And I thought, and both in that it would never work
    0:27:59 ’cause it would be like entirely too slow
    0:28:01 and the packet reassembly and all that would never work.
    0:28:04 And then also that it was a dumb idea
    0:28:07 because of course you want central control.
    0:28:12 So like they derided him in every direction possible.
    0:28:13 Yeah, yeah.
    0:28:16 Well, as late, so that was 1964, 20 years later.
    0:28:17 A horrible idea that would never work.
    0:28:19 Horrible idea that will never work, exactly right.
    0:28:21 So that was 1964 when he proposed this.
    0:28:24 As late 20 years later in 1984,
    0:28:26 a federal judge went to break up AT&T,
    0:28:28 which at that time was the national telecom monopoly.
    0:28:30 They owned and controlled everything.
    0:28:33 And AT&T actually got the secretary of defense
    0:28:35 in 1984, 20 years later to testify
    0:28:37 that if the federal judge broke up AT&T,
    0:28:39 it would permanently cripple the U.S.’s command
    0:28:41 and control capability for nuclear weapons, right?
    0:28:44 And so even 20 years later, people didn’t believe it.
    0:28:46 It was still a heretical idea.
    0:28:47 And by the way, 84 is significant
    0:28:50 because of course the very next year in ’85
    0:28:52 is when the NSF net was funded, right?
    0:28:56 And so it was like a 20 year journey
    0:28:58 to get from that original heretical idea
    0:28:59 with resistance all the way through
    0:29:01 to ultimately get to the point where Al Gore
    0:29:03 and his colleagues figured out that actually,
    0:29:04 no, it was actually a good idea
    0:29:06 and they should actually put money in it.
    0:29:08 So what I’d really like to know,
    0:29:10 and I think a lot of people would is,
    0:29:14 so you have this network with some supercomputers on it
    0:29:18 and a bunch of scientists and some news groups,
    0:29:21 like, how did you get to this idea?
    0:29:23 ‘Cause nobody else had the idea.
    0:29:25 I’d say like, first of all, nobody else had the idea.
    0:29:27 And then secondly, if you had not had the idea
    0:29:32 when you had it, the internet as we know it probably
    0:29:37 doesn’t happen in that the kind of Microsoft alternative,
    0:29:40 the oracle alternative would have had an opportunity
    0:29:42 to gain a network effect.
    0:29:45 And so the chance of all this getting built,
    0:29:48 I mean, maybe if it was invented six months later,
    0:29:50 but four years later, definitely not.
    0:29:53 And so what happened?
    0:29:55 – Yeah, so there were serious efforts underway.
    0:29:57 You alluded to this, but there were serious efforts at times.
    0:29:59 Let’s just itemize the efforts.
    0:30:01 And so there were three basically consumer online services
    0:30:04 that came out of the 80s, AOL, CompuServe and Prodigy.
    0:30:07 AOL became famous later, much larger.
    0:30:09 CompuServe kind of petered out at one point.
    0:30:10 Prodigy was actually an IBM joint venture.
    0:30:13 So they were actually kind of clued into that part of it
    0:30:14 early.
    0:30:17 And then, those systems existed in the early 90s.
    0:30:18 And those were all these proprietary,
    0:30:21 sort of proprietary stove pipes not interconnected,
    0:30:23 not open, these are by definition closed systems.
    0:30:25 And for people who don’t remember this,
    0:30:27 if you wanted to like put content up on AOL,
    0:30:32 you had to pay AOL, like you had to get their permission,
    0:30:33 their approval and they could take it down.
    0:30:36 And so it was, sort of any of these stove pipe
    0:30:38 proprietary things, somebody really is in charge.
    0:30:40 And the internet is the opposite of that.
    0:30:41 And so those systems ran like that.
    0:30:43 And then there were a set of companies
    0:30:45 that then we’re going to do, that you’re alluding to,
    0:30:46 that we’re going to do the leapfrog on that
    0:30:50 and kind of do the modern, gooey version of that.
    0:30:52 And that was specifically Microsoft with MSN.
    0:30:53 The time was called MSN.
    0:30:56 And then Apple had something at the time called eWorld.
    0:30:58 And then who else was running around?
    0:30:59 A whole bunch of these other companies were running.
    0:31:01 And then the media companies were doing these
    0:31:04 proprietary video interaction TV things
    0:31:06 that would also be centralized controlled.
    0:31:08 But yeah, in particular, I think probably at the time,
    0:31:11 it was really the big ones would have been AOL
    0:31:12 getting really big.
    0:31:15 It would have been Microsoft establishing its own,
    0:31:18 kind of permanent proprietary online service
    0:31:19 as an alternative to the internet.
    0:31:21 And then it would have been probably Apple
    0:31:23 with its own proprietary system.
    0:31:24 Probably would have been the big three.
    0:31:26 And look, those companies would have loved for that to happen.
    0:31:28 Like all three of those companies would have been much better
    0:31:29 off had that happened.
    0:31:32 Yeah, you get a big on every transaction.
    0:31:33 Yeah, this was actually the famous,
    0:31:34 the Ben just used the word big.
    0:31:36 So there was a famous interview with Microsoft CTO
    0:31:39 at the time that they were trying to make MSN work.
    0:31:42 They were a proprietary system and interesting guy.
    0:31:43 And he said, yeah, he said,
    0:31:46 and he actually to his credit, he kind of said it out loud.
    0:31:47 He said, yeah, the goal of this program
    0:31:49 is to get a big of every online transaction,
    0:31:53 big being the mafia term for your slice of the pie.
    0:31:55 Yeah, vigorous, vigorous.
    0:31:57 Exactly so.
    0:31:59 So, and yeah, they would have had,
    0:32:00 they would have had total control.
    0:32:01 And so if you think about the level of control
    0:32:03 that big tech has today,
    0:32:05 like it would have been like that times 10.
    0:32:08 And that really was where the industry was headed.
    0:32:10 And those companies had a big advantage at the time,
    0:32:12 ’cause one is they just had tremendous resources,
    0:32:15 like they were funded to do this.
    0:32:17 And then the other thing is that at the time,
    0:32:19 look to just get this stuff to work was hard.
    0:32:21 And they could marshal thousands of engineers
    0:32:22 and they could design everything to work
    0:32:23 in a completely integrated manner.
    0:32:25 And they had all these graphic designers
    0:32:26 to make it beautiful.
    0:32:27 And they had all these performance engineers
    0:32:28 to make it fast.
    0:32:30 And they could run big advertising campaigns
    0:32:32 and do consumer support.
    0:32:34 And I’ll tell the story later
    0:32:35 of how I became the consumer support.
    0:32:36 I became the user support desk
    0:32:39 for the entire internet for about a year and a half myself.
    0:32:40 – It’s an amazing job.
    0:32:41 – But you know, amazing job.
    0:32:44 They would have had the ability to,
    0:32:45 they had a lot of natural advantages
    0:32:49 to be able to do it in the proprietary way that they wanted.
    0:32:51 And so this was a critical period for that.
    0:32:52 Yeah, the internet as we know it today
    0:32:54 didn’t have to happen.
    0:32:56 Yeah, so basically, I think in retrospect,
    0:32:57 what just happened was a couple of things.
    0:32:59 So one is just the generation of super geniuses
    0:33:02 like Paul Baran and your friend Len Kleinrock
    0:33:05 and Vint Cerf and all these really bright guys
    0:33:07 who had created the internet as kind of
    0:33:10 the network side of it.
    0:33:11 You know, they just, they were networking people
    0:33:13 and they just didn’t, they didn’t,
    0:33:14 their natural, you know, kind of world
    0:33:18 was not user interfaces and consumer services
    0:33:20 and contents and media and, you know, gaming
    0:33:23 and, you know, all these, all these application level things.
    0:33:25 You know, they just, they, the way these systems are built
    0:33:27 is they just assume somebody else is gonna do all that.
    0:33:29 And that hadn’t really happened yet.
    0:33:31 And so, yeah, so just, part of it was people,
    0:33:33 they hadn’t tried.
    0:33:34 Part of it was it wasn’t a business.
    0:33:36 And so there was no business motivation to try to do it.
    0:33:38 And then also part of it was,
    0:33:39 there was another coincidental thing that happened
    0:33:43 which was the arrival of the, of the graphical PC.
    0:33:44 And so the arrivals, the arrival specifically
    0:33:46 of the Macintosh and then followed by that,
    0:33:48 the arrival of Windows, Windows version three
    0:33:50 and the, and the first graphical PCs.
    0:33:53 And so the, you know, before about 1992 or so,
    0:33:56 you weren’t gonna have a graphical user interface
    0:33:57 to anything ’cause you didn’t have graphical user interfaces
    0:33:58 at all.
    0:34:00 And so there was also a moment in time thing
    0:34:01 that happened there.
    0:34:02 So there was all that.
    0:34:04 Yeah. And so then my, my part of the story was,
    0:34:07 I was, I had a bunch of jobs in college
    0:34:09 and was getting my computer science degree.
    0:34:10 And then I ended up working for,
    0:34:13 was called NCSA, which was the National Center
    0:34:14 for Supercomputing Applications.
    0:34:16 And you’re a freshman at the time
    0:34:18 or a sophomore when you got that job?
    0:34:19 No, so I actually didn’t get,
    0:34:21 I actually just started working there as a junior.
    0:34:23 So I worked, when I was a freshman,
    0:34:26 I worked in a physics lab called the Materials Research Lab
    0:34:28 there, which was actually a great entry point for me
    0:34:30 ’cause that was one of the main labs
    0:34:32 using the big supercomputers.
    0:34:32 Yeah.
    0:34:35 I kind of got plugged into that world very early.
    0:34:36 And then I, and then my sophomore year,
    0:34:38 I spent nine months actually as a co-op student
    0:34:40 working for IBM in Austin.
    0:34:43 And I worked on the workstations at the time,
    0:34:44 which was again, very, very helpful for this
    0:34:46 ’cause these were kind of the leading edge user interface.
    0:34:48 You know, so like I worked on graphic systems.
    0:34:49 Well, I’m an NA at TCPIP, right?
    0:34:51 The workstations, yeah.
    0:34:54 They were built in and then IBM and Austin at the time,
    0:34:56 you know, this is when IBM was on top of the world.
    0:34:57 It was, you know, by far the most important tech company
    0:34:59 still at that point.
    0:35:00 And, you know, we had this,
    0:35:02 we had a 6,000 person division in Austin
    0:35:05 working on these Unix workstations
    0:35:06 at the time, graphical workstations.
    0:35:08 And again, they had the resources.
    0:35:09 Everybody there was also wired,
    0:35:10 everybody was on the internet.
    0:35:12 These workstations were designed to be used on the internet.
    0:35:13 Right, right.
    0:35:14 And I was, I was.
    0:35:17 At the time did not have any internet capability.
    0:35:20 You know, there was no, in the early 90s,
    0:35:22 there was no TCPIP, there was never none of it.
    0:35:24 Yeah, well, computers, you recall this.
    0:35:27 Yeah, computers, PCs and Macs up until ’93, ’94
    0:35:30 didn’t even come with TCPIP built into the computer,
    0:35:31 built into the operating system.
    0:35:32 Right, right.
    0:35:33 And you actually had to buy it,
    0:35:36 what was called the TCPIP stack is a separate thing.
    0:35:36 Windsock.
    0:35:38 Windsock and these things.
    0:35:40 And so, yeah, but the Unix workstations of that era,
    0:35:42 you know, the problem with the Unix workstations
    0:35:43 is they cost like $50,000.
    0:35:45 And so these were not consumer products.
    0:35:46 But if you had one,
    0:35:48 you had internet networking built into it.
    0:35:50 And then if you were at IBM, like I was,
    0:35:52 or at Illinois, like I was, you were also on the internet.
    0:35:54 And so, you know, I kind of got to see, you know,
    0:35:58 I kind of saw the bricks being put in place,
    0:35:59 you know, for what followed.
    0:36:00 And then I knew how it all worked.
    0:36:02 ‘Cause, you know, my job was to do engineering
    0:36:03 on all these things.
    0:36:05 And then basically there was this moment in,
    0:36:08 basically I think it was ’92, ’91, ’92.
    0:36:10 There was this moment where there were basically three
    0:36:13 online efforts to kind of do a front-end,
    0:36:15 new kinds of sort of user interfaces,
    0:36:17 interaction models for the internet at that point.
    0:36:20 And so, and it was famously, it was three of them.
    0:36:21 There was one called Gopher,
    0:36:22 there was one called Waze,
    0:36:25 and then there was the World Wide Web.
    0:36:25 Tim Berners-Lee.
    0:36:27 And so, and these were, in the very beginning,
    0:36:29 these were actually in a real bake-off with each other.
    0:36:30 There were a lot of people who had different opinions
    0:36:32 about which of these we’re gonna win.
    0:36:35 Gopher was actually based on the user interfaces
    0:36:37 of the BBS system in the ’80s.
    0:36:39 And so, it was a menuing system.
    0:36:41 And so, you could go down all these different menus
    0:36:43 and download content and so forth.
    0:36:45 And then Waze, W-A-I-S,
    0:36:47 I think it was called Wide Area Internet Search.
    0:36:50 Waze was like a pre-Google search engine.
    0:36:53 And so, it was sort of the idea that you would have,
    0:36:54 you know, type in search keywords and get back results.
    0:36:56 And then this guy, Tim Berners-Lee,
    0:37:01 in Switzerland, an English guy working at CERN in Switzerland,
    0:37:03 had this kind of really, at the time, radical idea,
    0:37:06 which was to take an old idea called hypertext
    0:37:07 and bring it onto the internet
    0:37:09 and basically be able to have documents
    0:37:11 that can link the point to other documents.
    0:37:13 And this is an idea that goes back to the ’50s.
    0:37:15 A guy named Doug Engelbart and other guy, Ted Nelson,
    0:37:18 you know, had kind of conceived of this idea decades earlier,
    0:37:20 but the computer systems in the ’50s, ’60s,
    0:37:21 were not quite capable of doing it yet.
    0:37:25 And so, Tim basically said, he was sitting at CERN,
    0:37:27 kind of doing related kinds of work that, you know,
    0:37:30 he was working in kind of support of the physicists at CERN
    0:37:31 in the same way that I was working in,
    0:37:33 support of the physicists at Illinois.
    0:37:35 So kind of a similar universe.
    0:37:37 And, you know, he had this idea basically,
    0:37:38 okay, we’re gonna put hypertext,
    0:37:40 we’re gonna put hypertext on the internet
    0:37:41 in the form of the web.
    0:37:43 But I would describe this at the time,
    0:37:44 as all three of these were like very,
    0:37:46 I would say nascent experimental efforts.
    0:37:48 And then really critically, all three were text-based.
    0:37:51 And again, the assumption here was the internet basically is,
    0:37:53 the assumption was the internet’s slow,
    0:37:55 which for most people at that time it was.
    0:37:56 And so the assumption was the internet’s slow,
    0:37:57 your computer’s slow,
    0:37:59 your network connection is slow.
    0:38:03 And so Gopher was, you know, literally text-based menus.
    0:38:04 Waze was type in a text keyword
    0:38:06 and then get back text results.
    0:38:08 And then the web was hypertext,
    0:38:09 and it was, there’s the text document,
    0:38:10 and then it contains links to other documents.
    0:38:12 But like just as an example, the web,
    0:38:15 and when it was originally conceived, didn’t have images.
    0:38:17 It’s just, ’cause the idea that the network would have
    0:38:19 the capacity to be able to do images
    0:38:21 was just still too much of a reach.
    0:38:23 And then basically, a bunch of people online
    0:38:25 started to play with this.
    0:38:28 And then we talked about what I was doing at the time,
    0:38:31 but I was working on a semi-related project
    0:38:33 and then figured out that with a bunch of my colleagues
    0:38:35 there at the time that there was a,
    0:38:38 we had the ultimate idea that led to Mosaic.
    0:38:39 – So what was your other job?
    0:38:42 – Yeah, so what I got hired to do at NCSA,
    0:38:44 what I got hired to do is I got hired into a group
    0:38:45 called the Software Development Group,
    0:38:48 which was the group that was basically supposed to make,
    0:38:50 it was again funded by the National Science Foundation,
    0:38:53 supposed to make tools, specifically open-source tools,
    0:38:56 that would make it easy for scientists to use the NSFnet
    0:38:58 and to use the supercomputers, right?
    0:39:00 And so those tools I mentioned earlier,
    0:39:01 this thing called Telnet.
    0:39:03 So we made this, we made NCSA Telnet,
    0:39:05 which was the main way you would log into remote computers.
    0:39:06 We had, I think at the time,
    0:39:09 I think we had an FTP client server.
    0:39:11 We had, so we had like a variety of these kinds of tools
    0:39:13 that you would use for these things.
    0:39:17 By the way, we also were doing early work in VR at the time,
    0:39:18 ’cause there was this whole focus,
    0:39:19 oh, there was this whole focus,
    0:39:21 what was at the time called scientific visualization.
    0:39:22 And this is sort of,
    0:39:24 and this is sort of what later became
    0:39:25 like special effects in movies,
    0:39:27 but this was actually pre-Jurassic Park
    0:39:29 and pre-Terminator 2.
    0:39:31 And so the idea was to like,
    0:39:33 the supercomputers would do these like black hole simulations
    0:39:35 or weather simulations or something.
    0:39:37 And then you could actually use these graphical workstations
    0:39:38 to actually render movies
    0:39:40 and you could actually show scientific results
    0:39:41 in visual form.
    0:39:43 And so the group did a lot of that.
    0:39:45 Actually, a lot of those guys actually went on
    0:39:47 and actually ultimately then created
    0:39:48 the computer graphics industry
    0:39:50 in both the computer industry
    0:39:52 and then also in the, in the, in film and television.
    0:39:54 So that was also a thing that was happening then.
    0:39:56 And then actually the VR idea
    0:39:57 was actually already present at the time.
    0:40:00 And so there were attempts to do VR.
    0:40:03 And our sister campus at University of Illinois, Chicago
    0:40:04 actually had something called the cave,
    0:40:07 which was, it was an alternate vision of VR.
    0:40:09 So the main VR idea, of course,
    0:40:10 was a headset strapped to your face,
    0:40:11 which is what people have today.
    0:40:14 At Chicago, they had the idea of the cave,
    0:40:15 which was, no, you’re actually in a physical space
    0:40:18 and you have giant monitors around you, right?
    0:40:20 And so you’re actually in a, you’re actually in a,
    0:40:22 – We’re in Las Vegas.
    0:40:23 – Like the, like the sphere in Las Vegas,
    0:40:24 like the sphere in Las Vegas.
    0:40:26 And also like the way that a lot of these new movies
    0:40:28 and TV shows are filmed now
    0:40:29 and something they call the volume,
    0:40:31 which are sound stages that are literally made up
    0:40:33 of walls and ceilings that are giant display panels
    0:40:36 showing, you know, graphic rendered scenes and imagery.
    0:40:38 – And so in my race, that’s the,
    0:40:41 become the most practical idea.
    0:40:43 – Yeah, yeah, yeah, that works really well.
    0:40:45 So the first TV show that used that technique
    0:40:47 was called the Star Wars show, The Mandalorian,
    0:40:48 which is a huge success.
    0:40:49 And if you watch The Mandalorian,
    0:40:51 it’s actually really, they did a great job on it.
    0:40:54 If you watch it, it seems like they’re outside
    0:40:55 all the time and they’re not.
    0:40:58 The most of that, most of that series was filmed
    0:40:59 when it seems like they’re outside.
    0:41:01 That was filmed in a very small sound stage
    0:41:05 in an environment with giant LCD displays on all sides.
    0:41:06 And then with all the software,
    0:41:07 it’s the control software they have
    0:41:09 where they could literally shift the perspective
    0:41:11 of the, of the, of like the background scenes
    0:41:13 to match like the motions of the actors.
    0:41:15 And they’d have like, they have overhead lights
    0:41:18 so they can like replicate the sun or like sunset.
    0:41:20 And so actually, so anyway, so that cave idea in 1992
    0:41:22 actually is now a state of the art in Hollywood.
    0:41:23 – Yeah.
    0:41:24 – You know, it was too early.
    0:41:25 We didn’t, you know, we didn’t have the quality
    0:41:27 of the screens back then or quality of the graphics.
    0:41:29 So it wasn’t ready yet, but like now it is ready.
    0:41:32 So it’s another one of these back to the future things.
    0:41:34 Yeah, so anyway, so that’s what the group at,
    0:41:35 at Illinois was doing.
    0:41:37 And then the specific project I was on
    0:41:38 was a project called Collage.
    0:41:39 And the idea for Collage today,
    0:41:43 you describe it as sort of a forerunner to zoom.
    0:41:45 Or to, you know, maybe Skype or something like that.
    0:41:48 And it did have the idea of doing audio
    0:41:50 and maybe hopefully doing video conferencing.
    0:41:52 But the main thing was like a shared whiteboard
    0:41:54 and then shared documents.
    0:41:57 And so specifically the idea was real-time collaboration.
    0:41:59 And so, you know, you and I are scientists
    0:42:00 in two different locations.
    0:42:01 We’re writing a paper together.
    0:42:03 We want to be able to look at the paper at the same time
    0:42:05 and be able to make edits such that we can,
    0:42:07 you know, see each other’s edits like the Google Docs,
    0:42:08 like the way Google Docs works today.
    0:42:11 Or to have a whiteboard where you could, you know,
    0:42:13 you could look at, you know, imagery
    0:42:15 or you could look at, you know, draw diagrams
    0:42:16 and you could share them and work on them together
    0:42:19 and annotate them like you had a shared whiteboard.
    0:42:20 And, you know, I think that was, that was like a good,
    0:42:21 I mean, that was a good idea.
    0:42:22 And like all of that stuff has happened
    0:42:23 and it’s very important today.
    0:42:25 It was just, I think it was in retrospect,
    0:42:26 it was just before it’s time,
    0:42:30 which is you just like the internet, what’s that?
    0:42:32 – Out of order and what you should build first, for sure.
    0:42:33 – Out of order.
    0:42:34 Yeah, well, there were two problems.
    0:42:35 Which is one is it was just hard to get it to work
    0:42:38 ’cause you just, you needed a certain speed of, you know,
    0:42:39 you needed a certain speed in network performance
    0:42:41 and graphics capability on the computers
    0:42:43 to make it work and it was kind of choppy.
    0:42:44 And then the other problem was
    0:42:46 to get a real-time collaborative system to work,
    0:42:49 people have to be online at the same time, right?
    0:42:50 And so you and I are, we’re collaborating,
    0:42:51 we have to be online at the same time
    0:42:53 and we might be in totally different time zones
    0:42:54 and, you know, like it’s just,
    0:42:57 so it’s hard to get critical mass for a network effect
    0:42:58 if you have to be online at the same time.
    0:43:00 Whereas, you know, things like email worked
    0:43:02 if, you know, regardless of when you’re online,
    0:43:04 you know, so-called asynchronous.
    0:43:06 And so, yeah, collage was, it was a good idea.
    0:43:08 It just wasn’t quite clicking.
    0:43:09 And then it just, it kind of became clear to me
    0:43:11 and a few of the other folks that I worked with there
    0:43:13 at the time that it’s just like, okay,
    0:43:14 something else is going to pop here
    0:43:15 and it’s going to pop hard.
    0:43:17 And it’s going to be something involving like this,
    0:43:20 you know, the web go for ways like this confluence
    0:43:22 of basically new thinking of user interfaces
    0:43:23 is going to take place.
    0:43:26 And then, by the way, it’s basically two big things,
    0:43:29 the two big things that sort of we insisted on,
    0:43:31 the two big leaps was one is we’re just going to assume
    0:43:33 that everybody has a graphical computer.
    0:43:36 We’re just going to assume that everybody has like Windows
    0:43:38 or a Mac or a Unix workstation.
    0:43:41 We’re not going to support not DOS, right?
    0:43:43 And all systems up until that point, you know,
    0:43:44 including by the way, the early, you know,
    0:43:46 the first web browser, the first web browser
    0:43:48 was a tech space, tech space browser,
    0:43:49 you know, the Tim Berners-Lee browser.
    0:43:51 It was a browser that actually was a tech space browser
    0:43:53 that ran on the next cube,
    0:43:55 of which there were maybe 5,000 of the world at that point.
    0:43:56 – Right, because that was like one
    0:43:59 of the most graphical machines ever.
    0:43:59 – But he had this problem.
    0:44:01 He had this problem is he had the problem.
    0:44:02 So first of all, the problem of just like,
    0:44:04 there was no graphical content, there was no graphical,
    0:44:06 you know, you just like, just the assumption was
    0:44:07 that it was going to be text-based.
    0:44:09 And then the other problem was we just assumed
    0:44:11 that the internet was going to be fast.
    0:44:13 And that was a, again, a heretical assumption.
    0:44:15 That was a heretical assumption at the time,
    0:44:17 ’cause at the time the internet was really slow.
    0:44:19 And most people run very slow connections.
    0:44:22 And so, you know, the experience a lot of people had
    0:44:23 the first time they used Mosaic on,
    0:44:25 even on a broadband connection, the first time they had it
    0:44:28 is you would literally watch the page load line by line.
    0:44:31 And then you would watch the images load line by line, right?
    0:44:34 And so, but it was a heretical idea at that point
    0:44:35 to say, no, we’re just going to assume everybody’s
    0:44:37 on a graphical interface and we’re going to assume
    0:44:39 that everybody’s on a fast broadband connection
    0:44:41 and we’re just not going to compromise.
    0:44:43 We’re going to build the correct user interface
    0:44:45 for that new world on those two fronts.
    0:44:47 And we’re not going to compromise to try to be backward
    0:44:49 compatible with the old text-based UIs
    0:44:51 or with the old narrowband connections.
    0:44:55 – And in a way that you were a university student
    0:44:58 with no company, no need to sell anything in the beginning.
    0:45:01 So it was like, fair enough.
    0:45:03 – Yeah, in my computer, because I worked at IBM
    0:45:06 and then I worked at NCSA and we had all this money
    0:45:07 for the government at that point.
    0:45:09 My computer was an SGI Silicon Graphics
    0:45:12 at the time company, leading a Unix computer company
    0:45:13 at the time, you know, an amazing company,
    0:45:15 but they, you know, they made these workstations
    0:45:19 and the workstations cost $50,000 in 1992 dollars.
    0:45:21 You know, it’s like a hundred and some thousand today.
    0:45:23 And, but that, you know, my computer was one of those.
    0:45:25 And so, and on a fast connection.
    0:45:26 And so I’m just like, look, I’m just going to build it
    0:45:27 for that.
    0:45:30 And then my colleagues built it versions for Windows and Mac,
    0:45:32 but like, we’re just not going to compromise
    0:45:33 for the old hardware that everybody else is on.
    0:45:34 We’re just going to assume that in the future,
    0:45:36 everybody gets something like this.
    0:45:37 – Yeah.
    0:45:37 – And then yeah, we, at your point,
    0:45:39 like we were running on federal research money.
    0:45:41 So we had no commercial, we had no commercial incentive.
    0:45:43 We had no reason to go for, you know,
    0:45:45 large numbers of users or, you know, try to, you know,
    0:45:48 make money or whatever at the time.
    0:45:50 So we, so we just basically, again,
    0:45:52 and the heresy we just designed for the future.
    0:45:53 And then there was a little bit,
    0:45:54 I had a little bit of a glimmer.
    0:45:55 I wouldn’t say I was confident on this,
    0:45:57 but I had a little bit of a glimmer at the time.
    0:45:59 That was like, look, if we designed for,
    0:46:01 if we designed for broadband, like the,
    0:46:03 if it’s a compelling enough user interface,
    0:46:05 it will actually cause broadband to happen.
    0:46:06 – That would be aggressive.
    0:46:07 – Right.
    0:46:09 This is a, my, my favorite philosopher,
    0:46:10 Nicollan has this term called hyperstition,
    0:46:12 which is the idea of sort of, you know,
    0:46:14 sort of willing an idea into existence,
    0:46:15 just by proposing it.
    0:46:16 It’s sort of like pulling the future forward.
    0:46:17 And it’s basic.
    0:46:19 And the idea basically was if people could just see
    0:46:21 what was possible with a modern, you know,
    0:46:24 Unix workstation on a modern broadband network,
    0:46:26 with, you know, with what we then built with,
    0:46:28 if they could just see that with Mosaic,
    0:46:30 they would be like, wow, I need that.
    0:46:32 And then they would price it and they would be like,
    0:46:34 oh my God, I can’t afford that.
    0:46:34 But then they would say, well,
    0:46:37 I need a version of that that I can afford.
    0:46:39 And then that would be a motivation for the phone companies
    0:46:41 to start to offer broadband and for the, you know,
    0:46:43 for the PC, for, you know, for the PCs
    0:46:44 to start to get built in internet connectivity
    0:46:47 and for people to upgrade from DOS to Windows
    0:46:49 and all these other things that followed.
    0:46:51 And so I, as I said, I wasn’t confident about that,
    0:46:52 but I had a glimmer of it.
    0:46:53 Cause I was like, look, like if,
    0:46:55 if you could get through this not whole,
    0:46:56 and if you could get the world to the other side
    0:46:59 where everybody has a GUI and everybody has broadband,
    0:47:01 then all of a sudden it’s just very clear
    0:47:03 that you just, you have all of these incredibly
    0:47:05 compelling things that you can do that are impossible otherwise.
    0:47:08 And so it was kind of a hard shove in that direction.
    0:47:10 And then the other, the other, I would say big breakthrough
    0:47:13 or that I would not break through the other really important
    0:47:15 conceptual rule that we had at the time, which was,
    0:47:17 which was sort of consistent with the internet philosophy
    0:47:19 of the time was it had to be an open platform.
    0:47:21 And specifically it had to be whatever it was,
    0:47:24 it had to be where anybody could create servers
    0:47:25 and anybody could create content.
    0:47:28 And so it had to be very easy to do that.
    0:47:29 And so, and you remember in those days,
    0:47:31 it was sort of famous that you could implement a web server
    0:47:33 and four lines of Perl script, right?
    0:47:34 To do whatever you wanted.
    0:47:36 And so, and you could create a webpage
    0:47:37 just by writing HTML by hand.
    0:47:38 – And then by the way, people did
    0:47:42 and there were scaling issues with those four lines.
    0:47:45 – That’s how a lot of the big internet companies
    0:47:46 started out that way, yes.
    0:47:47 And then that’s one of the reasons
    0:47:49 why the sites always crashed is exactly.
    0:47:52 But the point was, the point was to optimize for,
    0:47:54 it was to optimize for the quality experience
    0:47:55 and then optimize for the openness
    0:47:57 and the creativity that would follow.
    0:47:59 And again, there was a leap there, right?
    0:48:01 And we got, you remember we got a lot of criticism
    0:48:02 at the time, which was, wow,
    0:48:04 a lot of computer scientists at the time were like,
    0:48:06 wow, these guys are building the most inefficient,
    0:48:07 computer systems have ever been built.
    0:48:09 This thing is incredibly inefficient.
    0:48:09 It’s unoptimized.
    0:48:11 It’s wasting network bandwidth.
    0:48:14 – Where’s the ace and one encoding?
    0:48:16 Like this is strings.
    0:48:17 You guys are crazy.
    0:48:18 You’re wasteful.
    0:48:19 – Yeah, we were doing wasteful.
    0:48:20 Yeah, yeah, yeah.
    0:48:22 Big environmental arguments and wasting.
    0:48:24 You’re burning power, causing pollution.
    0:48:26 Yeah, these are all text-based protocols.
    0:48:29 So one of the design principles was all protocols
    0:48:29 have to be text-based.
    0:48:31 There were no binary protocols.
    0:48:32 Text-based protocols are much less efficient,
    0:48:34 much, much slower.
    0:48:36 But the enormous advantage is you can program
    0:48:38 a text-based protocol by writing text.
    0:48:40 And you can read it by reading text.
    0:48:41 Whereas if it’s in a binary format,
    0:48:44 you’re always dealing with an intermediary system
    0:48:45 and it’s just harder to develop for
    0:48:46 and harder to understand.
    0:48:47 The source, you know–
    0:48:51 – So as a little counter to the belief
    0:48:55 of the computer science world at the time,
    0:48:57 I mean, everybody read on ASM-1 encoding
    0:48:59 is that you have to do that.
    0:49:00 – Yeah, any CS professor of that era
    0:49:02 who looked at this said they’re doing it wrong, 100%.
    0:49:04 They said they’re absolutely doing it wrong
    0:49:05 ’cause it’s not optimized.
    0:49:06 I mean, so much of computer science at that point
    0:49:08 was about optimizing scarce resources
    0:49:10 ’cause that was all you had at that time.
    0:49:12 And they had spent decades figuring out how to do that.
    0:49:15 And we collectively decided to just break that rule.
    0:49:17 And again, it was not to break the rule just to break it.
    0:49:19 It was because what was on the other side of breaking
    0:49:22 that rule was openness and creativity and empowerment.
    0:49:23 And anybody can do anything and then–
    0:49:24 – Inclusivity, right?
    0:49:27 You didn’t have to be a computer scientist,
    0:49:31 networking expert to build a web server.
    0:49:32 – Yeah, that’s right.
    0:49:33 And the experience people had,
    0:49:36 the killer version of this that ended up working really well
    0:49:38 was this idea of View Source.
    0:49:40 So there was this feature we built into Mosaic
    0:49:41 and it was built into browsers,
    0:49:43 which was, I forget exactly when it popped up,
    0:49:45 but View Source, the idea basically was
    0:49:46 you’re looking at a web page,
    0:49:48 you’re looking at the rendered version of a web page,
    0:49:49 but you could click on View Source
    0:49:52 and it would show you the HTML source code for the page.
    0:49:55 And so anytime you wanted to see how a web page
    0:49:58 had been created to accomplish something that you wanted to do,
    0:49:58 you could just look at it
    0:50:00 and then it made it easy to learn and replicate.
    0:50:03 And again, that was like, that was not,
    0:50:07 that was like, there was no View Source
    0:50:08 for like network protocols before that.
    0:50:09 That was like, that was a new idea.
    0:50:12 – That created so many web design jobs.
    0:50:16 It was crazy, like, which could never have come about.
    0:50:17 It’d be, you know, like that little
    0:50:20 or a seemingly small thing was a massive thing.
    0:50:21 – Yeah, no, look, I meet people.
    0:50:24 I met people, I met somebody just the other day
    0:50:25 who, you know, literally it’s like that.
    0:50:28 It’s like, you know, they first got access to the browser
    0:50:30 and, you know, from their high school or whatever
    0:50:32 and college and then they literally,
    0:50:33 they literally do the View Source thing
    0:50:35 and they’re like, oh, I can write HTML
    0:50:36 and then they got a job as a web designer.
    0:50:37 – Yeah.
    0:50:38 – And then that paid their way through, you know, whatever
    0:50:40 to, you know, get to the career going
    0:50:42 or start their company and yeah, so that was,
    0:50:44 yeah, economic empowerment, yeah, inclusivity,
    0:50:47 yeah, maximal, I would say maximal inclusivity, you know,
    0:50:50 and then look, you know, technical whizzes could do more,
    0:50:51 but like, you did not have to be a technical whizz
    0:50:53 to get started and get going.
    0:50:55 And then it gave you a very powerful motivation
    0:50:57 to learn more and a very easy way to learn more.
    0:50:59 Yeah, and so that worked out really well.
    0:51:01 And then basically the mosaic idea basically was,
    0:51:02 okay, pull all this stuff together.
    0:51:05 So build basically the unified visual interface
    0:51:07 and mosaic out of the gate actually supported all three
    0:51:08 of the systems that I described.
    0:51:10 So we support it out of the gate with, you know,
    0:51:12 the web in a sort of text form at the time
    0:51:15 and then Gopher and then Waste.
    0:51:16 We actually also support FTP.
    0:51:18 We supported actually native support
    0:51:19 for internet news groups.
    0:51:22 And so it was sort of a single graphical user interface,
    0:51:23 you know, to rule them all.
    0:51:25 So we had support for all this and then, you know,
    0:51:26 the web obviously is the one that took off.
    0:51:29 And then the other part of it for mosaic was
    0:51:31 to then make the web graphical.
    0:51:33 And so to transition it from a text-based, you know,
    0:51:36 kind of text prompt DOS kind of situation
    0:51:38 to be full graphic web pages.
    0:51:39 And that was, of course, you know,
    0:51:40 that was then the thing that really, you know,
    0:51:43 kind of just got lit on fire.
    0:51:48 Yeah, you famously invented the image tag, if I recall.
    0:51:49 So there was a big dispute.
    0:51:51 There was a big dispute early on.
    0:51:52 So there was a big dispute.
    0:51:54 So there was opposition early on
    0:51:55 within the internet community.
    0:51:58 And I won’t name names, but within the set of people
    0:52:00 who were into this kind of thing, working on it,
    0:52:02 there was actually a lot of controversy
    0:52:03 around the idea of adding images.
    0:52:04 And there was a big argument.
    0:52:07 There are actually multiple arguments to not add images.
    0:52:10 And by the way, to not images means not make it graphical,
    0:52:11 right?
    0:52:12 Not bring it into the gooey world.
    0:52:14 And, you know, one argument was just efficiency.
    0:52:17 Again, network optimization, use of resources, you know,
    0:52:18 not, you know, and by the way, you know,
    0:52:20 sort of an equality argument, you know,
    0:52:22 not everybody has a graphical workstation.
    0:52:23 Yeah, right, yeah.
    0:52:24 Right, it would be unfair to them
    0:52:26 if there’s web pages that they can’t view.
    0:52:27 So that was part of the argument.
    0:52:29 You know, there was certainly a speed performance,
    0:52:31 you know, waste argument to it.
    0:52:34 And then there was also a cultural argument.
    0:52:35 And this was around the time
    0:52:36 that the internet was starting to really open up.
    0:52:39 And, you know, that kind of nirvana I was mentioning
    0:52:42 where everybody is like, you know, CS degree holder,
    0:52:45 you know, is starting to become a consumer thing early on.
    0:52:46 And there was a lot of anxiety around that.
    0:52:48 And so there was an argument at the time
    0:52:49 that content of the internet
    0:52:52 should remain only scientific and technical, right?
    0:52:54 And if you add features and capabilities
    0:52:56 like images and graphics,
    0:52:57 then you are encouraging the creation
    0:52:59 of sort of mass market content, right?
    0:53:01 And if you have mass market content,
    0:53:03 that’s going to draw more of the wrong kinds of users.
    0:53:05 A valid argument.
    0:53:08 It turns out that argument was correct.
    0:53:13 But, well, yes, it was correct.
    0:53:15 The people that made that argument
    0:53:17 were correct based on their own presuppositions.
    0:53:18 Yeah.
    0:53:20 I was on the other side of that argument.
    0:53:21 And I was on the other side
    0:53:22 of each of those arguments.
    0:53:23 But specifically on that argument
    0:53:25 is I just always thought
    0:53:26 everybody should be able to use this.
    0:53:29 I was very much on the side of, this is amazing.
    0:53:30 Everybody on the planet should be on the internet.
    0:53:31 Everybody on the internet should be on the web.
    0:53:33 Everybody on the web should be graphical.
    0:53:35 Like there should, yes, there should be content
    0:53:36 all over the internet that’s graphical.
    0:53:37 There should be, you know,
    0:53:39 all kinds of pictures and movies,
    0:53:40 animations and streaming and games.
    0:53:42 And like, yes, you should have all this
    0:53:43 and everybody should be on it.
    0:53:44 And we should maximize this.
    0:53:47 And that may, and again, heretical idea.
    0:53:50 That was, there were a lot of people at the time
    0:53:51 who were very important at the time
    0:53:53 who were very anxious about that.
    0:53:54 And then, and basically we just,
    0:53:56 so there was a big fight argument around that
    0:53:58 and we weren’t making progress on it.
    0:53:59 And then I just did a,
    0:54:00 ’cause I controlled, you know,
    0:54:01 I controlled Mosaic at that point.
    0:54:02 So I just did a fade of complete
    0:54:04 and I just declared it and I created the image tag.
    0:54:07 Yeah, and people put up images.
    0:54:09 And we were just, yes, I won though.
    0:54:11 What’s the, I won the,
    0:54:12 I won the de facto argument.
    0:54:14 It’s just through sheer authoritarian action.
    0:54:16 Yeah, you were a king of the internet.
    0:54:19 And then as well, tell us about like,
    0:54:21 okay, how did it take off?
    0:54:23 When did the press recognize it?
    0:54:26 And then, how did you become,
    0:54:27 go from king of the internet
    0:54:30 to customer support for the entire internet?
    0:54:31 That’s the same thing.
    0:54:32 It’s the same thing.
    0:54:34 Also the main blogger,
    0:54:35 maybe the first blogger,
    0:54:36 depending on how you score it.
    0:54:38 So it was also the sort of,
    0:54:39 I was the front page for a while.
    0:54:44 So yeah, so we started basically a group of us at NCSA
    0:54:46 basically kind of went rogue in 1991
    0:54:48 and, you know, started kind of working on this idea
    0:54:49 on nights and weekends.
    0:54:51 And in particular, my partner at the time,
    0:54:53 Eric Bina and myself,
    0:54:55 you know, we were the first two to kind of work on this.
    0:54:57 And just a full kind of acknowledgement here,
    0:55:00 Eric and I co-wrote the first version of Mosaic,
    0:55:01 which was for UNIX workstations.
    0:55:03 And then we had other colleagues who, you know,
    0:55:06 who are, you know, very famous in the history
    0:55:08 who developed the Windows version
    0:55:09 and developed the Mac version.
    0:55:10 And so, you know, we did develop
    0:55:12 for all three of those platforms,
    0:55:14 but the first version was the UNIX version.
    0:55:15 Eric and I built it.
    0:55:17 I always, I always credit it as I did the front end
    0:55:18 and then Eric did all the hard work.
    0:55:19 – Yeah, yeah, yeah.
    0:55:21 He was a great programmer, I guess, yeah.
    0:55:23 – He was fantastic, absolutely outstanding programmer.
    0:55:25 He is an outstanding programmer.
    0:55:28 And so I did the UI and Eric did the rendering engine.
    0:55:29 And so Eric built,
    0:55:31 the rendering engine is the core of it.
    0:55:32 Like the rendering engine is the thing
    0:55:33 that actually renders the page
    0:55:34 and has all the user interface elements
    0:55:36 and makes the links work and displays the images
    0:55:37 and all this stuff.
    0:55:38 And that was definitely the harder,
    0:55:40 the harder half of it from a programming standpoint.
    0:55:41 So I give Eric, you know,
    0:55:43 I give Eric like at least half the credit,
    0:55:45 if not more for that.
    0:55:46 And then my role was the front end.
    0:55:49 So it’s kind of everything around the rendering engine.
    0:55:50 And so it was the rest of the UI.
    0:55:51 And then it was the other, you know,
    0:55:54 I did the networking protocols and all the, you know,
    0:55:56 user, everything, user preferences and all the cache,
    0:55:58 you know, sort of caching in all the things
    0:56:00 to kind of make the rendering engine work.
    0:56:01 So it was the two of us.
    0:56:02 And it was really like the core of work
    0:56:06 was sort of a crash renegade project kind of off books.
    0:56:07 And for me, it was like off books in two ways.
    0:56:09 It was not what I was supposed to be doing at work,
    0:56:12 but it was also, I was doing this instead of going to class.
    0:56:15 This is when I almost got kicked out of college also.
    0:56:17 Yeah, so we sort of a crash course over the course
    0:56:18 of I guess the fourth quarter of ’92.
    0:56:21 And then, you know, we kind of worked really hard
    0:56:23 over the holiday break of ’92 to kind of get it working.
    0:56:24 And then I forget the exact sequence,
    0:56:27 but we put out the first kind of acceptable version,
    0:56:29 which I think was the 0.9 version.
    0:56:31 And like around Christmas or a little bit after ’92.
    0:56:33 And then I think got to quote 1.0
    0:56:35 and kind of the spring of ’93.
    0:56:38 And yeah, and basically it went vertical
    0:56:40 basically out of the gate with the 0.9 version.
    0:56:42 So it was basically a, yeah.
    0:56:45 So it’s sort of a year of preparatory work in ’92,
    0:56:47 and then it was sort of ’93 was the vertical takeoff.
    0:56:49 And ’93 was a very important year for me
    0:56:51 because it was my senior year in college also.
    0:56:53 And so, and I was off a semester,
    0:56:56 I was off cycle by semester for reasons.
    0:56:59 And then, and so anyway, so January to December in ’93
    0:57:01 where my, that was my senior year in college.
    0:57:04 And so this was like my chance to like really do that.
    0:57:06 And then, ’cause I just assumed I was gonna graduate
    0:57:08 and you know, leave and get a job at the end of the year.
    0:57:10 So I had about a 12 month run there
    0:57:11 where the thing really took off.
    0:57:12 And then yeah, look, it was the tiger.
    0:57:14 Oh, and then we had other colleagues who did the,
    0:57:18 did the, what was the, not the first web server,
    0:57:19 but the first kind of widely used,
    0:57:21 I would say robust scalable web server.
    0:57:23 And again, that also again gave us a lot of ability
    0:57:26 to move quickly ’cause we actually controlled for that period.
    0:57:28 We controlled both the client and the server.
    0:57:29 – Yeah.
    0:57:30 – And so we can move very fast.
    0:57:31 Yeah, so that, yeah.
    0:57:34 So the two of them came out and then people started
    0:57:35 to figure this out and it started to get, you know,
    0:57:38 widely used among existing internet users.
    0:57:39 And then it was an immediate reason
    0:57:40 for people to get online at home.
    0:57:42 And it was really the first reason for a lot of people
    0:57:43 to try to get online at home.
    0:57:45 And so it also I think helped catalyze the boom
    0:57:48 in what were called at the time consumer ISPs
    0:57:50 and for people to upgrade their PCs to be graphical
    0:57:53 and then have network, you know, have the network stack.
    0:57:55 And so the 93 was like this upward, you know,
    0:57:56 the straight kind of upward hurricane.
    0:57:58 But again, it was in this context of we’re working
    0:58:01 for a research institute funded by the federal government.
    0:58:04 And so, you know, we have, you know, we have no money.
    0:58:05 We have no revenue.
    0:58:06 We have no business model, you know,
    0:58:09 – ‘Cause we got a product out there that’s taken off.
    0:58:10 – It’s taken off like crazy.
    0:58:12 And then we put it out as open source,
    0:58:14 but under what’s called a hybrid license.
    0:58:17 We put it under a hybrid license that says it’s free for,
    0:58:19 it’s all free for academic and individual use
    0:58:20 and not profit use.
    0:58:22 But if you want to use it for commercial applications,
    0:58:23 you have to come talk to us.
    0:58:24 – Oh, right.
    0:58:25 – And then I had the mailbox
    0:58:27 for the incoming commercial queries.
    0:58:31 And I remember when it hit like 400 of basic companies,
    0:58:32 you know, like general councils and, you know,
    0:58:34 procurement officers at big companies saying, you know,
    0:58:36 we want to deploy this throughout our company.
    0:58:37 You know, who do we pay?
    0:58:38 And we had no way to take the money.
    0:58:40 We didn’t even have like a price sheet.
    0:58:40 We didn’t have any of this.
    0:58:43 And then very critically, we didn’t have any support, right?
    0:58:45 So we didn’t have any customer support resources.
    0:58:47 And so we had the support email address
    0:58:49 and I also had that email box.
    0:58:50 – Yeah.
    0:58:52 – And so in my spare time between coding sessions,
    0:58:54 I would literally just like answer questions.
    0:58:54 – Yeah.
    0:58:56 – And, but it was literally, it was, you know,
    0:58:58 it was supposed to be tech support for Mosaic,
    0:59:00 but it turned into tech support for the entire internet.
    0:59:02 So I, I helped a lot of people.
    0:59:04 – I think all the difference between that was the internet
    0:59:07 for everybody, you know, and a lot of ways still is.
    0:59:09 – Exactly. And so, so it really started to take,
    0:59:11 it then sort of became a formal project.
    0:59:14 It kind of got, got embraced and became a real project
    0:59:15 and got more resources.
    0:59:16 And then, but we were, you know,
    0:59:18 we were kind of just dying from the overhead
    0:59:19 and, you know, we needed more servers
    0:59:21 and we needed more people and the whole thing.
    0:59:25 And so we wrote, I remember we wrote a proposal to,
    0:59:27 for a grant, we wanted an incremental grant
    0:59:28 from the National Science Foundation
    0:59:31 and it was to staff a customer support desk
    0:59:32 so that we could support as we could hire, like,
    0:59:34 you know, whatever people.
    0:59:35 – Customer support.
    0:59:37 – Yeah, so this is actually my first trip to Washington DC
    0:59:39 as we, we, we, we issued this grant.
    0:59:41 We sent it to Dan and, and it,
    0:59:42 and the National Science Foundation, people to their credit,
    0:59:44 they were fascinated by this whole thing
    0:59:45 and they were glad that it was working.
    0:59:46 But, you know, we sent in this grant,
    0:59:48 it was the only place we had any sense of where to get money
    0:59:49 and we sent in this grant
    0:59:51 and literally it came back denied.
    0:59:54 You know, the National, the National Science Foundation
    0:59:55 is not in the business of, you know,
    0:59:56 funding customer support.
    0:59:59 One of the, one of the sort of fun twists here is,
    1:00:01 okay, you idiot, like this, like giant commercial
    1:00:03 opportunity is staring you in the face.
    1:00:06 Like you’ve, you literally have like inbound sales leads
    1:00:08 like coming out of your ears.
    1:00:09 Like why don’t you go raise venture capital
    1:00:10 and start a company?
    1:00:11 – Yeah.
    1:00:12 – And of course the answer was
    1:00:13 because I had no idea that there was such a thing
    1:00:14 as venture capital.
    1:00:16 – Yeah, venture capital.
    1:00:16 – I literally,
    1:00:19 – Yeah, you know what a tractor was.
    1:00:21 – Yes, exactly.
    1:00:23 You know, I had no conception whatsoever for, you know,
    1:00:25 for, I had just no clue at the time
    1:00:26 that it was actually a tractable thing
    1:00:28 that you could, you could, you could do that.
    1:00:30 And that was like something that like, you know, really,
    1:00:31 you know, rich, famous, fancy people did.
    1:00:32 Or, you know, I don’t know,
    1:00:34 people got lucky or people in Silicon Valley or something,
    1:00:35 but like people in Illinois,
    1:00:36 certainly we’re not doing that.
    1:00:37 And so, you know,
    1:00:40 and there was no venture capital in Champaign-Urban
    1:00:40 at that point.
    1:00:41 And then there was exactly,
    1:00:43 there was exactly one software startup at that point
    1:00:44 called Spyglass,
    1:00:46 which is a name that will come up later in the story.
    1:00:47 – Yeah.
    1:00:49 – But, but it was not doing well.
    1:00:51 And so it was like, it was more of a cautionary tale.
    1:00:52 And so we basically just, yeah,
    1:00:54 we had the tiger by the tail and then we just kind of held on,
    1:00:56 held on for dear life kind of through that year.
    1:00:57 – Incredible.
    1:00:59 – And then when did they kind of,
    1:01:03 when did the kind of media and the press get wind of it?
    1:01:04 – So this is a funny story.
    1:01:06 So, so there was a Wall Street Journal reporter
    1:01:07 named Jared Sandberg.
    1:01:08 – Yeah.
    1:01:10 Well, yeah, yeah, I remember Jared Sandberg.
    1:01:11 He was a funny guy.
    1:01:12 – He was a great guy.
    1:01:13 He was a great guy.
    1:01:15 You know, this is 30 years ago.
    1:01:17 So we’re using the was here for people who were still
    1:01:18 in perfectly good health.
    1:01:19 – Yeah, yeah, yeah.
    1:01:22 He was a great character.
    1:01:23 – Yeah, yeah.
    1:01:24 And it wasn’t as a great writer, a great reporter.
    1:01:26 And so he had sort of the tech beat
    1:01:27 at the Wall Street Journal at the time.
    1:01:29 And he figured this out early and called me up
    1:01:30 to the blue probably in, I don’t know,
    1:01:33 late ’92, early ’93, like super early.
    1:01:34 And he had the story ready to go.
    1:01:36 And he was intensely frustrated
    1:01:38 because he could not get his editors to run it
    1:01:41 because it was not an important story.
    1:01:42 – Yeah, of course Simon.
    1:01:43 You know, everybody’s talking about it.
    1:01:45 It’s just a bunch of idiot kids with bad grades.
    1:01:46 Can’t do writing software.
    1:01:47 – Yeah, yeah.
    1:01:48 On this internet thing that nobody cares about,
    1:01:51 that’s never gonna be a thing that’s about to get quashed,
    1:01:53 you know, squashed by MSN and AOL
    1:01:54 and interactive television.
    1:01:56 And like, I tell you again,
    1:01:58 to talk about the heresy aspect of this.
    1:02:01 Like, this is why I’m so distrustful of experts.
    1:02:03 Like, this is my origin story
    1:02:05 for why I don’t trust anybody with credentials
    1:02:06 or anything anymore.
    1:02:08 So I remember, another one.
    1:02:10 So I was working on, I remember working,
    1:02:12 it must have been, it was like December of ’92
    1:02:13 or January ’93.
    1:02:15 So I’m like working around the clock
    1:02:16 in my little office at NCSA.
    1:02:18 And you know, this is at Urbana-Champaign.
    1:02:19 It’s also, you know, it’s a little further south
    1:02:21 where I grew up, but it’s still frozen tundra
    1:02:22 most of the year.
    1:02:24 And the wind comes whipping over the Illinois plains
    1:02:25 and everything is frozen.
    1:02:27 And you know, you’re slipping fall every 10 feet,
    1:02:27 you know, in the middle of winter.
    1:02:29 And it’s just this kind of crazy thing.
    1:02:30 And I’d be working in the middle of the night,
    1:02:33 none of the restaurants are open and I’d get hungry.
    1:02:35 And so I’d walk down to the one convenience store
    1:02:37 that was open 24 hours and I’d buy my,
    1:02:39 whatever my hot dog or my cookies and something to drink.
    1:02:41 And I remember walking in one night
    1:02:44 and there was this new magazine on the newsstand called Wired.
    1:02:46 And it was Wired issue number one.
    1:02:48 And I was like, oh, that’s interesting.
    1:02:51 It’s a magazine about, it appears to be a magazine
    1:02:52 that’s about things that I’m interested in,
    1:02:54 which was a novel concept at the time.
    1:02:56 And so I bought it and I took it back to my office
    1:02:57 and I read it cover to cover.
    1:02:59 And they did not have the word internet in it once.
    1:03:05 And I was like, okay, you know, I was like, okay, like,
    1:03:07 I guess, I don’t count, you know, I guess, I, you know,
    1:03:09 I don’t count, we don’t count.
    1:03:10 This whole thing doesn’t count.
    1:03:12 You know, these are the experts,
    1:03:14 like they have a magazine, right?
    1:03:15 – They’re pros. – You know, these,
    1:03:16 yeah, these are the pros.
    1:03:18 And like, you know, what we’re working on
    1:03:20 is clearly not important enough to merit the magazine.
    1:03:22 And so I was just like, okay,
    1:03:23 I guess we’re just gonna keep working on our thing.
    1:03:25 But like, you know, it’s sort of like this constant message
    1:03:27 from the media, which is like, this is not important.
    1:03:28 This is not important.
    1:03:29 This is not important.
    1:03:31 So anyway, so Jared had this whole story is ready to go
    1:03:33 and he could not get his editors to run it.
    1:03:35 And then later in ’93,
    1:03:37 John Markoff at the New York Times figured this out.
    1:03:39 – Oh, a good tech reporter.
    1:03:41 I mean, John Markoff’s smart guy, yeah.
    1:03:44 – And a legendary, legendary, you know, tech reporter
    1:03:45 going back, you know, quite, quite a bit, you know,
    1:03:48 still very active, but at the time he was like a veteran
    1:03:49 and was very well respected in the industry
    1:03:51 and wrote a bunch of good books and so forth.
    1:03:53 And so he wrote a story for the New York Times.
    1:03:54 So the good news is he wrote a story.
    1:03:58 The bad news is it featured my boss and my boss’s boss.
    1:04:00 – Who had nothing to do with the project?
    1:04:02 Who had you work on something entirely else?
    1:04:04 – My boss at the time too, his credit, you know,
    1:04:06 he was aware and he, you know, he kind of, you know,
    1:04:09 he kind of, you know, he didn’t vigorously oppose us
    1:04:10 and then he supported us
    1:04:12 and then he ultimately sort of adopted as a project.
    1:04:13 And so he kind of used his way into it,
    1:04:14 but he ultimately was very supportive.
    1:04:17 And then, but my boss’s boss was the director of NTSA
    1:04:18 at the time.
    1:04:19 And look, this is one of those things where I like,
    1:04:21 I owe these guys a tremendous amount
    1:04:22 because they created this environment
    1:04:24 that I was able to do my work in.
    1:04:26 And I wouldn’t be here today if not for them, but, you know,
    1:04:27 you know, I kind of,
    1:04:29 I kind of a little bit of an iffy relationship
    1:04:29 with my boss to start with.
    1:04:33 And then I had never met my boss’s boss, right?
    1:04:34 And there was no reason for me to meet my boss’s boss
    1:04:36 ’cause I’m like an undergraduate like staff member.
    1:04:38 Like, you know, he’s a big, like a huge,
    1:04:39 he’s like a huge important researcher,
    1:04:41 astrophysicist and, you know,
    1:04:42 directing this huge supercomputing center.
    1:04:44 So he had no reason to meet me.
    1:04:46 But, you know, the story shows of the New York Times
    1:04:47 and it’s smiling photos of the two of them
    1:04:49 and not, you know, Eric and me.
    1:04:52 And I’m like, oh, okay, I see how this works.
    1:04:54 – And how did you feel at the time?
    1:04:57 ‘Cause I know how you would feel now if that had happened.
    1:04:59 Like, how did you feel then?
    1:05:00 – It was just a little bit,
    1:05:01 I don’t know, it was a little bit,
    1:05:02 it was a little bit annoying,
    1:05:03 but it was also a little bit of like,
    1:05:05 look, it’s the New York Times.
    1:05:07 Like, I don’t know, you know,
    1:05:10 I don’t, I guess they write about important people, right?
    1:05:11 And these are important people
    1:05:12 ’cause they’re running this thing.
    1:05:13 And I’m not an important person
    1:05:14 ’cause I’m only writing code.
    1:05:15 – Yeah, yeah.
    1:05:18 – And, you know, it’s like the project is important enough
    1:05:19 where they write about the project,
    1:05:20 but like the people actually writing the code
    1:05:22 are not important enough to talk about.
    1:05:23 And so it’s like,
    1:05:24 it’s kind of the same reaction I had to “Wired Magazine”,
    1:05:26 which is a little bit annoying,
    1:05:27 but I guess it means I just need to go back to work.
    1:05:30 ‘Cause there’s nothing else to be,
    1:05:31 it’s not like I can call the,
    1:05:33 it would never occur to me to call the editor
    1:05:34 the New York Times and complain.
    1:05:35 – One screen rather.
    1:05:38 – Nor would he have taken my call, you know?
    1:05:40 And so he certainly didn’t know who I was
    1:05:41 ’cause it certainly wasn’t in the story.
    1:05:44 So, you know, it was just like, it was like whatever,
    1:05:45 but it’s like this weird, you know,
    1:05:47 it’s like the Play-Doh shadows on a cave wall thing.
    1:05:50 Just like, okay, there’s all these things
    1:05:51 that people believe, right?
    1:05:53 Including up to the internet is like doomed
    1:05:54 and it’s never gonna be a thing
    1:05:56 and it’s gonna get swamped and all these things.
    1:05:58 And then we’re just like, okay,
    1:05:59 no, we just have this stuff in front of us
    1:06:01 and it just plainly works and we believe in it.
    1:06:03 And I guess we’re just gonna keep working on it.
    1:06:04 And maybe people will figure out maybe they won’t.
    1:06:06 Anyway, so Jared Samberg calls me up.
    1:06:08 I remember the day that story broke in the New York Times.
    1:06:10 Jared Samberg calls me up and he’s just absolutely livid.
    1:06:13 And he told me that he got the morning paper.
    1:06:14 And you know, this is like six months later
    1:06:15 or something after he, you know,
    1:06:17 he would have had the scoop.
    1:06:19 He would have had the first story on basically
    1:06:20 on all of this stuff.
    1:06:21 And he literally told me the story.
    1:06:22 He said he charged into his office that morning
    1:06:24 and slapped the New York Times down at the desk
    1:06:26 in one of these dramatic moments and said, you know,
    1:06:27 “See, I told you so, you know,
    1:06:28 “John Markov front page of the business section.
    1:06:30 “I told you this was actually a story.”
    1:06:33 And his boss was like, “Oh yeah, I guess you were right.”
    1:06:35 – Oh my God, that’s so crazy.
    1:06:38 – So that’s how, again, the heresy,
    1:06:39 like that’s how heretical it was.
    1:06:41 It was like actually, it was actually hard
    1:06:42 to get it in print.
    1:06:44 And I think the only reason it showed up in the New York Times
    1:06:46 is John Markov was such a legend.
    1:06:47 He was just a legendary,
    1:06:48 he was further along in his career at that point.
    1:06:51 So 93 was a phenomenal year
    1:06:53 ’cause it was the take-off year for the web,
    1:06:56 for the browser, for all this stuff, for Mosaic.
    1:06:58 Yeah, and so it was, and then, you know,
    1:07:00 the other part of it was just the ping pong effect
    1:07:02 was very interesting, which was, it was basically was,
    1:07:05 you know, it started out with like a few people with browsers
    1:07:07 and then a few people with web servers
    1:07:09 putting up these little individual pieces of content.
    1:07:11 But then you got in this kind of feedback loop
    1:07:13 back and forth, kind of ping pong thing
    1:07:14 where basically every time there was a new
    1:07:16 compelling piece of content put online,
    1:07:19 there was a reason for people to start using the browser.
    1:07:21 And then every time more people started using the browser,
    1:07:22 there was an additional incentive
    1:07:24 to put more content online, right?
    1:07:26 And so it was like the writers,
    1:07:28 you needed writers and readers.
    1:07:30 And so more writers meant more readers,
    1:07:31 more readers meant more writers.
    1:07:35 And so, and this is what our partner Andrew Chen
    1:07:36 refers to as the cold start problem, right?
    1:07:39 Is by default, if you have a situation like that
    1:07:41 where you’re gonna have a network, you know,
    1:07:43 at scale it’s gonna be great,
    1:07:44 but like to actually get it to scale
    1:07:45 is actually really hard.
    1:07:48 And most things that need to have that kind of network effect
    1:07:50 never get passed the cold start problem, right?
    1:07:54 They just, they strangle early because, you know,
    1:07:55 there’s just not enough, not enough writers,
    1:07:56 which means there’s not enough readers,
    1:07:58 there’s not enough readers, there’s not enough writers.
    1:08:01 – But this, the openness completely was a winner for you.
    1:08:02 Yeah.
    1:08:03 – That’s right.
    1:08:04 And so what happened from the very beginning
    1:08:07 was people all over the world started creating web servers
    1:08:08 and started putting up content.
    1:08:12 And they either used NCSA Mosaic, NCSA web server,
    1:08:13 which actually later became Apache.
    1:08:15 So it’s actually still kind of in use today.
    1:08:18 You know, it’s, you know, this derivation is much later.
    1:08:19 Or, you know, they literally could write their own web servers
    1:08:21 for the reasons we described earlier.
    1:08:24 And so there was no content arriving online.
    1:08:25 Just to give people a sense of this,
    1:08:28 in the early 93, it was like one new website a day.
    1:08:30 And by the way, by one new website,
    1:08:31 I don’t mean like one new website,
    1:08:33 I don’t mean like a new eBay a day or something.
    1:08:35 I mean like a new web page.
    1:08:36 Yeah, I remember it was a big day,
    1:08:38 the first restaurant menu came online.
    1:08:40 It was like a big, it was like an Indian restaurant
    1:08:42 and like some second tier city in England
    1:08:44 just decided to, somebody put the menu online.
    1:08:46 And then it was, I remember the first webcam.
    1:08:50 So the first streaming video, first webcam was a coffee pot.
    1:08:51 And it was literally a coffee pot
    1:08:53 ’cause the guy had actually rigged up a camera,
    1:08:55 an early webcam at the time, camera at the time,
    1:08:57 with the coffee pot down the hall
    1:08:58 in some computer science department somewhere
    1:09:00 so that he could see when the coffee pot was empty
    1:09:01 and go refill it.
    1:09:02 And then he basically just,
    1:09:03 so just pure utility for him.
    1:09:05 And then he put the coffee pot online.
    1:09:06 It was the first webcam.
    1:09:07 And so we all sat for like a week
    1:09:08 and just watched the coffee pot.
    1:09:10 Yeah, yeah, well I put it around the land
    1:09:12 when I can put it on the internet.
    1:09:12 Yeah, exactly.
    1:09:14 And then, you know, you can see it from home, right?
    1:09:17 And so, you know, we all watched the communal coffee pot.
    1:09:18 And so, you know, there was that.
    1:09:21 And anyway, so then one of the features built into Mosaic
    1:09:23 was what was called the what’s new page.
    1:09:25 And that was another, something that I had at the time,
    1:09:27 which was basically, it was sort of one of the first blogs
    1:09:30 or maybe the first one where it was every day, it was okay.
    1:09:33 It was literally, here are the new web pages for that day.
    1:09:34 And it was this period doubling thing
    1:09:35 where it started out being,
    1:09:38 here’s the new web page for today, right?
    1:09:42 And then it was a big deal when it started to be to a day,
    1:09:44 right? And then four a day, and then six a day,
    1:09:45 and then eight a day.
    1:09:46 And then, you know, by the end of the year,
    1:09:48 you know, I couldn’t keep up anymore.
    1:09:51 Yeah, the what’s cool web page.
    1:09:52 Well, then we added the what’s cool page, right?
    1:09:53 And the what’s cool page was the good stuff,
    1:09:56 exactly the editorial function.
    1:09:58 So yeah, so that was, yeah, that was a key moment.
    1:10:01 Getting to the windows and the Mac versions were key moment
    1:10:02 ’cause, you know, they followed
    1:10:04 and those guys did a great job on those.
    1:10:05 And that really opened things up.
    1:10:07 And then, and again, this was leading up to, I guess,
    1:10:11 AOL formally interconnected into the internet in September 93.
    1:10:13 So this was leading up to that period.
    1:10:15 And they, I don’t remember in AOL released their first
    1:10:17 built in, I don’t remember that when they first built in
    1:10:19 a web browser into AOL.
    1:10:20 Yeah, that was right, I think, yeah.
    1:10:21 I think it was, yeah.
    1:10:23 But you could kind of, you could kind of get a sense,
    1:10:25 you know, it started to become clear that number one,
    1:10:27 that they were going to interconnect to the internet,
    1:10:29 that they were going to bring their users out of the internet.
    1:10:31 And then it seemed inevitable that they would build
    1:10:32 in a web browser so that you started to get momentum
    1:10:33 from that.
    1:10:36 And then, oh, and then the NSF basically this coincided
    1:10:39 with the NSF handing off the NSF net
    1:10:41 to the commercial telecom companies.
    1:10:44 So this was what happened where, so all of this activity,
    1:10:47 like Mosaic, was driving the network bandwidth, right,
    1:10:49 on the backbone, crushing the backbone.
    1:10:52 The NSF was not in the business of providing
    1:10:53 commercial backbone services.
    1:10:55 And so they did a handoff to the three big telcos
    1:10:58 at the time and, you know, did the handoff as part of that.
    1:11:01 The acceptable use policy was revoked.
    1:11:04 And so then commercial use of the internet became legal.
    1:11:06 Immediately after that happened,
    1:11:09 there was a really pivotal moment in history,
    1:11:11 which is there was a big computer company
    1:11:12 at the time, you’ll remember called DEC,
    1:11:14 and they had a research lab in Palo Alto
    1:11:16 called the DEC Western Research Lab.
    1:11:19 And there was a guy there whose name I’m blanking on,
    1:11:21 but he, I think it was Brian Reed, if I remember correctly.
    1:11:23 And he was a computer science guy there
    1:11:24 and he was into this stuff.
    1:11:29 And there was a cult science fiction book retail store,
    1:11:31 tiny little hole in the wall bookstore on El Camino Real
    1:11:34 in I think Mountain View called Future Fantasy Books.
    1:11:37 And it was a cult retailer of like obscure science fiction
    1:11:38 and fantasy novels.
    1:11:41 And it was, it had, you know, it’s local clientele,
    1:11:43 but it also had a lot of, especially Japanese
    1:11:44 and German tourists, when they were in town,
    1:11:47 they would go by and they would buy all these science fiction
    1:11:49 novels that they couldn’t get back in their own countries.
    1:11:51 And so he had this international clientele.
    1:11:54 And so this guy at DEC, I remember went and talked to the,
    1:11:56 you know, kind of very hippie, you know,
    1:11:58 kind of, you know, ponytail old school,
    1:12:00 you know, owner of the Future Fantasy bookstore and said,
    1:12:02 oh, you know, let’s put your bookstore, you know,
    1:12:02 on the internet.
    1:12:05 And the guy’s like, I have no idea what any of those words meant.
    1:12:07 Could you please explain each of them to me in sequence?
    1:12:09 And Brian basically described, he’s like,
    1:12:11 we’re going to put your, we’ll create a website for you.
    1:12:13 We’ll put a catalog online and we’ll let people,
    1:12:16 you know, all these people, all these foreign buyers
    1:12:18 will be able to buy books from, you know,
    1:12:19 Japan and Germany.
    1:12:20 They’ll be able to see the catalog on the web
    1:12:22 and they can click and buy, which was a new idea.
    1:12:24 And then, you know, you can ship to the books
    1:12:25 and your business will grow so much.
    1:12:26 And the guy’s like, that’s great.
    1:12:29 He said, the problem is I don’t actually own a computer.
    1:12:31 And Brian’s like, well, what do you have?
    1:12:32 And he said, well, I do have a fax machine.
    1:12:34 And Brian said, let me get back to you.
    1:12:37 And so the, the deck guys literally created
    1:12:40 the future fantasy website and they, they got,
    1:12:42 they figured out how to digitize his inventory
    1:12:43 and they created the first e-commerce site,
    1:12:44 at least for books.
    1:12:45 – It’s the original Amazon.
    1:12:48 – Amazon and, and then they set up a fax gateway
    1:12:50 where you would order on the web
    1:12:52 and then it would fire off a fax message
    1:12:54 to this guy’s store and then he would ship you the book.
    1:12:56 And then, and then of course in sequence,
    1:12:57 you can imagine what happened next.
    1:13:00 So, so step one, his business doubled overnight.
    1:13:01 – Yeah.
    1:13:02 – It’s like the best thing that ever happened.
    1:13:05 And then of course step two is Jeff started Amazon
    1:13:06 and then, you know, destroyed, destroyed, you know,
    1:13:09 destroyed, destroyed, destroyed him and that’s like him.
    1:13:11 But there was like a year there
    1:13:12 where he had like the best year of his life.
    1:13:13 – Yeah.
    1:13:14 – Shipping books all over the world.
    1:13:15 And so that was the, that was the,
    1:13:17 I think that may have been the first e-commerce,
    1:13:19 like the, at least the first like formally commerce,
    1:13:20 e-commerce thing.
    1:13:21 And so that, that was in that period.
    1:13:23 – Wow, wow, wow.
    1:13:24 – Okay. So then you graduate.
    1:13:26 So what do you do?
    1:13:27 – Yeah. So, yeah.
    1:13:30 So I, and I just, look, this was like a, this was,
    1:13:31 I was an undergrad staff member.
    1:13:33 I was getting paid $6 and 25 cents an hour,
    1:13:35 capped, I think at 30 hours a week.
    1:13:36 It was fun, you know, it’s fine.
    1:13:37 I was having a great time, you know,
    1:13:39 and I just assumed as graduating with a computer science degree,
    1:13:40 I’d go get a job.
    1:13:42 I, you know, I didn’t, I didn’t know where or what,
    1:13:43 but I figured I’d do it.
    1:13:45 And again, that like, it was weird.
    1:13:46 It was like a schizophrenic experience.
    1:13:48 Cause like all of this stuff was, it was just like, you know,
    1:13:50 like all day long, I was just dealing with like this,
    1:13:53 just tremendous cascade of incoming, you know,
    1:13:54 stuff and seeing all this like activity,
    1:13:55 but like there was no money in it.
    1:13:56 There was no funding.
    1:13:57 There was no venture.
    1:13:59 There was no startups.
    1:14:00 There was no business.
    1:14:00 There was no nothing.
    1:14:02 And then the media was telling me, it’s, you know,
    1:14:04 primarily it’s stupid and the magazines, you know,
    1:14:07 and all this stuff and it just, and so again,
    1:14:09 I was sort of still, I was sort of halfway between this,
    1:14:10 like I’m seeing the future in front of me,
    1:14:12 but also it was like the rest of the world
    1:14:13 is not taking it seriously.
    1:14:15 And so maybe I’m just like, you know,
    1:14:16 I just like smoking my own exhaust.
    1:14:19 And maybe this is just like all gonna get crushed next year
    1:14:21 by MSN and it’s just all gonna be over.
    1:14:23 And like, it’s just like some weird, you know,
    1:14:24 it’s like, like I said, it’s just like the assumption was
    1:14:27 you left this stuff behind when you, when you graduated.
    1:14:30 And so I had like the advanced version of that conundrum.
    1:14:31 And so I was just like, well, you know,
    1:14:33 I guess I need to get a job.
    1:14:35 I talked to the NCSA guys about staying there.
    1:14:37 They did offer me a job to stay there,
    1:14:39 but you know, to kind of keep doing what I was doing,
    1:14:40 but it would have been a, you know,
    1:14:41 would have been a staff programming job
    1:14:43 and, you know, staying in Urbana.
    1:14:44 And I kind of wanted to get to,
    1:14:47 I wanted to get to A coast.
    1:14:49 I was somewhat ambivalent as to which coast,
    1:14:51 but I definitely wanted to get to A coast.
    1:14:54 And so I decided I needed a job.
    1:14:56 And so I, one of the things I had control of
    1:14:59 was the about page for the web browser.
    1:15:02 And so I added to the about page for the web browser
    1:15:03 that everybody used at the time.
    1:15:04 I added saying, by the way, you know,
    1:15:06 one of the primary authors of this browser
    1:15:08 is graduating and is available to be hired.
    1:15:10 – Good classifier.
    1:15:12 – Please send job offers to, you know, this mailbox.
    1:15:14 And I got, you know, to my credit,
    1:15:17 I got about a dozen job offers and a bunch of offers
    1:15:18 in the East coast, a bunch of offers in the West coast.
    1:15:20 And they got an offer from a little software company
    1:15:22 out in California.
    1:15:24 I got two, basically two offers in Silicon Valley
    1:15:26 that I strongly considered.
    1:15:28 One was a little software company that I joined.
    1:15:29 And then the other was,
    1:15:31 I got an offer actually from Sun at the time,
    1:15:34 which had a unit, they had a software unit of Sun
    1:15:35 at the time called First Person,
    1:15:38 which was creating what became Java later
    1:15:39 with James Gosling.
    1:15:40 It was his project.
    1:15:42 And they, I almost went there,
    1:15:45 but they had a phantom stock option program.
    1:15:47 – That doesn’t sound good.
    1:15:48 – I didn’t know much,
    1:15:50 but like if you’re applying the word phantom
    1:15:53 to your stock option program, that’s not a good sign.
    1:15:54 Well, they had a classic problem,
    1:15:55 which is they had a software group
    1:15:57 that they wanted to give an incentive to
    1:15:58 and they wanted to kind of have-
    1:16:01 – Hardware company where you have small stock options, right?
    1:16:03 – And so they wanted this thing
    1:16:04 to be like a separate research thing,
    1:16:06 but they didn’t want to spin it off.
    1:16:07 They wanted to retain control of it.
    1:16:10 And so they were creating basically a shadow,
    1:16:11 a shadow stock option program.
    1:16:12 And I was just like, I don’t understand this.
    1:16:14 This sounds like a scam.
    1:16:14 So I turned that down
    1:16:16 and then I went to this little software company called EIT.
    1:16:18 So yeah, so I literally got a job.
    1:16:21 And yeah, and then moved out to California
    1:16:22 in basically January ’94.
    1:16:24 Yeah, so basically I went to work for,
    1:16:26 you know, there’s this little software company called EIT
    1:16:27 and they were sort of a,
    1:16:29 they were a little basic contract research organization,
    1:16:31 very smart, like CS people in Palo Alto,
    1:16:33 doing like work for the government,
    1:16:35 for companies, you know, kind of very leading edge stuff.
    1:16:37 And then they just had, you know, to their credit,
    1:16:39 they were on the internet idea early.
    1:16:42 And so, you know, they wanted to kind of create,
    1:16:43 see if they could create like internet software products,
    1:16:45 which was a very kind of new idea at the time.
    1:16:47 And so, you know, they made me an offer
    1:16:49 and they flew me out and I moved out and it was great.
    1:16:50 And I went to work there.
    1:16:52 And, you know, I was like, okay, you know,
    1:16:53 I’ll work on some internet,
    1:16:55 it gives you a way to make money on internet software.
    1:16:57 And then, you know, what happened was just,
    1:16:59 I just kept having this kind of out-of-body experience though,
    1:17:01 which was just like, and then at that point,
    1:17:04 the internet started to get like serious media coverage.
    1:17:06 And, you know, if you remember those days,
    1:17:08 the books started to show up.
    1:17:10 And so, you know, before people had the internet,
    1:17:13 what happened was there were books about the internet.
    1:17:16 And this is where the O’Reilly Publishing Company
    1:17:17 became famous at the time and so forth,
    1:17:20 is you’d have, actually at the peak of this in ’94, ’95,
    1:17:23 you’d have walls and walls of books about the internet
    1:17:25 in bookstores and they’d be like guides to the internet,
    1:17:26 how to use the internet,
    1:17:27 how to write web pages, how to do all these things.
    1:17:29 And then there would often be like a floppy disk
    1:17:30 in the back of the book
    1:17:32 which would have the software, you know,
    1:17:33 get the TCP/IP stack.
    1:17:37 – That your TCP/IP stack for Windows all that, yeah, yeah.
    1:17:38 – Yeah, and then they’d have Mosaic
    1:17:40 or they’d have, you know, whatever on the disk.
    1:17:42 And so, you know, this started to become a thing
    1:17:43 and people started to figure this out
    1:17:45 and the press started to take it seriously
    1:17:47 and there started to be more interesting content.
    1:17:48 And so it’s like, okay, the thing is going
    1:17:50 and I’m like, you know, I kind of like,
    1:17:52 I left Mosaic behind and so I, you know,
    1:17:53 I didn’t have the, you know,
    1:17:54 the email addresses anymore and so forth
    1:17:56 but I knew how much commercial demand there was.
    1:18:00 And so, it was just like really schizophrenic thing.
    1:18:01 It was just like very unclear.
    1:18:03 And again, like I said, I had never heard of venture capital
    1:18:05 so I didn’t really have a sense that you could start a company.
    1:18:06 I didn’t really know what to do.
    1:18:08 And then, you know, another great kind of stroke of luck
    1:18:10 in my life was I got a call from Jim Clark
    1:18:13 who’s the, you know, co-founder of our company Netscape,
    1:18:15 you know, who was this legendary figure.
    1:18:17 And I won’t do the full version of all this
    1:18:18 because this gets into stuff that has already been,
    1:18:20 people have talked about it a lot in the past.
    1:18:21 He’s already plenty well documented.
    1:18:23 But, you know, he had been a co-founder
    1:18:25 of the founder of this company, Silicon Graphics,
    1:18:28 which was one of the leading tech companies of the era.
    1:18:29 And then he got sideways with the CEO there.
    1:18:31 He decided to leave and start his second company
    1:18:33 but he had a non solicit agreement with, you know,
    1:18:35 all the great people that he had, you know,
    1:18:37 he couldn’t hire the people at SGI.
    1:18:40 – Yeah, SGI was an amazing team that he had put together.
    1:18:41 – Amazing team, but he had a formal, you know,
    1:18:43 he had a formal agreement that he couldn’t hire them.
    1:18:46 So, and he had stock SGI with every smart person he knew.
    1:18:47 So he, you know, most of the people
    1:18:49 who he wanted to work with were, he couldn’t get.
    1:18:51 And so he basically was like,
    1:18:53 he was literally like sniffing around for talent
    1:18:55 and a guy who worked for him, Bill Foss,
    1:18:57 who later joined Netscape.
    1:18:59 Apparently, I mentioned to Jim one day is like, you know,
    1:19:01 one of the guys who made this mosaic browser is like,
    1:19:03 apparently he just like moved to Silicon Valley.
    1:19:06 And he likes, you know, the about page that the browser says,
    1:19:09 he’s available, you know, maybe you should go talk to him.
    1:19:12 And so Jim called me up and we had breakfast
    1:19:14 and which was a very traumatic experience for me
    1:19:17 because I was not eating breakfast in those days
    1:19:19 because I was not getting up early enough to have breakfast.
    1:19:21 – Yeah, yeah, I remember those.
    1:19:23 He used to wake up much later.
    1:19:24 – Yeah, I was like programmer hours.
    1:19:26 And so I had to be up at seven in the morning
    1:19:28 to meet Jim for breakfast at El Farnayo
    1:19:30 in Palo Alto at seven a.m. on Sunday.
    1:19:32 So I had to recalibrate my entire sleeping schedule
    1:19:34 that week to try to make the meeting.
    1:19:36 And I was still blurry when I got there,
    1:19:37 but they had good coffee.
    1:19:39 And so anyway, so Jim and I, you know, again,
    1:19:42 without belaboring it, Jim and I decided to start a company,
    1:19:44 but it was still this weird thing where,
    1:19:46 and Jim knew all about the internet, the browser,
    1:19:47 and, you know, I was still watching everything,
    1:19:48 but it was still this thing of like,
    1:19:50 it’s just not, it’s not a,
    1:19:52 it’s just the overwhelming assumption in the industry was,
    1:19:53 this is not a serious thing.
    1:19:54 This is not a real thing.
    1:19:56 This is a momentary thing.
    1:19:57 It’s going to go away.
    1:19:58 The big companies are going to take over.
    1:20:00 This is not going to be a,
    1:20:01 the internet’s not going to be a commercial medium.
    1:20:02 It’s not going to happen.
    1:20:06 And so our first two business plans for our company
    1:20:07 actually were not this.
    1:20:09 It was, we had a business plan.
    1:20:10 We had, our first business plan was to do
    1:20:13 interactive software for interactive television.
    1:20:15 So the, to build software to replace the guy
    1:20:17 on the roller skates that I told you about.
    1:20:18 Jim had, because Silicon,
    1:20:19 Jim’s company had been one of the main companies
    1:20:20 building those systems.
    1:20:22 And so he had the insight on that.
    1:20:24 And so we were going to do that,
    1:20:26 but then we sort of priced out like what, you know,
    1:20:29 we sort of modeled out sort of how interactive TV was going,
    1:20:30 what it was going to cost and how it was going to work.
    1:20:32 And we actually concluded it wasn’t going to work.
    1:20:34 It was, it was, it was, it was too expensive
    1:20:35 and the technology wasn’t ready.
    1:20:36 So we gave up on that idea.
    1:20:38 And then, and then plan number two was Jim had
    1:20:40 a really good relationship with the CEO of Nintendo,
    1:20:43 because SGI had done this deal to do
    1:20:45 the first 3D graphics chip for a game console,
    1:20:47 which is the Nintendo 64.
    1:20:51 And so he went to visit the guy in Japan who ran Nintendo.
    1:20:55 This is super genius guy, Yama Ushisan,
    1:20:58 who ran, basically built modern Nintendo,
    1:20:58 as we know it today.
    1:21:02 And basically struck a handshake deal to basically build,
    1:21:05 you know, the online service for the Nintendo gaming machines.
    1:21:07 And so to build basically what today you would call
    1:21:10 Xbox Live or the PlayStation Network,
    1:21:11 but to do that, you know.
    1:21:14 – That’s probably a little early for that idea.
    1:21:15 – Also too early.
    1:21:18 – Yeah, that was closer though.
    1:21:21 – It was closer, but like, again, it was modems, right?
    1:21:22 It would have been all dial-up.
    1:21:23 And so you would have,
    1:21:24 you would have been doing interactive gaming
    1:21:27 on dial-up modems with like 14, 14 kilobit modems
    1:21:28 and with low latency.
    1:21:31 And so it, and actually Nintendo actually had
    1:21:34 had an online service on their earlier devices in Japan.
    1:21:35 And they actually had an early online,
    1:21:36 Nintendo online or whatever they called it
    1:21:39 that had like, it had like early e-commerce
    1:21:40 and it was a proprietary system,
    1:21:41 but it had like early e-commerce
    1:21:43 and I think it had food delivery in the 80s.
    1:21:45 And so there was like an early version of this,
    1:21:46 but it didn’t quite take.
    1:21:48 And so this idea was to do the modern version of it.
    1:21:50 But we, again, we modeled the whole thing out.
    1:21:51 I like built all the spreadsheets
    1:21:53 and all the modem banks you would need and all this stuff.
    1:21:57 And we just, we figured out that it couldn’t quite work.
    1:21:59 And so literally we took a walk
    1:22:00 and it was like, it was like, it was like a discouraging thing
    1:22:03 ’cause it’s like we had these two ideas they didn’t pan out.
    1:22:04 And it’s like, you know, should we like, you know,
    1:22:06 should we still, is there still anything to do together?
    1:22:08 And, you know, and I remember saying on the walk,
    1:22:10 I was like, you know, well, this internet thing
    1:22:12 keeps going, right?
    1:22:14 Like it’s going.
    1:22:16 And think about what we had just experienced there
    1:22:18 between Jim and I, which was like, okay,
    1:22:21 what basically what the press was telling everybody
    1:22:22 and all the experts were telling us was,
    1:22:24 it was either gonna be the big companies
    1:22:25 were gonna do interactive television
    1:22:27 or it was gonna be these, you know, home,
    1:22:28 you know, sort of video game like service.
    1:22:30 It was gonna be, the assumption was it was gonna be
    1:22:33 one of those, but those were gonna replace the internet
    1:22:34 when this stuff got serious for consumers.
    1:22:37 And then, and we basically concluded that the,
    1:22:38 when daddy comes home,
    1:22:41 you little kids can go play in your room.
    1:22:42 – Oh yeah.
    1:22:44 Yeah, if you read, if you look at the magazines
    1:22:45 and I keep bringing up the magazines
    1:22:46 ’cause at the time, again,
    1:22:47 this is like the internet’s getting started.
    1:22:49 And so the way people got their news
    1:22:51 was literally reading one of the three big news magazines
    1:22:52 or reading one of the three big newspapers.
    1:22:53 Like that’s how you learned about things.
    1:22:55 And that’s where all the experts showed up.
    1:22:57 And if you just go back and look at the magazine covers
    1:22:59 from that era, it’s basically all these big company CEOs
    1:23:01 just pouring scorn on the internet
    1:23:03 and declaring that it’s a joke and a toy.
    1:23:04 And the thing that they’re gonna come out with
    1:23:06 their proprietary thing is gonna be so much better.
    1:23:11 And so we literally had this moment where it was just like,
    1:23:13 well, if we have proven to ourselves
    1:23:15 that interactive TV is not gonna work,
    1:23:16 and if we’ve proven to ourselves
    1:23:18 that you can’t build this based on these video game boxes,
    1:23:20 then by process elimination,
    1:23:22 it kind of has to be the internet.
    1:23:24 It’s the only thing that works, right?
    1:23:26 And it’s like, and yes, it has every issue
    1:23:27 that people complain about.
    1:23:29 It’s slow, it’s inefficient, it’s insecure.
    1:23:30 There’s no business on it.
    1:23:32 There’s no this and that and the other.
    1:23:35 And it’s hard to get online and all this stuff.
    1:23:36 There’s all these reasons to believe it wasn’t gonna work,
    1:23:40 but we literally knocked out all the other ideas
    1:23:44 and said, okay, this thing, it has to be the thing.
    1:23:45 It’s the only thing that works.
    1:23:48 And Jim is a total whiz on these things
    1:23:49 and knew all about this stuff.
    1:23:50 And so we sat down and said,
    1:23:53 well, what if we did this incredible heretical idea?
    1:23:56 And he had very heretical as late as, this is April 94.
    1:23:59 So still very far into this, but still very heretical,
    1:24:02 which is like, how about we build a software company
    1:24:04 to make internet software?
    1:24:08 And that was just like, wow, that seems like a risky,
    1:24:09 crazy idea.
    1:24:11 Now in retrospect, it was like the most obvious idea
    1:24:13 of all time at that moment.
    1:24:15 But that’s the true story of how we actually got
    1:24:16 to that idea.
    1:24:20 So anyway, we ended up basically commercializing,
    1:24:21 we ended up basically building the commercial version
    1:24:23 of everything that we had built at Illinois.
    1:24:25 It just, we got through the hard way.
    1:24:27 It was not the obvious idea.
    1:24:30 – Counter-programming conventional wisdom
    1:24:34 and media advice is still works now.
    1:24:36 It’s amazing.
    1:24:37 – It’s incredible.
    1:24:38 I just, I have this constant,
    1:24:41 I live in this constant state of out-of-body,
    1:24:43 kind of experience amazement where these people
    1:24:45 just show up on TV or in the papers or whatever.
    1:24:47 And they’re just, they have all these credentials
    1:24:48 and they’ve got all these degrees.
    1:24:50 They’ve got all these initials after their names
    1:24:51 and they’ve got these incredible resumes
    1:24:53 and they’ve got all these publication credits.
    1:24:55 And they’ve got all this stuff and these government grants
    1:24:57 and like on like every possible credential
    1:24:59 and Harvard at MIT and like all this stuff.
    1:25:01 And they just, they say shit.
    1:25:06 And I just, I’m, and I’m just like, like, okay.
    1:25:09 Like maybe they’re right, but like if they’re wrong
    1:25:11 and they’re wrong like a lot of the time, like, okay.
    1:25:13 What consequences do they bear for being wrong?
    1:25:15 And the answer is none at all.
    1:25:16 – Zero, yeah.
    1:25:18 And they’re just back on tomorrow.
    1:25:20 – On tomorrow with some new line of bullshit.
    1:25:22 And, and they, there’s this great book.
    1:25:23 I often tell friends, it’s this great book.
    1:25:25 This guy Phil Tetlock who’s a professor
    1:25:27 who studies this exact topic.
    1:25:28 And it’s this great book called,
    1:25:29 it’s called expert political judgment.
    1:25:31 And he did this comprehensive study of the,
    1:25:33 he came at it through political predictions.
    1:25:36 So basically, you know, experts showing up in, you know,
    1:25:38 columns in the newspaper and on TV talking about like,
    1:25:39 is there going to be, you know, war here, you know,
    1:25:41 what’s going to happen with Israel or whatever,
    1:25:42 all these predictions.
    1:25:43 And he, he goes through and he basically,
    1:25:46 he basically, the conclusion of it is the, the sort of
    1:25:49 average, well-credential expert in the media on any topic
    1:25:50 evolving sort of politics or global affairs
    1:25:54 is somewhat less, is somewhat less than random,
    1:25:55 likely to be correct.
    1:25:58 So, so, so the, right, the credentialed experts
    1:26:00 to score it like 40% and a monkey flinging,
    1:26:03 you know, shit at a dartboard is like 50%.
    1:26:03 Right?
    1:26:06 And the big thing that he points out is there,
    1:26:09 there’s no, there are no repercussions for being wrong.
    1:26:12 There are no, there’s no career damage.
    1:26:13 There’s no economic damage.
    1:26:14 There’s no nothing.
    1:26:15 And then he says the thing, if they were,
    1:26:16 if they were being, if they were being epistemically
    1:26:18 honest, the thing that they would do is like when,
    1:26:20 when the talking heads on TV talking about something,
    1:26:22 there would be a scoreboard and it would show like
    1:26:23 their last 20 predictions and then it would have like,
    1:26:26 you know, red or green, were they right or wrong?
    1:26:27 It’s ’cause it’d be the only way to ever have a sense
    1:26:29 of whether you’re talking to somebody who knows
    1:26:30 what they’re talking about.
    1:26:32 And that scoreboard, of course, never appears.
    1:26:34 – Never materialized, yeah.
    1:26:37 – You never, ever, ever, ever see it.
    1:26:39 And he pointed, he wrote this book like 20 years ago
    1:26:40 and like everybody read it and they’re like,
    1:26:41 yeah, that’s right.
    1:26:42 And then everybody just completely ignored it
    1:26:44 and kept doing things the same way that they’re doing it.
    1:26:47 And so I just, I had this like, I had this experience
    1:26:49 where I just feel, I just feel like a complete,
    1:26:51 like, I, I mean, you know, it worked out,
    1:26:54 but like I, I still feel dumb is in the sense of like,
    1:26:56 I read all this stuff, I believed it all at the time.
    1:26:58 It caused me to be insecure about the thing
    1:27:01 that I was actually doing, that I saw was actually working.
    1:27:04 I knew it was working like, and I knew why it was working
    1:27:06 and I knew why it would keep working.
    1:27:08 And even still it was just this wall of, wall of doubt
    1:27:10 and skepticism that kind of kept, kept, kept eating away
    1:27:11 at me.
    1:27:12 So yes.
    1:27:14 – The good news is we’ve used that to our advantage,
    1:27:16 you know, many times since then.
    1:27:20 I remember when, when we made the Coinbase investment,
    1:27:24 I guess Bitcoin, which was the, the, the one cryptocurrency
    1:27:28 at the time was, I don’t know, was some number
    1:27:32 of hundreds of dollars and everybody, economists,
    1:27:34 everybody was writing that it was a complete scam
    1:27:37 and total bullshit and never be worth anything.
    1:27:40 And here it is, I don’t know what it’s worth today,
    1:27:43 like $63, $64,000, something like that.
    1:27:46 And all you had to do is just listen to the experts
    1:27:49 and do the opposite and you make so much money.
    1:27:50 – Yeah, it’s amazing.
    1:27:52 Yep, it’s amazing, but I tell you, it’s hard.
    1:27:54 Like, I, you know, I don’t know about you, like,
    1:27:55 I feel like I still have this problem.
    1:27:58 Like I, I, I now have like 30 years of evidence
    1:28:00 that this, this is all the case and, and, and even still,
    1:28:02 it’s just like, I still have this problem where I’m like,
    1:28:05 okay, the experts say it’s still like a real effort of will.
    1:28:09 You know, it’s basically, they don’t actually know
    1:28:09 what they’re talking about.
    1:28:11 They don’t actually have any predictive capability.
    1:28:13 They’re, they’re in a system where the incentives
    1:28:14 are absolutely terrible.
    1:28:17 – Well, I always find like, if somebody’s super dismissive
    1:28:20 about something, that’s a great thing to study.
    1:28:25 Cause it’s almost surely not a dead zero, right?
    1:28:28 Like it may not work, but there’s no way it’s as bad
    1:28:31 as they’re, you know, saying it, if somebody says something
    1:28:36 is like a scam or a Ponzi scheme or a bullshit or this,
    1:28:40 then that’s almost always worth looking into.
    1:28:42 So you started Netscape with Jim Clark.
    1:28:44 It was actually called Mosaic, right?
    1:28:45 At the time.
    1:28:46 – Mosaic, Mosaic.
    1:28:49 Yeah, so, so we, so we, you know, again, I had graduated.
    1:28:52 We, you know, the other people, you know, the other,
    1:28:53 our other colleagues at Illinois were, you know,
    1:28:54 working either, they were either students
    1:28:56 or staff members there.
    1:28:58 Everybody was working under federal research funding
    1:29:00 on a specifically non-commercial project, you know,
    1:29:03 which was open source, you know, there’s, and so,
    1:29:04 and you know, like I said, there was no, you know,
    1:29:06 there was no, the university didn’t have,
    1:29:08 there was no commercial anything, you know, of value,
    1:29:10 at least according to what everybody thought at the time.
    1:29:13 And so we, we start Netscape, we, we actually go out,
    1:29:15 Jim and I actually flew back out to Urbana in the middle,
    1:29:18 and it was still an incredible snowstorm
    1:29:21 and hired, you know, I think basically all but one,
    1:29:23 I think of the original Mosaic team members
    1:29:24 to join us in Netscape.
    1:29:25 So that was the original, the original thing.
    1:29:27 Most of them were able to move out to California
    1:29:30 and were core members of, of what followed at Netscape.
    1:29:31 And so, and then we booted up the company.
    1:29:33 We, and then we, we named it Mosaic.
    1:29:35 And, and that was sort of the first issue
    1:29:36 that got us in trouble.
    1:29:38 And the reason we named it Mosaic was not because we planned
    1:29:40 to literally like offer Mosaic as a product.
    1:29:43 We, we very specifically decided we were going to leave
    1:29:44 the source code behind.
    1:29:47 – Hey, you, you wrote it like when you were skipping class.
    1:29:48 – Really?
    1:29:49 – Yes.
    1:29:51 We knew it was not a commercial,
    1:29:52 we knew it was not commercial grade.
    1:29:55 We knew it had all, you know, just had, it had just issues.
    1:29:56 It had issue performance issues.
    1:29:58 It had, you know, you just, you create one of these things,
    1:29:59 you know all the issues.
    1:30:01 And so we, we just knew it had all these issues.
    1:30:02 And so we knew we needed to start from,
    1:30:04 we wanted to start from scratch and build kind of the correct
    1:30:05 commercial product.
    1:30:08 And we, and we, and we knew what we needed to do to do that.
    1:30:10 And so we, we, we very specifically did not bring
    1:30:12 the source code with us, but you know, all the, all the
    1:30:14 stand HTML and HTTP and all these standards were open,
    1:30:16 open standards and they were all free to, you know,
    1:30:17 people on the internet were able to use them
    1:30:18 and do whatever they wanted.
    1:30:20 So, so we’re like, okay, we, we have no like,
    1:30:22 we have no copyright issues here, but you know,
    1:30:23 we’re not taking the code.
    1:30:25 And then on the, on the trademark side, you know,
    1:30:28 we, we, there, there’s a long history and Silicon Valley
    1:30:30 of companies that are sort of named after the projects
    1:30:32 that spawn them, often out of a university setting
    1:30:33 or some other setting.
    1:30:35 And so there were two, two famous examples,
    1:30:37 Sun Micro, Sun Microsystems at the time,
    1:30:40 which was a, you know, a huge, a huge successful company.
    1:30:43 The name Sun actually came from the project at Stanford,
    1:30:45 which was Stanford University Network, S-U-N.
    1:30:47 And so that was like that, the name of that company was
    1:30:48 like an homage to the Stanford environments
    1:30:49 that those guys came out of.
    1:30:51 And then Oracle was the code name of a project
    1:30:53 that Larry Ellison had done for the government
    1:30:54 in the 1970s, right?
    1:30:57 And so there was this like, what I thought at the time
    1:30:58 was like a time-honored tradition of like,
    1:31:01 you can basically use the name as an homage and, you know,
    1:31:03 Illinois does, they don’t have a commercial, you know,
    1:31:04 interest in this and so what we’ll just do it.
    1:31:07 But in retrospect, that was sort of the crack.
    1:31:09 You know, we sort of introduced a crack in the armor
    1:31:10 from the very beginning by doing that.
    1:31:13 And then basically what happened was as, as, as I was leaving
    1:31:17 moving to California, the other people at Illinois
    1:31:18 started to figure out that there was actually, you know,
    1:31:20 they got access to the commercial mailbox
    1:31:23 that had all the commercial inbound licensing requests.
    1:31:24 And so they started to get a sense
    1:31:25 that there might be money in it.
    1:31:28 And so the founders of this, that company,
    1:31:31 Spyglass I mentioned, which was like the one software company
    1:31:33 in Champaign Urbana actually approached,
    1:31:35 without me having any awareness of this,
    1:31:37 they approached the University of Illinois Administration
    1:31:39 and they basically struck a deal to license the Mosaic,
    1:31:42 our code to license the Mosaic software code
    1:31:44 that we had written for commercial sales.
    1:31:47 And they, they started offering a commercial product
    1:31:50 called Spyglass Mosaic, you know, and totally within rights
    1:31:53 of the University to do this and within Spyglass to do this
    1:31:55 and that deal was great and off they went.
    1:31:57 But, but then we, we then announced Netscape.
    1:31:59 And of course we were the team that had written
    1:32:01 all that code and then this started to become, you know,
    1:32:03 by now the press has started to take it seriously.
    1:32:04 So we started to become, you know, famous and well-known
    1:32:06 and Clark was this legend.
    1:32:08 And so we started to get all this press coverage.
    1:32:09 And so Spyglass started to get really worried
    1:32:11 that we were going to, you know, snuff them, you know,
    1:32:12 and we were going to lap them with the products.
    1:32:16 And so Spyglass enlisted the administration
    1:32:19 of the University of Illinois to basically try to kill us.
    1:32:25 And the form of, the form of the murder attempt was to,
    1:32:28 they didn’t receive, they didn’t sue us.
    1:32:29 And they didn’t sue us because they didn’t have a good claim
    1:32:31 because like we weren’t actually violating copyright
    1:32:34 and you know, the trademark, you could just change the name.
    1:32:36 So they didn’t actually have like a good legal case to sue us.
    1:32:38 And so instead of suing us, what they did instead
    1:32:41 was they called Spyglass any situation we were in
    1:32:43 where we were competing with Spyglass for a sale,
    1:32:45 they, the University of Illinois administrators
    1:32:46 would call the customer and tell them
    1:32:48 that they were going to sue us.
    1:32:49 – Good Lord.
    1:32:51 – That’s a thing to do to a startup.
    1:32:54 That’s like the dirtiest thing you can do to a startup.
    1:32:56 – It’s like a super nefarious, you know,
    1:32:58 and you know, cause like who wants to, you know,
    1:33:01 any big company doesn’t, you know, is already kind of,
    1:33:02 you know, worried about doing business
    1:33:03 with the startup to start with.
    1:33:04 And if the startups literally about to get sued,
    1:33:06 like why, why take the risk?
    1:33:09 And so our whole sales pipeline froze up and you know,
    1:33:10 we’re running on, you know, we’re running a venture capital
    1:33:12 and like, you know, money’s getting, you know,
    1:33:13 and so like we don’t have that, you know,
    1:33:15 so not, you know, VC wasn’t in those days,
    1:33:17 what it is today, we didn’t have that long of a runway.
    1:33:18 And so we needed revenue.
    1:33:21 And, and so this, this became a big problem.
    1:33:22 And so we, we kind of got everybody together
    1:33:23 and talked about it.
    1:33:24 And so we, we then decide,
    1:33:25 and I’m very proud of this decision.
    1:33:29 We preemptively sued the University of Illinois on this case.
    1:33:31 And we sued them for, you know,
    1:33:32 certain interference of trade.
    1:33:34 There’s these, there’s these sort of laws
    1:33:35 that are not great laws to sue on,
    1:33:36 but they worked in this case,
    1:33:38 which is this thing called torturous interference.
    1:33:39 You can kind of, you can, in theory,
    1:33:42 it’s illegal to like just gratuitously interfere
    1:33:43 in somebody else’s business,
    1:33:45 try to unhook other people’s contracts.
    1:33:48 It’s, it’s not great law that doesn’t often get enforced,
    1:33:49 but like at least it is on the books.
    1:33:50 And so we sued Illinois.
    1:33:53 They, furious negotiation followed.
    1:33:56 We offered them at the time $4 million worth of stock
    1:33:59 in the company when the company was worth,
    1:34:00 I don’t know, 20 million or something.
    1:34:04 – And most of you youngsters eventually sold for 10 billion.
    1:34:07 So you can do that matter.
    1:34:08 – Yeah. So it was, yeah, it was a billion,
    1:34:09 you know, it was a billion plus or, you know,
    1:34:11 some depending on exactly what, but, you know,
    1:34:13 but it would have been, it would have been a lot of money.
    1:34:16 And they turned that down and instead they demanded cash.
    1:34:16 And so-
    1:34:18 – One thing you didn’t have.
    1:34:19 – We didn’t, we didn’t have.
    1:34:20 Although, you know, we, we, at that point,
    1:34:21 it was starting to work.
    1:34:22 And so we raised money from Kleiner Perkins
    1:34:24 and we had other investor interests.
    1:34:26 And so we, we, and we had sales, you know, starting to come in.
    1:34:28 And so we, we, we, we, we paid them the cash
    1:34:31 and did the settlement and got them off our backs.
    1:34:34 Yeah, that decision on their part,
    1:34:35 yeah, it costs them at least a billion dollars
    1:34:38 in direct stock, plus all the downstream philanthropy
    1:34:41 from me, plus, plus all the downstream philanthropy
    1:34:43 from Jim Clark, plus all the other founding engineers.
    1:34:47 – They lost a few buildings, I would thank you.
    1:34:48 – They lost, I think, a campus.
    1:34:49 – Yeah.
    1:34:51 – You know, I, I, I’m just going to speculate.
    1:34:53 They lost probably $3 billion in, you know,
    1:34:55 1990s dollars with that decision.
    1:34:58 Now, again, this is why I gave the disclaimer up front.
    1:35:00 Like, you know, look, like the alternate universe,
    1:35:02 Mark, with a different skill set would have,
    1:35:04 you would have had a very different way of dealing with us.
    1:35:05 – Yeah.
    1:35:08 – But like Mark, as he actually existed on earth one,
    1:35:10 like, I never met the University of Illinois administrators.
    1:35:11 Like, I didn’t, you know,
    1:35:12 I didn’t know the president of the university.
    1:35:13 – Yeah.
    1:35:15 – I’m like a random undergrad, right?
    1:35:17 And so like, I didn’t know the president of the university.
    1:35:19 I, you know, I could have called him, you know.
    1:35:21 – Yeah, that’s true, that’s true.
    1:35:22 Although it’s still like, you know,
    1:35:25 the calculus that they made, but it’s a bureaucracy
    1:35:30 to, to harass their own students and side with like,
    1:35:32 somebody who wrote him a check is,
    1:35:36 is still a little on the evil side, I would say.
    1:35:39 – Yeah, I thought it was really bad.
    1:35:40 I get really upset.
    1:35:42 I was really upset for a long time.
    1:35:44 To be totally honest, I’m still upset.
    1:35:46 Every, every subsequent administration,
    1:35:49 every subsequent new administration at the university
    1:35:51 has attempted to reach out and repair the bridge.
    1:35:52 I have not returned the calls.
    1:35:55 – Yeah, no, you’re a grudge holder.
    1:35:58 You and my biggest grudge holders, I know.
    1:36:00 – I greatly value my grudges, they’re very important to me.
    1:36:03 So, yeah, so, yeah.
    1:36:05 And, you know, the broader point, Ben,
    1:36:06 that you brought up is really key,
    1:36:08 which is like, look, there are a small number
    1:36:10 of universities in the world that,
    1:36:11 and you’d put certainly Stanford in this category
    1:36:13 and MIT and a bunch of others,
    1:36:14 but, you know, there’s a certain number of them
    1:36:16 that really understand, and this is maybe Stanford’s
    1:36:18 great genius over the last 50 years.
    1:36:20 As an institution is, you kind of understand
    1:36:21 that it’s actually really good.
    1:36:23 If this kind of thing happens, like if your students
    1:36:25 or even your faculty, you know, go off and do something new
    1:36:26 and are successful in business.
    1:36:29 And then the, you know, the money that you’ll get,
    1:36:30 the money that you’ll get back in philanthropy
    1:36:32 is going to be orders of magnitude higher
    1:36:34 than whatever technology licensing fee you could extract
    1:36:37 or whatever threat you could extract people, you know,
    1:36:39 money you could extract people out of or whatever.
    1:36:41 – Well, it goes back to the original mosaic story, you know,
    1:36:44 like it seems like you’re giving a lot up by being open,
    1:36:47 but, you know, you’re actually opening the whole world to you.
    1:36:50 It’s actually a great metaphor for life,
    1:36:53 which is, you know, if you’ve lived in abundance,
    1:36:54 you will get abundance.
    1:36:57 And if you live in scarcity, you’ll screw yourself.
    1:37:00 And I think good that those universities are abundant
    1:37:03 and it’s good that you are abundant with the internet.
    1:37:06 And that’s how we live in the world we are in today.
    1:37:09 So what an amazing.
    1:37:11 Yeah, I often think about the alternate universe.
    1:37:16 If, you know, if you don’t write mosaic,
    1:37:19 if it doesn’t work, if you don’t start Netscape,
    1:37:22 like it does seem like we would have had an elect.
    1:37:25 Most systems or many systems are proprietary, right?
    1:37:28 Like the smartphones are, you know, everybody pays a tax
    1:37:31 to download their app from the app store
    1:37:33 ’cause Apple alone said it’s not open.
    1:37:36 And, you know, Google is an extremely powerful company
    1:37:38 because, you know, if you want to search something,
    1:37:40 that’s where you have to go and so forth.
    1:37:45 And these, you know, it was just such an amazing anomaly
    1:37:48 in the industry that the internet happened
    1:37:49 and that anybody could join
    1:37:50 and anybody could put up a website
    1:37:52 and anybody could build a great business.
    1:37:53 And, you know, in fact, including Google,
    1:37:56 including, you know, some of the big tech today
    1:37:59 was all created because of the openness of the internet.
    1:38:01 So, thank you for that.
    1:38:03 And thank you for the conversation.
    1:38:04 What a good start.
    1:38:04 – Oh, I’m not done yet.
    1:38:07 – Oh, we got one more, nevermind.
    1:38:07 Pause.
    1:38:09 – I got more, I got to bring it, I got to bring it,
    1:38:10 I got a great climax to the whole thing.
    1:38:12 – Okay, okay.
    1:38:13 Climates.
    1:38:15 – So let me just start with, you know,
    1:38:16 Ben, I’m glad you just went through what you just went
    1:38:18 through, I totally agree.
    1:38:20 And specifically look like this has a lot to do
    1:38:22 with the debate raging around AI right now,
    1:38:24 which is, you know, these big companies,
    1:38:25 you know, the big companies in those days
    1:38:27 had every reason, you know, they had all these stories.
    1:38:28 By the way, a lot of the story,
    1:38:30 the big companies told about the internet early on
    1:38:31 was it’s unsafe.
    1:38:32 – Unsafe.
    1:38:32 And it was.
    1:38:35 And it wasn’t true to that.
    1:38:37 It was, you know, but it was literally going to be,
    1:38:38 I mean, there was an, it took a long time
    1:38:40 for e-commerce to take off in retrospect,
    1:38:41 relative to how fast it could have taken off,
    1:38:42 ’cause people literally just were worried
    1:38:44 that their credit card was going to get stolen.
    1:38:46 Like you had to get over that hump.
    1:38:48 And there was just this constant fear of like cybercrime
    1:38:50 and this and that and then spam and like abuse
    1:38:51 and like all these things.
    1:38:53 And so, and so the big companies always had like
    1:38:56 all these reasons why they needed to have total control.
    1:38:57 And, you know, the government needed to protect them
    1:38:59 and they needed to have all these regulations
    1:39:00 and they needed to have, you know,
    1:39:02 that it just, the world needed to be a world
    1:39:03 not of open systems like the internet,
    1:39:05 it needed to be a world of proprietary systems.
    1:39:07 And look, a lot of the way the world works today
    1:39:08 is for proprietary systems.
    1:39:11 You know, the banking system is not open, right?
    1:39:13 You know, you’re just, if the bank decides to debank you,
    1:39:15 they debank you or whatever it is.
    1:39:16 Or if they don’t want to let the money go through,
    1:39:17 they don’t let the money go through.
    1:39:20 And so, you know, most of the world,
    1:39:21 most of the economy is with these big companies
    1:39:22 with total control.
    1:39:25 And so, yeah, I think it’s, I wanted to go through that
    1:39:27 ’cause I think it’s a major miracle
    1:39:29 when you’re able to actually get one of these open systems
    1:39:31 to work and it’s like, and then years later,
    1:39:32 you’re just like, oh my God, I can’t believe
    1:39:34 we almost have the much worse world
    1:39:36 where the big companies ran everything,
    1:39:38 but it is amazing how the pattern keeps repeating
    1:39:42 and it’s specifically repeating again today with AI.
    1:39:44 Again, ironically, and to your point,
    1:39:46 ironically, some of the companies that are lobbying hardest
    1:39:48 for regulatory capture and cartel, you know,
    1:39:50 kind of government cartel status for AI
    1:39:52 are companies that exist today
    1:39:53 because the internet was open.
    1:39:56 And so, they are engaged in a particularly
    1:39:59 advanced form of hypocrisy and mental gymnastics.
    1:40:01 – I think the founders are gone.
    1:40:05 So, been taken over by the other people.
    1:40:08 – The other people, although I still blame the founders.
    1:40:10 Anyway, so, okay, so the climax of the story,
    1:40:11 ’cause I just can’t resist ’cause I just think
    1:40:13 this is so amazing given what happened, what followed.
    1:40:16 So, okay, so then we settled with Illinois,
    1:40:17 we get underway, we’re shipping our products,
    1:40:19 we’re starting to get revenue, we’re starting to work.
    1:40:21 This is around, I think, you know, the time you joined us
    1:40:22 kind of during this period.
    1:40:25 And so, but we’re competing.
    1:40:26 We’re competing with, you know,
    1:40:27 there’s a bunch of other companies that are starting,
    1:40:29 you know, people figured out that this was actually a,
    1:40:30 the internet was gonna be a thing.
    1:40:32 And so, a bunch of other software companies
    1:40:33 got funded and started.
    1:40:35 And then, this company, Spyglass, was still out there.
    1:40:38 And Spyglass was selling, they were selling,
    1:40:40 Spyglass was like, they were selling our own code against us.
    1:40:41 – Yeah.
    1:40:42 – Right?
    1:40:44 – It’s a little maddening.
    1:40:45 – Yeah, it’s a little frustrating.
    1:40:47 But, you know, again, they have the legal right to do it,
    1:40:48 but like, it’s a little frustrating.
    1:40:49 And, you know, it’s fine.
    1:40:51 And we’re, you know, we’re competing with them whatever,
    1:40:52 but it’s a little bit fine.
    1:40:54 You know, there’s like price war going on and, you know,
    1:40:56 we’ll, you know, the sort of back and forth going on.
    1:40:59 And then Spyglass gets this call from Microsoft
    1:41:01 and said, the Microsoft guys call Spyglass.
    1:41:04 And they’re like, yeah, we wanna license Spyglass Mosaic.
    1:41:05 So we can build it into Windows.
    1:41:08 And the Spyglass guys say, you know, yeah, that sounds great.
    1:41:09 You know, basically how much per, you know,
    1:41:12 how much per copy are you gonna, you know, pay us for that?
    1:41:14 And Microsoft says, you don’t understand,
    1:41:16 we’re gonna pay you a flat fee.
    1:41:17 You know, which is the same, you know,
    1:41:19 which is the same, you know,
    1:41:20 the same thing that Microsoft did when they originally
    1:41:22 licensed DOS way back when.
    1:41:24 And so, but Microsoft said, you know,
    1:41:25 basically, or at least my understanding
    1:41:28 of what Microsoft said was, you know, don’t worry about it.
    1:41:30 Like, you know, we’re gonna sell it as an add-on to Windows.
    1:41:32 And, you know, so we’ll have like Microsoft, you know,
    1:41:34 Mosaic and then you’ll still have Spyglass Mosaic
    1:41:36 and you can sell it on, you know,
    1:41:38 other operating systems or compete with us
    1:41:39 or whatever, do whatever you want.
    1:41:41 And so they, they struck the deal.
    1:41:43 I think it was like a million dollar one-time payment.
    1:41:45 And the Spyglass guys thought they had struck gold
    1:41:47 ’cause they had this like massive endorsement, you know,
    1:41:50 the big blow to us ’cause we didn’t get the Microsoft deal.
    1:41:51 And then they were gonna, you know, sort of, you know,
    1:41:53 the whole industry is gonna benefit from this
    1:41:54 and then they’re gonna go out and sell lots of other versions
    1:41:56 of Spyglass Mosaic.
    1:41:57 And then there was this,
    1:41:58 Microsoft had the press conference
    1:42:00 where they originally announced Internet Explorer,
    1:42:03 their browser, which was Spyglass Mosaic,
    1:42:05 again, our code, re-labeled.
    1:42:07 And there’s a famous, famous moment
    1:42:09 where the Microsoft guys are on stage
    1:42:12 and then they do the, you know, the one more thing part.
    1:42:14 And then, oh, by the way, we’re gonna make it free.
    1:42:15 And there’s a famous moment, you know,
    1:42:17 the Spyglass CEO with his head in his hands
    1:42:19 in the front row, you know, of the press conference,
    1:42:22 you know, realizing that his business had just ended.
    1:42:25 You just, you know, he sold out his entire business
    1:42:26 for a million dollars.
    1:42:28 So that was the end of Spyglass.
    1:42:31 So, you know, all’s well that ends well.
    1:42:32 – Yeah, happy ending.
    1:42:33 – Not that I’m competitive
    1:42:34 and not that I don’t hold grudges.
    1:42:36 – Well, that’s hilarious.
    1:42:38 Thank you all for listening to the Mark and Ben Show.
    1:42:40 We won’t tell the Netscape story,
    1:42:42 which is also a good story, but, you know,
    1:42:44 maybe if you reply in the comments, you wanna hear it.
    1:42:46 Well, we’ll consider that one too.
    1:42:48 But thank you again, and we enjoyed it.
    1:42:49 We hope you did too.

    “The Ben & Marc Show,” featuring a16z co-founders Marc Andreessen and Ben Horowitz. 

    In this special episode, Marc and Ben dive deep into the REAL story behind the creation of Netscape—a web browser co-created by Marc that revolutionized the internet and changed the world. As Ben notes at the top, until today, this story has never been fully told either in its entirety or accurately. 

    In this one-on-one conversation, Marc and Ben discuss Marc’s early life and how it shaped his journey into technology, the pivotal moments at the University of Illinois that led to the development of Mosaic (a renegade browser that Marc developed as an undergrad), and the fierce competition and legal battles that ensued as Netscape rose to prominence. 

    Ben and Marc also reflect on the broader implications of Netscape’s success, the importance of an open internet, and the lessons learned that still resonate in today’s tech landscape (especially with AI). That and much more. Enjoy!

    Watch the FULL Episode on YouTune: https://youtu.be/8aTjA_bGZO4

     

    Resources: 

    Marc on X: https://twitter.com/pmarca 

    Marc’s Substack: https://pmarca.substack.com/ 

    Ben on X: https://twitter.com/bhorowitz 

    Book mentioned on this episode: 

    – “Expert Political Judgment” by Philip E. Tetlock https://bit.ly/45KzP6M 

    TV Series mentioned on this episode: 

    – “The Mandalorian” (Disney+) https://bit.ly/3W0Zyoq

     

    Stay Updated: 

    Let us know what you think: https://ratethispodcast.com/a16z

    Find a16z on Twitter: https://twitter.com/a16z

    Find a16z on LinkedIn: https://www.linkedin.com/company/a16z

    Subscribe on your favorite podcast app: https://a16z.simplecast.com/

    Follow our host: https://twitter.com/stephsmithio

    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • The Art of Technology, The Technology of Art

    AI transcript
    0:00:03 Artists have been dealing with technological changes
    0:00:05 and expressing the visceral feelings
    0:00:08 of inhabiting new technological moments
    0:00:10 for a very long time.
    0:00:12 As a person who is looking at the history of artists
    0:00:15 designing for particular mediums,
    0:00:17 you could do stuff with mobile and social
    0:00:19 that you couldn’t do before.
    0:00:22 I think the notion that Pop Art proposed
    0:00:24 that your role as an artist is to describe
    0:00:26 how it feels to occupy that contemporary world.
    0:00:27 And you’re not an ethical agent.
    0:00:29 It’s just like, I go into the street
    0:00:30 and I see a giant billboard
    0:00:31 and it does something to my heart
    0:00:33 and that is culture.
    0:00:36 When they looked at NFTs for the first time,
    0:00:39 I think a lot of them saw outsider art.
    0:00:41 One of the interesting things about blockchain as a medium
    0:00:43 I think is that the cultural asset
    0:00:45 and the financial container is the same thing.
    0:00:49 Throughout history, art has helped us make sense
    0:00:53 of the most exciting and mystifying technology of the day.
    0:00:54 And simultaneously,
    0:00:56 technology has constantly rewritten
    0:00:58 how we express our creativity.
    0:01:00 Leonardo da Vinci, for example,
    0:01:03 was influenced by his new understanding of anatomy.
    0:01:05 Meanwhile, the industrial era
    0:01:08 was welcomed by images of foreign machines
    0:01:10 that would forever change society.
    0:01:13 And cameras, then browsers, then phones
    0:01:16 gave artists new canvases to create with.
    0:01:21 Over and over, art and technology have evolved hand in hand.
    0:01:23 And of course, today is no different.
    0:01:26 In fact, artists are not just creating work
    0:01:29 about the blockchain, but also on the blockchain
    0:01:33 with Web3 changing the way artists can monetize their work.
    0:01:35 This episode, originally published on our sister podcast,
    0:01:38 Web3 with A16Z, features Simon Denny,
    0:01:41 a global artist inspired by entrepreneurial culture
    0:01:43 whose cutting edge work exists where,
    0:01:46 once again, art and technology collide.
    0:01:49 Simon’s is done with longtime A16Z podcast toes,
    0:01:50 sonotoxy.
    0:01:52 So if you like this episode,
    0:01:56 be sure to check out more episodes of Web3 with A16Z.
    0:01:58 In the meantime, I hope you enjoy this episode
    0:02:02 that itself is at the intersection of art and technology.
    0:02:09 (upbeat music)
    0:02:12 – Welcome to Web3 with A6 and Z,
    0:02:14 a show about building the next air of the internet
    0:02:17 from the team at A6 and Z Crypto.
    0:02:20 We’re excited to be back with all new episodes.
    0:02:22 I’m Sonal, editor-in-chief at A6 and Z Crypto,
    0:02:25 and today’s episode is all about how technology
    0:02:29 has changed art and how artists change with technology
    0:02:31 from the emergence of the browser, the iPhone,
    0:02:36 and social media to generative art and blockchains to NFTs.
    0:02:38 We also discuss debates that seem to come up
    0:02:40 in every art and tech shift,
    0:02:43 including between inventing versus remixing,
    0:02:45 between commercialism and art,
    0:02:48 between mainstream canon and outsider art,
    0:02:50 whether we’re living in an artistic monoculture now
    0:02:52 and much, much more.
    0:02:54 Our special guest is Simon Denny,
    0:02:56 and we recorded this live in London
    0:02:58 a few days after we opened our London office,
    0:03:00 which is fitting since Denny is a global artist
    0:03:03 based in Berlin, but has shown his work
    0:03:06 in various countries, Biennales, museums, and galleries,
    0:03:09 including a metaverse landscape solo show
    0:03:12 called Read Right Own at Altman Siegel Gallery
    0:03:14 in San Francisco last year.
    0:03:16 As a reminder, none of the following
    0:03:19 is investment, business, legal, or tax advice.
    0:03:22 Please see asyncansy.com/disclosures
    0:03:23 for more important information,
    0:03:26 including a link to a list of our investments.
    0:03:28 The first half of our hallway style conversation
    0:03:31 tours through the evolution of art with technology,
    0:03:34 and the second half goes deeper into blockchains and art.
    0:03:37 But we began briefly with Denny’s tech journey
    0:03:40 and how he thinks of entrepreneurship as an aesthetic.
    0:03:43 Obviously this is a crypto show,
    0:03:45 and it’s also a technology show.
    0:03:47 Crypto is all about technology.
    0:03:48 One of the reasons I’m in this world
    0:03:50 is it’s a very multidisciplinary field.
    0:03:52 It brings together economics,
    0:03:54 it brings together philosophy,
    0:03:55 it brings the other networking,
    0:03:57 it brings together security, cryptography,
    0:03:59 like there’s so many layers to crypto.
    0:04:02 And I definitely want to focus in on the art aspect.
    0:04:04 Tell me a little bit more about your actual practice today too,
    0:04:06 and then we’ll go back to the evolution.
    0:04:09 At the moment today, I work across lots of different media
    0:04:10 in lots of different contexts.
    0:04:13 So I make both installations for museums and art galleries.
    0:04:18 I paint as well, but I also am very involved in crypto and crypto art.
    0:04:20 So I design NFT projects.
    0:04:22 But I guess maybe where I really specialize
    0:04:25 is I make things that join the museum world with the crypto world.
    0:04:27 So I’m interested in the history of art
    0:04:30 and artists who make for new technologies as they emerge
    0:04:32 to kind of explore what’s possible on them
    0:04:33 that wasn’t possible on other platforms.
    0:04:34 Exactly.
    0:04:37 But I personally got really interested in people,
    0:04:38 the people who were making the platforms,
    0:04:40 the people who were designing the systems.
    0:04:42 Because these were new systems, we were experiencing them,
    0:04:44 we were feeling different ways, doing different things on them.
    0:04:47 One of the first times I encountered entrepreneurial culture,
    0:04:50 for example, that just inspired me unendingly, right?
    0:04:52 Because it was so different than the attitude of my artist peers
    0:04:53 that I encountered.
    0:04:54 They were excited.
    0:04:56 They were bullish about the future.
    0:04:58 You know, in my world at the time,
    0:04:59 I think it’s actually different now,
    0:05:00 but at the time in my art world,
    0:05:04 it was very common to be incredibly critical in cynicism.
    0:05:05 Cynicism was the go-to.
    0:05:06 And I get that culture.
    0:05:07 I kind of love that culture.
    0:05:10 It’s sort of like indie rock or something like that, you know?
    0:05:12 But then I encountered all these incredible optimists.
    0:05:14 And I was like, “Wow, this is a force that I can’t understand.”
    0:05:15 -Culturally, you know? -Oh, that’s fascinating.
    0:05:18 I never thought about that you’re coming from a cynical,
    0:05:20 kind of default cynical art world,
    0:05:23 and then being like totally inspired by the optimism.
    0:05:25 Because I feel like those of us in Silicon Valley take that for granted.
    0:05:28 Yeah, I guess I’m really attracted to value systems,
    0:05:29 aesthetically, because I’m an artist,
    0:05:31 and I think visually and culturally,
    0:05:33 that I don’t know everything about,
    0:05:34 and I don’t completely understand, you know?
    0:05:36 So I started to go to technology conferences.
    0:05:39 And the first thing that I did is I went to a prominent conference
    0:05:41 in Munich called DLD.
    0:05:44 And I made an artwork about DLD in 2013,
    0:05:46 a one-year history of the conference a year later.
    0:05:50 I made a maze that people would walk through in this museum space,
    0:05:51 just down the road from the conference,
    0:05:55 where there was a graphic panel for every talk panel, basically.
    0:05:56 -Interesting. -So you would look at pool courts
    0:05:58 that I’d pulled out from the entire conference
    0:06:00 and encounter things that Jack Dorsey was saying,
    0:06:02 the things that the founder of Wikipedia was saying,
    0:06:03 Pavel Durov was saying,
    0:06:06 like interesting entrepreneurs that they were able to gather there,
    0:06:08 and the things they were saying about the world.
    0:06:10 -And it was kind of overwhelming. -Sounds really immersive too.
    0:06:12 It was super immersive, but very digital.
    0:06:14 I also leaned into the design interfaces that were contemporary at the time,
    0:06:17 which look really ancient now, which is really interesting too,
    0:06:19 because it was like iOS when it was skeuomorphism.
    0:06:22 So it was like all of these bookshelves as stages,
    0:06:23 as whatever, digital buttons.
    0:06:25 And that was the kind of graphic language I used.
    0:06:28 It was like cartoon font that looks very strange.
    0:06:30 But it gave this overall sense of this really vibrant community,
    0:06:32 which I hadn’t really encountered before as an artist.
    0:06:35 Again, the art world’s a little different in terms of culture.
    0:06:36 And that was one of the first times that I was like,
    0:06:37 “Wow, this is incredible.
    0:06:40 There are people here who are really optimistic,
    0:06:42 super excited about the future.
    0:06:43 Yes, they’re critical thinkers as well,
    0:06:45 but they really want to build something.”
    0:06:47 And that was the first time I encountered that culture.
    0:06:51 Tell me a little bit about how you actually came as an artist to the technology world.
    0:06:53 So, yeah, I grew up in New Zealand.
    0:06:56 I went to university at the University of Auckland to first study art.
    0:07:00 Like, that was the thing that I fell in love with as a painter when I was younger.
    0:07:03 New Zealand’s amazing, but it’s also very small and quite remote.
    0:07:06 And I learned about how big the kind of contemporary art world was,
    0:07:08 which made me want to go study in Germany.
    0:07:11 Germany is a really special country for contemporary art.
    0:07:16 Every little town has a major contemporary art museum, which is really unusual.
    0:07:17 In the post-war period,
    0:07:20 it’s been a really important place for lots of different artists internationally
    0:07:22 to kind of do museum shows early.
    0:07:23 There’s also an incredible education system there.
    0:07:26 So, I went to art school then in Frankfurt
    0:07:30 at this very special school called the Städelschule in the mid-2000s.
    0:07:35 And at that time, the director of the school was also the director of the Venice Biennale.
    0:07:38 And all the teachers that I was learning from there were these international artists
    0:07:40 that I saw in the cover of all the magazines that I was reading.
    0:07:44 So, it was a really exciting hub of international practice.
    0:07:47 And there I got super interested in the history of technology and art
    0:07:51 because I moved there in 2007, the year the iPhone came out.
    0:07:53 And, like, I moved with a laptop.
    0:07:56 Didn’t have an iPhone because it was a brand new, very expensive thing.
    0:08:00 But we were all just starting to use social media, like Web2, in a really interesting way.
    0:08:03 And of course, because I moved away from all my friends and family,
    0:08:05 that was one of the things that really kept me connected.
    0:08:08 Laptop I used for education, watching movies,
    0:08:11 but also keeping in touch with friends in a really intense way.
    0:08:13 And so, a bunch of artists that were studying at that time
    0:08:17 got really interested in this new wave of, like, technological stuff
    0:08:19 that was enabling a different type of engagement.
    0:08:21 And Berlin’s a, for those who don’t know Germany,
    0:08:24 it’s like Berlin’s, I guess, a place where a lot of contemporary artists live and work.
    0:08:26 And there were, like, this little hub of people
    0:08:28 that were really interested in the history of contemporary art,
    0:08:33 the history of art made for digital platforms, like WebArt from the 1990s,
    0:08:35 which is a very interesting specialist field.
    0:08:39 So, when browsers came about, when the World Wide Web started,
    0:08:42 when people started using Mosaic and Netscape,
    0:08:44 there were artists designing for that as a specific medium.
    0:08:48 Yes, I want to go back to how, when you were in art school,
    0:08:50 you and your cohort came across the iPhone for the first time.
    0:08:51 Oh my God.
    0:08:54 And you don’t necessarily immediately think it viscerally about the iPhone
    0:08:59 as, like, a creative medium, the way one thinks about caves for cave painting,
    0:09:02 or paper for drawing, or canvas for painting,
    0:09:07 or LED lights for certain kind of electronic art installations at mass scale,
    0:09:09 or whatever, neon.
    0:09:13 It’s funny that you mentioned that, because it’s like just sort of like this little tiny,
    0:09:14 like, it’s a device, it’s a computing device.
    0:09:18 So, can you tell me a little bit about how you and your cohort at the time sort of experienced
    0:09:21 the advent of the iPhone as, like, the moment that tipped into your interest
    0:09:23 and the intersection of technology and art?
    0:09:26 I mean, I think it was a conflation of a few different things
    0:09:28 that I was really compelled by when the iPhone came out.
    0:09:31 One was the really strong marketing component to that.
    0:09:32 I think I was particularly impressed by that.
    0:09:34 Like, the Steve Jobs moment was very compelling, right?
    0:09:35 The narrative part of it.
    0:09:36 The narrative part of that.
    0:09:39 You know, like, the way that Steve and other entrepreneurs around him at the time
    0:09:42 seemed to be offering a really cohesive vision of the world,
    0:09:43 but also the aesthetics.
    0:09:45 There was a kind of design hegemony that got installed,
    0:09:51 but also as a person who was looking at the history of artists designing for particular mediums,
    0:09:55 you could do stuff with mobile and social that you couldn’t do before, right?
    0:09:57 Artists had been making amazing artworks for browsers.
    0:09:59 There’s an incredible history of that.
    0:10:02 They’d even been making artworks that dealt with the culture of companies.
    0:10:06 There was an amazing browser-based group in the ’90s who were called E-Toy.
    0:10:09 And E-Toy was a real company.
    0:10:11 – Right, I remember that, actually. – And E-Toy started before E-Toy’s.
    0:10:13 But they tended to be quite antagonistic.
    0:10:16 A lot of browser-based work from the ’90s came from artists who were really resistant
    0:10:18 to the commercial aspects of the internet.
    0:10:19 They were really anti-commerce.
    0:10:21 There was a periodist about the internet for just communication.
    0:10:22 Exactly.
    0:10:26 And I think they really idealized moments where it was a more collective experience
    0:10:28 and the commercial part seemed to be a difficult thing.
    0:10:29 But E-Toy, I think, was an amazing collective
    0:10:31 because they were completely anonymous
    0:10:35 and they basically ended up coordinating a DDoS attack on E-Toy, the real company.
    0:10:37 – That’s like activist art in some ways, right? – Exactly.
    0:10:39 – Activist art was really close to that browser-based work. – Right.
    0:10:42 Now, me and my cohort were less anti, right?
    0:10:45 Like, I’d come up already through a commercial art world that was offline.
    0:10:48 I really valued the work that commercial agents were doing
    0:10:51 to make the work known, and I didn’t have a problem with that.
    0:10:53 And I think a lot of the people who were using social media early
    0:10:56 were also okay with the idea of promoting themselves.
    0:10:58 So, we were less against.
    0:11:01 We designed things that didn’t necessarily have this kind of anti-commercial message.
    0:11:03 I mean, there’s always been this long history intention,
    0:11:05 as you obviously know, with artists and the commercial aspect.
    0:11:09 I mean, Andy Warhol is the most obvious example that comes to mind for that.
    0:11:13 And it’s interesting because we’ll get to how this may play out with the NFT world.
    0:11:16 You talked about the early days of Web 2.
    0:11:20 Browser-based art is maybe the moment in your age and demographic.
    0:11:25 Web 1, Browser-based, Web 2, Instagram, social and mobile.
    0:11:29 One of the greatest examples, I think, of people making artwork for social media
    0:11:33 plus mobile was this work that a friend of mine, Amalia Ohman, did a little bit later,
    0:11:34 like in the early 2010s.
    0:11:37 And this was when Instagram was really the medium
    0:11:40 that everybody was using in the art world, at least, in our art world.
    0:11:43 And we were all posting our exhibition photos on there,
    0:11:44 posting selfies of ourselves, whatever.
    0:11:46 But she was using it in a different way,
    0:11:49 where she really occupied this proto-influencer idiom.
    0:11:51 She started taking photos of her.
    0:11:54 And then gradually, over time, her image changed.
    0:12:00 It was less art world girl, more basic, quote unquote, looking person.
    0:12:03 Her makeup was more extreme, her body became more extreme.
    0:12:06 And then at one point, she was announcing that she was going to have surgery on her body.
    0:12:10 And then we, as a community of artists that knew her, were like,
    0:12:13 “Wow, Amalia’s really changed. This is really super difficult.”
    0:12:17 And then she had these incredible pre and post things of an operation or whatever.
    0:12:19 And then it came out that it was all a performance.
    0:12:21 And we were all completely duped by the whole thing.
    0:12:23 It was really, really believable.
    0:12:27 And again, it used all of these emergent properties of that medium
    0:12:30 to really do something that said something about the way that the world was going.
    0:12:32 Yes, that sounds like performance art.
    0:12:33 I actually think I heard about this.
    0:12:37 Exactly. And speaking of the specific properties of that medium,
    0:12:39 you also mentioned the word proto-influencer,
    0:12:40 which I think is very interesting,
    0:12:44 because obviously there is this element of influencers today on Instagram
    0:12:47 and beyond in social media and influencer culture.
    0:12:50 So this is sort of pre, that sort of case.
    0:12:51 It was emergent with it, I would say.
    0:12:52 Mergent with it, okay.
    0:12:53 And I think this is what artists are good at doing.
    0:12:56 They’re good at seeing emergent properties that are happening,
    0:12:59 both in visual conventions, like how photos are looking,
    0:13:00 because that was another thing.
    0:13:03 Like visually, there was a particular style to these images, right?
    0:13:05 That came from the hardware, came from the way that the phone looked,
    0:13:09 came from the lighting that was common in a bedroom or whatever.
    0:13:12 All of this also was a kind of an aesthetic layer to it.
    0:13:14 It was also constrained by the technology at the time, right?
    0:13:18 Yeah, exactly. And all of those things come together to make a particular medium possible,
    0:13:21 including the network, which I think is also interesting
    0:13:22 if we’re thinking in the future about NFT.
    0:13:25 When you say the network, do you mean the network is in the community around her
    0:13:28 or the network of her followers and her social graph,
    0:13:29 or what do you mean by network?
    0:13:31 I think there’s a few different layers to the network thing.
    0:13:33 The performance, if you categorize it as a performance piece,
    0:13:35 happened first to her friends that knew her,
    0:13:38 because the strangeness of experiencing that change
    0:13:40 was the thing that made the effect, right?
    0:13:45 But that network of friends also had a second order network of people that knew of her.
    0:13:48 So this classic social network kind of social graph world,
    0:13:50 it spread out into, but also the hardware,
    0:13:52 like technological layer of the network,
    0:13:56 where you couldn’t have these distributed performative moments
    0:13:59 without iPhones, without satellites, without cables.
    0:14:03 So it’s really like quite a lot of things coming together in this network, I think.
    0:14:06 Interesting. So then Simon, on that note,
    0:14:08 what are some of the other milestones for your experience
    0:14:11 in evolution as an artist in the technological moments?
    0:14:14 I mean, artists have been dealing with technological changes
    0:14:17 and expressing the visceral feelings of inhabiting
    0:14:20 new technological moments for a very long time.
    0:14:23 Surrealism and data is an early 20th century moment
    0:14:25 that dealt a lot with the changes, both in advertising language
    0:14:28 and mediums around communication.
    0:14:31 Surrealism really leaned into the illustrative aspect of that.
    0:14:35 But data and stuff, artists like Picabia and people making images of machines,
    0:14:38 of post-industrial revolution kind of worlds.
    0:14:41 A lot of early modernism is depicting machinic worlds.
    0:14:45 When you then jump, let’s say, to the post-war period in the 1960s and 70s,
    0:14:48 you started to have groups of artists around pop art and neopop,
    0:14:50 dealing again with the language of advertising and ambivalence
    0:14:52 called commercial culture.
    0:14:55 Artists like Robert Rauschenberg, who was a kind of proto-pop artist,
    0:14:58 working with people like in collectives like EAT,
    0:14:59 the experiments in art and technology,
    0:15:02 which happened in dialogue with Bell Labs at the time.
    0:15:04 Oh, I didn’t know about that. Tell me a little bit more about that.
    0:15:07 I mean, I’m not an expert, but there was this really amazing moment
    0:15:10 where these very prominent people were in dialogue with people in Bell Labs,
    0:15:15 and so they made experimental, technologically-enabled sculptures.
    0:15:16 There was one Rauschenberg piece that I’m thinking of.
    0:15:18 Actually, I don’t know if you made it in EAT or not,
    0:15:21 but it was like a bed of mud that was bubbling
    0:15:23 that then had a sensory component on it as well.
    0:15:26 Like really amazing kind of machine and object-based work,
    0:15:29 but also a lot of kind of theater-based experiments and performances
    0:15:32 which were also done with early computer systems.
    0:15:35 There was also people being given, for example, early porta-packs,
    0:15:38 which was the kind of first video equipment by Sony.
    0:15:40 So Sony was really involved in donating to artist groups,
    0:15:42 and there was an artist group that was in New York
    0:15:44 that was really adjacent to the whole earth catalog
    0:15:45 in the Stewart Brand World.
    0:15:46 Yes, yes.
    0:15:48 There was another magazine called Radical Software,
    0:15:50 which was produced at the time as well,
    0:15:54 and Radical Software was run by an early artist corporation
    0:15:55 called Raindance Corporation.
    0:15:56 They incorporated themselves,
    0:15:58 and they had a space in New York
    0:16:01 where several porta-packs were that artists could come and use.
    0:16:03 They would make footage, they would bring the footage back,
    0:16:05 and then they would make artist libraries
    0:16:08 that you could pull as stock footage and make montages from.
    0:16:10 So that was also like a really interesting early moment
    0:16:12 that inspired me a lot.
    0:16:14 And out of that group came early experiments
    0:16:17 in broadcast television and cable network television.
    0:16:20 There was an amazing collective called Top Value Television,
    0:16:22 and they, for example, produced one of the most amazing
    0:16:24 artist-made documentaries that was then screened
    0:16:26 on cable television at the time,
    0:16:28 looking at Madison Avenue and advertising producers,
    0:16:30 but also a Nixon convention.
    0:16:32 They went and made a kind of political documentary.
    0:16:34 And then, of course, there’s like more famous examples
    0:16:36 like Warhol Television and stuff like that
    0:16:37 and cable networks.
    0:16:40 When you said that the example of the early stock library type
    0:16:42 of idea that people could take,
    0:16:44 and that you said that inspired your work,
    0:16:46 what really stuck in my mind about that is like,
    0:16:48 that’s like an analog version of remix culture.
    0:16:49 Absolutely.
    0:16:51 And so tell me about how it inspired your work specifically.
    0:16:53 Well, I’m a bit of a historian,
    0:16:55 and I actually made a show here in London in 2012
    0:16:57 at the Institute of Contemporary Art, the ICA,
    0:17:01 where I managed to convince the broadcasting network
    0:17:03 who were changing over from analog broadcasting to digital
    0:17:07 to give us one of the old analog broadcasting machines.
    0:17:10 And I dumped that in the middle of the Institute for Contemporary Art
    0:17:13 and put all of these libraries of old network videos
    0:17:15 made by people like Randolph Corporation and the Peers
    0:17:17 around in a video library where people could watch them.
    0:17:20 And one of the things that I found in an archive of theirs
    0:17:23 was a way of categorizing different types of tapes.
    0:17:26 They made early data versions representing
    0:17:27 what was being made in those libraries.
    0:17:30 So I found those resonant with what people were doing on YouTube,
    0:17:32 what other artist peers of mine were making,
    0:17:35 which were kind of remixed things and appropriated things.
    0:17:38 A bunch of my work is very liberal with ownership.
    0:17:40 I believe that one doesn’t invent something.
    0:17:43 I believe that one finds things and combines them with things.
    0:17:45 So I prefer the notion of like a value add
    0:17:47 than like a kind of invention.
    0:17:48 So I don’t believe that you can invent things.
    0:17:51 This is why I think movements like pop art were so profound
    0:17:53 because the correct appropriative touch
    0:17:55 of making an image of a Campbell soup can
    0:17:57 and claiming that as an original thing,
    0:17:59 recontextualizing it was one of the biggest things.
    0:18:01 And I think sampling culture and all of that stuff
    0:18:02 like built on the back of that assumption.
    0:18:04 I find that so personally fascinating too.
    0:18:07 So we talked about some of the pre-influences
    0:18:08 in the technological side.
    0:18:11 Let’s talk about some of the post-influences, post-iPhone.
    0:18:13 Like are there any other technological moments?
    0:18:15 Yeah. So I think the next big moment in the mid-2010s,
    0:18:19 I was lucky enough to do the Venice Biennale Pavilion for New Zealand.
    0:18:22 The Venice Biennale is kind of like the biggest art show in the world
    0:18:24 and there’s country by country pavilions.
    0:18:26 So I got to do New Zealand and in order to do that,
    0:18:30 it was 2013-14 I was working on it and 15 I presented it.
    0:18:32 I was interested in the WikiLeaks moment at that time.
    0:18:35 Artists like Trevor Paglin were involved in those communities.
    0:18:37 So I was sort of perfectly aware of those groups
    0:18:38 around transparency and stuff like that.
    0:18:40 When they released all these documents,
    0:18:43 I found the kind of like clip art on the DoD
    0:18:45 and internal NSA documents.
    0:18:47 I found them really aesthetically surprising.
    0:18:48 They were these very playful images
    0:18:51 that were representing kind of very serious things.
    0:18:52 That’s so interesting. I never thought about that.
    0:18:55 You had literally like a magic card standing in
    0:18:58 for like a big offensive that was looking in on everybody’s privacy or whatever.
    0:19:00 But I was so interested that I really wanted to find
    0:19:02 some concrete example of who was making those images.
    0:19:04 Who were those artists, right?
    0:19:06 And I found this one guy at LinkedIn page.
    0:19:08 This guy called David D’Arcicourt.
    0:19:10 And David D’Arcicourt was self-proclaimed on his LinkedIn.
    0:19:12 This is again social media art in a way.
    0:19:15 He claimed that he was the creative director of the NSA
    0:19:17 for the 20 years preceding the leaks.
    0:19:21 And he had a really big Adobe platform portfolio of his work on it as well.
    0:19:24 So he had designs he’d done for the NSA, slip mats,
    0:19:26 mouse pads, training posters, all these things.
    0:19:28 And I made copies of all of them.
    0:19:31 I made giant interpretations of his work.
    0:19:32 I changed medium from them.
    0:19:35 So I made sculptures out of things that were diagrams.
    0:19:37 And I situated them in this library
    0:19:40 right in the middle of Venice next to the Doge’s Palace,
    0:19:41 which was designed by Sansevino,
    0:19:43 this very important architect then.
    0:19:47 And that is a very ornate room that has images of druids and wizards
    0:19:49 and all these fantasy things that went into Tintoretto
    0:19:51 and all these artists that were working in that period.
    0:19:53 And I put his work alongside their work.
    0:19:58 And there were these crazy synergies, bearded men, strange books, fantasy imagery
    0:20:01 that was throughout the NSA material in clip art form
    0:20:04 was very close and resonant with these kind of like renaissance images.
    0:20:07 And also, I guess the key thing was it was a performative piece
    0:20:09 because D’Arcicourt didn’t know that I did this work.
    0:20:12 I was about to ask you if he knew and if you talked to him.
    0:20:13 So it was all appropriated.
    0:20:15 And the only moment that he found out that that happened
    0:20:17 was when the Guardian called him on the opening day
    0:20:20 and said, “Hey, did you know there’s a bunch of stuff with your work?”
    0:20:21 Where did he react, by the way?
    0:20:23 Oh, I think he was a little confused.
    0:20:25 He’s like, “What is this guy doing with this?”
    0:20:27 Yeah, I mean, it was really important to him at the time
    0:20:29 and this came out in the Guardian article too
    0:20:30 when the Guardian spoke to him.
    0:20:32 But it was really important that he was attributed, which he was.
    0:20:35 His phone number was on there just like it was on the web.
    0:20:36 And that was part of my gesture.
    0:20:38 And I think he found it really interesting, of course,
    0:20:41 as the gesture was a little bit like performing something like
    0:20:45 what the NSA was performing on all of us, but on an artistic work.
    0:20:48 And I think that was again complicated by the fact that I was from New Zealand.
    0:20:50 This is US culture in a certain sense.
    0:20:52 So I think there was a lot of really interesting tensions around ownership.
    0:20:55 Right. And it’s funny because the technological underpinnings
    0:20:58 are fascinating to me because you said briefly that in a way,
    0:21:01 him putting that he was a creative director for the NSA
    0:21:03 on his LinkedIn profile is almost performance art.
    0:21:04 Exactly.
    0:21:07 And then the other point is that these materials you’re talking about,
    0:21:09 these artifacts were leaked online.
    0:21:12 Yeah. And I think this brings up the kind of art networks
    0:21:13 that preserve and take care of culture.
    0:21:17 I think they take care of things that are otherwise not seen and not cared for.
    0:21:19 So I really like to act in that domain.
    0:21:22 But of course, that’s a sort of object based medium in itself.
    0:21:24 You want to go into a room in a museum
    0:21:25 and you want to have a rich experience in there.
    0:21:28 Translating browser based work into a projector in a room
    0:21:30 doesn’t always work so well, right?
    0:21:32 Did you create it for the Biennale?
    0:21:33 I created it for the Biennale.
    0:21:35 The way that it works is you get commissioned.
    0:21:36 You can kind of do whatever you like.
    0:21:37 You work with a curator.
    0:21:39 The government of the country sponsors that.
    0:21:41 And then the Biennale acts as a sort of presenter in a way.
    0:21:46 Were there any other technology milestones on the way to crypto and blockchain art?
    0:21:47 I’ll say one more.
    0:21:48 So I mentioned this piece that I made
    0:21:51 where I was looking at entrepreneurs through DLD,
    0:21:52 through going and hanging out at conferences.
    0:21:55 That was really inspiring aesthetically and everything for me.
    0:21:57 That’s so funny to hear about entrepreneurship as an aesthetic.
    0:21:58 Yeah, I love it.
    0:22:02 And so this is the thing I leaned into the Berlin of that time as well.
    0:22:04 And I made a series of works about young startups.
    0:22:09 So for example, I took a wired roundup like top 10 startups in Berlin
    0:22:12 and I made almost like a deal toy meets a gaming computer,
    0:22:16 meets a kind of like a piece that might go in a trade fair booth or something like that.
    0:22:18 And I would make these pop art inspired sculptures
    0:22:21 that were celebrating the culture of entrepreneurship.
    0:22:26 That was something that I ended up culminating in a big show that I did also in 2015,
    0:22:29 that MoMA PS1, which was called the Innovators Dilemma.
    0:22:30 It was like named after…
    0:22:32 Blake and Christensen’s famous book, yeah.
    0:22:34 Where it brought together a bunch of different projects
    0:22:36 that are doing in general about entrepreneurship.
    0:22:39 I made something about South Korean entrepreneurship.
    0:22:42 I made a big project about Samsung during those years as well,
    0:22:45 which looked at their turn to be more global in the 1990s.
    0:22:48 I also did a really big round of work based on Peter Thiel.
    0:22:50 It was inspired by a moment in New Zealand
    0:22:53 where it was realized that Thiel was a citizen.
    0:22:54 And I made like a big group of artworks
    0:22:57 that were based on board gaming and the language of gaming,
    0:23:01 which mapped out ideological narratives that came from Peter’s world,
    0:23:03 which is very, very influential in entrepreneurship.
    0:23:06 So I did a show that was at a small gallery in Auckland in New Zealand,
    0:23:10 not a kind of big space, but Peter ended up coming there.
    0:23:11 He ended up seeing the show.
    0:23:13 We ended up getting in touch after that
    0:23:15 when he was still based in San Francisco.
    0:23:17 And that was, again, this really interesting moment
    0:23:20 of bringing the way that certain ideas were received in a local space
    0:23:22 with something that was very influential
    0:23:24 in the business world and the technology world.
    0:23:27 I also made artworks about Kim.com,
    0:23:29 who is this German Finnish entrepreneur
    0:23:31 who built a platform called Mega Upload,
    0:23:34 which was one of the most used piracy network things
    0:23:37 for downloading like Hollywood content.
    0:23:41 And he was sued by the US government, I think in 2013, 2012 even maybe,
    0:23:43 and there was a massive bust on his home,
    0:23:46 which was a collaboration between the New Zealand Armed Forces
    0:23:48 and Police Network and the US.
    0:23:50 And they tried to extradite him ever since.
    0:23:52 Of course. We did a covers during Kim.com at work.
    0:23:54 That cover story I was very inspired by at the time,
    0:23:56 and also because he was based in New Zealand.
    0:24:00 And the whole bust went down in this very glamorous property in Auckland.
    0:24:02 I have to say, he’s still living in New Zealand.
    0:24:05 They never managed to actually successfully extradite Kim.
    0:24:07 And he made other platforms since.
    0:24:10 I was also watching all of my content on his platform at the time.
    0:24:12 There was another thing, living in Germany,
    0:24:14 you couldn’t get Netflix at the time.
    0:24:16 Yeah, we were all pirates at some point in our career,
    0:24:19 especially if you grew up in any point in the 90s and onward.
    0:24:20 It was all pre-Netflix.
    0:24:22 Like that was the only way to get things.
    0:24:24 Do you remember Burning CDs?
    0:24:25 Oh, of course I remember Burning CDs, exactly.
    0:24:26 Now I look back on it.
    0:24:27 You wouldn’t download a car, you know.
    0:24:29 Well, now I look back on it as a creator,
    0:24:30 and there’s a big difference when you talked about
    0:24:32 how you were doing literal appropriation art
    0:24:34 in the case of that NSA artist.
    0:24:37 That’s like a specific performative type of thing.
    0:24:38 It’s a gesture, exactly.
    0:24:42 Now I’m mortified as a creator at how I treated other creators’ works
    0:24:45 when I realized that we just like burn CDs, pass them to our friends.
    0:24:47 This is like a Web2 question as well, right?
    0:24:48 A little bit.
    0:24:51 Because it’s also about what is promotion, what is popularity,
    0:24:54 what is a tension value worth, and where do you monetize that.
    0:24:56 Burning CDs is a proto expression of that problem, right?
    0:25:00 You’ve mentioned a few times, actually, this tension between art and commercialism,
    0:25:01 and I want to go back to it.
    0:25:02 It’s quite fascinating.
    0:25:03 There’s a thread in your work.
    0:25:06 You seem very inspired by advertising culture.
    0:25:06 Oh my God, yes, yeah.
    0:25:09 And a lot of people would argue advertising is not art.
    0:25:09 Yeah.
    0:25:11 So clearly you’ve all in this other camp.
    0:25:12 Yeah.
    0:25:12 Tell me more about that.
    0:25:16 I mean, I think it’s also not so unusual within the art worlds that I occupy,
    0:25:18 but essentially pop art is a really great example
    0:25:19 because everybody’s heard of Warhol.
    0:25:22 But there’s many practices that came in the wake of that big idea
    0:25:25 and also the scale that he was able to bring to that big idea.
    0:25:28 I think the notion that pop art proposed that your role as an artist
    0:25:31 is to describe how it feels to occupy that contemporary world.
    0:25:33 And you’re not an ethical agent.
    0:25:36 It’s just like I go into the street and I see a giant billboard
    0:25:38 and it does something to my heart and that is culture, right?
    0:25:38 Yes.
    0:25:40 Like that is the claim of pop art.
    0:25:40 That is culture.
    0:25:41 Yeah.
    0:25:44 But one thing I do have to ask you about on the advertising and also globalization,
    0:25:45 so two themes here.
    0:25:45 Yeah.
    0:25:47 But I think back to like when I used to go to India,
    0:25:50 and I’d see like Bollywood posters, which is its own aesthetic.
    0:25:51 Yeah, hand painted often.
    0:25:51 Totally.
    0:25:53 That actually is dying art now,
    0:25:55 but it was an incredible thing to see that art form,
    0:25:57 especially in my parents’ tiny village.
    0:25:58 Yeah, incredible.
    0:26:01 It’s like this pop of color and this kind of almost desert landscape.
    0:26:02 Yeah, and glamor as well.
    0:26:03 It’s glamor.
    0:26:04 Exactly.
    0:26:04 Exactly.
    0:26:06 I edited one of my friends.
    0:26:08 She’s also an author of Virginia Postural.
    0:26:09 She wrote a book called Glamor,
    0:26:11 which actually, it’s funny you said the word glamor
    0:26:13 because it has certain specific connotations to it,
    0:26:14 which I think is great.
    0:26:15 Right, right.
    0:26:16 But I do have to ask you, Simon, like,
    0:26:19 do you think there’s also this kind of
    0:26:23 monoculture that’s happening because of that globalization
    0:26:24 and in that aesthetic?
    0:26:27 Because I feel, especially in the case of pixel art,
    0:26:30 that there was a point when everyone got
    0:26:32 a little too digitally influenced,
    0:26:35 and everything started looking like the 8-bit thing,
    0:26:36 and I got very bored of that, isn’t it?
    0:26:37 Yeah, yeah.
    0:26:39 And so I just wonder if you think there’s this sort of
    0:26:42 homogenization happening as well in the aesthetic.
    0:26:44 Yeah, I guess this is a narrative that comes up
    0:26:45 from time to time.
    0:26:46 I mean, it’s not only an art that it comes up, right?
    0:26:47 Right.
    0:26:48 I mean, Netflix culture is a great example.
    0:26:50 Netflix culture is a great example too,
    0:26:51 but I think people bring it up politically,
    0:26:53 which is like the most charged context for it.
    0:26:54 Oh, yeah, yeah, totally.
    0:26:55 You know, there’s these kind of conversations
    0:26:57 about how homogenous things are becoming
    0:26:58 because of like the speed of travel,
    0:27:00 the ease of travel, these kinds of things,
    0:27:01 but I don’t really believe that
    0:27:03 that will ever make a true homogenization.
    0:27:06 And my understanding of the way that cultures have emerged
    0:27:09 is they always emerge in hybridization, right?
    0:27:10 There is no such thing, again,
    0:27:12 this is an originality question, right?
    0:27:13 Like, there’s no such thing as a true
    0:27:15 original flavor of X or Y.
    0:27:16 There’s no first anything.
    0:27:17 Right.
    0:27:19 And there’s only kind of encounters,
    0:27:20 and I tend to think I’m sort of like
    0:27:22 an encounters maximalist or something like that.
    0:27:24 Yeah, I like that, an encounters maximalist.
    0:27:26 I mean, that’s something I literally just coined.
    0:27:26 I love it.
    0:27:28 We were inventing things on the podcast.
    0:27:28 That’s how we go.
    0:27:31 But I tend to think that more hybridization
    0:27:33 is always positive, and I don’t believe
    0:27:35 that this true homogenization really ever happens.
    0:27:37 There are kind of trends and moments
    0:27:41 where certain boringnesses settle into a market or whatever,
    0:27:43 where a lot of people try and do that thing.
    0:27:46 And yes, I get very bored about that very quickly.
    0:27:48 Boring homogenous stuff is boring and homogenous,
    0:27:52 and I think the way that NFTs stratified very quickly in 2021
    0:27:54 into particular genres bought the hell out of me.
    0:27:56 I mean, this is true in the art art world
    0:27:57 as well as the NFT art world.
    0:28:00 Like, expensive things are considered to be important,
    0:28:01 but on the edges of those things,
    0:28:03 I could tell you 10 examples of things
    0:28:06 that did incredible stuff with the kernels
    0:28:07 of things that went into those strata,
    0:28:09 but then did something truly amazing on the side of it.
    0:28:12 At the fringes, at the side of those movements
    0:28:15 are always something where there’s somebody mixing that
    0:28:16 with something that’s never been seen before.
    0:28:17 That’s great.
    0:28:18 And then that makes something new.
    0:28:20 And I think that’s a very old story.
    0:28:22 I also think globalization is a much older story
    0:28:23 than is often assumed colloquially.
    0:28:26 Cultures have been mixing across Eurasia, for example,
    0:28:27 for very long time.
    0:28:28 Oh, totally.
    0:28:30 I love that you pointed out that this kind of intermixing
    0:28:32 has been happening for, like, eons.
    0:28:33 That’s great.
    0:28:36 There are many examples across the history of art and culture
    0:28:38 of things that happen on the fringe of those environments
    0:28:41 that are a little harder to see at the time
    0:28:43 that certain enthusiasts get really excited about
    0:28:45 around them as they happen,
    0:28:47 but don’t scale in the same way.
    0:28:48 Don’t reach the same price points.
    0:28:50 Don’t enter the same museum collections
    0:28:52 that are then kind of later looked back on
    0:28:54 and seen that there’s things that happened there
    0:28:56 that were just super exciting, right?
    0:28:57 That’s fascinating.
    0:28:59 But when I think of even the outsider art movement–
    0:28:59 Right.
    0:29:01 And, you know, this is a very literal interpretation of fringe.
    0:29:04 And I know what you mean as fringe is more nuanced than that.
    0:29:06 But I have a piece by Howard Finster.
    0:29:06 Oh, interesting.
    0:29:07 It’s one of his dinosaurs.
    0:29:09 It’s like this little cardboard cut-out dinosaur
    0:29:11 on, like, a little platform.
    0:29:14 And he’s handwritten in Sharpie, all these biblical verses,
    0:29:16 like, kind of like fire and brimstone.
    0:29:20 And it’s really fascinating because he was an ex-minister.
    0:29:22 And to me, that’s an encounter between, like,
    0:29:24 Christian faith and thinking
    0:29:26 combined with this encounter with evolution
    0:29:27 and what it means.
    0:29:29 Because it’s, like, so bizarre to have, like,
    0:29:31 biblical verses on a dinosaur.
    0:29:31 Yeah, that’s incredible.
    0:29:32 It’s, like, so great.
    0:29:33 Oh, my God, I want one.
    0:29:34 Oh, yeah.
    0:29:35 I think what’s really interesting
    0:29:37 about outsider art in general as a category
    0:29:39 is really interesting because I think a lot of people
    0:29:41 that came from the art world that I’ve been talking about
    0:29:43 up until now, like the world that kind of circles
    0:29:45 around museums and art fairs and galleries,
    0:29:47 when they looked at NFTs for the first time,
    0:29:50 I think a lot of them saw outsider art, right?
    0:29:52 Because it was people who were not trained in the art tradition,
    0:29:54 who were given a certain technological stack,
    0:29:56 who were then able to create and promote
    0:29:58 and sell whatever were.
    0:30:00 And that kind of opened up to a whole lot of creators
    0:30:02 that were definitely not schooled in the cannons.
    0:30:04 And then lots of super interesting weird stuff
    0:30:05 happened on the side of those,
    0:30:08 which I personally found as a wealth of compelling examples
    0:30:09 of emergent culture.
    0:30:12 And then there became own kind of homogenizations
    0:30:14 in cannon buildings within that sub-community
    0:30:15 around NFTs.
    0:30:18 And those things I found often a little less interesting.
    0:30:18 You know what I mean?
    0:30:20 Yes, I totally agree.
    0:30:22 I’m about to ask you about blockchains and NFTs
    0:30:23 in just one more minute.
    0:30:25 I’m also trying to think of when outsider art
    0:30:27 becomes establishment in other ways.
    0:30:29 Henry Darger is a very canonical example.
    0:30:31 It’s a very strange hierarchy that gets established,
    0:30:33 especially with the use of the term outsider.
    0:30:35 It also kind of brand somebody as not legible
    0:30:36 and included them in the cannon.
    0:30:38 But as an outsider, right?
    0:30:39 I mean, these tensions are very strange.
    0:30:41 It’s about academy versus not.
    0:30:43 And certain people who are able to say that’s important
    0:30:46 and that’s not and value and where money lies
    0:30:47 and all these other things
    0:30:48 that are really interesting around culture.
    0:30:49 Okay, great.
    0:30:51 Let’s talk now about blockchains and crypto art.
    0:30:54 So you mentioned like all these technological milestones
    0:30:56 and your way to your evolution as an artist.
    0:30:59 Tell me about how you came to blockchain art.
    0:30:59 Yeah.
    0:31:02 So of course, if you’re muddling around in Berlin,
    0:31:03 in the communities that are building new products
    0:31:06 and new companies in the early mid-2010s,
    0:31:07 you come across Bitcoin.
    0:31:09 And the more I dug into Bitcoin culture,
    0:31:11 the more fascinated I was.
    0:31:12 I was just like, well, as somebody who’s looking
    0:31:14 for new, inspiring narratives,
    0:31:16 this notion of sovereign free money,
    0:31:18 I then started to pay attention to people
    0:31:20 who were kind of advocating around X versus voice
    0:31:22 and also self-sovereign.
    0:31:24 I read the sovereign individual as a book.
    0:31:25 And then of course, in Berlin,
    0:31:26 you heard about Ethereum as it emerged
    0:31:28 because the Ethereum Foundation was getting set up
    0:31:29 and started there.
    0:31:32 So for the 2016 Berlin Biennale,
    0:31:34 I made my first big piece about crypto.
    0:31:37 And that was three different fictional trade fair booths
    0:31:39 based on three different entrepreneurs
    0:31:41 that were looking at three different narratives
    0:31:42 that were emerging from blockchain.
    0:31:44 One of them was Blythe Masters.
    0:31:47 So Blythe Masters was coming from the banking world.
    0:31:49 She came out of securities in the 1990s
    0:31:52 and she made this company at the time called Digital Asset.
    0:31:53 I made a big kind of installation about her.
    0:31:56 I made a big installation about Bellagy
    0:31:59 and about 21.ink before it was changed or whatever.
    0:32:01 And then I made a big one about Ethereum and Vitalik.
    0:32:03 And it was like those three narratives
    0:32:04 I was looking at at the same time.
    0:32:06 I made little postage stamps
    0:32:08 that I worked on with the German postal
    0:32:10 because I thought postage stamps were both expressions
    0:32:11 of sovereignty, right?
    0:32:13 They were also design objects
    0:32:14 and they were also kind of a currency,
    0:32:15 like a parallel currency.
    0:32:17 That’s also, by the way, fascinating about postal stamps
    0:32:20 is that they are an expression of sovereignty
    0:32:22 but they’re also like ways to get out.
    0:32:24 They move objects around the world.
    0:32:24 Exactly, they’re infrastructure.
    0:32:26 It’s so fascinating, right?
    0:32:26 Exactly.
    0:32:28 So I thought they were like the perfect sculptural form
    0:32:29 for work about this emergent network.
    0:32:33 So far you described how you were using blockchain
    0:32:35 and crypto as inspiration for your art,
    0:32:37 the subject matter of the art.
    0:32:39 But now blockchain is a medium.
    0:32:40 Let’s talk about that.
    0:32:42 Yeah, so there were a few people at that time
    0:32:44 who were starting to design kind of web-based art,
    0:32:45 like browser art that I described earlier
    0:32:47 or web 2 art, let’s say,
    0:32:50 that was based on coding on emergent blockchains, right?
    0:32:52 So there was a project called Ascribe
    0:32:54 which was actually something Vitalik worked on
    0:32:55 as well at the time,
    0:32:58 which was an early system that tried to put artworks
    0:33:00 and link them to the Bitcoin network.
    0:33:03 There was a conference in 2014 at 7on7 that Rhizome did
    0:33:05 which was connected to the new museum
    0:33:08 where they pair an artist with a technologist
    0:33:11 and at the time they designed something based on colored coin
    0:33:13 which was essentially an NFT.
    0:33:16 And then I started to learn about other projects.
    0:33:17 I’d learned about TerraZero
    0:33:18 which was a really interesting project
    0:33:20 which was a group that were proposing
    0:33:23 to make trees own themselves as entities.
    0:33:24 Trees own themselves.
    0:33:26 Yeah, exactly.
    0:33:26 They were like, look,
    0:33:28 if you can do a blockchain system based on Ethereum,
    0:33:29 if you can have smart contracts,
    0:33:32 then why not give the sovereignty of ownership to the trees?
    0:33:34 Why not have a commercial forest
    0:33:36 on the produce of its own work?
    0:33:37 I was fascinated by that.
    0:33:39 So I curated a little show in 2018
    0:33:42 at a space in Berlin called the Schinkel Pavilion
    0:33:43 and that was about artists
    0:33:44 that were doing these experiments.
    0:33:47 So also included in that was CryptoKitties.
    0:33:47 Okay.
    0:33:48 So I don’t know if you remember this
    0:33:51 but Christie’s did a weird little collaboration with Consensors
    0:33:54 where they sold a hardware wallet
    0:33:56 with a specially designed CryptoKitties on it
    0:33:58 where Gile Twardowski
    0:34:00 who was the guy who invented the visual aspect
    0:34:01 of the CryptoKitties project,
    0:34:02 so not the kind of mechanics,
    0:34:04 but the actual cats.
    0:34:05 Yeah, made a special one
    0:34:07 and they sold it as a hardware wallet
    0:34:09 which was also specially designed in an auction
    0:34:11 and it was big news in the New York Times.
    0:34:12 And so I included that in the show.
    0:34:14 I included Keira Zero,
    0:34:15 this forest project in the show.
    0:34:17 I included other artists like Kea Kroetler
    0:34:20 who was also working around Nosus at the time,
    0:34:21 doing interesting designs for that.
    0:34:23 And the whole show was set up.
    0:34:25 The curatorial premise was also based on blockchains
    0:34:28 because I didn’t want to decide everybody in the show.
    0:34:29 I asked somebody else to choose two things
    0:34:31 and then they would choose two things.
    0:34:33 And then we did a transparent publishing
    0:34:35 of all of the decision-makers on the wall
    0:34:36 as a curatorial protocol.
    0:34:39 So you turned curation, the act and art
    0:34:42 of curation itself into a form of art
    0:34:45 that actually also showed the process behind the outcomes.
    0:34:46 Exactly, transparency, networks,
    0:34:48 all of these things that kind of so important to blockchain.
    0:34:50 Decentralized decision-making, right?
    0:34:53 And so yeah, we had this kind of protocol that we designed
    0:34:55 where everybody knew who picked them for being in the show
    0:34:57 and I wasn’t making all the decisions.
    0:34:58 And that show was called Proof of Work,
    0:35:00 but that was way before NFTs were a thing.
    0:35:03 Yes, and before we talk more about NFTs,
    0:35:06 what do you think is unique about blockchains
    0:35:07 as a medium for art?
    0:35:09 You know, one of the interesting things
    0:35:10 about blockchain as a medium,
    0:35:13 I think is that the cultural asset
    0:35:16 and the financial container is the same thing, right?
    0:35:18 That’s sort of true in art in a way,
    0:35:19 but literally as an NFT,
    0:35:22 those things are much more structurally combined, right?
    0:35:24 And Web2Art and Art Design for Social Networks,
    0:35:27 they’re also like networked objects.
    0:35:28 They’re connected to other things.
    0:35:30 And settlement is immediate, right?
    0:35:31 I mean, one of the things that artists
    0:35:33 got really, really excited about
    0:35:34 with the emergence of blockchain art,
    0:35:37 and this is really going into the NFT moment now,
    0:35:40 but the idea that you could have settlement immediately on sale
    0:35:42 and that you wouldn’t have to have an intermediary
    0:35:43 because, you know, gallerists and whatever,
    0:35:45 it’s a very complicated system.
    0:35:47 So the simplicity and the directness of that
    0:35:48 was really attractive,
    0:35:50 but also this notion of resale royalties.
    0:35:52 The idea that you would sell something on a secondary market
    0:35:54 and immediately the original creator
    0:35:56 would receive some compensation for that,
    0:35:58 that’s been something that the art world’s
    0:35:59 been dreaming about since the 70s.
    0:36:01 There’s a conceptual art piece
    0:36:03 by a very famous curator, Seth Sieglaub,
    0:36:06 that he did in the early 1970s, called The Artist Contract.
    0:36:08 So let’s talk about NFTs specifically.
    0:36:10 So we’ve obviously been dancing around
    0:36:12 that this entire conversation,
    0:36:15 but I think crypto art is bigger than just NFTs, to be clear.
    0:36:15 Right, agreed.
    0:36:18 And blockchains as a medium is bigger than just NFTs.
    0:36:18 Agreed.
    0:36:19 So we agree on that.
    0:36:21 But let’s talk about NFTs specifically,
    0:36:23 because that’s the thing that really captured
    0:36:25 the mainstream attention,
    0:36:29 and actually maybe even catapulted crypto
    0:36:30 into much more mainstream awareness.
    0:36:32 And to be clear, I mean this well beyond
    0:36:34 the financialization aspects.
    0:36:36 Like I’m talking about as an artistic thing.
    0:36:38 This includes multiple auction houses,
    0:36:42 like doing NFT auctions, like being participating in it,
    0:36:45 multiple people who only came to crypto
    0:36:47 for the first time and set up a wallet
    0:36:49 in order to buy NFTs.
    0:36:51 Like who knew, of course we knew,
    0:36:53 that culture would be the thing
    0:36:54 that brings people to technology.
    0:36:56 I mean, retroactively it looks logical,
    0:36:58 but I don’t think that was a given.
    0:36:59 Oh, interesting.
    0:36:59 Tell me why.
    0:37:00 Well, I don’t know.
    0:37:02 I mean, I think the moment that changed from me,
    0:37:04 from knowing about a small group of people
    0:37:05 messing around with blockchains,
    0:37:06 making art with it,
    0:37:08 to like the post-people auction moment,
    0:37:09 I guess that’s maybe like the…
    0:37:10 People is the right thing.
    0:37:11 People post people.
    0:37:12 BB and PB, yes.
    0:37:13 Right, exactly.
    0:37:14 BB and PB.
    0:37:16 And that was also in cohorts with the auction houses.
    0:37:18 I mean, people was not an unknown entity
    0:37:19 before that auction,
    0:37:21 but he was known in the graphic arts world, right?
    0:37:23 Like he was a very, very well-known figure there.
    0:37:25 But then with the signal from the blue chip art world,
    0:37:27 you know, from those auction houses,
    0:37:28 I think those are the things
    0:37:30 that created that change in awareness.
    0:37:32 Yeah, say more like why you think
    0:37:34 it wasn’t a given that this would happen.
    0:37:36 Well, if I think back to Web 2, for example,
    0:37:38 I don’t think culture was the thing
    0:37:40 that brought that into like mainstream awareness and usage.
    0:37:42 I mean, unless you count kind of
    0:37:43 “sociality” as a layer of culture,
    0:37:46 which I guess one could and I guess I do in a way,
    0:37:47 but it’s not high culture.
    0:37:49 Like you didn’t learn about Facebook or Myspace
    0:37:51 because of an exponent art.
    0:37:53 Whereas I think a lot of people’s mainstream adoption
    0:37:55 and understanding of Web 3
    0:37:56 came around that moment,
    0:37:58 which was associated with an art and an artist.
    0:37:59 Web 1 also didn’t happen like that.
    0:38:01 You know, you didn’t hear about the internet
    0:38:03 because you heard of some artist piece being made by an artist.
    0:38:05 No, I agree. I totally agree with you.
    0:38:07 You’ve said multiple times about this conversation
    0:38:08 that culture emerges.
    0:38:11 And so what do you think about this moment
    0:38:13 made this like the time, like why now?
    0:38:15 Well, I mean, I think auction houses
    0:38:17 are always looking for new things, new markets.
    0:38:18 They’ve constantly done that.
    0:38:19 You know, before the 1970s and ’80s,
    0:38:20 they didn’t sell contemporary art.
    0:38:22 For example, they only sold old masters.
    0:38:25 So moving into new areas is kind of like a textbook thing.
    0:38:27 But then DeFi Summer came
    0:38:28 and there was all this liquidity created
    0:38:31 in the ecosystem from people who’d been successful,
    0:38:33 which then they started to filter into these cultural assets.
    0:38:35 And I think that was what built up to the crypto market.
    0:38:37 Yes, but why the art?
    0:38:38 Because they could have also funneled that liquidity
    0:38:40 into something else.
    0:38:41 You know, I can’t answer that question.
    0:38:43 But I think people want to buy art
    0:38:46 that support the cultures that they believe in.
    0:38:47 It’s about identity and belonging.
    0:38:48 Yeah, exactly.
    0:38:49 And affiliation.
    0:38:51 And people who’d been excited by what was possible
    0:38:52 within the state by world,
    0:38:54 within the kind of crypto world in general,
    0:38:56 saw an emergent cultural package
    0:38:58 that kind of embodied the value of that.
    0:39:00 And they were like, okay, I believe in this culturally.
    0:39:03 And I think that mostly really happened around PFCs.
    0:39:05 Yes, like profile pic type art.
    0:39:07 Profile pic type art, like crypto kitties and crypto punks.
    0:39:09 Artistically, it’s really an interesting mechanism.
    0:39:12 You sell something initially to a large community.
    0:39:14 A bunch of people hold the same thing.
    0:39:16 And then that also moves around in networks.
    0:39:18 It changes ownership, owner to owner, right?
    0:39:19 And with that, the community grows.
    0:39:21 The people who have touched that asset.
    0:39:24 And that means that a large group of people
    0:39:27 are suddenly almost fractal participators
    0:39:29 in kind of one cultural moment, right?
    0:39:31 And one cultural asset, you know what I mean?
    0:39:31 Yes, exactly.
    0:39:33 They’re designed to participate in networks
    0:39:35 so that the provenance is important.
    0:39:35 Yes.
    0:39:36 You know, where it came from,
    0:39:38 where it’s going to is important.
    0:39:41 Tracing these relationships as a part of the medium
    0:39:42 is what’s so super interesting about that.
    0:39:43 It’s fascinating.
    0:39:43 Yeah.
    0:39:45 And the networks themselves are in the cloud.
    0:39:46 Yeah.
    0:39:47 Or blockchain.
    0:39:48 One of our colleagues, Tim Ruffgaard,
    0:39:51 and calls blockchains computers in the sky.
    0:39:51 Yeah.
    0:39:53 It could be operate without like any central.
    0:39:55 In any matter, they’re accessible to all.
    0:39:57 You talked earlier about coming from New Zealand
    0:40:00 and this idea of like the borders and the inspiration
    0:40:03 for you being like almost global by default.
    0:40:04 Yeah.
    0:40:05 This is that exact very example.
    0:40:05 Exactly.
    0:40:07 Like the portability of the asset.
    0:40:08 It’s not just that.
    0:40:10 It’s like the portability of your humanity,
    0:40:12 your identity, like who you are, your network.
    0:40:13 Yeah.
    0:40:15 Or even belonging in a network, regardless of border,
    0:40:19 place, location, into a different kind of identity online.
    0:40:19 Yeah.
    0:40:21 And I mean, there’s a sort of more humanity side
    0:40:22 to this argument as well.
    0:40:24 Like, you know, the Donna Haraway notion
    0:40:26 of the community of kin.
    0:40:29 But it’s that within a digitally designed artwork network.
    0:40:30 I mean, that’s so beautiful.
    0:40:31 They’re more of a community of kin.
    0:40:34 Well, one of the cool things that I found in art school
    0:40:36 was like me and this one other person
    0:40:38 loved this one artwork by this one artist.
    0:40:38 Yes.
    0:40:40 And we found a passion in there that meant
    0:40:42 we were compatible across all sorts of different things.
    0:40:44 Oh my God, you’re so right.
    0:40:44 Yeah.
    0:40:46 One of my absolute favorite artists is this New Orleans artist
    0:40:47 named Rebecca Raboucher.
    0:40:49 I’m a big fan of her work.
    0:40:49 Very fantasy.
    0:40:50 She had a lot of portals.
    0:40:51 Yeah.
    0:40:52 I love that type of thing.
    0:40:52 Yeah.
    0:40:53 And I collect a lot of her pieces.
    0:40:54 Oh, interesting.
    0:40:56 As I went to her art patron dinner,
    0:40:58 and I’ve been to multiple shows of hers.
    0:40:58 Yeah.
    0:41:01 And I feel like the community that comes around the art,
    0:41:03 these are people I’ve never met before.
    0:41:03 Right.
    0:41:06 I have no history, no demographic in common.
    0:41:09 It’s like an instant affiliation and true connection.
    0:41:10 Yeah, exactly.
    0:41:13 Because what better proxy for understanding
    0:41:14 that kind of like-mindedness than having
    0:41:15 that same shared love?
    0:41:16 Oh my God, I totally agree.
    0:41:18 It’s a really precise cultural signal.
    0:41:20 There’s also another artwork that I want to mention here
    0:41:23 that is maybe less known and is working differently
    0:41:25 than many NFTs in terms of dynamics.
    0:41:27 It’s a project by Sarah Friend,
    0:41:29 which I actually showed in another curated show
    0:41:31 that I did later on called Proof of Stake.
    0:41:33 And that was all about ownership in particular.
    0:41:35 And she did this piece called Lifeforms,
    0:41:36 which were designed on polygon.
    0:41:40 But the NFTs were designed to only live, quote unquote,
    0:41:41 if they were transferred.
    0:41:45 And so they had like a time life programmed into them
    0:41:48 where if they stayed in one wallet longer than three months,
    0:41:50 they would completely self-destruct.
    0:41:51 Yeah, got it.
    0:41:53 I don’t know if you’ve heard of this, but OG Crystals?
    0:41:54 Oh, yeah, sure.
    0:41:55 And the artist was Michael Jew.
    0:41:57 And he did it with Daniel Krivorichko.
    0:42:01 Anyway, what’s really fascinating about it is that the NFT,
    0:42:03 to your point, like that’s an example of like,
    0:42:05 that has to be transferred in order to exist.
    0:42:06 Yeah, with Sarah Friend’s Lifeforms.
    0:42:08 And I love that it’s called Lifeforms.
    0:42:10 This was really interesting on the coral reef diversity side
    0:42:13 where every time you transfer this NFT,
    0:42:16 like the properties of other things in that person’s collection,
    0:42:19 inhabit, it’s like an organism.
    0:42:20 Inhabit that NFT.
    0:42:24 So what happens is, for instance, if you own like meabits,
    0:42:27 then that NFT, the crystal, the form it expresses,
    0:42:31 will have like this like 3D, like kind of cubic element
    0:42:34 to the coral, exactly.
    0:42:34 And it evolves.
    0:42:39 And so the art itself evolves as it gets transferred,
    0:42:42 which I think is so fascinating.
    0:42:44 Like that is, I have goosebumps talking about this
    0:42:48 because that is the essence of truly being native to the medium.
    0:42:51 Because it’s not just taking something and then taking it
    0:42:53 and like, oh, I’m going to apply it to blockchains.
    0:42:56 It’s taking the inherent nature of blockchains
    0:42:57 and evolving that with the art.
    0:42:59 It’s just incredible to me.
    0:43:00 Yeah, I agree.
    0:43:02 And the online offline connection is also still really important
    0:43:04 because even the virtual is so physical, right?
    0:43:06 Because screens are real, pixels are real.
    0:43:09 You know, like networks are made of atoms as well as bits, you know.
    0:43:11 And the recent body of work that I made
    0:43:14 that was actually named a little bit close to this book from Chris.
    0:43:19 So I made oil paintings of other people’s metaverse property tokens.
    0:43:21 Ah, you made the digital physical.
    0:43:24 Yeah, in a way, because I thought about territory.
    0:43:25 I thought about community.
    0:43:26 I thought about history.
    0:43:28 And I thought about like the fact that these tokens,
    0:43:31 when I looked at something like Decentraland or Sandbox,
    0:43:33 these very popular, you know, crypto-based metaverses,
    0:43:35 when I looked at the ownership tokens
    0:43:37 for owning a piece of property in those worlds,
    0:43:41 I saw a grid that looked to me like mid-century painting.
    0:43:42 Because it’s a grid.
    0:43:45 These projects, if you buy a token, you get an NFT
    0:43:47 that looks like a part of the map of the project.
    0:43:48 But I was thinking, oh, that’s so interesting
    0:43:50 because it looks so much like mid-century painting.
    0:43:52 And then I was like, oh, wouldn’t that be funny to paint that actually?
    0:43:55 And then I was like, that would be a landscape painting
    0:43:58 of a piece of property in the metaverse.
    0:43:58 That’s so weird.
    0:44:00 And then I was like, what is landscape painting?
    0:44:03 And that, again, goes back to my background.
    0:44:04 I grew up in New Zealand.
    0:44:06 The first thing we learned about is colonial landscape painting.
    0:44:10 And I was like, oh my God, when I see these NFTs, this gridded system,
    0:44:12 it’s like modernism is being projected onto the metaverse.
    0:44:16 So it’s taking an old modernist trope and putting onto the metaverse.
    0:44:20 But it was important for me to underline the networked element as well.
    0:44:22 So while there were paintings of somebody else’s property,
    0:44:25 I included two QR codes on the side of each painting.
    0:44:27 And the first one links to the original property.
    0:44:29 So you can kind of look at the property that the painting is also.
    0:44:31 You know exactly because that’s interesting as well
    0:44:32 about metaverse interfaces.
    0:44:35 That’s already gone through a few rounds of UX.
    0:44:38 So the painting is often kind of early version of a landscape.
    0:44:41 And then you have a link to what the real one looks like now.
    0:44:43 But then I designed an NFT that looks like an ownership card
    0:44:46 that you would get a monopoly for owning a piece of property
    0:44:48 and tells you who owns that piece right now.
    0:44:51 And it links you to the person that owns that piece,
    0:44:52 but it’s also permissionless, right?
    0:44:56 So it’s a painting which is permissionless of a property that you don’t own,
    0:44:58 that then you have a kind of other piece of ownership property
    0:45:00 that always links you to the person who currently owns it.
    0:45:03 It’s like so fascinating to explore the nature of ownership.
    0:45:06 So this is the exhibition you debuted in San Francisco.
    0:45:09 Why did you title it Read Write Own?
    0:45:13 Well, I was really interested in always like what are good descriptions
    0:45:14 of what’s different about networks, right?
    0:45:17 And when I read about Chris’s book coming out
    0:45:20 and Read Write Own was kind of like underlined as a way
    0:45:22 to summarize Web 1, Web 2, and Web 3.
    0:45:23 It was the title of the book.
    0:45:26 It resonated with also the design on the cover.
    0:45:28 It was a little square in the middle
    0:45:30 and a kind of landscape like object around it.
    0:45:33 And I was like, oh my God, like this is what I’ve been painting.
    0:45:36 I’ve been painting the difference of ownership in Web 2 and Web 3.
    0:45:38 And kind of how these things layer up.
    0:45:41 Also like ownership is really something that’s really important in art.
    0:45:42 It always has been important.
    0:45:43 Yes.
    0:45:46 And so people owning properties, people owning images of other properties.
    0:45:48 Again, these notions around landscape.
    0:45:51 When you paint a landscape, it doesn’t mean you own it, right?
    0:45:53 It’s a picture of something you often don’t own.
    0:45:56 The other thing that’s fascinating to me about what you’re saying about this
    0:45:59 is that this idea of ownership and what you’re doing with the paintings
    0:46:00 in your exhibit for Read Write Own.
    0:46:04 It’s this idea too that we ourselves are transient humans
    0:46:07 and the ways we put our stamps on the world sometimes,
    0:46:09 like the only thing that endures is art.
    0:46:12 Whether physical or emotionally, like the things we leave behind.
    0:46:16 And it’s funny because I used to be a huge fan of Christo and John Claude.
    0:46:17 Oh yeah, sure.
    0:46:19 Big fan because I love landscape art.
    0:46:23 You would think it’s so inane, like you’re putting plastic to cover trees.
    0:46:25 How is this art?
    0:46:28 But I love this idea that humanity is conquering nature
    0:46:31 in a way that’s not like extractive,
    0:46:34 but that’s actually beautifying it and showing our presence.
    0:46:37 And I find that building, it’s just beautiful.
    0:46:39 There’s something extremely exquisite about it,
    0:46:41 which I’m bringing it up because it resonates
    0:46:43 with what you’re describing with the Read Write Own exhibit you did.
    0:46:44 Well, exactly.
    0:46:46 I mean, John Claude, for those who haven’t heard of them,
    0:46:49 they basically, as a giant sculptural gesture, would rap significant things.
    0:46:52 For example, the Bundestag in Berlin, that was a really big one.
    0:46:52 That’s right.
    0:46:53 They just did in Paris.
    0:46:57 Well, actually, one of them obviously died, but the spouse is still alive.
    0:46:57 Yeah, John Claude.
    0:47:00 Yes, and they just did the rapping of the…
    0:47:01 Arch de Triomphe, exactly.
    0:47:03 So often symbolic things, but also whole islands.
    0:47:05 Surrounding the Florida Keys.
    0:47:07 Yeah, and it makes a monumental gesture,
    0:47:09 but it’s also at the same time a light touch, right?
    0:47:11 You occupy it and then you unoccupy it, right?
    0:47:11 It kind of comes back.
    0:47:14 It’s like ephemeral, but it is light touch,
    0:47:16 but it’s so heavy in the moment that it’s there.
    0:47:18 And by the way, logistically, incredibly difficult.
    0:47:19 Yeah, very resource-intensive.
    0:47:20 Oh my gosh, yeah.
    0:47:23 They’re like massive engineering projects, actually.
    0:47:27 And I bring that up because it is an example of how art is engineering.
    0:47:31 And you’re describing a lot of technology as art, as art is engineering.
    0:47:32 Yeah, absolutely.
    0:47:33 And I think that’s exactly what art does really well.
    0:47:36 That’s what NFT art is doing really well for blockchain networks
    0:47:39 and other types of crypto art as well, like TerraZero that we design.
    0:47:44 The notion of being able to give ownership to trees over their own sovereign space.
    0:47:46 These kinds of things are only possible
    0:47:50 because technologists have architected a certain platform or a certain environment.
    0:47:51 Yes.
    0:47:53 So let’s do some quick lightning round style, wrap up.
    0:47:55 But first, there’s a couple of recurring themes.
    0:47:57 So let’s just kind of pick them up and bring them back full circle.
    0:48:04 So one is you’ve talked a lot about commerce and the relationship to commerce.
    0:48:08 What do you think about this in the context of NFTs and art in NFTs?
    0:48:10 Like what would you say, beyond obviously the valuation aspect?
    0:48:10 Yeah.
    0:48:12 Well, one of the things about NFTs and art,
    0:48:16 the fact that the kind of financial container is the same as the artistic container,
    0:48:19 one of the knock-on effects that has happened because of that
    0:48:23 is that often value is accrued completely to price.
    0:48:26 And I think that is not necessarily the case for all culture, right?
    0:48:27 Like there’s a term like priceless.
    0:48:29 Often you talk about priceless cultural works.
    0:48:34 But also there’s this notion that something cheap can also be something valuable, you know?
    0:48:39 And I think that’s harder to express in the current technological stack of NFTs.
    0:48:40 What do you think the opportunity is to build that?
    0:48:45 Well, I think that there should be another layer of accruing and showing value
    0:48:47 in NFT projects that is not about how much they cost.
    0:48:51 I’m thinking about like something that could be like a curatorial infrastructure
    0:48:55 for giving different signals that aren’t only expressed in how expensive something is.
    0:48:58 Of course, expensive things that are in museums are
    0:49:00 important culturally and valuable in that way as well.
    0:49:03 And part of the price of them being so expensive
    0:49:05 is about how much their love does culture.
    0:49:09 But you can make something experimental that might not sell at first
    0:49:12 or that might not be expressed as something expensive as first,
    0:49:15 that will later be something that is cherished and really valuable.
    0:49:16 There’s this notion of the avant-garde,
    0:49:18 which is something really important to modernism,
    0:49:21 where you can have a small group of people doing an experimental thing
    0:49:25 that is really unpopular and very hard to understand at the time,
    0:49:28 that then later gets interpreted and valued in a different way, you know?
    0:49:31 And I think that’s a little bit missing from the NFT art world,
    0:49:34 where financial success is the only expression of cultural value.
    0:49:36 It’s not that I want to divorce that completely.
    0:49:37 No, you can’t.
    0:49:39 I just think that it needs to be more complex than that.
    0:49:40 I would say multi-dimensional,
    0:49:43 because it’s basically like if you think about all these properties,
    0:49:45 like there’s community, there’s belonging, there’s expression,
    0:49:49 there’s the aesthetic, there’s the technological underpinnings.
    0:49:50 There’s so many different dimensions,
    0:49:52 you can assess something on those, a reputation.
    0:49:55 I totally agree that there needs to be more dimensions on that.
    0:49:58 One example that I think is really fascinating here,
    0:50:03 so I co-edited a piece by Kai Sheffield who works at Visa,
    0:50:07 and he wrote a very thoughtful piece on fantasy Hollywood
    0:50:11 and this idea that you can essentially create characters
    0:50:13 that can be represented by NFTs
    0:50:18 and essentially create like a whole set of storytelling
    0:50:19 around these characters.
    0:50:23 And so the idea is that NFTs are characters,
    0:50:27 and the other point is it’s really about who gets to make,
    0:50:30 this is a recurring theme in what you’ve been talking about,
    0:50:31 who gets to make these characters,
    0:50:34 because right now it’s like centralized Disney,
    0:50:35 or like a certain type of artist.
    0:50:37 Yeah, the IP world, right?
    0:50:37 Yes, exactly.
    0:50:41 And so this idea that you can actually share and create this IP,
    0:50:44 but the real idea here is that NFTs in that sense
    0:50:47 represent community, belonging, character creation,
    0:50:51 collaboration, and then like a community of storytelling.
    0:50:53 And it’s funny because I was debating this with Bob Iger
    0:50:55 a couple of months after we did our podcast together
    0:50:57 with Chris Dixon that we did on the show,
    0:50:59 which he kind of brought up like,
    0:51:02 is it really possible to tell really good stories
    0:51:03 in a decentralized way?
    0:51:05 And I was like, you know, it’s funny you say that
    0:51:07 because you acquired Lucasfilm,
    0:51:10 and we talked about Star Wars like this franchise
    0:51:11 that was created out by one person.
    0:51:15 And after that, many people took over and extended the canon
    0:51:16 and did different things at the stories.
    0:51:20 But there’s actually a pre-story that no one talks about,
    0:51:24 which is that Star Wars itself is oral myth and storytelling
    0:51:26 that’s been propagated over centuries.
    0:51:28 Right, yeah, based on these hero story archetypes.
    0:51:31 Exactly, like the Cambelian myths and the archetypes,
    0:51:33 exactly the Jungian ideas.
    0:51:36 And that bubbled up into what became Star Wars,
    0:51:38 which now has become, there’s a canon,
    0:51:40 and then that went beyond canon.
    0:51:43 And then we went back to a new canon and it’s like continuing.
    0:51:45 And so if you think about the NFT aspect,
    0:51:47 like this is very empowering for people
    0:51:48 and you could add value that way.
    0:51:50 This relates back to my pop art thing
    0:51:52 and also the best parts of NFT art,
    0:51:53 which is this permissionless thing
    0:51:54 that I was leaning into with my canvases.
    0:51:57 You know, this notion that you can kind of take something
    0:51:59 that has a powerful effect in the world,
    0:52:01 like a Campbell’s soup can or whatever,
    0:52:04 that has a cultural effect that you live in and live with.
    0:52:07 And you can work with that and make expressions of your own.
    0:52:09 I mean, that’s kind of what Andy Wall did, right, in a way.
    0:52:12 And there was no kickback to Heinz,
    0:52:13 but in a way there was an attention kickback
    0:52:15 or a kind of valuation, a branding kickback maybe,
    0:52:17 eventually, because it’s like the
    0:52:20 the notion of the candle soup can is like, is retroactively.
    0:52:23 But I think there could be a more nuanced ecosystem
    0:52:25 around defining where value is added in that exchange.
    0:52:25 That’s right.
    0:52:27 I do want to ask you a question about like,
    0:52:30 where you think generative art and blockchains intersect.
    0:52:32 I think we get to a little bit of a problem here
    0:52:34 with like term definitions as well.
    0:52:37 Because like, I understand the broader definition
    0:52:39 of a generative piece is where you set up a protocol,
    0:52:40 you put something through a protocol,
    0:52:42 and it has a series of outputs.
    0:52:44 And those outputs are artworks, right?
    0:52:48 But I think generative art now has come to mean, colloquially,
    0:52:50 like a particular aesthetic, actually,
    0:52:51 that is not about the process.
    0:52:52 Oh, you’re right.
    0:52:54 It’s rather about like, oh, this looks sort of like
    0:52:55 an abstract shape.
    0:52:56 It has a gradient to it.
    0:52:58 Yeah, you’re right.
    0:53:00 I find that trope, unfortunately, a little dull,
    0:53:02 because this is where the homogenization question comes in
    0:53:04 and it actually starts to get really boring.
    0:53:07 But the notion of like artists setting up protocols
    0:53:09 and having outputs, and that being a methodology,
    0:53:10 that I find super interesting.
    0:53:11 I agree.
    0:53:12 So I would say there’s three layers.
    0:53:14 So one is the generative as like,
    0:53:16 you actually have a beginning of something,
    0:53:19 and it sets up a protocol, and it creates a certain output.
    0:53:20 And there’s a dynamic nature.
    0:53:22 I mean, the OG Crystals project that evolves
    0:53:24 is by definition generative.
    0:53:26 And a lot of PFB projects are also generative by definition,
    0:53:28 even though that’s maybe not what you think of
    0:53:30 of generative art, because this is a by necessity thing
    0:53:31 as well, right?
    0:53:33 If you want to make a collection of a thousand things,
    0:53:35 you’re not going to design every single one from scratch,
    0:53:35 the same one.
    0:53:38 You make up a protocol, and then it produces a thousand of them.
    0:53:39 That I would argue is a different definition,
    0:53:41 because this comes to the debate between customization
    0:53:44 and configuration, which is there is something
    0:53:45 that’s truly generative.
    0:53:47 It’s like unknown what the output’s going to be.
    0:53:49 Some of the PFB projects fall in this category, not all,
    0:53:52 but some of them just have even more nuance about it.
    0:53:55 It’s actually, in that case, more that you have a set of attributes
    0:53:57 that you’re just applying like Crypto Coven,
    0:53:59 like each of those witches, they have a very thoughtful,
    0:54:01 they’ve actually written some beautiful pieces.
    0:54:02 I’ll link them in the show notes
    0:54:05 on how they thought about the properties that would manifest
    0:54:07 as different people minted the witches
    0:54:09 and how they constrain them.
    0:54:12 That’s another aspect of that, so I agree with that.
    0:54:13 And then there’s a third part, which you’re saying
    0:54:16 you’re kind of bored by, and I don’t disagree to some extent,
    0:54:18 which is sort of this aesthetic,
    0:54:20 where now this is all what generative art looks like.
    0:54:22 I personally do love that aesthetic, I have to say.
    0:54:23 There’s nothing wrong with the aesthetic.
    0:54:24 It’s just a lot of it.
    0:54:26 I agree, but there’s Zankan, and there’s really
    0:54:30 interesting people who are doing very interesting riffs on it.
    0:54:32 Those are the people that immerse to the bubble,
    0:54:34 and Helena Sarin, I love her work.
    0:54:37 There’s a lot of artists who work bubbles up in that sense,
    0:54:38 and they bring a certain element to it.
    0:54:42 But like Solarwit, how would you connect him into this movement?
    0:54:44 Well, again, Solarwit is this mid-century artist
    0:54:46 who basically designed instructions.
    0:54:47 And when you bought an art piece of hers,
    0:54:49 you bought the right to perform the instruction,
    0:54:51 or even the right to employ somebody to perform the instruction.
    0:54:53 So it’s kind of an algorithm that you buy,
    0:54:54 which is really amazing.
    0:54:57 These are for wall drawings in the case of Solarwit,
    0:54:59 and like coincidentally,
    0:55:01 they look like what we think of as generative art.
    0:55:03 Like long e-aesthetic.
    0:55:06 Yeah, it’s based on kind of vectors and gradients and lines
    0:55:07 and patterns and stuff like that.
    0:55:09 So it has this kind of abstract element
    0:55:11 that reminds us of what we think of as generative art now.
    0:55:14 But Solarwit, to me, the interesting part is weirdly,
    0:55:16 so I’m going to say something maybe controversial here.
    0:55:17 Love it.
    0:55:19 Like the notion of buying the idea
    0:55:22 is the thing that I like about Solarwit.
    0:55:25 The way they look on the wall, I mean, fine.
    0:55:26 I’m with you.
    0:55:27 But like, it’s, you know.
    0:55:29 Oh my god, I’m 100% with you, Simon.
    0:55:30 In fact, this is a great example
    0:55:33 where I think people, and as a collector,
    0:55:35 I’m very careful to watch myself
    0:55:38 for if I’m falling for the idea of the thing,
    0:55:40 and also the actual visual response of the thing.
    0:55:42 So sometimes I have to hold myself back
    0:55:44 because intellectually,
    0:55:46 and definitely that’s a component of my decision-making,
    0:55:49 for sure, I have to intellectually respond to it.
    0:55:52 Like the visual language, that symbolism, the lore.
    0:55:55 But at the same time, I have to have a visual response
    0:55:59 inside that I feel something and visual response
    0:56:01 that I really want to look at every day.
    0:56:04 And that’s incredible and very difficult to capture.
    0:56:05 It’s very difficult to capture.
    0:56:07 But that’s the Holy Grail of the art experience.
    0:56:09 But I do think like, you know, some projects
    0:56:11 in the academic, let’s say, conceptual art moment,
    0:56:13 which came up in the mid-century, in the ’60s and ’70s,
    0:56:15 were explicitly anti-visual, right?
    0:56:16 The work didn’t exist.
    0:56:19 You were only moved by the pure idea, right?
    0:56:20 That was like a kind of aesthetic notion
    0:56:22 that came up around conceptualism.
    0:56:24 And I mean, the earliest example of that,
    0:56:26 that has actually been interestingly revisited
    0:56:28 in NFTs actually, is if Klein,
    0:56:31 and this moment of the kind of invisible artwork,
    0:56:32 he made a piece that was made in French.
    0:56:34 And basically, it was one of the first motions
    0:56:36 in the late ’50s, where people bought something
    0:56:37 that was actually invisible.
    0:56:40 And you were only buying the aura as a kind of genre.
    0:56:42 Interestingly, an artist, Mitchell Chan,
    0:56:44 also revisited that in 2017,
    0:56:47 prior to the protocols that became NFTs.
    0:56:49 But he designed an immaterial artwork
    0:56:51 that was also based on that notion as a history.
    0:56:53 Because what felt like at the time,
    0:56:55 you were buying when you bought an NFT was very ephemeral.
    0:56:57 And that work, for example, I love.
    0:57:00 Even though there’s no visual necessarily associated with it,
    0:57:04 I’m as moved by it as I am by a very visceral painting.
    0:57:06 Sometimes just the idea is the thing that moves you.
    0:57:08 Yes, there’s also this thing that happens
    0:57:10 with early technologies where people are limited.
    0:57:14 They think they don’t see the expressivity that’s possible.
    0:57:17 And so they almost go for the most reductionist way
    0:57:20 of interpreting that piece and thinking about it.
    0:57:23 And that, to bring it back to Generative Art today,
    0:57:25 I think we’re gonna see a lot more
    0:57:26 very interesting things happen.
    0:57:28 One thing I’ll say from a technological perspective,
    0:57:30 I ask everybody this question,
    0:57:31 because that’s a Generative Art.
    0:57:33 Again, for a very long time,
    0:57:35 which is what is unique about blockchains?
    0:57:38 Generative Art is not native to blockchains as a medium,
    0:57:41 but it seems like it’s found its native in blockchains.
    0:57:43 And one of the technological answers I heard
    0:57:45 from one of the people on our team, Michael Blau,
    0:57:47 and a couple of people who made this observation
    0:57:48 that at the end of the day,
    0:57:51 it was so compute intensive to unfurl the code
    0:57:54 and the package and the storage involved.
    0:57:55 So there’s something really great
    0:57:57 about having this executable on chain
    0:58:00 that lets you kind of unfurl these things visually.
    0:58:02 So I think it’ll be really fascinating to see
    0:58:04 as like the technological constraints get lifted
    0:58:07 and we advance blockchain performance, scalability,
    0:58:09 everything, what will then become possible
    0:58:12 when you can unfurl things online on chain.
    0:58:12 Totally.
    0:58:14 And so I think we’re gonna see a lot,
    0:58:15 like the thing that you’re frustrated by,
    0:58:17 which is a sort of generic aesthetic,
    0:58:20 I think we’re gonna see a lot more expressivity at that point.
    0:58:21 I mean, one of the generative projects
    0:58:22 that I really, really love,
    0:58:24 that I think falls under your categories as well
    0:58:26 of finding it is terraforms by math castles.
    0:58:28 I mean, I think that is a project
    0:58:30 which really does all of those things.
    0:58:31 And it plays with history as well,
    0:58:32 because it’s this ASCII component,
    0:58:33 it plays with complexity
    0:58:35 because of this territory component,
    0:58:37 also this notion that you have this kind of metaverse
    0:58:40 of terraforms that you can kind of invert
    0:58:42 and participate in on different levels.
    0:58:43 Like all of that, I think it’s like, again,
    0:58:45 pushing the medium of generative art
    0:58:48 to something like beyond just an output of an algorithm
    0:58:49 that is really boring.
    0:58:52 So last question for you, another recurring theme,
    0:58:53 especially with your own history,
    0:58:54 just come full circle of where we started,
    0:58:55 where we’ve been talking.
    0:58:59 So you have kind of traveled from this legacy
    0:59:01 to digital art world.
    0:59:03 What are some of the things,
    0:59:06 if you were to tell people on the legacy side
    0:59:07 about the digital side,
    0:59:10 and then the vice versa for the digital world
    0:59:11 trying to understand that legacy world,
    0:59:13 what would you sort of say as a person
    0:59:15 who travels between both of those worlds?
    0:59:17 I think about it a lot because I do exactly that.
    0:59:20 And I value those communities as much as each other.
    0:59:22 I think they’re both really compelling places to be
    0:59:24 and to care about culture and to make things
    0:59:27 and to learn about things and to collect things.
    0:59:29 So I would say speaking to a legacy person
    0:59:31 about the digital art world,
    0:59:33 I would say take the time to get to know somebody
    0:59:36 who’s passionate about what is going on there
    0:59:39 and don’t start with the New York Times or whatever.
    0:59:41 Don’t just look at what you see first
    0:59:43 and come with your priors and biases.
    0:59:46 Embrace the learning curve that is the exciting moment
    0:59:47 of getting to know somebody’s passion
    0:59:50 and why they think this project is interesting
    0:59:51 and that project is boring.
    0:59:52 And what would you say specifically
    0:59:54 about crypto and blockchain art to that same?
    0:59:57 Well, one of the challenges I’ve always had
    0:59:58 with addressing the legacy art world
    1:00:00 with crypto and blockchain art
    1:00:02 is that people in the legacy world
    1:00:04 hear the word crypto, hear the word blockchain
    1:00:06 and think, A, too complex.
    1:00:08 I’m not part of that community.
    1:00:09 I don’t understand the technology.
    1:00:11 Therefore, it’s too much work to engage.
    1:00:12 And two, they also have a whiff
    1:00:14 of kind of a scandal around it or a swindle.
    1:00:16 To a lot of art world people,
    1:00:18 that’s really like a red flag for bullshit.
    1:00:20 You know, so like they just don’t want to see that.
    1:00:23 So I would also say this is like a little avant-garde community
    1:00:25 that has its own aesthetic dimensions.
    1:00:27 Yes, there’s a kind of a learning curve to understanding it.
    1:00:29 But honestly, in the art world,
    1:00:30 there’s always a bit of a learning curve.
    1:00:32 You have to study art for several years
    1:00:33 to kind of really get into histories
    1:00:34 of the avant-garde and whatever.
    1:00:36 And that’s a rewarding process.
    1:00:37 People stay there because they love that.
    1:00:40 They love to get into those complicated discourses and histories.
    1:00:43 So there’s actually a lot of rewards for legacy art people
    1:00:44 if they would kind of take the jump.
    1:00:45 And then what would you say on the flip side?
    1:00:47 For both the digital artists,
    1:00:48 undershame the legacy world
    1:00:50 and then specifically for crypto.
    1:00:51 Yeah. So digital artists,
    1:00:52 understanding the legacy world,
    1:00:54 I think there’s a lot more continuity there
    1:00:55 than they might imagine, right?
    1:00:57 I think that often around these worlds,
    1:00:59 the notion of new things has a high premium.
    1:01:01 And I think understanding histories
    1:01:04 that actually have played into those is kind of undervalued.
    1:01:06 So I would say to those people,
    1:01:07 and I actually often do this,
    1:01:08 oh, you’re really interested in this artist
    1:01:10 that made this kind of digital artwork.
    1:01:13 Here’s this legacy art person who you probably never heard of,
    1:01:15 who did something like Solar Word or whatever
    1:01:17 that resonates with exactly that gesture.
    1:01:19 And they’re often really charmed by that, you know?
    1:01:20 And by the way, you’re not saying that in,
    1:01:22 I’m assuming this in a pedantic way of,
    1:01:25 oh, like grumpy, like, oh, that happened before.
    1:01:28 It’s more understand some of the previous movements
    1:01:30 because it might inform and inspire you.
    1:01:31 Yeah. I’m a pedagogue sometimes too.
    1:01:32 So I have to like watch my tone,
    1:01:35 but the situation is more like, you love this,
    1:01:36 you’ll also love this.
    1:01:37 Lusters of interest.
    1:01:39 Exactly. It’s like an Amazon recommendation
    1:01:40 or something like that.
    1:01:41 And that’s about sharing passion again.
    1:01:43 That’s a beautiful thing.
    1:01:44 And then on the crypto specific side,
    1:01:46 what would you say to that, you know, group,
    1:01:49 that is digital thinking about the legacy artwork?
    1:01:51 Well, I would do a more nuanced version of the same thing
    1:01:53 where I say, oh, you’re interested in the history
    1:01:55 of networked artworks based on this particular asset form.
    1:01:57 You know, there’s this amazing group of people
    1:02:00 that were making things for cable networks in the 90s and 80s,
    1:02:01 you know? Isn’t that incredible?
    1:02:04 Look at this porta pack art that was created around this thing.
    1:02:06 And again, it’s about encouraging
    1:02:08 and getting the kind of infectiousness
    1:02:10 of the love that comes at the core of those projects.
    1:02:13 Well, I think that’s a beautiful note to end on, Simon.
    1:02:13 Yes.
    1:02:15 This has been a fun conversation.
    1:02:18 And I’m so excited to see more of your work.
    1:02:21 The next thing I’m doing is building a big project about space.
    1:02:23 I’m looking at the kind of space networks
    1:02:26 and the way that people are imagining about building an outer space.
    1:02:28 I’m building an augmented reality work
    1:02:31 that is based on a sculpture of a megastructure
    1:02:33 that will hang in the Auckland Art Gallery in New Zealand,
    1:02:35 but will hopefully travel in the future as well.
    1:02:38 And that is actually based on the work of a company as well.
    1:02:41 I love it because it’s going all the way from the outer worlds,
    1:02:43 the inner worlds to like external like space worlds.
    1:02:45 Exactly. And technological paradigms
    1:02:48 enabling new types of culture and worlds.
    1:02:49 It’s like a totally different kind of world building.
    1:02:53 Well, thank you so much for joining this episode of Web3 with A6 and Zee.
    1:02:54 Thank you very much.
    1:02:57 I’ve been a long time listener, first time caller, I guess, yeah.
    1:02:58 Thank you.
    1:02:59 Yes, thank you so much.
    1:03:07 Thank you for listening to Web3 with A6 and Zee.
    1:03:10 You can find show notes with links to resources, books,
    1:03:13 or papers discussed, transcripts, and more.
    1:03:15 At A6 and Zee Crypto.com.
    1:03:19 This episode was produced and edited by Sonal Choksi, that’s me.
    1:03:22 The episode was technically edited by our audio editor,
    1:03:24 Justin Golden.
    1:03:26 Credit also to Moonshot Design for the Art
    1:03:29 and all thanks to support from A6 and Zee Crypto.
    1:03:31 To follow more of our work and get updates,
    1:03:34 resources from us, and from others,
    1:03:37 be sure to subscribe to our Web3 Weekly newsletter.
    1:03:40 You can find it on our website at A6 and Zee Crypto.com.
    1:03:43 Thank you for listening and for subscribing.
    1:03:44 Let’s go.
    1:03:47 [MUSIC PLAYING]
    1:03:49 you

    We know that technology has changed art, and that artists have evolved with every new technology — it’s a tale as old as humanity, moving from cave paintings to computers. Underlying these movements are endless debates around inventing versus remixing; between commercialism and art; between mainstream canon and fringe art; whether we’re living in an artistic monoculture now (the answer may surprise you); and much much more. 

    So in this new episode featuring Berlin-based contemporary artist Simon Denny — in conversation with a16z crypto editor in chief Sonal Chokshi — we discuss all of the above debates. We also cover how artists experimented with the emergence of new technology platforms like the web browser, the iPhone, Instagram and social media; to how generative art found its “native” medium on blockchains, why NFTs; and other art movements. 

    Denny also thinks of entrepreneurial ideas — from Peter Thiel’s to Chris Dixon’s Read Write Own — as an “aesthetic”; and thinks of technology artifacts (like NSA sketches!) as art — reflecting all of these in his works across various mediums and contexts. How has technology changed art, and more importantly, how have artists changed with technology? How does art change our place in the world, or span beyond space? It’s about optimism, and seeing things anew… all this and more in this episode.

     

    Resources: 

    Find Denny on Twitter: https://x.com/dennnnnnnnny

    Find Sonal on Twitter: https://x.com/smc90

     

    Stay Updated: 

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    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

  • Cybersecurity’s Past, Present, and AI-Driven Future

    AI transcript
    0:00:03 – It’s time to hand over cybersecurity to computers.
    0:00:05 – Entropy is increasing.
    0:00:09 They have more apps, more entitlements, and more actors.
    0:00:11 – Every single year, it’s exponential growth
    0:00:12 in the number of public breaches,
    0:00:15 the size of the breaches, the damage in the breaches.
    0:00:17 Vendors still exploding.
    0:00:19 – How can they watch out for a bank run
    0:00:22 that’s orchestrated by a deep-fake campaign?
    0:00:23 If this is indeed state-backed,
    0:00:25 this is probably not the only thing they did
    0:00:26 in that two-year period.
    0:00:30 – In 2022, $8.8 billion was lost
    0:00:32 by consumers alone in the U.S.
    0:00:35 – How can we build compound businesses from day one?
    0:00:38 How can you actually build a platform from day one,
    0:00:40 even though you’re a startup?
    0:00:41 – Who does security?
    0:00:42 Nobody does security.
    0:00:46 – The cost to launch a disinformation campaign
    0:00:49 that’s AI generated is quickly approaching zero.
    0:00:52 – Now that the cybersecurity industry commands
    0:00:55 a market of hundreds of billions of dollars,
    0:00:57 it’s easy to forget how this industry
    0:00:59 once ceased to exist.
    0:01:01 And in its few decades of rapid growth,
    0:01:03 things have changed a whole lot.
    0:01:06 So in today’s episode, we’ll take you on a tour
    0:01:08 through the history of security,
    0:01:09 which can’t be disentangled
    0:01:12 from the history of the internet and culture.
    0:01:13 This episode was actually recorded
    0:01:16 at A16Z’s campfire sessions event this April,
    0:01:18 where our infrastructure team
    0:01:21 brought in some of the top security minds in the industry.
    0:01:23 And just like any good campfire session,
    0:01:26 today you’ll hear four people talk candidly
    0:01:28 about what’s really keeping them up at night,
    0:01:30 from what really happened with the X and U-Tills attack,
    0:01:32 to new AI threat factors
    0:01:34 that are already impacting companies,
    0:01:37 to empowering overworked developers, and a lot more.
    0:01:41 For those both inside and outside the security community,
    0:01:43 I hope this episode is a helpful reminder
    0:01:45 of just how much has changed throughout the years
    0:01:49 for both offenders and defenders of trustworthy computing.
    0:01:52 So with that, we’ll start with Travis McPeak,
    0:01:54 co-founder and CEO of resource aid.
    0:01:57 And we’ll walk us through how we really got here.
    0:01:59 Let’s kick things off in 1995.
    0:02:05 As a reminder, the content here
    0:02:07 is for informational purposes only.
    0:02:09 Should not be taken as legal, business, tax,
    0:02:10 or investment advice,
    0:02:12 or be used to evaluate any investment or security,
    0:02:14 and is not directed at any investors
    0:02:17 or potential investors in any A16Z fund.
    0:02:19 Please note that A16Z and its affiliates
    0:02:20 may also maintain investments
    0:02:23 in the companies discussed in this podcast.
    0:02:25 For more details, including a link to our investments,
    0:02:28 please see A16Z.com/disclosures.
    0:02:35 – Okay, phase zero, The Dark Ages.
    0:02:37 The year is 1995.
    0:02:40 Billboard number one song, “Gangster’s Paradise.”
    0:02:43 The box office number one was “Batman Forever.”
    0:02:45 Nostalgia for the old people here.
    0:02:46 Who does security?
    0:02:47 Nobody does security.
    0:02:48 It was a totally different world.
    0:02:50 You have to realize that
    0:02:52 we didn’t have much internet connectivity.
    0:02:54 Patching wasn’t really much of a thing.
    0:02:56 Vendors was basically like antivirus
    0:02:58 in the start of firewalls.
    0:03:00 Milestones of this Dark Ages time,
    0:03:02 we had the first DEFCON,
    0:03:03 we had the first CISO,
    0:03:04 Steven Katz at City Corp.
    0:03:07 So that year, they actually had a breach
    0:03:09 where somebody stole money.
    0:03:12 And they said, “This can never happen again
    0:03:14 “without us having someone to go chop their head off
    0:03:15 “when it happens.”
    0:03:17 So this is the first CISO.
    0:03:19 We had the first word macro virus.
    0:03:20 The first bug bounty came from Netscape.
    0:03:21 As we’ll get to your Netscape,
    0:03:24 did a lot of cool things that moved forward security.
    0:03:26 And of course, the hackers movie.
    0:03:28 It was web 1.0.
    0:03:30 It wasn’t an app that you went and dealt with.
    0:03:31 It was a site that you came to.
    0:03:33 So this is Apple’s site from ’97.
    0:03:35 Hackers are like these dingy people.
    0:03:36 It’s not like an actual job.
    0:03:39 One of the things that really moved from this
    0:03:41 to the next phase was web browsers went from
    0:03:43 like that Apple thing that I just showed you
    0:03:45 to a place that you go do business.
    0:03:47 Netscape made a lot of those things possible.
    0:03:50 So they brought forward SSL.
    0:03:52 They had the first bug bounty.
    0:03:53 They were putting forward a standard
    0:03:55 of how we’re gonna build out apps on the internet.
    0:03:57 And that standard was JavaScript.
    0:03:59 At the same time, we had Java,
    0:04:02 which was one of the first ways of building apps
    0:04:04 on the internet from an old company called Sun,
    0:04:06 today known as Facebook.
    0:04:09 Checkpoint was founded in 1993
    0:04:11 from somebody that came directly out of IDF
    0:04:12 and used all of the stuff that they learned
    0:04:15 to productize the web application firewall.
    0:04:17 Okay, phase two.
    0:04:19 Security is an actual thing, but it’s a function of IT.
    0:04:21 So the year is 2001.
    0:04:23 Billboard number one is hanging on by a moment.
    0:04:25 Box office number one is Harry Potter
    0:04:26 and the Sorcerer’s Stone.
    0:04:27 Who does security?
    0:04:29 IT does security.
    0:04:31 So context here, this is the start
    0:04:32 of when we get like big hacking.
    0:04:35 So it’s not just like a thing that happens once in a while.
    0:04:37 Businesses have all either moved online
    0:04:39 or rapidly moving online.
    0:04:43 Vendors now is antivirus firewalls, systems management,
    0:04:46 milestones here, Microsoft engineers coined
    0:04:48 the term SQL injection in ’98.
    0:04:50 The first big internet worm
    0:04:53 that made it like bad for business was Code Red.
    0:04:56 The first patch Tuesday was in 2003.
    0:04:58 And I don’t know, for anybody that’s old like me,
    0:04:59 we had this Y2K thing,
    0:05:01 which was actually like complete nothing burger.
    0:05:03 But what was interesting about it is
    0:05:05 we cared enough about computers
    0:05:07 and what they do that we thought it might be a thing.
    0:05:12 So one of the changes here was bug track and full disclosure.
    0:05:14 So back in the day, we had mailing lists, bug track,
    0:05:17 people would send security vulnerability reports
    0:05:19 and vendors would basically do nothing with it.
    0:05:20 They just sit on it forever.
    0:05:22 And so there was this big moment at the time,
    0:05:23 full disclosure where it’s like, okay, well,
    0:05:26 we’re just gonna put like the full gory details
    0:05:28 of this thing and force action from vendors.
    0:05:30 And then that led to regular patching cycles.
    0:05:32 So Microsoft quickly copied that.
    0:05:36 We also had the first web application security tools.
    0:05:38 So this is Nikdo and old one from 2001.
    0:05:39 It was kind of open source,
    0:05:41 but this is the beginning of these tools
    0:05:43 being broadly available.
    0:05:45 And then this is the beginning of what I call
    0:05:46 the tail wagging the dog
    0:05:48 when it comes to vendors and security.
    0:05:50 So from some of the folks I talked to you,
    0:05:52 we basically have these new attack paths
    0:05:54 and the buyers, in this case, IT,
    0:05:56 we’re very uneducated about how this works.
    0:05:59 So it’s like, you need to have your web port open.
    0:06:01 It needs to be legit open.
    0:06:02 And I can get in and compromise you through that.
    0:06:04 IT didn’t understand it very well.
    0:06:06 So vendors had to do their part
    0:06:09 to come and educate the IT buyers that this was possible.
    0:06:10 What this looked like was basically,
    0:06:12 I just completely compromised all your systems.
    0:06:13 And they said, how did you do that?
    0:06:16 And then you explain why this web application security
    0:06:20 is an actual thing and why they need vendor solution for it.
    0:06:23 All right, phase two is the risk sign off function.
    0:06:25 So the year is 2004.
    0:06:27 Billboard number one is, yeah,
    0:06:30 by usher little John box office is Trek two.
    0:06:32 This is what phones look like.
    0:06:34 By the way, these phones will last longer than you will.
    0:06:36 These things were like basically indestructible.
    0:06:37 Who does security?
    0:06:38 Now we have a security team that does it.
    0:06:40 So this isn’t just like a thing that like IT does
    0:06:41 with some of their time.
    0:06:43 So this is when we start to get the beginning
    0:06:45 of traditional security activities.
    0:06:48 We have Microsoft basically getting popped in the mouth
    0:06:49 and they need to do some stuff differently.
    0:06:51 Tech companies start hiring people
    0:06:53 that are actually called security.
    0:06:54 Vendors now is exploding.
    0:06:57 So we have Anabirus firewall still email security web
    0:06:59 application firewall, Dast and Sast.
    0:07:02 Milestones here, we had the first use of the term
    0:07:04 cross-site scripting again by Microsoft engineers.
    0:07:07 OOSP was founded in 2001.
    0:07:08 The first use of the term shift left.
    0:07:10 I actually thought it was much more recent,
    0:07:11 but this is a very old term.
    0:07:13 And then socks regulation was,
    0:07:14 I think the first compliance standard
    0:07:17 that actually mandated some security activities.
    0:07:19 There was a growing community of folks
    0:07:21 that were really interested in web security
    0:07:23 and all of what’s possible here.
    0:07:25 And Mark curfee started this group called OOSP
    0:07:28 to basically make this knowledge more socialized
    0:07:29 so that people knew about it.
    0:07:32 One of the first projects in OOSP was the OOSP top 10.
    0:07:33 And that immediately became like,
    0:07:36 how can I get my vendor shit to be one of the top 10 things
    0:07:37 that people are buying?
    0:07:39 So this is, you know, yet more tail wagging the dog.
    0:07:41 It’s like, oh, my thing should be, you know,
    0:07:42 in the top five for sure,
    0:07:44 because it’s going to help us sell a lot more of it.
    0:07:47 Now we have the beginning of the big internet worms.
    0:07:49 So at the time windows basically
    0:07:50 didn’t come with any firewall.
    0:07:52 You started up, it would get immediately
    0:07:53 compromised by stuff.
    0:07:55 The worms here were costing a lot of money.
    0:08:00 So we had like attacks like a mafia boys DDoS in 2000.
    0:08:02 It took down like more than 1 million
    0:08:03 of the 5 million IS servers
    0:08:06 and cost an estimated $2.6 billion in damages.
    0:08:08 And so for part of this,
    0:08:10 basically Microsoft had these big customers
    0:08:11 that were saying like,
    0:08:13 hey, we’re just getting killed because we’re using windows.
    0:08:16 And then this led to in part to trustworthy computing.
    0:08:18 Basically we need to see the light.
    0:08:20 We can’t just keep doing business as is.
    0:08:23 Bill Gates saw a very early version of a book
    0:08:25 that Microsoft folks were writing
    0:08:26 on these security practices.
    0:08:29 And basically that led him to say like,
    0:08:31 we need to completely change what we’re doing.
    0:08:32 We’re losing trust with customers.
    0:08:33 And then that was the beginning
    0:08:36 of what we consider traditional security activities today.
    0:08:38 We have threat modeling, stride,
    0:08:41 all of these things are being birthed around this time.
    0:08:43 We also get more compliance.
    0:08:46 So PCI DSS version one was written in 2004.
    0:08:48 This mandated security activities.
    0:08:50 Again, vendors are trying to get themselves
    0:08:53 into the standards so that they can sell more product, right?
    0:08:54 It’s like, okay, well,
    0:08:56 if you’re going to deal with payment card data,
    0:08:59 then you need to do web scanning, for example.
    0:09:01 Proofpoint was an example of one of the companies here.
    0:09:04 This was founded in 2002, still around today,
    0:09:06 very successful by email security, right?
    0:09:08 So as soon as you have email being used
    0:09:09 as widely as it is today,
    0:09:11 and we also have email viruses, it’s okay,
    0:09:12 we’re going to need something
    0:09:14 to filter out spam and viruses.
    0:09:16 So Proofpoint started that.
    0:09:19 And then also improve a big web application firewall
    0:09:21 that’s also still around today.
    0:09:23 Okay, phase three is DevSecOps.
    0:09:25 So the year is 2013,
    0:09:26 billboard number one is ThriftShop,
    0:09:29 box office number one is Ironman.
    0:09:30 Who does security?
    0:09:31 It’s everybody’s job.
    0:09:32 We’ve collectively decided
    0:09:34 that basically security doesn’t scale.
    0:09:36 Like we’ve been this sign off function
    0:09:38 that you have to do with security
    0:09:40 before you ship your product for the year.
    0:09:41 And now we’re moving to cloud
    0:09:43 and we’re doing continuous deployment.
    0:09:43 And security is like,
    0:09:45 I don’t know when I do these assessments anymore.
    0:09:48 So what we do is we basically take every single developer
    0:09:50 and tell them, guess what,
    0:09:52 good news, you’re a security person now.
    0:09:54 So we’re also getting more and more mega breaches.
    0:09:56 If you look at the numbers from this time,
    0:09:58 every single year it’s exponential growth
    0:10:00 in the number of public breaches,
    0:10:02 the size of the breaches, the damage in the breaches,
    0:10:04 vendors still exploding.
    0:10:06 So EDR, Next Gen Firewall detection,
    0:10:09 all the posture managements, dev training, bug bounty.
    0:10:12 Milestones, the first use of the term DevSecOps
    0:10:13 was actually in 2013.
    0:10:15 And we had the first CSPM,
    0:10:17 which gave birth to this massive posture management industry
    0:10:18 that we have today.
    0:10:20 We start to see no before, right?
    0:10:22 It’s like we’re gonna train developers continuously.
    0:10:24 Developers are gonna learn about
    0:10:25 all of the types of cross-site scripting
    0:10:28 and SQL injection with one day,
    0:10:29 like once per year of training where they learn it
    0:10:32 and then they immediately forget it the next day.
    0:10:34 We also have big bug bounties.
    0:10:36 So crowd sourcing more and more vulnerabilities
    0:10:38 in the hopes that the attackers aren’t gonna use these things
    0:10:40 to cause massive breaches for us.
    0:10:42 So much posture management.
    0:10:45 So the first was cloud security posture management.
    0:10:47 Evident was the first company here.
    0:10:49 At Netflix, they had also created SecurityMonkey,
    0:10:51 which is basically open source posture management.
    0:10:53 And since then it’s just like posture management
    0:10:55 just exploding all over the place.
    0:10:57 We have AppSec posture management,
    0:10:58 Data Security posture management,
    0:11:01 Identity posture management, SSPM,
    0:11:03 like whatever that bottom posture management is,
    0:11:05 just so much posture management everywhere.
    0:11:07 And what these things are really good at doing
    0:11:08 is like going and finding problems
    0:11:10 after they’re already deployed, right?
    0:11:11 And then you have to go do something about it.
    0:11:12 ‘Cause just knowing about risk,
    0:11:14 you can just tell your boss like,
    0:11:16 “Hey, okay, well, here’s all the risk that we have.
    0:11:18 They’re gonna want you to reduce it somehow.”
    0:11:19 And so what we moved to,
    0:11:21 since this is now developer zoning security,
    0:11:22 is we rip a bunch of JIRA tickets for them
    0:11:24 and we call it a day.
    0:11:26 So we also are getting at this time job shortage.
    0:11:29 The first time the job shortage news articles
    0:11:31 was in 2015, early 2016.
    0:11:34 We’re short a million jobs already in 2016.
    0:11:35 This is just piling up more and more.
    0:11:36 We don’t have enough security people
    0:11:39 to actually do the work that we need them to do.
    0:11:41 So where does this leave us?
    0:11:43 I think that we’re entering a new phase,
    0:11:44 phase four of security,
    0:11:46 where basically telling developers,
    0:11:48 “It’s your job, you fix security all the time.”
    0:11:49 Didn’t particularly scale well.
    0:11:52 I think that that’s becoming very evident today.
    0:11:53 So years 2020,
    0:11:55 blinding lights is number one,
    0:11:57 box office is bad boys for life.
    0:11:58 Who does security?
    0:12:00 I think systems do security.
    0:12:02 What we’re doing doesn’t scale.
    0:12:04 We have developer fatigue.
    0:12:05 I hear people tell me all the time like,
    0:12:07 “Oh, we take the posture management
    0:12:08 and then we just filter out everything
    0:12:09 that’s not higher critical.”
    0:12:12 And then we ship those JIRA tickets to developers.
    0:12:13 Training relentlessly, obviously,
    0:12:15 it doesn’t matter how many times we’ve trained developers
    0:12:17 on like all the SQL injection types.
    0:12:19 They still don’t remember it
    0:12:20 and really they shouldn’t have to.
    0:12:22 So Milestones, one of the projects
    0:12:24 they really informed how I see this is Limer,
    0:12:26 the Netflix released in 2015.
    0:12:30 Google launched the Identity Aware Proxy in 2017.
    0:12:33 Chrome added a password manager by default back in 2018.
    0:12:35 And Clint Gibbler, one of my friends
    0:12:37 and somebody that has done a lot of work in the space
    0:12:39 did his talk in 2021
    0:12:42 called “How to Eradicate Vulnerability Classes.”
    0:12:45 So Limer, when I got to Netflix, it was in 2017.
    0:12:46 And I remember just being blown away
    0:12:48 at how easy it was for our developers
    0:12:50 to just get things like certificates
    0:12:53 without having to select a Cypher Suite
    0:12:54 and pick crypto parameters and rotate it
    0:12:57 and store your private keys securely.
    0:12:58 It was just made it like dead symbol.
    0:13:00 And the benefit of this is that developers
    0:13:02 never have to learn about crypto anything.
    0:13:03 They just get it for free.
    0:13:06 Google has done just probably more work than anybody here.
    0:13:10 So we’re gonna upscale people to HTTPS automatically.
    0:13:12 Chrome updates itself, which became standard
    0:13:14 for many other pieces of software.
    0:13:16 We have these basically like impossible
    0:13:18 to mess up Golang libraries
    0:13:20 to handle a lot of security things.
    0:13:22 And actually, my mom sent me this article recently.
    0:13:25 Mom’s so funny, she knows that I work in security
    0:13:27 and sends me like everything that has security in it
    0:13:28 out of Wall Street Journal.
    0:13:29 And usually it’s like something
    0:13:31 that either happened three months ago
    0:13:33 or it’s got nothing to do with me.
    0:13:35 But this one was written by Larry Ellison
    0:13:36 and it’s not very old.
    0:13:38 His point is it’s time to hand over
    0:13:40 cyber security to computers.
    0:13:42 Basically just relentlessly hounding the users
    0:13:44 and like trying to get the users to be smarter.
    0:13:45 Like it doesn’t work anymore.
    0:13:47 What we want to get is developers
    0:13:50 back to just writing app code, like working on the business
    0:13:52 and not having to be like security people all the time.
    0:13:54 So today, if you think about it,
    0:13:57 devs have to burn down this never ending pilot Jira tickets.
    0:13:59 This causes annoyance with the security team.
    0:14:00 If you had a friend that only showed up
    0:14:02 when they wanted you to do something,
    0:14:03 you’re probably gonna start avoiding that friend
    0:14:04 and we’re getting a ton of that.
    0:14:07 What if instead, if they just use systems,
    0:14:09 they made good security choices on their behalf
    0:14:11 and forget about all of this like
    0:14:13 training relentlessly all the time.
    0:14:15 So conclusions, I was part of this move
    0:14:18 from like waterfall to continuous and then saw this.
    0:14:21 We just heap stuff onto our developers plate
    0:14:23 and then saw developers learn to resent
    0:14:24 and avoid security more and more.
    0:14:27 I think what we should do instead is help them out.
    0:14:28 Like they’re very, very busy people.
    0:14:31 We should build a system that makes it fast and easy
    0:14:33 for them to go do something they want to do
    0:14:35 and then has security victim as a side effect.
    0:14:38 So it’s like when you want your dog to take vitamins,
    0:14:40 you don’t just put vitamins in your hand
    0:14:41 and offer them to the dog.
    0:14:42 You put the vitamins in the peanut butter
    0:14:43 and the dog wants the peanut butter
    0:14:45 and the dog gets the vitamins too.
    0:14:46 I think this is what we should be doing
    0:14:47 for our developer users.
    0:14:50 – Speaking of meetings to make things easier
    0:14:52 for our developers, let’s get a sense
    0:14:55 of what these hacks can really look like in 2024.
    0:14:57 – Now, usually in this talk,
    0:14:58 I like to talk about solar winds,
    0:15:00 but we actually have a better example
    0:15:03 that was gifted to us, the XT-utils attack.
    0:15:05 So everybody here has heard about this by now,
    0:15:09 but this was some group likely, I think backed by a state
    0:15:12 that infiltrated an open source data compression project
    0:15:14 called XT-utils.
    0:15:19 – That was Faraz Abukadijay, founder and CEO of Socket.
    0:15:22 So XT-utils has taken the security industry by storm
    0:15:25 since it introduced a backdoor via open SSH,
    0:15:27 which is a critical piece of infrastructure
    0:15:30 used by millions of servers around the world.
    0:15:32 Let’s hear from Faraz regarding what really happened there.
    0:15:34 To get a sense of the kind of security offenders
    0:15:37 we’re now dealing with in 2024
    0:15:38 that can involve multiple years,
    0:15:40 multiple contributors, social engineering,
    0:15:42 the potential for state actors and more.
    0:15:46 – The way that they did this was just so interesting.
    0:15:49 And it’s something that, I mean, look, I’m sad that it happened,
    0:15:51 but I’m also like, I’ve been telling you guys
    0:15:52 about this for so long.
    0:15:54 I’m sort of like kind of satisfied in a way
    0:15:56 that finally there’s an example
    0:15:58 that’s really caught the imaginations of folks.
    0:16:02 So what happened here was we had a group,
    0:16:03 like I said, probably state backed,
    0:16:05 winning over the contributor of the project
    0:16:07 over several years of work.
    0:16:09 So that’s like a scale of time invested in this
    0:16:12 that we haven’t seen in other attempts like this.
    0:16:14 And then they introduced a sophisticated though
    0:16:17 not flawless backdoor that was aimed
    0:16:19 at compromising SSH servers.
    0:16:22 So it’s a pretty multi-layered vulnerability.
    0:16:23 There were multiple personas involved
    0:16:25 from identities that hadn’t been seen
    0:16:26 anywhere on the internet before.
    0:16:28 So that kind of is another indication
    0:16:31 that probably this was someone relatively sophisticated.
    0:16:33 This wasn’t just someone doing it for the LULs.
    0:16:36 And so probably suggesting kind of state backed actors here.
    0:16:38 And then just the way the timeline
    0:16:40 and the kind of some of the stuff that they did
    0:16:42 also seems to indicate that it might be
    0:16:44 like the same people behind SolarWinds.
    0:16:46 Probably, but again, this is all just kind of speculation.
    0:16:47 I want to kind of go into a little bit of,
    0:16:49 so you can kind of see just the character
    0:16:51 of what this attack kind of looks like.
    0:16:54 So this is kind of individual who ended up committing
    0:16:56 and releasing the malicious code.
    0:17:00 And this is his first email patch to the mailing list
    0:17:04 where they do the development for this project XCutils.
    0:17:05 And it’s interesting.
    0:17:08 This is just kind of a totally pointless patch, right?
    0:17:09 This is like the kind of thing that as a maintainer
    0:17:12 you get all the time someone just drive by dropping in
    0:17:15 an editor config file, which is basically does nothing, right?
    0:17:17 It’s a no op in terms of the functionality of the project.
    0:17:19 And oftentimes you’ll see these from people
    0:17:20 who just want to get to be able to say
    0:17:22 that they’re a contributor to a project.
    0:17:24 It doesn’t require any understanding of the project.
    0:17:26 So it’s just noise, but you can see their first attempt
    0:17:28 to kind of get involved in the project.
    0:17:30 Then they sent another patch a month later,
    0:17:33 fixing some kind of build problem.
    0:17:36 And they also sent a couple of more patches after this one,
    0:17:38 all totally ignored by the maintainer,
    0:17:41 who at this point has been maintaining this project
    0:17:43 for about 15, maybe 20 years.
    0:17:45 This is a long time project.
    0:17:47 And the guy running it is just,
    0:17:49 at this point it’s in maintenance mode.
    0:17:51 It’s basically, he’s sort of burned out.
    0:17:53 He’s sort of kind of half maintaining it,
    0:17:55 checking the mailing list once in a while,
    0:17:57 but really not actively working on this anymore.
    0:18:00 So it’s something that a lot of the maintainers go through.
    0:18:01 And so then finally the maintainer,
    0:18:03 this is like, I think three more months
    0:18:05 after the last email, we see that the maintainer
    0:18:09 just randomly comes by and merges a couple line change
    0:18:11 to the project that is the first code
    0:18:14 from this GITAN individual that’s actually
    0:18:15 included in the project.
    0:18:17 And what I think is interesting about this is
    0:18:19 all of his other patches were ignored.
    0:18:22 The patch that was merged is this like trivial two line patch
    0:18:24 that you can just look at and kind of,
    0:18:25 as an overloaded maintainer, you can look at this
    0:18:27 and sort of figure out what it’s doing.
    0:18:28 And oh, it fixes a bug, cool.
    0:18:29 Let me just merge it and move on.
    0:18:33 The bigger multi-hundred line patches were ignored, right?
    0:18:34 Typical, also typical behavior
    0:18:36 for an overloaded maintainer, right?
    0:18:38 Okay, then a couple of months go by
    0:18:41 and now we see a new character enter the picture.
    0:18:45 This guy Gigar Kumar sends kind of a few emails
    0:18:49 complaining that some of GITAN’s patches weren’t landing.
    0:18:53 This is often used to pressure maintainers
    0:18:55 to include code in projects.
    0:18:56 Patches spend years on this mailing list.
    0:18:58 There’s no reason to think anything is coming soon.
    0:18:59 So aggressive, right?
    0:19:01 At this point, remember he’s already landed
    0:19:03 a few of the patches, but the pressure is building here.
    0:19:07 And then this is insert project name still maintained.
    0:19:09 That is the bane of a maintainer’s existence.
    0:19:11 It’s the meanest kind of issue you can open up
    0:19:13 on a project, in my opinion.
    0:19:15 This has happened to me many times.
    0:19:16 I had a couple screenshots here.
    0:19:18 Is this still being developed?
    0:19:19 And like on a perfectly active project
    0:19:21 because their PR wasn’t looked at for a little while, right?
    0:19:23 Here’s another one on one of my projects.
    0:19:24 Is this project dead?
    0:19:25 It’s not nice.
    0:19:27 Don’t do this, people.
    0:19:28 And I think one of the interesting things
    0:19:29 about this whole situation is that,
    0:19:31 this is another one of the things I’ve seen change
    0:19:33 in the way that open source is done is,
    0:19:35 traditionally, you think of a project like Linux
    0:19:37 or WordPress or these big foundation-backed projects.
    0:19:39 They have the structure up here at the top
    0:19:41 where you have one project, one entity,
    0:19:43 with many, many maintainers that are participating
    0:19:44 in the project.
    0:19:46 A lot of times they’re paid by their employer
    0:19:47 to even work on the project
    0:19:49 and to submit patches as part of their day job, right?
    0:19:52 But what we see a lot more of as we’ve shifted
    0:19:55 into this world of many, many, many dependencies,
    0:19:58 a lot of tiny dependencies is more of a structure like this
    0:20:00 where you have an individual with hundreds, potentially,
    0:20:02 hundreds of projects that they take care of.
    0:20:04 And that was the case here with Lassie Collin.
    0:20:06 He had multiple projects that he was managing
    0:20:08 as an individual maintainer.
    0:20:09 Okay, so let’s continue on.
    0:20:11 So this is three months has gone by.
    0:20:13 He replies, he apologizes for the slowness,
    0:20:16 and he also adds in a bit about how Giotan
    0:20:19 has helped him off-list with XTutils.
    0:20:21 So probably they have some kind of chat conversation
    0:20:24 going off-list now and they’re collaborating more closely,
    0:20:25 building up the trust.
    0:20:28 And he says he might have a bigger role in the future,
    0:20:29 at least with XTutils.
    0:20:31 It’s clear that my resources are too limited
    0:20:33 and something has to change in the longterm.
    0:20:36 So the kind of idea has now been planted in his mind
    0:20:38 that he probably should give access to somebody else
    0:20:40 to help maintain the project.
    0:20:41 And again, this all sounds nefarious
    0:20:43 ’cause I’m doing it in a talk and I have slides up here,
    0:20:45 but this is also open source working correctly.
    0:20:46 This is thinking about, oh, hey,
    0:20:47 maybe I’m not the best maintainer.
    0:20:49 Maybe I should hand this off to somebody
    0:20:51 that’s pretty normal as well.
    0:20:53 At this point, nothing actually nefarious has happened.
    0:20:54 By the way, there’s no bad code that’s been included.
    0:20:56 This is just laying the foundation.
    0:20:57 He said a couple of weeks go by.
    0:21:00 So now we have this character, Jigar Kumar, who enters
    0:21:03 and this person’s much more aggressive
    0:21:04 and really starts to apply more pressure.
    0:21:07 So they go over one month and no closer to being merged.
    0:21:08 Not a surprise.
    0:21:10 So like dropping into threads to just sort of
    0:21:12 nag the maintainer and kind of make him feel
    0:21:13 like he’s not doing a good job.
    0:21:16 Progress will not happen until there is a new maintainer.
    0:21:18 And then the maintainer finally replies and pushes back
    0:21:19 and says, hey, I haven’t completely lost my interest here,
    0:21:21 but I’ve been having some mental health issues
    0:21:23 and I have a lot of things going on in my life.
    0:21:25 But again, maybe Gia Tan will have a bigger role
    0:21:26 in the project.
    0:21:28 And so a few months after that,
    0:21:30 Lassie Collin merges the first commit with Gia Tan
    0:21:32 as the author you can see here.
    0:21:33 And they actually are listed as an author.
    0:21:36 This is a pretty innocuous change.
    0:21:39 And then again, the pressure continues from Jigar and Dennis
    0:21:41 who’s this other persona that are both there
    0:21:43 and really just support the idea
    0:21:44 that Gia should be made a maintainer.
    0:21:46 And you can see here, you ignore the patches
    0:21:48 that are rotting away on this mailing list.
    0:21:50 Right now you choke your repo.
    0:21:53 Why wait until 5.4.0 to change maintainer?
    0:21:55 Why delay what your repo needs?
    0:21:56 Right?
    0:21:58 So applying the pressure.
    0:21:59 And then again, the last one here is great.
    0:22:01 Like, why can’t you commit this yourself, Gia?
    0:22:02 I see you have recent commits.
    0:22:03 So just kind of pushing more and more.
    0:22:06 And then finally Lassie says, again,
    0:22:08 Gia Tan has been really helpful off-list.
    0:22:10 He’s practically a co-maintainer already.
    0:22:12 And then finally, this is the first email
    0:22:15 about two years after the very first interaction
    0:22:17 with the mailing list where Gia Tan
    0:22:20 is actually now doing the release notes for the project.
    0:22:21 He’s been made a maintainer
    0:22:23 and this is the first release going out.
    0:22:26 So two year kind of effort here.
    0:22:27 If this is indeed state-backed,
    0:22:29 this is probably not the only thing they did
    0:22:31 in that two year period, right?
    0:22:33 They probably have other things going at the same time, right?
    0:22:35 So we shouldn’t overreact and assume
    0:22:37 that Linux is like totally backdoor or anything like that.
    0:22:39 But also like, probably this isn’t the only thing
    0:22:40 that these folks were working on, right?
    0:22:42 So the truth is like somewhere in the middle here.
    0:22:46 – Sophisticated software supply chain attacks
    0:22:49 are not the only ones on our hands in 2024.
    0:22:50 In fact, the XAU Tells Attack
    0:22:53 was performed really without AI.
    0:22:56 So let’s hear from Kevin Tien, founder and CEO of Doppel,
    0:22:59 around the ways that AI is introducing new threat vectors
    0:23:02 and already impacting real world businesses.
    0:23:08 – In 2022, $8.8 billion was lost by consumers alone in the US.
    0:23:11 We’ve had 39 billion credentials
    0:23:14 stolen by bad actors that same year.
    0:23:18 And the cost to launch a disinformation campaign
    0:23:21 that’s AI generated is quickly approaching zero.
    0:23:24 So if you’ve seen a lot of the startups
    0:23:26 that are currently pitching about
    0:23:29 how we can make it easy to generate AI videos
    0:23:33 or how we can make it easy to generate AI voices, right?
    0:23:35 That same sort of stuff is going to the bad guys as well.
    0:23:37 And so how are we seeing this manifest today
    0:23:41 with real world people and real world businesses?
    0:23:45 So one common scheme that has grown super quickly
    0:23:46 just in these past couple of months
    0:23:49 has been the emergence of a lot of deep fake videos,
    0:23:53 specifically deep fake videos of individual personas.
    0:23:56 It could be Taylor Swift, could be Travis Kelsey,
    0:23:57 could also be your CEO
    0:24:00 and could be your financial institutions,
    0:24:02 chief technology officer.
    0:24:04 And so what we’ve quickly been seeing here, right,
    0:24:09 in terms of the landscape is more and more deep fake videos
    0:24:11 being produced in the exact same way,
    0:24:14 models being trained in a very similar way,
    0:24:16 the voice being generated in very similar way
    0:24:18 and the intention of the tech being operated
    0:24:21 in a very similar way all across different platforms,
    0:24:23 whether it’s YouTube, TikTok,
    0:24:26 any sort of video platform out there.
    0:24:27 We’re already seeing deep fakes emerge
    0:24:31 and this impacts a whole bunch of different sort
    0:24:34 of individuals, whether it’s business,
    0:24:37 whether it’s celebrities or even political campaigns.
    0:24:39 Of course, big federal election this year,
    0:24:41 it’s top of mind for everyone.
    0:24:44 The good news, bad news is that it’s already happening
    0:24:46 and we’re seeing it happen across a lot
    0:24:47 of different platforms.
    0:24:49 So I think the biggest thing here though is like,
    0:24:52 this is not necessarily entirely novel,
    0:24:55 attack surface right or entirely new threat, right?
    0:24:57 Like we’ve always had social media,
    0:24:59 we’ve always had video platforms
    0:25:02 and we’ve had bad guys try to create fake content
    0:25:04 to achieve certain means.
    0:25:06 I think the main lesson here
    0:25:08 in terms of what we’re seeing is that
    0:25:10 it’s just become a lot easier to do.
    0:25:12 And so just there’s entire markets around fishing kits
    0:25:16 and there’s entire markets around cyber crime in general.
    0:25:17 We’re gonna start seeing,
    0:25:20 and we’re already seeing that same sort of stuff
    0:25:23 come around with deep fake technology,
    0:25:24 impersonation technology and just,
    0:25:27 how do you personalize attacks more and more
    0:25:29 for your target victim?
    0:25:31 I think the biggest thing too is that
    0:25:33 we’re seeing this not only to run scams,
    0:25:36 but ultimately this stuff is impacting businesses at large.
    0:25:38 I actually just wanna talk this morning,
    0:25:40 chatting with some big banks out there
    0:25:41 and one of the biggest concerns for them
    0:25:44 is how can they watch out for a bank run
    0:25:46 that’s orchestrated by a deep fake campaign, right?
    0:25:48 Or we’ve even seen this effect
    0:25:50 companies outside the financial sector
    0:25:52 where pharmaceutical company had a impersonator
    0:25:54 talk about how Viagra’s gonna be free now
    0:25:58 and saw that impact of stock price very, very quickly.
    0:26:03 It’s again stuff that has happened before,
    0:26:05 but what we’re seeing in 2024
    0:26:08 and what we’re expecting in 2025 and beyond
    0:26:10 is that this just gets easier and easier to do
    0:26:13 and it gets to the point where it makes it really hard
    0:26:15 to tell what’s real or not online.
    0:26:18 And it’s not just deep fakes.
    0:26:20 Here’s a completely different approach.
    0:26:23 This one is a SEO poisoning case,
    0:26:27 so specifically something that we’ve seen out there
    0:26:30 a lot for airline industry, finance industry,
    0:26:33 any industry that has customer support, phone numbers,
    0:26:35 things like that, right?
    0:26:38 We’ve got the traditional SEO poisoning attack
    0:26:41 where people will find a way to get content upranked
    0:26:42 for any given company.
    0:26:45 And what’s interesting is basically
    0:26:48 how well can people do this in 2024?
    0:26:50 What we’re seeing a lot of things happening today
    0:26:53 is that they’re putting it on these third party sites
    0:26:55 that do have great domain ranks.
    0:26:58 Things like Microsoft, it could be LinkedIn.
    0:27:00 We’ve seen a lot with Hub as well of course
    0:27:02 and Webflow, other platforms like that.
    0:27:04 And so they’re taking advantage of the fact
    0:27:06 that these are legitimate third party sites
    0:27:08 with great domain health,
    0:27:10 stuff that Google will quickly uprank
    0:27:12 or any other search engine will quickly uprank.
    0:27:16 And they’re generating content and conversations on forms.
    0:27:19 For example, how do I speak to a live agent at United?
    0:27:22 How do I speak to a live agent at Uber, right?
    0:27:24 And what we see happen here is,
    0:27:27 they’re able to generate a bunch of the spam content
    0:27:29 across these different third party forms,
    0:27:30 get them all upranked,
    0:27:34 get them all to dominate that first page of search results.
    0:27:36 And again, it’s just a classic case of,
    0:27:38 well, they would have to script this, right?
    0:27:40 And generate the content now.
    0:27:42 They can make it more dynamic with AI
    0:27:44 and generate the AI specifically.
    0:27:48 – Of course, it’s not all doom and gloom.
    0:27:50 With every opening on offense,
    0:27:52 there’s equal opportunity for defense.
    0:27:55 Here is Andrey Sofansi, founder and CEO of Lumos,
    0:27:58 taking us back to where we started in this episode
    0:28:00 through a historical arc that brings us
    0:28:03 to a digital era of autonomy.
    0:28:05 So what do we do now that we’re in this new era?
    0:28:06 And if you happen to be a company
    0:28:08 hiring security professionals,
    0:28:11 should you be thinking about things any differently?
    0:28:14 – I just want to take you a little bit
    0:28:17 on a historical journey, all right?
    0:28:20 So the funny thing is, if you look 60 years back,
    0:28:22 we are all ideas.
    0:28:24 So there’s two types of factories.
    0:28:28 There’s a product factory and there’s an idea factory.
    0:28:30 So what the product factory is,
    0:28:32 is usually where the cars are born, right?
    0:28:34 Or where windows are made.
    0:28:36 And where the idea factory is,
    0:28:40 is where we create and design those cars, right?
    0:28:44 And especially the idea factory changed in the recent years
    0:28:47 and changed like two years ago again.
    0:28:51 So the idea factory looks something like the office
    0:28:53 or more like, you know, in the ’60s.
    0:28:55 In the ’60s, ’50s, there were no computers.
    0:28:57 So it was really interesting.
    0:29:01 And we mostly used typewriters and pen and paper.
    0:29:03 So then the computers came about
    0:29:05 and we digitized the office.
    0:29:07 That was kind of the first step.
    0:29:11 IBM, SAP, Oracle, Microsoft,
    0:29:14 all those big companies came about and digitized it.
    0:29:16 So that was step one.
    0:29:20 Step two is we cloudified, I guess, the office.
    0:29:22 I was like with Salesforce.
    0:29:25 They kicked it off and Workday and Atlassian,
    0:29:26 those were the first cloud companies.
    0:29:27 So suddenly we’re in the cloud.
    0:29:29 So it was where AWS was born.
    0:29:33 I think 2004, 2005, that’s when we cloudified it.
    0:29:35 Then something interesting happened
    0:29:37 is we made it collaborative, right?
    0:29:39 Workday is not really collaborative.
    0:29:40 Neither is Salesforce.
    0:29:44 But then suddenly Zoom, Slack, Figma, Airtable,
    0:29:46 all those kind of great companies
    0:29:48 came about in the 2010s.
    0:29:50 And suddenly it became very collaborative.
    0:29:51 So that was like kind of, I would say,
    0:29:55 the third change that happened in software,
    0:29:56 which is pretty cool.
    0:30:00 Now, what changed in the last two years
    0:30:04 is we moved from just like digitizing it to cloud,
    0:30:08 to collaboration, to autonomy, right?
    0:30:11 So we’re creating more and more autonomous software.
    0:30:12 And it started honestly for the first time
    0:30:14 with something like a Grammarly,
    0:30:17 where they are like more like kind of co-pilots
    0:30:18 that help you kind of do a job better.
    0:30:20 Even like GitHub, this is GitHub co-pilot,
    0:30:21 they’re in the middle.
    0:30:23 They’re not fully autonomous,
    0:30:25 but they help you do your job better.
    0:30:27 The big trend that we’re seeing right now
    0:30:29 is especially OpenAI is bringing out
    0:30:30 at the end of the year,
    0:30:33 reason, models that can reason.
    0:30:35 And they can literally talk with themselves
    0:30:37 and do certain things, so really spooky.
    0:30:39 And we’ve seen this as well like Devon,
    0:30:41 that’s kind of a new kind of type of software engineer
    0:30:43 and AI software engineer
    0:30:45 that just like basically codes themselves.
    0:30:48 So we’re moving from GitHub co-pilot or Grammarly
    0:30:50 to actually systems and services
    0:30:53 that build things themselves.
    0:30:56 So that is actually a whole new paradigm
    0:30:56 that’s changing.
    0:30:58 And we’re like, okay, shoot,
    0:31:00 how do we equip ourselves for that?
    0:31:02 So to summarize,
    0:31:03 actually there are kind of three waves,
    0:31:05 I just call them two.
    0:31:07 The first wave is the digitization,
    0:31:09 the second one is a collaboration,
    0:31:11 the third one is the autonomy.
    0:31:13 And now we’re at the third one.
    0:31:15 So the interesting thing is that I’m thinking about
    0:31:18 on a daily basis is apps and access.
    0:31:21 If you think about everything that you’re using,
    0:31:22 those are apps.
    0:31:23 We’re on Zoom, then on Slack,
    0:31:26 then we go and SSH into a server,
    0:31:28 which is also an app more or less,
    0:31:30 then we use GitHub, so everything is apps.
    0:31:33 Apps are literally our live blood without apps.
    0:31:35 We can’t do things.
    0:31:36 The question is like,
    0:31:37 I think that we as security professionals
    0:31:40 need to ask ourselves more and more is,
    0:31:43 how are we gonna manage all those apps
    0:31:45 with more and more service accounts coming up, right?
    0:31:49 And with like software doing the job themselves.
    0:31:50 So how do we deal with that?
    0:31:54 So I love the metro framework.
    0:31:55 I really love it.
    0:31:58 If you think about identities,
    0:32:00 there are certain identities on different tracks.
    0:32:03 So marketing has their identities, right?
    0:32:07 Marketing ops, the mansion, content,
    0:32:09 customer success has their tracks.
    0:32:13 And each station is more or less an application
    0:32:15 or like an entitlement, right?
    0:32:17 And some of those overlap, right?
    0:32:20 So for example, customer success and sales overlap
    0:32:21 maybe in Salesforce.
    0:32:25 Then design and marketing overlap in Figma.
    0:32:27 And then especially engineering,
    0:32:29 there are probably like multiple engineering departments
    0:32:32 if we zoom in and they overlap when it comes to,
    0:32:34 especially on an entitlement level,
    0:32:36 different permissions that they have access to.
    0:32:38 So the only interesting thing is people,
    0:32:41 which are more of those wagons,
    0:32:44 they jump from one station to another.
    0:32:47 And each station again is an app on entitlement.
    0:32:49 And why I think that this is interesting is,
    0:32:51 right now how we think about the world
    0:32:52 as a world of RBAC.
    0:32:55 – Quick interruption here.
    0:32:59 For the uninitiated, RBAC means role-based access control.
    0:33:01 So instead of assigning permissions individually,
    0:33:03 you’re granting them based on a role.
    0:33:08 – RBAC is not moving stations.
    0:33:11 RBAC basically means, you are a marketing person
    0:33:15 and you have access to everything on this marketing tier.
    0:33:19 Even though probably a lot of that stuff you never use.
    0:33:22 And sales or engineering is especially spooky.
    0:33:24 Engineering, you and DevOps,
    0:33:26 you have access to all customer data
    0:33:29 because an incident might happen and you need access to it.
    0:33:31 Now on top of that,
    0:33:34 we have all those service accounts coming up
    0:33:38 and soon autonomous actors, agents coming up,
    0:33:41 that will also, if we still use RBAC,
    0:33:44 get access to all of those things.
    0:33:45 Even though they don’t need it.
    0:33:47 So the concept is I’m a metro station
    0:33:49 and I need each permission entitlement
    0:33:51 just for a short amount of time.
    0:33:55 And I think especially as complexity rises.
    0:33:58 So we are going from like a hundred actors
    0:34:00 to a thousand to 10,000.
    0:34:02 And also the apps become more complicated.
    0:34:06 So instead of having just one or two or three metro stations,
    0:34:08 I will have thousands of metro stations.
    0:34:12 Because I can get access to 10 EC2 instances
    0:34:14 and just like the granularity and the cloud
    0:34:15 and the snowflake is gonna become
    0:34:17 more and more and more granular.
    0:34:19 So the question is like, how are we gonna manage that?
    0:34:22 What’s the new paradigm to manage that?
    0:34:25 So what I believe, how we need to rethink things
    0:34:28 is security was often seen as analysts, right?
    0:34:31 Actually, security started as hackers.
    0:34:34 Security people were those people that hacked the networks
    0:34:36 and they were the people that were deep in Linux
    0:34:38 with assist admins.
    0:34:40 And actually most security people were assist admins before
    0:34:43 because there was no security 30 years ago
    0:34:45 and they were true hackers.
    0:34:47 And then suddenly all those kind of great solutions
    0:34:50 came about and they said, here’s an alert,
    0:34:52 there’s an alert, here’s an alert.
    0:34:53 And we’re gonna alert you about all those things
    0:34:56 and you can remediate it very easily.
    0:34:58 And so I feel like more and more security
    0:35:01 became an operating department.
    0:35:02 Similar thing happened to IT.
    0:35:05 IT used to be the hackers and slowly but suddenly
    0:35:07 they became ticket resolvers.
    0:35:10 Security became a little bit of alert resolvers.
    0:35:12 IT became ticket resolvers.
    0:35:14 And I think the new paradigm that we need to think about
    0:35:16 as we’re thinking about entitlements and access
    0:35:20 as a metro station, security and IT needs to see themselves
    0:35:25 as the architects of that metro station, more or less.
    0:35:28 And what DevOps and infrastructure is to full stack teams.
    0:35:31 So I think the same thing we need to think about
    0:35:32 IT and security.
    0:35:37 IT and security need to become so to say infrastructure teams
    0:35:40 to each department, right?
    0:35:42 And this kind of moves us back to security
    0:35:46 actually hiring for engineering rather than analysts.
    0:35:48 Especially also, as the AI will probably automate
    0:35:50 most of the analyst work.
    0:35:52 So that’s I think a very important insight
    0:35:54 is when it comes to career development,
    0:35:57 as it comes to what type of profile you need to hire,
    0:35:59 especially engineers and analysts
    0:36:01 and building on top of solutions that you’re buying
    0:36:03 is very important.
    0:36:07 So basically the premise in this first act is
    0:36:09 software is becoming an autonomous.
    0:36:12 It enables us to create more and more.
    0:36:15 Because of that, entropy is increasing.
    0:36:19 There are more apps, more entitlements and more actors.
    0:36:23 And so what needs to change is security needs to handle
    0:36:27 this infrastructure with some type of technology operations
    0:36:30 or without some kind of technology infrastructure.
    0:36:33 So I think that is kind of one important change
    0:36:36 that we need to see as this whole market is changing.
    0:36:39 Now, here’s the second thing.
    0:36:41 It’s about startups by the way.
    0:36:44 This is like kind of an appell to all my entrepreneurs.
    0:36:46 I believe that we need to build compound businesses
    0:36:47 from day one.
    0:36:49 So what does that mean?
    0:36:52 So security CISOs probably have this problem
    0:36:56 that they need to use 50 different tools.
    0:36:57 And that actually lasts two years,
    0:37:00 especially as the economy has gone a little bit down.
    0:37:02 CISOs ask themselves a lot of,
    0:37:05 in terms of like, how can I consolidate?
    0:37:07 And that kind of sucks for startups at the beginning,
    0:37:08 I would say.
    0:37:12 Like, okay, we’re starting solving this unique pain point.
    0:37:13 But then CISOs are like, yeah,
    0:37:16 but you know, I have 80 vendors to manage.
    0:37:19 And so the question is that I ask myself a ton
    0:37:23 is how can we build compound businesses from day one?
    0:37:26 So how can you actually build a platform from day one,
    0:37:27 even though you’re a startup?
    0:37:29 And actually counter if people say,
    0:37:30 I need to consolidate,
    0:37:33 that you start up actually can consolidate.
    0:37:35 So it was 2023.
    0:37:37 The top three priorities for CISOs
    0:37:40 was vendor consolidation, optimizing SaaS licensing.
    0:37:43 Because of course you don’t wanna let people go.
    0:37:46 You rather wanna kind of first increase your software spend.
    0:37:48 So what does it mean for entrepreneurs?
    0:37:49 The question for entrepreneurs is like,
    0:37:51 how can I build a compound business from day one?
    0:37:54 We’ve seen this actually done well across many companies.
    0:37:56 I think Datadog is an awesome company
    0:37:59 that does this super well more on the DevOps side.
    0:38:03 For the longest time, right, they’ve had one product.
    0:38:04 And then actually they switched
    0:38:06 and became this kind of layered product
    0:38:08 for anything observability,
    0:38:10 whether it’s security observability,
    0:38:13 infrastructure observability, application observability,
    0:38:15 they were able to build a compound product.
    0:38:18 And Figma rethought this whole kind of process
    0:38:21 of before there was Sketch, there was Zeppelin.
    0:38:23 And what basically Figma said is like,
    0:38:24 what is the underlying concept
    0:38:27 that’s the same across all of those?
    0:38:30 And how can I build a solution that covers that all?
    0:38:30 And I think by the way,
    0:38:32 the whole kind of thing that we’ve seen in here
    0:38:34 is like we had first the bundling era.
    0:38:37 By the way, with Microsoft Oracle and SAP,
    0:38:38 people didn’t have a lot of applications.
    0:38:41 They said like, Oracle is doing it all.
    0:38:42 That was that at the beginning.
    0:38:44 And then slowly with like cloud,
    0:38:47 especially AWS and Azure made that happen,
    0:38:50 cloud became so approachable by everyone
    0:38:51 that suddenly, you know,
    0:38:54 we had all those collaboration tools come up.
    0:38:59 I do think we’re changing back to an industry of rebundling,
    0:39:02 especially as we have this autonomous wave coming up.
    0:39:03 I do believe, I mean, like Wiz is actually
    0:39:05 a great example of that,
    0:39:07 is they started with like kind of a point solution,
    0:39:10 but spread out very aggressively
    0:39:12 and build a compound product very quickly.
    0:39:15 So how are you going to manage that complexity?
    0:39:17 And then the question is like,
    0:39:19 how much did I protect my insider threat in some way?
    0:39:20 Why?
    0:39:23 Because go back to the metro station,
    0:39:25 if the developers access to everything,
    0:39:27 suddenly this intruder can just like hop
    0:39:30 from one station to another and do harm.
    0:39:33 So how can we make sure that it’s kind of just in time,
    0:39:35 only when you are at the station,
    0:39:37 you actually can have access to it?
    0:39:39 Now, that gets kind of hard
    0:39:42 with like millions of permissions.
    0:39:43 So what I believe it’s going to happen,
    0:39:45 and this is something that we are really working on right now
    0:39:48 with models that come out at the reason.
    0:39:52 Basically, I think models will be able to reason better
    0:39:54 than our security analysts
    0:39:58 in terms of what a certain role should have access to, right?
    0:40:01 So basically an agent on your identity
    0:40:04 and access management system will look into, okay,
    0:40:09 we had 20 new tickets where these engineers needed access
    0:40:13 to this type of database that live in North America.
    0:40:16 They will automatically update your roles
    0:40:17 and downgrade your roles,
    0:40:19 or at least at the beginning be a co-pilot for you
    0:40:22 and suggest, hey, this role should be updated in this way,
    0:40:25 or those two roles should be merged in that way.
    0:40:27 So this is just like a case study
    0:40:31 where agents will have a huge impact.
    0:40:33 The biggest story I think about security is,
    0:40:36 is that there’s enormous complexity and risk,
    0:40:38 you can never reduce risks to zero.
    0:40:42 The cool thing is if you move more to an engineering mindset,
    0:40:45 where you actually fine-tune your agents and models
    0:40:47 on top of your infrastructure,
    0:40:50 you will be able to solve certain problems
    0:40:53 that you were never able to solve before.
    0:40:56 The RAG will look into, okay, is this privileged access?
    0:40:58 So basically the AI will be able,
    0:41:00 you think about you have a million permissions,
    0:41:02 how are you gonna tag where this permission
    0:41:05 is actually sensitive or not?
    0:41:06 It doesn’t always say read only,
    0:41:09 it doesn’t always say admin access.
    0:41:12 So the AI will be able to understand or can understand
    0:41:14 if that permission is sensitive or not, right?
    0:41:15 So you can reason, okay,
    0:41:18 this person has privileged access or not,
    0:41:21 and then this person can also reason on role anomalies.
    0:41:24 Oh man, you know, you are in sales
    0:41:27 and you have access to this right, access in AWS,
    0:41:31 and no one else on your team has that access.
    0:41:32 So basically, you know,
    0:41:35 a RAG will ask themselves is,
    0:41:38 how privileged is this permission, right?
    0:41:40 What is your usage in that permission?
    0:41:44 And is anyone else that has similar HRIS characteristics,
    0:41:45 do they have that access?
    0:41:48 And you can already do this now pretty easily, right?
    0:41:49 This is like kind of more,
    0:41:51 it’s not reasoning themselves,
    0:41:53 but you kind of guide them to go through those steps.
    0:41:55 That’s what chain of thought means.
    0:41:56 And the last thing I want to say is like,
    0:41:59 the cool thing about access is it can be preventative.
    0:42:02 So here’s one thing that we’re already doing.
    0:42:04 If you create a ticket in JIRA,
    0:42:06 or if you create a Slack message and say like,
    0:42:09 hey, can I get this access please in a public channel?
    0:42:12 How AI can detect that you ask for access?
    0:42:15 And usually the worst thing that can happen
    0:42:16 is like back channel access.
    0:42:18 What that means is someone gives you access
    0:42:20 without following processes.
    0:42:23 Now, you can alert yourself that this happened,
    0:42:25 oh, this person got access without approval,
    0:42:26 but the better way is to prevent
    0:42:29 that from happening in the first place.
    0:42:30 I think the main takeaway is,
    0:42:32 there will be less and less analysts
    0:42:33 because agents will take over
    0:42:36 and you need to upscale them to become more engineers
    0:42:38 or even prompt engineers.
    0:42:39 That’s kind of one big thing.
    0:42:41 The second big thing is think about now,
    0:42:43 like the world is changing so quickly,
    0:42:46 what you can do and what you can demand from vendors
    0:42:50 or what you as an entrepreneur can implement
    0:42:52 when a system can reason by itself,
    0:42:54 that’s the second thing.
    0:42:55 And the third thing is I believe
    0:42:57 because I’m passionate about the industry
    0:42:59 is that this global identity will increase
    0:43:01 over the next couple of years, more and more.
    0:43:06 – All right, that is all for now.
    0:43:09 Obviously security is always a moving target.
    0:43:11 A cat and mouse chase through progressively
    0:43:15 more complex terrain with more complex tools on both sides.
    0:43:17 Now, if you do have any suggestions
    0:43:20 for future topics to cover, feel free to reach out to us
    0:43:22 at podpitches@a16z.com.
    0:43:24 And if you did like these exclusive excerpts
    0:43:27 from our A16Z campfire sessions event,
    0:43:28 make sure to leave us a review
    0:43:32 at ratethispodcast.com/a16z.
    0:43:34 We’ll see you next time.
    0:43:37 (upbeat music)
    0:43:39 (upbeat music)
    0:43:42 (upbeat music)

    Is it time to hand over cybersecurity to machines amidst the exponential rise in cyber threats and breaches?

    We trace the evolution of cybersecurity from minimal measures in 1995 to today’s overwhelmed DevSecOps. Travis McPeak, CEO and Co-founder of Resourcely, kicks off our discussion by discussing the historical shifts in the industry. Kevin Tian, CEO and Founder of Doppel, highlights the rise of AI-driven threats and deepfake campaigns. Feross Aboukhadijeh, CEO and Founder of Socket, provides insights into sophisticated attacks like the XZ Utils incident. Andrej Safundzic, CEO and Founder of Lumos, discusses the future of autonomous security systems and their impact on startups.

    Recorded at a16z’s Campfire Sessions, these top security experts share the real challenges they face and emphasize the need for a new approach. 

    Resources: 

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    Find Feross Aboukhadijeh on Twitter: https://x.com/feross

    Find Andrej Safundzic on Twitter: https://x.com/andrejsafundzic

     

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    Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.