0:00:04 It’s just so interesting to me how far we’ve come with music generation.
0:00:06 This is kind of like a cheat code for any creator out there.
0:00:10 Two years ago, none of the stuff existed, and now it’s like central to my workflow.
0:00:12 And that’s why I think AI is so magic.
0:00:16 The reason I mentioned it and wanted to bring it up with you is because you had the Kanye thing.
0:00:19 Was there backlash, good feedback, bad feedback?
0:00:21 Mostly negativity for sure, man.
0:00:23 I was getting lambasted.
0:00:25 I think that was like one of the most viral things in AI that I saw.
0:00:26 Oh, yeah.
0:00:28 I knew it was going to go viral.
0:00:32 I studied this stuff really deeply, like there was so many things in that script
0:00:34 where I was like, this is going to go nuclear.
0:00:38 Hey, welcome back to the next wave podcast.
0:00:39 My name is Matt Wolf.
0:00:41 I’m here with my co-host, Nathan Lanz.
0:00:46 And with this show, we bring you all of the latest news and information in the AI world
0:00:51 and have fascinating conversations with the people that are building this AI world.
0:00:54 And today we’ve got another really awesome conversation.
0:00:57 Today we’ve got Roberto Nixon on the show.
0:01:02 Roberto is a serial entrepreneur, and he’s one of the top creators on Instagram
0:01:04 and TikTok in the AI world.
0:01:08 You may even know him from his viral Kanye West clone video
0:01:11 that was all over the internet about a year ago.
0:01:15 He also recently interviewed Mark Zuckerberg on Instagram
0:01:17 all about what they’re doing in the world of AI.
0:01:21 And we have some amazing conversations with him in this episode.
0:01:25 We talk about the crossover between content and AI.
0:01:29 We talk about the responsibility we have as content creators
0:01:33 to keep people the best informed possible in the AI world.
0:01:39 And we also talk to him about how the heck did he manage to get Mark Zuckerberg on his show?
0:01:41 So many cool rabbit holes we’re going out in this one.
0:01:43 So excited to share it with you.
0:01:45 And let’s dive right in with Roberto Nixon.
0:01:49 Thank you so much, Roberto, for joining us.
0:01:50 How are you doing today?
0:01:51 Dude, I’m pumped to be here, man.
0:01:54 Next wave, first of all, congrats on the podcast.
0:01:55 Been listening to everything.
0:02:00 I’ve been a like religious follower of you guys for some time.
0:02:04 And actually, Matt, I was introduced to you.
0:02:06 Forget how it must have been about a year ago now.
0:02:08 And I think I’ve watched every single one of your videos.
0:02:10 It’s like part of the reason how I keep updated on the space.
0:02:12 Everybody always asks me, how do I keep updated?
0:02:15 Like, you’re one of the names that I always put out there
0:02:18 as well as as as Lore and Nathan’s newsletter and everything.
0:02:19 So like, I’m pumped to be here, man.
0:02:21 I’m excited to talk with you guys.
0:02:23 Lot to, lot to talk about.
0:02:24 Yeah, there’s a lot to cover.
0:02:27 You know, I think I first came across you.
0:02:29 You had both Instagram Reels and I think TikTok
0:02:32 were sort of the domain you’ve been playing in, right?
0:02:34 And I came across your TikTok
0:02:38 about how you recreated like a Kanye sounding song.
0:02:40 And that video just went super viral
0:02:43 and just I followed along to your journey ever since as well.
0:02:45 So it’s, you know, it’s really cool.
0:02:48 And I think that’s what we want to get into a little bit today
0:02:50 is all three of us here are creators.
0:02:52 We all consider ourselves creators.
0:02:57 And, you know, that overlap between creator and AI,
0:02:59 you know, it’s just that Venn diagram,
0:03:01 that center of that Venn diagram
0:03:03 is getting bigger and bigger every single day.
0:03:05 So let’s start with your story a little bit too.
0:03:07 How did you get into AI in the first place?
0:03:09 Like, what was, what was the catalyst for that for you?
0:03:11 Dude, it’s a long story, but I’m going to make it short.
0:03:15 So basically the last decade I was actually in product.
0:03:17 So my obsession was UI, user interfaces.
0:03:21 I’ve been a UI UX designer for some time,
0:03:23 first started off doing it for agencies
0:03:27 and then consulting for companies small and large.
0:03:30 And then I actually got into building iOS apps.
0:03:32 So for like the last eight years,
0:03:36 or I would say like 2013 to 2021, that’s all I was doing.
0:03:37 I was just like obsessed with building
0:03:39 creativity software for iOS.
0:03:43 We had like some major years in 2015, 2016.
0:03:46 We had an app called HitGlab that was a top photo editor.
0:03:48 The most downloaded photo editor in the United States
0:03:51 for that year, we had something like 75 million downloads
0:03:53 across our suite of apps.
0:03:57 And then sold some of them 2017, 2018,
0:04:00 and then exited the rest of them in 2021.
0:04:03 And then I was like, alright, what do I want to do next?
0:04:03 Right?
0:04:04 Like I kind of had no idea.
0:04:07 I found actually web three and it was super interesting.
0:04:08 So I kind of got into that.
0:04:10 But then I said, you know what?
0:04:12 I want to start making content personally.
0:04:15 ‘Cause for so long I’ve been creating content,
0:04:17 like every one of my app brands and other brands
0:04:18 had big Instagram pages.
0:04:21 That’s been like my domain for like the last 10 years.
0:04:23 So like really intimately understand
0:04:24 how to communicate with an audience on Instagram
0:04:26 and how to grow audiences there and whatnot.
0:04:28 But it’s always been faceless.
0:04:30 It’s always been for my apps or faceless media brands,
0:04:32 some of which I still run today.
0:04:33 And I decided, you know what?
0:04:35 I want to do this individually personally.
0:04:37 And I chose AI because at the time
0:04:40 we were building this SaaS platform.
0:04:42 It was called a Luna media generation.
0:04:45 So we’re now pivoting and we’re building this other platform
0:04:47 called post coming out too much I’m really excited about.
0:04:50 And initially when I started making content,
0:04:51 I was like, I’m going to make content
0:04:54 ’cause I’m looking for customers for my SaaS.
0:04:55 That’s it, nothing else.
0:04:58 I’m going to ride this AI trend just because, you know,
0:04:59 that’s how we’re going to do it.
0:05:00 But then a few months into it,
0:05:02 I fell in love with the creative process, man.
0:05:04 And like now I’m like doing stuff.
0:05:06 Some of the stuff doesn’t even have
0:05:08 like an economic incentive behind it.
0:05:10 It’s just like me exploring my creative curiosities.
0:05:13 And I’ve really just fallen in love with the process.
0:05:15 And now it’s like, it’s just,
0:05:17 I wake up every day excited to just create
0:05:21 whether it be business focused or just creatively focused.
0:05:23 And that’s sort of where I’m at today, man.
0:05:25 And that’s kind of like the long story cut short.
0:05:28 (upbeat music)
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0:06:13 (upbeat music)
0:06:16 – I feel the same way about video production
0:06:17 as I feel about AI, right?
0:06:18 Like for me, like that’s where the,
0:06:21 like coming back to this sort of Venn diagram metaphor, right?
0:06:23 That’s where it sort of overlapped for me
0:06:25 was I loved production, I love video,
0:06:27 I love all the toys.
0:06:28 And then I saw AI and I’m like,
0:06:30 this is just another of that.
0:06:33 It’s more like toys, but more, more digital,
0:06:35 more online, more SaaS.
0:06:37 Dude, I play with so many of them.
0:06:39 Like every time, I mean, not as much as you,
0:06:41 like future tools, this must be like,
0:06:43 you must be tired of actually seeing AI tools.
0:06:47 But yeah, I mean, bro, there’s probably like 15 tools
0:06:50 that are part of my workflow, I would say right now.
0:06:52 I’m like using so many.
0:06:54 And the thing about the space that you guys know is
0:06:55 use it for like two weeks
0:06:57 and then something better comes along.
0:06:59 And it’s like, things get outdated
0:07:00 really, really quickly in the AI space.
0:07:03 So that’s something that, it can get exhausting.
0:07:06 I really don’t know how you do it curating future tools.
0:07:07 It’s like, it’s just too much.
0:07:10 – I get sick of seeing the same damn tool
0:07:12 over and over and over again.
0:07:13 That’s the frustrating part for me, right?
0:07:17 Is the people that submit the tools now are mostly like,
0:07:19 okay, we’ve already seen 15 other tools
0:07:21 that do this exact same thing.
0:07:24 Why do you need to go create another version of it
0:07:26 and try to charge people for it?
0:07:27 It just doesn’t make sense.
0:07:29 That’s the part I get frustrated with.
0:07:31 But when I see something new that I haven’t seen before,
0:07:35 like, you know, I’m still just as dirty and excited
0:07:37 about it as, you know, any other thing
0:07:39 that I’ve seen for the first time.
0:07:40 – Well, a bit on a tangent.
0:07:42 Like, ’cause I was kind of guilty of it.
0:07:44 Like, candidly with Illuna, we had this great idea
0:07:45 of stable diffusions, unbelievable,
0:07:47 but there’s no good UI for it.
0:07:49 So we’re like, we’re gonna be the first to build this out.
0:07:52 But you know, it was like 5,000 other entrepreneurs
0:07:53 who kind of built the same thing.
0:07:56 That product went, we hit 25K MRR pretty quickly,
0:07:59 but it was, we understood very soon, all right?
0:08:01 We don’t feel like competing against mid-journey
0:08:04 and Google and Adobe.
0:08:05 So now we’re building something
0:08:07 that hopefully people haven’t seen before.
0:08:09 I’ll let you know when that comes out.
0:08:10 And you can be honest with me
0:08:13 if it’s not, you know, good enough for future tools.
0:08:14 Not a problem.
0:08:15 (laughing)
0:08:15 – I’m sure it will be
0:08:17 because you’re probably approaching it from the same way.
0:08:19 You know, someone like us would approach it as like,
0:08:21 all right, let’s actually do something
0:08:24 that you haven’t seen other people doing yet.
0:08:27 Or, you know, at least put a twist on it, right?
0:08:29 Like put some sort of twist on it
0:08:31 where it’s like, okay, maybe it’s art generation,
0:08:33 but it’s niche to this specific industry
0:08:35 or something, right?
0:08:37 – Well, let me ask you guys this,
0:08:39 ’cause I actually think this is a really interesting question.
0:08:40 I’d love to get your guys’ take.
0:08:43 It’s like, are the incumbents just gonna take all?
0:08:45 Or is there, I mean, like right now,
0:08:46 people have had head starts.
0:08:47 Like mid-journey came out
0:08:49 and to me they’re still best in class,
0:08:52 but I don’t know if you guys saw image in three from Google.
0:08:53 It’s like right there, you know?
0:08:55 And some of these other tools now,
0:08:56 even some of these stable diffusion models
0:08:57 that we see on Civiti,
0:09:00 they’re like very close to mid-journey’s output.
0:09:03 And some of these head starts have been kind of erased.
0:09:06 And I just feel like there is this possibility
0:09:10 that the incumbents, you know, Google, Meta, Microsoft,
0:09:12 they’re just, they’re gonna take the whole pie.
0:09:14 – I don’t know, my feeling is like, you know,
0:09:16 like when’s the last Google, like new Google product
0:09:18 that like people actually use?
0:09:19 I can’t name one.
0:09:21 I mean, they own YouTube, that’s great.
0:09:22 You know, they bought that,
0:09:25 but what have they built that people actually use
0:09:26 that’s new?
0:09:27 – Nothing, basically.
0:09:30 So mid-journey has a lot of users who love the company.
0:09:32 And so even if like Google releases something
0:09:33 that’s like similar in quality,
0:09:35 I don’t think that means everyone’s just gonna jump ship
0:09:37 to the new Google product.
0:09:38 I don’t see it.
0:09:40 – You know, this is actually a conversation we had
0:09:41 with a mutual friend.
0:09:43 We had Greg Eisenberg on the show
0:09:46 and we actually had this conversation with Greg as well.
0:09:48 And Greg’s point was, you know,
0:09:51 the tools that managed to build a community around them,
0:09:54 the tools that managed to build like some sort of brand,
0:09:56 maybe even in a smaller niche,
0:09:58 will probably still get some traction
0:10:00 over the big incumbents.
0:10:04 I think the general population will probably migrate
0:10:06 towards the big incumbents, right?
0:10:08 The Microsofts, the Googles, you know,
0:10:10 I would say open AI, but, you know,
0:10:12 Microsoft is just building everything open AI does
0:10:14 into it anyway.
0:10:16 But I think, you know, the majority of the population
0:10:18 will probably move to the big incumbents,
0:10:20 but the ones that managed to build community around them
0:10:22 will still manage to get traction
0:10:25 and build pretty solid businesses around them.
0:10:28 Will they turn into multi-billion dollar unicorns?
0:10:29 Probably not.
0:10:32 And the ones that I think do things really unique
0:10:35 that do a good job will probably just get scooped up
0:10:36 and acquired by Google.
0:10:38 You know, Google has a,
0:10:41 they don’t really create a lot of new stuff
0:10:42 that gets people excited,
0:10:45 but they’re really good at acquiring products
0:10:47 that once people are excited about it,
0:10:49 then Google comes in and scoops it up, right?
0:10:52 You know, the last big products that Google made
0:10:55 that are really, really still popular to this day
0:10:59 are pretty much Gmail and Android, right?
0:11:01 Everything else that’s really popular
0:11:04 was something that Google came in and acquired.
0:11:05 – Yeah, I mean, it’s really tough.
0:11:07 Even if like, okay, even if your model
0:11:09 is a little bit better, if, you know,
0:11:11 I’m used to Google search,
0:11:12 although that’s even been disrupted.
0:11:13 I’m using Proplexity a lot.
0:11:16 I’m using Met AI, I’m using ChatGBT now on my Mac,
0:11:17 which has been awesome.
0:11:20 But I think for most people it’s like this behavior
0:11:23 that they’ve, it’s like muscle memory
0:11:24 over the last 20 years.
0:11:26 If like, they’re probably still gonna use Google search,
0:11:28 even if Proplexity or even, you know,
0:11:30 if these models like benchmark a little bit higher,
0:11:32 the average person couldn’t care less, right?
0:11:35 And so, yeah, man, I mean, it’s interesting.
0:11:37 I like, I’m not huge on predictions,
0:11:40 but I love just being on the play-by-play like you guys.
0:11:43 And so it’ll be fascinating to watch it all play out.
0:11:45 – I think it’s fun to make predictions
0:11:46 because the ones that I’m right all, you know,
0:11:47 six months from now,
0:11:49 it’s been a round of glory before I was right.
0:11:49 – You re-surfaced them.
0:11:50 – Exactly.
0:11:51 – And then the ones where I was wrong,
0:11:53 I just never mention them again.
0:11:55 – Dude, this is so like in finance,
0:11:56 like all these stock market guys
0:11:58 where they just every single day
0:11:59 they predict the market’s gonna collapse.
0:12:01 And like the one day that it does,
0:12:02 they ride that wave forever
0:12:03 and they just build a career off it.
0:12:04 Totally get it.
0:12:06 – I actually want to go back to something you mentioned.
0:12:09 You mentioned that you were using like 15 different tools
0:12:11 in your creative workflow.
0:12:13 Let’s dive into that a little bit.
0:12:15 I’d like to compare notes a little bit
0:12:17 because I use a lot of AI tools,
0:12:19 a lot of non AI tools in my creative workflow.
0:12:21 So yeah, I’m curious,
0:12:23 what are the tools that you find yourself using
0:12:25 to actually put the content out?
0:12:27 – Well, there was a video I made the other day would be,
0:12:28 it was such a process.
0:12:31 It was actually the longest I’ve ever spent editing a video,
0:12:33 probably took like 12 hours over the course of a week.
0:12:35 And I was like, what did I get myself into?
0:12:37 But the process behind that video
0:12:39 was first creating a lot of images on mid-journey.
0:12:41 So I’d be like step one.
0:12:43 Mid journeys upscaler is decent, it’s not the great.
0:12:45 So then I’d use Magnific.
0:12:47 Shout out to Javi, I know he’s a mutual friend.
0:12:50 I think that’s probably the best in class upscaler.
0:12:53 So at mid-journey and then upscaled in Magnific,
0:12:55 then there was a lot of work in Photoshop to be done.
0:12:57 If you saw the video, you’d understand what I’m getting to,
0:13:00 but basically it was like these buildings
0:13:02 with the windows changing like different colors
0:13:03 and different things happening in the building
0:13:04 as it was like zooming in and out.
0:13:06 So then I’d bring it into Photoshop
0:13:08 and there was a lot of masking and like manual work
0:13:10 in Photoshop, but I also found myself using
0:13:11 a lot of generative fill.
0:13:16 Like generative fill is a huge part of my process.
0:13:18 So mid-journey, Magnific, generative fill.
0:13:20 And then I needed some elements animated,
0:13:22 so then I’d bring it into runway
0:13:24 and then I’d like mask out the exact elements
0:13:28 that I needed animated and I spent some time working there.
0:13:30 There’s by the way, runway, man,
0:13:32 if they can like improve that product just a little bit,
0:13:35 like it’s my favorite UI and like my favorite product,
0:13:38 but I feel like it’s lagging behind a little bit.
0:13:40 And so that process alone, it’s like,
0:13:41 hopefully there’ll be a tool that’ll be able
0:13:42 to automate all of this.
0:13:44 And I actually think this is why
0:13:46 going back to the incumbent conversation,
0:13:48 I actually think Adobe Photoshop and Premiere
0:13:50 will be able to do all this stuff.
0:13:51 And that’s why I was asking,
0:13:53 maybe I won’t need to use mid-journey, Magnific, et cetera,
0:13:56 but for now I’m using like those four tools.
0:13:57 And then I put them together in Premiere
0:13:59 and then I found myself editing my audio
0:14:02 in the enhanced audio, which is new to Premiere.
0:14:05 And so that is an example of five tools
0:14:08 being used right there to like output this one video.
0:14:10 And depending on what I’m doing,
0:14:11 I’m finding myself.
0:14:14 And then before that, even just research and ideating,
0:14:17 just conversationally brainstorming with an LLM.
0:14:18 I mean, like, and it’s crazy, man.
0:14:20 Like two years ago, none of the stuff existed.
0:14:22 And now it’s like central to my workflow,
0:14:24 allowing me to like tell stories
0:14:25 that I previously wouldn’t be able to tell.
0:14:28 And that’s why I think AI is so magic.
0:14:30 (upbeat music)
0:14:31 – We’ll be right back.
0:14:33 But first I want to tell you about another great podcast
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0:15:03 He recently did a great episode called,
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0:15:10 You’re going to want to check out the podcast,
0:15:12 listen to Science of Scaling,
0:15:14 wherever you get your podcasts.
0:15:17 (upbeat music)
0:15:18 – Yeah, well, Generative Fill is one
0:15:21 that I feel like doesn’t get enough talk,
0:15:22 but I use it almost daily.
0:15:25 I love Generative Fill inside of Photoshop.
0:15:26 – Dude, it’s magic.
0:15:28 And it matches the color and like contrast.
0:15:31 It’s actually, it’s the closest thing to magic
0:15:33 that I’ve seen in like the AI space.
0:15:34 It’s like you said,
0:15:36 it’s underappreciated and under talked about.
0:15:39 Yeah, one tool that I find myself using a lot more lately,
0:15:42 and this kind of actually gets into a topic
0:15:43 that we want to discuss too,
0:15:46 is I’ve been using Suno a lot because in videos,
0:15:49 it makes like the perfect music for videos.
0:15:51 Like one thing I’ve started to experiment with
0:15:53 is if I’m showing off a long process
0:15:55 and there’s like a montage going off,
0:15:58 I almost make like a South Park like,
0:16:01 or Team America like montage song, right?
0:16:03 Like here’s my montage of me coding.
0:16:06 It’ll just be like lyrics that I typed into Suno
0:16:08 about what I’m doing on the screen.
0:16:10 And now there’s music playing during the montage,
0:16:12 explaining what I’m doing, right?
0:16:15 I’ve been doing that a lot more in videos as well.
0:16:17 And Suno is really, really impressive.
0:16:19 But the reason I mentioned it
0:16:20 and wanted to bring it up with you
0:16:23 is because you had the Kanye thing.
0:16:25 And it’s just so interesting to me
0:16:28 how far we’ve come with music generation.
0:16:30 ‘Cause I’m assuming back when you did the Kanye thing,
0:16:33 you had to use like the Soviets, SVC,
0:16:35 and you probably had to like run it
0:16:37 through like your terminal on your computer.
0:16:39 And it was a pretty complicated process.
0:16:42 I’m imagining, I don’t remember the exact workflow,
0:16:46 but music generation has just come so damn far since then.
0:16:49 – I mean, that’s how I first learned about Roberto is like,
0:16:51 I think that was like one of the most viral things in AI
0:16:52 that I saw was like you doing this thing
0:16:56 where you’re singing like basically like training,
0:16:59 creating a new Kanye song where you sing the song
0:17:02 and then it goes and it sings it back to you
0:17:03 with Kanye’s voice.
0:17:04 And that was just such a magical thing.
0:17:06 – Well, it helped you that Roberto actually
0:17:07 can kind of rap too.
0:17:09 Like, if I was to try to do the same thing,
0:17:11 it would not have come out like that.
0:17:12 – Kind of is generous.
0:17:14 Dude, a couple thoughts there.
0:17:18 One is, yeah, it was a pretty complicated process back then.
0:17:20 And this is kind of like a cheat code for any creator
0:17:23 out there is like, and part of the process
0:17:25 that we’re trying to streamline with Pulse is like,
0:17:29 I have 30 subreddits that in a folder
0:17:32 and I have them sorted by rising and new, right?
0:17:35 And so a lot of the magic is in the rising and new
0:17:37 that people that never picks up and never makes it
0:17:39 to like the hot or never makes it to the top of the feet.
0:17:41 And I saw this thing like some kid did this thing
0:17:44 with Kanye, he like developed this model
0:17:46 and he put it on Google collab and it was like this discord
0:17:48 but I was searching through Twitter,
0:17:51 nobody was talking about it except for like this small
0:17:54 subset of people in this like random ass discord.
0:17:56 And I went in there and I tried it out
0:17:58 and I ran the Google collab and dude,
0:18:00 I was like mind blown.
0:18:02 I said, this is gonna change everything.
0:18:04 And so I made the video, I’ll put it out there.
0:18:05 And it was really, I think the first like mainstream
0:18:07 introduction of this technology to the world.
0:18:09 And it went mega viral to the point
0:18:12 where I always tell people I’ve had in the last 18 months,
0:18:16 like 70 videos do a million plus views on like short form.
0:18:19 You know, I’ve had five, 10, 20 million view videos.
0:18:21 But like that’s the only video that I consider viral.
0:18:25 And the reason why, because that was like every YouTuber
0:18:26 covered it, like even the big ones,
0:18:29 Unbox Therapy, Penguins, Moist Critical,
0:18:31 like every journalist was reaching out.
0:18:33 I talked to a lot of like label heads actually,
0:18:35 like really prominent label heads,
0:18:38 everybody wanted to understand the technology more,
0:18:40 like TV interviews, everybody was like reaching out.
0:18:42 And I said, whoa, this is crazy.
0:18:47 And then like weeks later it even when there was a kid
0:18:50 named Ghostwriter, you guys might remember that.
0:18:53 And he was making, he had a Drake track with the weekend
0:18:55 where I was like, if this was a real song,
0:18:57 this would be like in Drake’s top 10.
0:18:58 Like it was just absurd to me.
0:19:00 And so yeah, that was a fun time,
0:19:03 probably definitely the video that put me
0:19:04 in a lot of people’s radars.
0:19:06 And I’ve been searching for like that viral,
0:19:08 viral crazy moment ever since.
0:19:10 So that’s why I have my ears and eyes always
0:19:12 to like the AI emerging tech world.
0:19:14 – It sucks that, you know, Drake started going
0:19:15 after everyone after that too.
0:19:17 Like that was one of my first big Twitter threads.
0:19:19 So I learned about you and I’m like, oh, this is amazing.
0:19:22 And then the Drake thing came out
0:19:24 and then the Grimes AI song as well.
0:19:26 And I did like two big Twitter threads
0:19:28 where I like, I wrote my thoughts on all like,
0:19:30 what this means for the future of music.
0:19:30 – Yeah, I remember that.
0:19:32 – And those, you know, they went pretty big.
0:19:35 And then like everyone who was making the Drake threads
0:19:36 or sharing the song,
0:19:38 they started getting like takedown notices on Twitter.
0:19:40 – But yeah, one golden nugget for that real quick
0:19:43 is like definitely a lot of the crazy stuff happening
0:19:45 like the tinkerers in the community,
0:19:46 they’re on Reddit, they’re on Discord.
0:19:48 They’re not so much on like Twitter, Instagram, YouTube,
0:19:51 like some of the more mainstream platforms.
0:19:53 And so keeping your ears and eyes
0:19:56 to these little subsets and weird little subcultures online
0:19:59 is how you can find a lot of the stuff
0:20:01 that’s like starting to bubble.
0:20:03 – Yeah, there’s been so many videos I’ve made
0:20:06 that just kind of spun up from like a cool like subreddit
0:20:08 that I found or from like a random tweet
0:20:09 that nobody else noticed.
0:20:11 And I’m like, why isn’t anybody else talking about this?
0:20:13 – 100%.
0:20:15 – But I’m curious, was there like backlash,
0:20:17 good feedback, bad feedback?
0:20:21 Like what was the general feeling from that video?
0:20:24 Did you get more sort of negativity as a result of it?
0:20:27 More positivity, like how did that land?
0:20:29 – Mostly negativity for sure, man.
0:20:30 I was getting lambasted.
0:20:33 I would say, I knew it was gonna go viral, all right?
0:20:35 Because I’m like, I’m kind of a practitioner.
0:20:38 I’m like, I study this stuff really deeply,
0:20:39 like virality on the internet,
0:20:41 how to create content, how to best.
0:20:44 And there was so many things in that script
0:20:46 and some where I was like, this is gonna go nuclear.
0:20:48 I already knew, I even, I think I tweeted before,
0:20:51 I’m about to drop a video that’s gonna go super viral.
0:20:53 Part of the reason why, I didn’t expect, okay,
0:20:57 so like the woke mob came after me for digital blackface,
0:21:00 which was like CNN had published an article like right after.
0:21:03 And so everybody was like, oh, this is racist,
0:21:07 like a black dude’s voice, white dude singing it.
0:21:10 Okay, but then the other part was,
0:21:11 that part was not deliberate.
0:21:12 I didn’t quite expect that.
0:21:13 The part that was deliberate,
0:21:16 like the way that I engineered the lyrics,
0:21:19 one part where I kind of like took a shot at Kanye,
0:21:21 or remember he did like the whole anti-Semitism thing.
0:21:22 And I took a shot at him,
0:21:26 like for talking down an entire culture,
0:21:28 and I said it was ignorant, this and that.
0:21:31 And then another one was I included a lyric,
0:21:33 and I didn’t mean it for it to be disrespectful,
0:21:36 but I included a lyric about Donda, like his late mother.
0:21:37 That was supposed to be like endearing,
0:21:40 but somebody was like, oh, not only is he digital blackface,
0:21:42 he’s also talking about his mom as him.
0:21:44 This is, I think moist critical called it like diabolical.
0:21:46 So man, I was getting like heat left and right,
0:21:48 which I kind of expected.
0:21:49 So it wasn’t too big of a deal.
0:21:52 But yeah, and then from the artist community,
0:21:55 all here they come to steal the virtue of artists
0:21:56 and human artists and that.
0:21:59 So it was just like negativity straight throughout.
0:22:01 But I think a lot of the technologists and stuff
0:22:02 appreciated it.
0:22:04 But yeah, certainly an interesting time, man.
0:22:05 That was an experience for sure.
0:22:06 – Did that linger on?
0:22:07 Did that continue or?
0:22:09 – Nah, it just, and that’s another thing with the internet.
0:22:11 Like there’s so much like blatant,
0:22:13 not to go on the super tangent,
0:22:15 but there’s like so much blatant corruption in the world.
0:22:16 And they’re just like,
0:22:18 people don’t care anymore because what happens online, man,
0:22:20 you for 24 hours,
0:22:22 you get a bunch of people angry on Twitter
0:22:23 and like writing mean,
0:22:26 dredging comments on this and then everybody forgets
0:22:27 and then they’re on to the next thing.
0:22:30 And so that’s, you know,
0:22:32 people are more fickle now than ever.
0:22:34 – How do you think the like the sentiment around AI music
0:22:36 has changed because now, you know,
0:22:40 you’ve got like Udio and Suno and stuff like that.
0:22:45 And Udio actually has like common and who else?
0:22:47 There’s like a few musicians actually attached
0:22:49 to that product now.
0:22:51 So it seems like more musicians are getting on board.
0:22:53 I was actually at the Google IO event
0:22:56 and Lupe Fiasco was actually there at the event,
0:22:59 wandering around and I got to talk to him for a minute,
0:23:00 but, you know,
0:23:03 he’s actually working with Google on text effects,
0:23:06 but now they have a new one called music effects
0:23:09 that they were showing off at Google IO as well.
0:23:11 And that’s where actually bumped into Lupe
0:23:13 was he was actually playing around
0:23:15 with the music effects tools in real life,
0:23:19 like mixing beats and generating AI music.
0:23:22 And he was like super blown away, super impressed by it.
0:23:23 So like, I mean,
0:23:27 it feels like the sentiment among musicians
0:23:29 is sort of starting to come around,
0:23:31 but I don’t know, what are your thoughts?
0:23:34 – In general, like I actually think about this a lot.
0:23:36 I think anything that’s purely AI generated
0:23:38 is actually really boring.
0:23:40 And I don’t think there’ll ever be a market for it.
0:23:42 I just don’t, aside from the initial novelty,
0:23:44 like when we first started seeing mid-journey images,
0:23:46 you guys probably remember, it was mind-blowing,
0:23:48 but now I see an image from mid-journey
0:23:51 and maybe I don’t know it’s AI at first.
0:23:52 Maybe it looks like an artist,
0:23:54 but once I learned that it’s purely AI generated,
0:23:55 I just don’t care.
0:23:57 Like, and I think as humans,
0:23:58 we all desire that human element.
0:24:01 And case in point, like Sam Altman made this point,
0:24:05 it’s like, hey, we love chess as a game,
0:24:07 the strategy behind it, all this.
0:24:10 Robots can outperform humans in chess,
0:24:12 but we don’t want to watch a robot playing a robot.
0:24:14 So there has to be that human element,
0:24:17 and I think they’re very same in art and in music.
0:24:19 So if something’s purely AI generated,
0:24:20 I actually don’t think it’ll ever hit.
0:24:22 I don’t think there’ll be a market for it.
0:24:23 Now, there is a caveat.
0:24:25 There may be a time where literally we don’t know,
0:24:28 but I do think there just has to be that human element,
0:24:30 like the story behind the art.
0:24:34 So I look at AI as a tool, specific to music.
0:24:37 I look at, you know, like there’s producers
0:24:40 who sample old songs and recreate them and make beats.
0:24:43 So I think people will use AI to like create samples,
0:24:47 to then sort of remix, maybe create drums, drum kits,
0:24:48 that kind of stuff.
0:24:50 But I do think there needs to be that human element.
0:24:52 Otherwise, I just don’t think there’s a lasting market
0:24:55 for purely AI generated media.
0:24:57 – Yeah, I actually feel kind of the same way.
0:25:01 I feel like I’ll hear stuff, be really impressed by it,
0:25:04 but same thing, when you realize it was made by AI
0:25:07 and it wasn’t like a human doing something awesome,
0:25:10 you kind of, it kind of leaves something a little bit there.
0:25:14 I feel like AI is the best sort of helpful tool out there,
0:25:17 both for art and music and, you know,
0:25:20 all of the creative forms, when it comes to writing,
0:25:22 almost all of us now can spot chat GPT, right?
0:25:24 You can read an article and almost immediately go,
0:25:27 okay, I feel like chat GPT wrote this article now, right?
0:25:31 But if you have chat GPT, write you an article,
0:25:34 and then you go back and sort of see that as a rough draft
0:25:35 and clean it up and add your own voice
0:25:37 and add your own comments and opinions,
0:25:39 now you have something that people actually want to read.
0:25:41 Same with like music, right?
0:25:43 Like the stuff that Lupe Fiasco is doing,
0:25:45 for instance, with text effects,
0:25:48 he’s helping, they built an AI to help you come up
0:25:52 with lyrics and alliterations and rhyming words
0:25:54 and synonyms and all that kind of stuff
0:25:56 to help with the creative process,
0:25:57 but then the musician still gets involved
0:25:59 and creates the music.
0:26:01 You know, the stuff that Google was showing off
0:26:02 with their music effects,
0:26:04 it wasn’t actually doing any lyrics
0:26:05 that sounded like a musician,
0:26:07 but it was creating really good beats
0:26:11 by taking styles from this musician and this musician,
0:26:13 blending them together, creating something novel,
0:26:16 and then a rapper or a singer can go
0:26:19 and then put the lyrics over the top of it.
0:26:21 That’s where I feel like AI really shines,
0:26:23 is like that sort of co-pilot,
0:26:25 that tool to help you do the creative thing
0:26:27 you’re trying to do.
0:26:28 – I don’t know, I think we’ll see,
0:26:30 like if it keeps improving, right?
0:26:33 Like I do see it becoming maybe its own genre of music
0:26:33 in the future, right?
0:26:36 ‘Cause like, yeah, we’re talking about like AI music now,
0:26:38 but like, okay, three years from now, five years from now,
0:26:40 maybe it’s producing shit that just like blows our minds.
0:26:44 It’s beyond any human’s ability to create, right?
0:26:46 And so at that point, I don’t know, we’ll see.
0:26:48 – Well, here’s an interesting question
0:26:51 that I’d be curious both of your answers on.
0:26:53 If, let’s say Drake, for instance,
0:26:56 really got on board the AI train and let’s,
0:26:58 I don’t know if you guys are Drake fans or not,
0:27:00 but let’s assume you guys are Drake fans.
0:27:02 Let’s say he trained his voice into the algorithm
0:27:04 and he has like oversight,
0:27:08 but he’s making AI Drake songs and it’s Drake’s oversight.
0:27:10 He’s sort of, you know, deciding the beats
0:27:12 that go underneath it.
0:27:15 He’s helping steer the lyrics,
0:27:17 but the song itself is fully AI generated.
0:27:20 Would that change how you feel about this song?
0:27:21 – So that’s the tricky part.
0:27:23 Like if we knew, so a lot of people,
0:27:26 once they find out Drake has an army of ghost writers
0:27:28 and this and that, like their affinity for him
0:27:29 just goes down a little bit as an artist ’cause it’s like,
0:27:31 oh, he didn’t even write the lyrics, right?
0:27:35 But that’s the part, that’s the big caveat.
0:27:38 If we know, so do you guys know Varun Maya?
0:27:41 He’s a creator, I think he’s mostly on Instagram,
0:27:45 but all of his Instagram content,
0:27:47 all the shorts are AI generated.
0:27:49 Meaning it’s like his model and then he just goes
0:27:52 and writes a script and it’s AI voiced, AI generated.
0:27:54 The script may even be, but people don’t know that.
0:27:57 But because he’s a real human that had like this affinity
0:27:58 in this audience and stuff,
0:28:00 people don’t really mind, I don’t think.
0:28:03 Now, if that was a pure AI-generated creation,
0:28:05 like if that human actually didn’t exist,
0:28:06 I don’t think it would work.
0:28:08 But because there was a human and a story
0:28:11 and a body of work behind it, it sort of does.
0:28:13 And I think it could be the same for music,
0:28:16 where it’s like, if Drake, if he has like seven shows
0:28:17 coming up in the next 10 days,
0:28:20 but he’s gotta get a song out for whatever reason,
0:28:22 there may be a chance, like just get my model to do it.
0:28:25 Nobody will know, if it’s not now,
0:28:27 it’ll be indistinguishable very soon.
0:28:30 And that’s kind of the uncanny value behind it,
0:28:33 where it’s like, if we know, we’re not gonna like it.
0:28:37 But we probably will never know now from here on out,
0:28:40 if something is wrapped by an artist
0:28:41 or just generated by their model.
0:28:45 And that to me is the part where it’s a little eerie.
0:28:46 – I think in the future too,
0:28:48 when like some of these great artists start to pass away,
0:28:50 there’s gonna be more demand there too, right?
0:28:53 Technology gets very good, Drake is no longer around.
0:28:55 There’s still Drake fans.
0:28:57 And now, like maybe he’s sold his rights
0:29:01 before he passed away and you can still have him in songs.
0:29:04 – Yeah, I mean, I wouldn’t be surprised if musicians
0:29:06 actually start writing that kind of stuff into their will,
0:29:11 like what happens to my voice IP once I’m gone.
0:29:14 – But like, to me, it’s still like,
0:29:16 we can make great Tupac songs right now with his,
0:29:19 I will just, and he’s my favorite hip hop artist
0:29:21 of all time, I will still never love them,
0:29:23 like I love the, ’cause it’s just not,
0:29:24 there’s something lacking there.
0:29:25 There’s like, that’s-
0:29:26 – You could patch a human to it though, right?
0:29:28 You could do like a collaboration song, right?
0:29:29 Where it’s like, I’m the new Tupac,
0:29:32 and now I brought in an AI Tupac into my song.
0:29:33 – Well, Drake just did that, right?
0:29:35 And got sued.
0:29:38 – But even then, I think like the novelty’s cool,
0:29:40 but once that wears off, there’s no market for it.
0:29:45 And so my thing is will and will there be regulation
0:29:46 or what will happen here?
0:29:49 But like, if I were a label and I wanted to maximum,
0:29:51 like say I’m representing Drake and he died,
0:29:56 like, do you then just say these were unreleased vocals
0:29:57 from when he was alive?
0:29:58 Because that will hit a lot.
0:30:01 And so then it becomes like an ethical and moral question,
0:30:02 maybe legal, maybe regulatory.
0:30:05 So yeah, man, there’s so many,
0:30:07 it’s so fun to be at the forefront of all this stuff,
0:30:08 ’cause there’s so many questions
0:30:11 and it’s all being sort of written in real time, but-
0:30:12 – Oh yeah, we found a new Beatles album.
0:30:15 It just was hidden in a store somewhere.
0:30:17 – Right, and that would be more impactful
0:30:20 than we just generated John Martin’s voice.
0:30:23 Nobody’s, you know, so that’s where I feel.
0:30:24 It’s like, we need the human element.
0:30:27 There won’t be a market for purely AI-generated stuff,
0:30:30 but a big question, will we even know?
0:30:31 – Yeah, yeah.
0:30:32 Well, I mean, a lot of the vocals from these musicians too
0:30:34 are from their own personal experiences,
0:30:35 their life experiences, right?
0:30:37 You know, talking about Tupac, right?
0:30:40 He lived a pretty crazy life.
0:30:43 So his songs are all about the life that he lived.
0:30:45 So songs that came out now
0:30:48 wouldn’t represent his thoughts, his feelings,
0:30:50 his life story at all.
0:30:52 And I think there’s that element to it
0:30:55 that people just know that this isn’t really him.
0:30:58 And that just diminishes it by quite a bit, I think.
0:30:59 – Yeah, I mean, in art theory,
0:31:01 it’s a concept called the aura.
0:31:04 So it’s like, hey, there’s artists today
0:31:07 that can replicate the Mona Lisa to exact perfection,
0:31:09 but we never, it’ll never hit the same
0:31:10 because of that aura.
0:31:13 Like this was a piece of cardboard
0:31:17 or whatever it was that Leonardo da Vinci himself sculpted.
0:31:19 This was in different fires and a ward almost broke down.
0:31:22 It passed the hands of different monarchs through history
0:31:24 and like that’s what makes it compelling.
0:31:26 It’s not like the actual art or the design
0:31:28 or the way that the colors are strung together.
0:31:30 It’s the story behind it.
0:31:31 And I think it’s with all media, all art,
0:31:35 it’s like we’re drawn to the story behind something,
0:31:37 piece of art, a piece of media,
0:31:40 not so much like the actual construction
0:31:42 of the whatever it is.
0:31:44 And so I think we’ll see that play out with AI
0:31:47 where it’s like, yeah, again,
0:31:48 through our earlier example,
0:31:50 a purely AI generated mid-journey,
0:31:51 it’s just not interesting.
0:31:53 That I don’t care how cool it is or how impressive.
0:31:54 It’s like, it’s not interesting.
0:31:58 I need the story behind the art, the human element.
0:31:59 – I’m gonna shift gears here for a minute too.
0:32:01 I wanna talk about a little bit
0:32:03 about like the ethics of content creation.
0:32:05 Is this is something that,
0:32:07 I mean, I battle with it a little bit.
0:32:08 It’s not too big of a battle
0:32:10 because I know who I’m making the content for,
0:32:12 but there’s this sort of battle
0:32:15 between creating the content for the audience
0:32:17 and making them aware of what’s out there
0:32:18 and what’s not out there.
0:32:21 But then you also have the creators,
0:32:23 the creators of the products, right?
0:32:25 The software companies.
0:32:27 In my case lately, it’s been the Googles
0:32:28 and the Microsofts of the world
0:32:31 who will actually like pay me to fly out to their events
0:32:33 so that I’ll talk about them in videos.
0:32:35 And then I have this sort of dilemma.
0:32:39 Do I, if I’m not impressed with what they’re showing me,
0:32:41 but they paid me to be there
0:32:43 to talk about what they’re showing me,
0:32:45 am I tailoring to the audience?
0:32:47 Am I tailoring to Google?
0:32:49 – Did you do that with Google?
0:32:51 – If you’ve watched my Google videos, you know I don’t,
0:32:56 but this is something that I wanted to talk to you about
0:32:59 because it’s something that I’ve struggled
0:33:00 with a little more recently
0:33:03 because I’ve had companies come to me
0:33:06 and offer me like equity to be an advisor in the company
0:33:09 or who may have reached out
0:33:12 because they want me to be an investor in their company
0:33:13 or something like that.
0:33:16 And for the most part, I’ve said no to almost all of them
0:33:20 because I worry about if I’ve got skin in the game
0:33:21 for some of these companies,
0:33:23 is it going to, you know,
0:33:27 taint how the audience sees me talking about that product.
0:33:30 And so it’s something that’s always kind of on the top
0:33:34 of my mind of, you know, how do I strike this balance
0:33:36 between the thing that’s gonna make me money
0:33:40 as an entrepreneur, but also being true to the audience
0:33:43 and making the best piece of content for my audience.
0:33:44 – I think it’s super important.
0:33:46 And then I definitely want to hear your guys thoughts
0:33:47 because it’s something I struggle with a lot.
0:33:49 I actually have two recent examples.
0:33:52 So one was I was doing some work for Rabbit.
0:33:55 Obviously, you know, disclose paid promo
0:33:57 before the product actually came out.
0:34:00 So I did two, I think sponsored posts for them.
0:34:03 And I actually liked what they were building.
0:34:05 I thought it was like whimsical, it was charming,
0:34:06 it was $200, no subscription.
0:34:08 I was like, there’s a market for this.
0:34:12 And then I had a paid post sponsorship deal lined up.
0:34:15 I got the product, I was gonna review it.
0:34:17 And, you know, make a glowing little,
0:34:20 not so much a review, but like almost like a commercial
0:34:21 online, like a short form video,
0:34:23 TikTok, Instagram, Twitter, et cetera.
0:34:25 And it was just not something that I was comfortable
0:34:27 recommending to my audience.
0:34:28 Not that it’s a bad product.
0:34:30 I think there could be a future for it.
0:34:32 I think there could be a market for it, et cetera.
0:34:36 Like, look, so I didn’t want to like knock Rabbit
0:34:38 or knock the team, but I canceled the deal.
0:34:40 I was like, this is not something comfortable.
0:34:41 And by the way, it was like,
0:34:42 I’m not like the super rich dude
0:34:44 where I can just cancel deals, not a big deal.
0:34:47 Like right now, my creator business sponsorships
0:34:49 and ad and brand deals and stuff
0:34:51 probably represents 50 to 60% of my revenue.
0:34:53 And so, and it was like a pretty well paid thing.
0:34:56 So it wasn’t like easy to do,
0:34:57 but I do feel like as creators,
0:34:59 we got to take those short-term hits
0:35:02 if we’re playing in decades for that long-term trust.
0:35:05 Because I do think that, especially in the age of AI,
0:35:08 trust is gonna be the commodity.
0:35:10 Like everything else can be replicated.
0:35:11 Another example was Google.
0:35:13 Like I was invited to the dinner.
0:35:14 You went too mad.
0:35:16 I couldn’t make it ’cause I had something to do in LA.
0:35:17 But I love Google.
0:35:19 I love the relationship I have with the DeepMind team,
0:35:21 et cetera, but I didn’t really love the presentation.
0:35:23 I thought it was lackluster,
0:35:25 not the technology that they were presenting,
0:35:26 but the way that they presented it.
0:35:29 And so I went on threads and I wrote,
0:35:30 this was really boring.
0:35:31 Google has some work to do on productizing
0:35:36 and on showmanship and presentation,
0:35:37 all that kind of stuff.
0:35:41 Like I worry that will probably hurt me.
0:35:44 Like they’ll probably pull back some potential future deals
0:35:44 because it’s like, well,
0:35:46 this guy’s talking negatively about us online.
0:35:48 But it’s like, those are my honest and true thoughts.
0:35:50 I don’t want to hold them back
0:35:53 just because I may get paid by them in the future.
0:35:54 And it’s really tricky, man.
0:35:57 I mean, like MKBHD obviously has been like super big news
0:36:00 over the last month on this topic itself.
0:36:02 And so my answer would be,
0:36:06 protect the long-term trust with your audience at all costs,
0:36:08 even if there’s some short-term money
0:36:09 that you got to leave on the table.
0:36:11 Yeah, in the early days of my newsletter lore,
0:36:15 I had this sponsor, there was this Korean startup,
0:36:18 was doing like AI pictures kind of stuff early on.
0:36:21 And they sponsored the newsletter for like a month,
0:36:24 paid very well, and then they just like disappeared
0:36:25 and then didn’t say anything.
0:36:27 Like didn’t notify me.
0:36:29 Like I think I maybe even put up an ad,
0:36:31 like a write when their website went down.
0:36:34 And then some users like emailed me like,
0:36:38 hey, I like paid for like a monthly subscription or whatever.
0:36:40 And like now the website is just like gone.
0:36:42 And so that was like a first experience for me like,
0:36:45 oh, like you gotta be careful like which sponsors you take.
0:36:46 You know, it wasn’t huge money at the time,
0:36:47 but it was still, it was like, God,
0:36:48 that’s a horrible experience.
0:36:51 And then for, and obviously you lose a lot of trust
0:36:52 by doing that, right?
0:36:53 Can actually for a while,
0:36:55 I stopped taking sponsors for that reason.
0:36:56 – Yeah, no, I’m on the same page.
0:36:58 I think in what we’re doing,
0:37:01 the credibility and the trust is everything.
0:37:02 That is our biggest currency.
0:37:04 That’s what matters more than anything.
0:37:07 And you know, when it comes to companies like Google,
0:37:08 right?
0:37:10 I’ve made a lot of videos that were critical of Google,
0:37:13 you know, back when they put out their Gemini promo video,
0:37:16 I was very, very critical of them kind of hiding the fact
0:37:18 that this wasn’t real time.
0:37:19 And I put out a whole video
0:37:21 about how disappointed I was in Google.
0:37:23 And I’ve worked with Google in the past
0:37:25 and I’m working with Google again.
0:37:28 So the fact that I’m working with Google again now
0:37:30 shows that they get over it, right?
0:37:31 At the end of the day,
0:37:34 if you build a brand that has an audience
0:37:37 and people are paying attention to what you say,
0:37:39 these companies are gonna get over the fact
0:37:41 that you were negative about them once
0:37:43 because they know that you have the audience.
0:37:48 You’re the trusted voice that people are checking in on.
0:37:52 And so, you know, I would say for every one sponsor
0:37:54 that I have on my channel and in my newsletter,
0:37:56 there was probably 10 that I said no to.
0:37:59 I say no, like I leave so much money on the table
0:38:01 because I look at their product and go,
0:38:02 I don’t wanna promote this.
0:38:05 Like I can already do this inside of chat GPT.
0:38:07 You just like put a wrapper around it
0:38:10 and are charging the same amount as chat GPT.
0:38:13 Why did I pay 20 bucks a month to do this thing
0:38:14 when I can do it in chat GPT
0:38:16 plus everything else chat GPT does.
0:38:18 Like it just doesn’t make sense to me.
0:38:19 I’m not gonna talk about it.
0:38:21 It feels like I’d be pointing my audience
0:38:24 to something that I don’t think is valuable to them.
0:38:27 So I just had that philosophy of like the trust
0:38:30 and the credibility is 100% what we need to live by
0:38:32 as content creators.
0:38:33 And as soon as you lose that
0:38:35 and they start to think of you as like a sellout,
0:38:38 then it’s all downhill from there.
0:38:39 And again, these companies,
0:38:41 if you’ve got the audience, they’ll forgive you.
0:38:42 They’ll come back.
0:38:44 – First of all, respect to you.
0:38:46 And I think that’s why you’re so respected in space
0:38:47 and respect to Google.
0:38:48 Now I think it’s important for companies
0:38:50 to take that criticism.
0:38:53 You know, they gotta take the bad with the good
0:38:55 ’cause some companies do weaponize it.
0:38:57 I don’t know if you guys follow like Dr. Disrespect.
0:38:58 He’s one of my favorite creators.
0:38:59 I think he’s like one of the greatest entertainers
0:39:02 in the world, but like very famously
0:39:03 Call of Duty has blacklisted him.
0:39:05 He’s not invited to any events.
0:39:05 He’s not, you know,
0:39:08 every other creator gets a deal from Call of Duty.
0:39:09 He doesn’t because he like–
0:39:12 – Which too, you got blacklisted by Twitch also.
0:39:14 – And he like insults the game.
0:39:16 And he’s like, these developers are lazy and this and that.
0:39:17 And he’s like, he’s given his honest thoughts.
0:39:20 And, but I think longterm that works out even better
0:39:22 for Dr. Disrespect ’cause he’s way more trusted
0:39:25 than these other creators who may just be looked at
0:39:29 as like a NASCAR with 40 logos on them.
0:39:29 They don’t like,
0:39:31 you don’t really care what they have to say
0:39:34 just because you know they’re just up for sale
0:39:35 to the highest bidder.
0:39:37 – I just think it’s so important,
0:39:40 especially as being in an industry
0:39:42 that’s so sort of uncertain feeling.
0:39:44 Like I don’t know if you guys feel this way at all,
0:39:47 but when I started making content around AI,
0:39:50 this was, you know, somewhere mid 2021 was
0:39:52 when I really started to make content about AI.
0:39:54 And then I really ramped it up in 2022.
0:39:58 But when I was making content about AI in the early days,
0:40:01 I had zero, zero inclination that this was
0:40:03 a controversial topic.
0:40:04 Like this was just me going,
0:40:06 this is a really fun tool.
0:40:07 Everybody should know about this.
0:40:09 Why don’t more people go play with this mid journey thing?
0:40:11 Why is nobody talking about this?
0:40:13 Or like this GPT three thing.
0:40:16 Like you can go play with it on open AI’s playground.
0:40:17 This is prior to chat GPT.
0:40:19 You can go play with this on open AI’s playground
0:40:21 and have it right copy for you
0:40:24 and have it and have conversations with this thing.
0:40:25 Why aren’t more people talking about this?
0:40:27 This is so much fun.
0:40:29 That was like my approach when I started creating content
0:40:33 around AI was just like, this is just fun stuff.
0:40:36 I had no clue that this was going to be so controversial.
0:40:38 And as, you know, more and more,
0:40:39 I don’t really want to say hate,
0:40:42 but more and more like anti AI,
0:40:45 doomerism, that kind of stuff started to bubble up.
0:40:47 And I started to get more of that kind of stuff
0:40:49 on my comments and my feed.
0:40:51 It actually made me go, okay,
0:40:54 I want to understand why people are so scared of this.
0:40:57 Why, like, what is the big deal with this?
0:40:58 What are the fears?
0:41:00 And so I’ve always tried to take this
0:41:03 like very empathetic approach of like,
0:41:06 I really, really think this stuff is cool and fun.
0:41:09 And I see a lot of use cases for it.
0:41:10 But I also understand that a lot of people
0:41:11 are scared of this now.
0:41:13 And I need to like sort of lean into that.
0:41:15 And I need to talk about that narrative as well.
0:41:18 And I need to, you know, help people that have those fears,
0:41:20 kind of get over those fears.
0:41:23 And even to some degree talk a little bit
0:41:25 about the fears that are, in my opinion,
0:41:28 like actual worthy fears to think about, you know,
0:41:32 things like the deep fake scams of like the voice cloning
0:41:35 where people are calling other people using cloned voices
0:41:36 and scamming them out of money.
0:41:39 Or, you know, we talked about a story on the show
0:41:42 about somebody in, I think it was Hong Kong
0:41:44 that got scammed out of $25 million
0:41:46 over a deep fake Zoom call, right?
0:41:49 And so there are like these genuinely scary things.
0:41:53 And I think it’s important to be very holistic
0:41:56 with what we talk about because there is that fear
0:42:00 and not building that trust with people in this time
0:42:02 where everybody feels so uncertain
0:42:05 just seems like a very, very short-sighted approach
0:42:07 to content creation.
0:42:10 – Yeah, I mean, look, some of the fears are warranted, right?
0:42:12 Like there are voice actors on Fiverr, for example,
0:42:14 they’re probably gonna get wiped out.
0:42:15 So I understand it.
0:42:17 But another thing that I often say is like,
0:42:19 the more that we talk about this stuff,
0:42:21 the more people understand what’s going on.
0:42:23 And I do think that knowledge is power.
0:42:27 And, you know, the more we talk about it
0:42:28 and the more other creators and other people talk about it,
0:42:31 the less chance it has to be used maliciously
0:42:32 because now we’re, oh, wait a second,
0:42:35 I just got called from my aunt demanding money.
0:42:36 I saw this on Twitter.
0:42:38 I saw Matt talking about this on YouTube.
0:42:41 Like, this could be a scam, you’re a little bit more aware.
0:42:44 And so the impact, the negative impact that it could have
0:42:45 is gonna diminish.
0:42:48 So I should just think it’s,
0:42:49 first of all, forget the comments, man.
0:42:51 Like this is one thing I’ve learned about
0:42:53 being a creator on the internet is like,
0:42:55 once you have like a really intimate site,
0:42:57 understanding of human psychology,
0:43:00 you begin to understand why different comments are happening.
0:43:03 Okay, this comes from fear.
0:43:06 This is a comment that’s rooted in insecurity.
0:43:06 Oh, I see this guy.
0:43:09 And so like all of a sudden you have like this shield
0:43:11 and invincibility surrounding you once you understand
0:43:13 like kind of the psychology behind it.
0:43:16 Because I think talking about this stuff is not a negative.
0:43:20 I think it’s definitely a net positive because of that.
0:43:21 Like people have to understand what’s going on.
0:43:24 This is technology that’s gonna impact everybody’s life.
0:43:27 And so, you know, kudos to you guys for staying on top of it
0:43:31 and like covering, like Matt, like your YouTube channel is,
0:43:32 dude, it’s like an encyclopedia.
0:43:36 It’s like you can go, it’s like a historical time capsule.
0:43:36 It’s amazing.
0:43:37 I really appreciate that.
0:43:39 And you are as well too.
0:43:40 I love following you on Instagram.
0:43:43 Your videos you put out on Instagram are amazing.
0:43:44 I believe you’re on TikTok as well,
0:43:46 but I mostly see you on Instagram.
0:43:47 I’m not really on TikTok.
0:43:51 I don’t even know if TikTok’s gonna exist in nine months or not.
0:43:53 But that’s a whole different rabbit hole.
0:43:56 Real quick though, prediction, Nathan,
0:43:57 what is TikTok’s fate?
0:43:59 Like, what prediction?
0:44:00 Oh, what’s, okay.
0:44:02 So I’m, you know, I don’t know if you know that.
0:44:04 So I studied Mandarin in Taiwan.
0:44:06 So I’m probably biased against China.
0:44:11 So, so I’m definitely very, you know,
0:44:12 I’m concerned about China.
0:44:15 That’s actually one of the big reasons I’m like, you know,
0:44:17 I don’t know if I’d come up with a member of EAC,
0:44:20 but you know, I do want to, for America to win at AI.
0:44:21 I think it’s very important.
0:44:24 And so I don’t think China should win at AI.
0:44:26 I think that’d be very bad for the world and for freedom.
0:44:30 And so I’m, I think that TikTok will get divested.
0:44:31 I think that they, like, yeah, sure,
0:44:33 they’re saying that they won’t do that.
0:44:34 And the reason they’re saying they won’t
0:44:36 is because they definitely are,
0:44:37 they definitely do indirectly have connections
0:44:39 to the Chinese government.
0:44:41 Like every, like, like China,
0:44:42 like most people don’t realize this,
0:44:44 but like, I think it was like maybe four years ago,
0:44:45 or something like this.
0:44:47 You know, I had a, I have a friend in the Chinese government.
0:44:48 I actually used to spend time out there.
0:44:49 They tried to get me to move out there
0:44:52 and set up an office for me maybe 10 years ago.
0:44:53 And so I got a lot behind the scenes.
0:44:57 And, you know, probably five years ago,
0:45:00 the Chinese government like put a member of the government
0:45:03 on every single board of every major tech company.
0:45:05 And almost nobody reported on it,
0:45:08 but like everybody who like knows people in China,
0:45:09 they all know this.
0:45:10 It’s like, holy crap, that happened.
0:45:13 And it, it like happened overnight where all of a sudden
0:45:16 there’s a board member on every single major tech company
0:45:18 in China and, and that board member,
0:45:19 even if they’re just one board member,
0:45:21 they basically have control of the companies now.
0:45:24 So, yeah, I don’t think we should have a company
0:45:25 that has any connection to the Chinese government
0:45:28 having influence on young people in America.
0:45:32 And, and, and so I, so my prediction is it will be divested.
0:45:33 And, and I think that’s a good thing.
0:45:37 – I do think that probably some company in the US will buy them,
0:45:40 but they’re really hesitant about giving another company
0:45:43 access to their algorithm, right?
0:45:45 So I feel like if that does happen,
0:45:47 it’ll end up being a watered down version of TikTok.
0:45:50 And yeah, I don’t really know
0:45:54 because I’m not somebody that uses TikTok much.
0:45:56 I’ve posted like three videos ever
0:45:57 that have never gotten any traction
0:46:01 and I’ve maybe scrolled the TikTok feed twice my entire life.
0:46:04 So I don’t know a whole lot about TikTok,
0:46:06 just other than what I hear in the news.
0:46:09 But I do think they’ll end up working
0:46:12 with some American company to, you know, get it sold.
0:46:14 But then there’ll be some sort of weird thing
0:46:16 where they don’t actually get access to the algorithm.
0:46:18 And then it’ll be a watered down version of TikTok.
0:46:21 And then I think Reels will end up just taking over
0:46:23 and replacing TikTok anyway.
0:46:27 But again, that is of, you know, it’s not a very hot take
0:46:30 ’cause I don’t really know what I’m talking about in that realm.
0:46:31 – We made an interesting point about Reels.
0:46:32 Like I’m so bullish on Reels.
0:46:36 Actually, the Reels business already generates more revenue
0:46:38 than TikTok’s entire business.
0:46:41 And I think we’re going to continue to see that as creators,
0:46:42 you know, sort of start spreading their eggs
0:46:44 across different baskets.
0:46:46 ‘Cause I do think it’s going to get,
0:46:47 I think it’s going to get banned.
0:46:50 Like maybe just China’s sort of using that as leverage,
0:46:53 saying that divestiture is not an option, this and that.
0:46:55 But it is funny, man, it’s like the one thing
0:46:57 that legislators in the United States
0:46:59 from the left and the right can agree on.
0:47:02 And so it’s like, they’re very determined to take TikTok out.
0:47:04 I do think it eventually happens.
0:47:07 And, you know, just six months ago, I would have told you no.
0:47:09 That’s another reason why I’m very bullish on Meta.
0:47:12 I think they’re the biggest beneficiaries of,
0:47:14 and YouTube and Google, of course.
0:47:16 But I think they’re the biggest beneficiaries
0:47:18 of TikTok’s potential demise.
0:47:20 – Yeah, it’s funny you mentioned that.
0:47:22 As soon as Meta started open sourcing,
0:47:24 like their llama models and stuff like that,
0:47:26 I started buying up stock in Meta because I was like,
0:47:28 all right, Meta’s actually,
0:47:30 Meta’s redemption arc just started.
0:47:33 And I feel– – Not financial advice.
0:47:34 – Not financial advice.
0:47:39 I’m not telling anybody to go buy Meta stock.
0:47:40 But I went and bought Meta stock
0:47:42 as soon as they started open sourcing
0:47:44 because I went, all right, Meta,
0:47:46 I think Meta’s doing the right thing here.
0:47:51 I think their redemption story is turning the corner, right?
0:47:54 I feel like Mark Zuckerberg has gotten some,
0:47:56 you know, bad press in recent years,
0:47:57 but I think what they’re,
0:47:59 the direction they’re taking Meta in
0:48:02 is the right direction with the open source
0:48:04 and really putting the focus on AI.
0:48:08 And, you know, I’m personally still bullish on like VR
0:48:09 and the Meta quest and stuff.
0:48:10 I have a Meta quest.
0:48:11 It is really, really fun
0:48:13 when you get in there and play with groups.
0:48:15 So yeah, I’m a fan of Meta.
0:48:17 – I think the Zuckerberg arc has been hilarious.
0:48:20 Like, you know, just to see his transition.
0:48:22 So I got to say hi to him one time,
0:48:23 but he has no idea who I am.
0:48:24 He was like at a party,
0:48:26 at a game industry party way back in the day.
0:48:28 And, but just seeing how he’s changed,
0:48:30 he looks dramatically different now.
0:48:31 And there was a while, you know,
0:48:33 there was a period where he was like learning Mandarin
0:48:35 and he was trying to get Facebook into China.
0:48:37 – I mean, Facebook being banned in China,
0:48:38 that’s another reason.
0:48:40 It’s like, hey, the reciprocity here
0:48:43 is another reason why I’m not super
0:48:44 against TikTok being banned.
0:48:46 But yeah, come in and dude,
0:48:48 I’ve been buying a lot of Meta stock
0:48:50 and definitely not financial advice.
0:48:52 Cause if you follow my trade, you’re going to go bankrupt.
0:48:54 I’m just letting you know.
0:48:55 But I think if I had a,
0:48:57 I do think Facebook’s on the way
0:48:58 to a $2 trillion market cap.
0:48:59 I think it’ll happen in the next three years.
0:49:01 And I think Mark Zuckerberg is going to be
0:49:03 the richest person in the world.
0:49:03 I just, I mean,
0:49:05 4 billion people using their products.
0:49:07 I think again, like,
0:49:10 I think people still highly undervalue
0:49:14 the power of Instagram, WhatsApp, Facebook.
0:49:15 The reality labs and all that stuff
0:49:17 is still yet to be seen.
0:49:21 But I think the biggest reason that I’m bullish on Meta,
0:49:23 and I just interviewed Mark Zuckerberg.
0:49:25 So obviously like there’s a bias there,
0:49:26 but I think it’s him.
0:49:28 Like he’s a founder.
0:49:30 He’s been there for 20 plus years now.
0:49:32 He’s the, maybe the most, like he’s a killer.
0:49:35 Like he’s the most competitive person.
0:49:36 I think in entrepreneurship.
0:49:38 Like he wants it all.
0:49:39 He’s coming for it all.
0:49:40 He actually just wore a shirt
0:49:43 for his 40th birthday post that says,
0:49:45 I think death to Carthage,
0:49:46 which is basically,
0:49:50 it’s a modern day sort of rallying war cry.
0:49:52 And to me represented,
0:49:53 I don’t have any insider information,
0:49:55 but to me it represented like,
0:49:57 he wants to win.
0:49:58 He wants all the smoke.
0:49:59 He’s coming.
0:50:01 Like the guy is kind of like Sam Altman,
0:50:04 just absurdly competitive.
0:50:06 And that’s one guy that I,
0:50:07 much like Tom Brady,
0:50:09 much like Kobe back in the day.
0:50:12 It’s like one guy that I could just never bet against.
0:50:13 – Yeah, yeah.
0:50:14 Did you watch the roast, by the way?
0:50:16 – I love the roast.
0:50:16 And by the way, I have,
0:50:17 dude, I have an idea.
0:50:18 Like everybody,
0:50:21 okay, like Zuckerberg’s arc has been incredible.
0:50:23 Like he’s been,
0:50:24 and by the way,
0:50:27 working with his PR and communications teams,
0:50:28 I get it.
0:50:30 Like these people are sharp.
0:50:32 Like they are so tuned into the culture.
0:50:33 They’re brilliant.
0:50:34 I love the whole experience.
0:50:38 But I think him or Elon or Sam Altman or Sundar,
0:50:40 one of these guys should have a roast.
0:50:42 Because if you want to like humanize
0:50:44 and endear people to a founder,
0:50:47 like there’s no better way to be humanized
0:50:49 and endeared than self-deprecation
0:50:52 and getting shit on for two hours by famous committees.
0:50:55 So if anybody’s out there from Zuck, Elon,
0:50:56 whoever’s team,
0:50:58 like get one of these guys on a roast, man.
0:51:00 I think it’s a good move.
0:51:01 – That’s such a great idea.
0:51:03 But speaking of Zuck,
0:51:04 is there any like,
0:51:06 what’s the story behind how you got them?
0:51:07 I don’t know if that’s something
0:51:08 you’re open to sharing or not,
0:51:09 but is there a story there?
0:51:12 Like how did you actually land Zuck for an interview?
0:51:13 – Yeah, man.
0:51:15 I mean, the first thing I’ll say is a lot of luck involved.
0:51:18 But then I also say that kind of just a PSA
0:51:19 to anybody listening,
0:51:20 you can create your own luck.
0:51:23 So basically what I think happened,
0:51:26 I don’t know what haven’t asked his team, why me,
0:51:30 but I’ve been creating content now about emerging tech
0:51:33 on Instagram for over two years now,
0:51:35 not necessarily on my page,
0:51:36 but on my media pages.
0:51:37 One is called metaverse,
0:51:38 second is a three,
0:51:41 the other one aluna.ai.
0:51:44 And I’ve put a lot of work into that, man.
0:51:45 Like a lot, a lot of work,
0:51:46 especially early in the day,
0:51:48 I’d have like these long,
0:51:49 you know, 10 post care cells,
0:51:50 so much information,
0:51:52 data rich, really well designed.
0:51:53 And it obviously caught the eye
0:51:56 of a lot of people at meta.
0:51:58 And I’d be friended,
0:52:01 dude, this is another reason why I bought so much stock.
0:52:03 Like I have so many friends at meta now
0:52:05 and the teams there are just so talented, man,
0:52:08 across like all of their endeavors.
0:52:11 And I’m doing a lot of work with meta over this year,
0:52:12 like we’re going to Cannes in a month
0:52:14 and like got a lot of stuff going on,
0:52:16 but I’ve befriended a lot of people in meta
0:52:17 and I’ve just like developed
0:52:19 this really great relationship with them.
0:52:21 And they always hit me up and it’s like,
0:52:22 Hey, we got some news drop
0:52:23 and do you mind like covering it,
0:52:25 maybe making a video putting on metaverse or whatever.
0:52:27 And I’m like always happy to do it
0:52:29 just because I love this stuff.
0:52:32 And I’ve never asked for anything in return.
0:52:35 So like my intuition says that
0:52:37 because I’m like an Instagram first creator
0:52:39 and I’ve been like doing so much for them
0:52:41 for two years now without ever asking
0:52:42 for anything in return,
0:52:44 I think it’s almost like this karma
0:52:46 that was just put out there
0:52:47 and they sort of honored me
0:52:50 and rewarded me with it for that.
0:52:51 That’s my guess.
0:52:54 I don’t know for sure,
0:52:56 but I just tell people, yeah, luck,
0:52:57 but you can create your own luck.
0:52:59 I think the last two, two and a half years
0:53:02 creating on Instagram has kind of proven that.
0:53:03 – You know, that actually leads me something
0:53:05 that I wasn’t planning on asking you,
0:53:07 but now I’m curious ’cause you brought it up.
0:53:11 Like how does like the monetization on Instagram work,
0:53:14 is it mostly like sponsors sponsoring your content
0:53:16 or does meta actually pay you similar
0:53:18 to like how YouTube and Twitter does now?
0:53:20 – No, definitely not off platform.
0:53:22 And like that’s another fascinating conversation
0:53:24 that we can get into.
0:53:26 The economics of why it’s,
0:53:28 even though TikTok with the creativity programs doing it,
0:53:29 but I think they’re subsidizing a lot.
0:53:31 I don’t think that’s a longterm thing,
0:53:34 but you know, YouTube, the magic of YouTube is like,
0:53:36 hey, you have pre-roll, you have interstitial,
0:53:38 you have like all these ad placements.
0:53:40 And because it’s an eight plus minute video,
0:53:42 20 minute, in your case, sometimes 30, 40 minute video,
0:53:46 it’s like they can attribute that direct ad revenue
0:53:48 to the creator bringing in these people.
0:53:50 On Instagram, it doesn’t, Instagram and TikTok,
0:53:52 like when I say a lot,
0:53:54 people are more fans of the platform
0:53:55 than they are the creator.
0:53:57 And on YouTube, people are more fans of the creator
0:53:59 than they are necessarily the platform.
0:54:02 So like TikTok, Instagram’s doing the heavy lifting,
0:54:04 getting the discovery, getting people to use,
0:54:06 and making their app sticky, getting people to use it.
0:54:07 And like you’re a beneficiary of that,
0:54:10 but it’s hard to pinpoint and attribute,
0:54:12 you know, where the revenue should be directed.
0:54:14 So like I understand why they don’t pay directors,
0:54:16 or sorry, creators directly.
0:54:19 But yeah, all of my revenue on Instagram,
0:54:20 I just use that as discoverability.
0:54:22 And then the revenue happens third party,
0:54:24 whether it be sponsors, ads, paid communities,
0:54:26 whatever it might be.
0:54:29 But yeah, they don’t pay creators, well they do,
0:54:30 but it’s not a lot.
0:54:33 Like I think one month I had like 30 million views
0:54:35 and I got paid like $32.
0:54:37 (laughing)
0:54:39 – The Twitter actually stays better than that.
0:54:40 (laughing)
0:54:43 – Dude, dude, everything pays better than that.
0:54:44 But yeah, that’s what I say.
0:54:46 Like Instagram’s a discovery platform
0:54:49 with relationship components built in.
0:54:51 But if you’re looking to get paid direct from platform,
0:54:54 I mean YouTube’s a place to be 100%.
0:54:56 – Well, I think, you know,
0:54:58 I think we could probably have
0:55:00 like another hour long conversation,
0:55:02 but I think we’ll have to have you back on, you know,
0:55:04 as one of our more regular guests,
0:55:06 ’cause I feel like we can probably nerd out frequently
0:55:07 about whatever is going on.
0:55:10 But you know, I do wanna be respectful of your time.
0:55:12 – Dude, I could go on for hours and hours.
0:55:14 So anytime you guys need like a third,
0:55:16 even like co-host or whatever you just wanna riff,
0:55:18 I’m always available.
0:55:21 But I do wanna leave with a question.
0:55:22 What do you guys think?
0:55:25 WWDC, I think this episode will go out before then.
0:55:28 So all lies on Apple.
0:55:29 Just we don’t have to get into it super,
0:55:33 but from one to 10, like how big of an impact
0:55:36 or how impactful is that event gonna be,
0:55:38 you guys think from one to 10?
0:55:40 – Three.
0:55:42 So they just now inked the deal with OpenAI.
0:55:43 So that tells me two things.
0:55:45 Like if they’re partnering with OpenAI,
0:55:45 that means I mean,
0:55:48 I think they’re gonna be quite reliant on OpenAI.
0:55:51 And so I doubt that we’re gonna see a major Siri update
0:55:53 ’cause they’re probably relying on OpenAI for that.
0:55:55 So I think a month is so soon
0:55:58 for them to have something amazing new with Siri by then,
0:55:59 but who knows?
0:56:01 Maybe this has been in the works and yeah.
0:56:04 – Unless we saw a sneak peek of what Siri is gonna be
0:56:08 on Monday with the OpenAI GPT-40 demo.
0:56:09 – Yeah.
0:56:11 – That could be what Siri is.
0:56:13 – Yeah, that could be.
0:56:16 That’s gonna, yeah, that’d be like a huge alliance
0:56:18 between OpenAI, Microsoft, and Apple.
0:56:20 And then I guess you’ll have, you know,
0:56:23 Amazon will be, you know, partnering with Interopik.
0:56:24 – I don’t know if Microsoft’s really gonna be a piece
0:56:25 of that deal. (laughs)
0:56:28 I don’t think Microsoft and Apple still have much love
0:56:31 for each other, but I don’t know, it’ll be interesting
0:56:34 because it feels like Microsoft and OpenAI are starting
0:56:35 to make moves to sort of separate
0:56:37 from each other a little bit, right?
0:56:39 – Yeah, but certainly that’s very hard.
0:56:41 Like unless OpenAI comes out with AGI.
0:56:42 – Which you know.
0:56:44 – And they determine what AGI is.
0:56:45 So that’s a whole another.
0:56:47 – Like I said, we’ll do another episode for all this,
0:56:49 but yeah, Matt, one to 10 out of curiosity.
0:56:54 You, like where are your expectation levels for WWDC?
0:56:55 – I, not as great.
0:56:57 The expectation was a lot bigger last year
0:57:00 ’cause we knew Vision Pro was coming this year.
0:57:02 I feel like the big thing they’re gonna be talking about
0:57:06 is, you know, whatever updates they make to Siri.
0:57:08 And I think it’s gonna be stuff
0:57:10 that we’ve already seen before, right?
0:57:13 It’ll be new to Apple, but those of us that are in the AI
0:57:15 world paying attention, you know,
0:57:17 that have seen a few things already.
0:57:18 – Yeah.
0:57:20 – Gonna feel like nothing new to us.
0:57:23 That’s kind of what I’m expecting.
0:57:26 – So my prediction is like you just said,
0:57:30 it’s what we saw with OpenAI, GPT40,
0:57:32 and with Google’s project Dastra.
0:57:34 I think that was a sneak peek,
0:57:36 sort of a preview of what we’re gonna see with iOS,
0:57:38 where it’s like Siri’s gonna be revamped.
0:57:40 It’s gonna be powered by, you know,
0:57:42 some sort of omnimodal LLM that takes,
0:57:45 you know, that uses a lot of the hardware and the device.
0:57:47 And I think it’s basically going to power
0:57:50 the entire ecosystem of Apple devices.
0:57:53 But the difference is they’re gonna present it
0:57:55 in such a spectacular way.
0:57:56 Like I made this point where Google,
0:57:58 it’s like they’re presenting this incredible technology,
0:58:00 but they don’t make us excited about it.
0:58:04 Where Apple sometimes presents like a feature
0:58:06 that nobody ever uses or nobody ever will use,
0:58:07 but we’re like, oh my God,
0:58:09 it’s the coolest thing I’ve ever seen.
0:58:11 And so even if they just announced sort of what we
0:58:14 already expect and what we already have seen,
0:58:16 the way that they will announce it
0:58:17 is gonna get people psyched.
0:58:19 So I’m like, I’m more interested in the presentation,
0:58:21 the cinematography, the visuals.
0:58:22 So I’m really excited, man.
0:58:24 I have a lot of, I have a high expectation,
0:58:27 so I’m just setting myself up to be let down,
0:58:28 but we’ll see.
0:58:29 – I think behind the scenes
0:58:30 some really big things are probably happening,
0:58:32 ’cause like open AI partnering with Apple,
0:58:33 and then Apple’s been saying that they’re building
0:58:35 all these new chips that are getting better and better
0:58:37 for AI, you know, and you combine that with Sam Altman
0:58:40 saying that the big limitation on AI right now
0:58:42 is chips and having more chips
0:58:44 and not just relying on Nvidia, you know,
0:58:45 I wouldn’t be surprised if there’s some huge alliance
0:58:48 going on there where like open AI and Apple
0:58:50 are gonna collaborate on new AI chips
0:58:51 or something in the future.
0:58:54 – Well, yeah, the M4 may be a puzzle piece there,
0:58:56 but all really interesting, man.
0:58:58 I’m really excited for WWDC.
0:59:00 And for your video covering it, Matt,
0:59:02 I’m gonna be the first one that I watch.
0:59:05 – Yeah, I won’t actually be at WWDC this year,
0:59:07 but yeah, no, I’m excited to watch the stream
0:59:08 and talk about it.
0:59:09 – It’s better when you’re not there,
0:59:10 ’cause then you’re in the lab like ready
0:59:11 to crank something out.
0:59:13 – Yeah, yeah, yeah.
0:59:15 I mean, going to these events is really cool
0:59:17 because you actually get to meet the people in the company.
0:59:22 And I made a point in my video about the Google I/O event
0:59:28 is that it’s like really easy to sort of think
0:59:30 of these Googles and Apples and Microsoft
0:59:32 as these big faceless companies
0:59:33 that they just want your data
0:59:35 and they don’t really care about the individual.
0:59:37 But then you go to these events
0:59:38 and you talk to the engineer
0:59:40 that built this one feature
0:59:42 that they’re gonna be announcing on stage today.
0:59:44 And that one engineer is like nervous
0:59:47 and anxious and excited that they’re one thing
0:59:51 that they made is being presented today
0:59:53 and they can’t wait to see how it’s being perceived.
0:59:56 And they’re all giddy and nerdy and excited
0:59:58 about this piece that they worked on.
1:00:02 And you start to realize the humanity at these companies.
1:00:03 You start to realize that Google
1:00:05 isn’t a giant faceless company.
1:00:07 It’s made up of people that are just as excited
1:00:10 and nerdy about all of this stuff as we are.
1:00:13 But on the news and all of that,
1:00:16 you just see it as this giant faceless corporation.
1:00:18 And I think putting faces to these companies
1:00:21 and having that sense of humanity behind
1:00:24 like the people actually engineering these things
1:00:26 is really, really powerful.
1:00:29 And I’ll make YouTube videos talking about
1:00:30 like the latest thing Google just dropped
1:00:32 and like half the comments,
1:00:33 I know we need to ignore the comments
1:00:35 but half the comments will be things like,
1:00:36 oh, Google’s evil.
1:00:38 Why are you even talking about them?
1:00:40 Oh, they’re all just trying to harvest our data.
1:00:41 They don’t care about you.
1:00:42 But going to these events,
1:00:46 you realize that’s not really fully the truth.
1:00:47 And so–
1:00:50 – That is so well said, man.
1:00:51 I’ll end it with this,
1:00:52 like Mark Zuckerberg was very similar.
1:00:55 Like I have, I’m living in Charlotte right now.
1:00:58 I have like a lot of family who are kind of like
1:01:00 suspicious of Mark Zuckerberg.
1:01:02 – Not even as a lizard person or whatever.
1:01:03 – Yeah, you see these comments.
1:01:04 Isn’t he like Illuminati?
1:01:06 Like trying to just like ruin the world.
1:01:08 And I’m talking to the guy and he’s just like,
1:01:10 the craziest part about interviewing him,
1:01:12 he’s like, it was like talking to you guys.
1:01:13 He’s just a bro.
1:01:14 Like he’s just one of us.
1:01:17 He loves, I mean with $150 billion in his bank account,
1:01:20 but he really loves this stuff, man.
1:01:22 He’s like a tinkerer at heart.
1:01:24 Like he was so personable.
1:01:27 I was like, he’s going to probably be in a rush
1:01:30 or maybe like, you know, like here’s another funny thing.
1:01:32 Like I looked it up last year, you know,
1:01:35 his net worth balloon and it amounted
1:01:38 to nine and a half million dollars per hour that he made.
1:01:40 So I was like, okay, so my 40 minutes with him
1:01:42 is worth like $7 million for the guy.
1:01:44 He’s going to be like in a rush, like hurry up.
1:01:46 But we got to chat like five minutes before,
1:01:49 five minutes after, like he even wanted to stay longer,
1:01:50 just like shooting the shit about the UFC.
1:01:51 But his team was like, all right,
1:01:52 we got to go next meeting or whatever.
1:01:56 But he was just so weirdly normal.
1:01:57 – Yeah, yeah.
1:01:59 – And I was kind of off put by that.
1:02:01 I was expecting somebody just kind of like annoyed
1:02:03 that he had to talk to me.
1:02:05 But yeah, man, it was a really cool experience.
1:02:07 So to your point, like these people working
1:02:09 at these companies are actual human beings
1:02:10 who love what they’re doing.
1:02:13 They’re not trying to destroy humanity.
1:02:15 – Well, thanks again for hanging out with us today
1:02:18 and nerdin’ out with us before to do it again.
1:02:20 – That was a lot of fun, guys.
1:02:21 I love this.
1:02:21 That was awesome.
1:02:24 (upbeat music)
1:02:27 (upbeat music)
1:02:29 (upbeat music)
1:02:32 (upbeat music)
1:02:34 (upbeat music)

0:00:01 (upbeat music)
0:00:03 – I’m still very bullish on Google
0:00:05 because I think it’s like the tip of the iceberg
0:00:07 of what you see in tech companies
0:00:09 and the submerged part is just amazing.
0:00:10 They’ve got the most complete models
0:00:12 of the physical and digital world.
0:00:15 They’ve got ubiquitous distribution
0:00:17 and an existing ecosystem of ads and sales
0:00:19 to plug monetization in.
0:00:21 So I think it’s still a magical combination.
0:00:27 – Hey, welcome to the Next Wave podcast.
0:00:28 I’m Matt Wolf.
0:00:30 I’m here with my co-host, Nathan Lans.
0:00:33 And with this podcast, it is our goal
0:00:36 to keep you looped in with all of the latest AI news,
0:00:38 the latest AI tools,
0:00:41 and just help you keep your finger on the pulse
0:00:43 so that you are prepared for the next wave of AI
0:00:44 that’s coming.
0:00:47 And today we have an amazing guest on the show.
0:00:50 We have Bilival Sidhu on the show.
0:00:52 He is the host of the TED AI podcast.
0:00:54 He’s an ex-Googler.
0:00:56 We’re gonna talk to him about what it was like
0:00:59 working on AI and visual effects over at Google.
0:01:02 We’re gonna talk about the difference
0:01:04 between whether or not we should be accelerating AI
0:01:06 or slowing down AI.
0:01:08 We’re also gonna learn about how some
0:01:11 of these AI visual effects tools work
0:01:13 because this is the field that Bilival worked in
0:01:14 for so long.
0:01:15 It’s an amazing episode.
0:01:17 You’re gonna learn a ton
0:01:18 and can’t wait to share it with you.
0:01:20 So let’s jump on in with Bilival Sidhu.
0:01:24 Thanks so much for being on today, Bilival.
0:01:25 – Thanks for having me, gentlemen.
0:01:26 Pleasure to be here.
0:01:29 – Yeah, so I wanna just kind of dive right into it.
0:01:32 Your background is Google, right?
0:01:35 So I think when you and I first connected
0:01:38 and we first started having some chats over Twitter DM,
0:01:41 you were still actually working over at Google at the time
0:01:43 and you also were kind of doing a creator business
0:01:45 on the side with your YouTube channel
0:01:46 and everything you had going on.
0:01:48 But Bilival Sidhu, what were you doing over at Google?
0:01:49 What was your role there?
0:01:52 You know, what was your experience like over there?
0:01:53 – Gosh, yeah, it was awesome.
0:01:55 So, you know, I’ve spent a decade in tech,
0:01:57 six years at Google.
0:01:58 I’ve been able to work on projects
0:02:00 that blend the physical and digital world.
0:02:03 And I started off in the AR/VR team really
0:02:06 when spatial computing, as it’s now called,
0:02:07 was first popping off.
0:02:10 This is like right after the DK2 came out,
0:02:11 Google Glass was a thing.
0:02:15 And everyone was talking about what is the next iteration
0:02:16 of computing platforms?
0:02:19 Where are we gonna go from like this mobile revolution?
0:02:22 And so I had a chance to work on a bunch of cool stuff there,
0:02:26 YouTube VR content, livestreaming Coachella,
0:02:28 Dean Choice Awards, Elton John,
0:02:30 the camera systems that we used
0:02:33 to do stereoscopic 3D capture, AR SDKs,
0:02:35 when that became popular, augmented reality,
0:02:37 sort of hit the scene.
0:02:40 And then after that, I spent four years at Google Maps,
0:02:43 basically creating a ground up 3D model of the world,
0:02:45 sort of remapping the world, if you will,
0:02:48 and then turning the world into an AR canvas
0:02:51 with the AR Core Geospatial API.
0:02:53 It’s been a lot of fun and yeah,
0:02:55 it’s been awesome to work with some really talented folks
0:02:59 to work on these projects that have been blurring this line
0:03:01 between the world of bits and atoms.
0:03:03 – So I’m curious, working on all this stuff,
0:03:05 in my mind, I can’t even imagine
0:03:07 what a day-to-day looks like at Google.
0:03:09 I’ve been on the Google campus
0:03:13 and it looks like a giant playground for tech nerds.
0:03:14 So I’m just kind of fascinated
0:03:17 by what it’s like to work at Google.
0:03:19 Like what does a day-to-day look like over there?
0:03:20 – You know, so I was a product manager
0:03:23 and so a day-to-day for me is gonna be very different
0:03:26 than if you go talk to like an engineer or designer.
0:03:27 For me, really it was a lot of meetings.
0:03:30 Let me be perfectly honest, just like a ton of time.
0:03:31 But there’s some very cool things.
0:03:34 I think like Google and big tech companies generally
0:03:37 are sort of this like interesting microcosm
0:03:39 where it’s like, you know, I’ll send out an email
0:03:43 and the guy that wrote the book on computer vision,
0:03:46 like the computer vision book that like everyone reads,
0:03:48 like a response to it and I get a bunch of pings
0:03:51 and you’re like, oh, so-and-so respond to your thing.
0:03:53 And it’s like all these Pokemon that like, you know,
0:03:55 these companies have caught that are available
0:03:58 at your back, back in call to share ideas with,
0:04:01 pull into your own projects and really just like,
0:04:05 you know, there’s such a, it’s like the tip of the iceberg
0:04:07 of what you see in tech companies
0:04:09 and the submerged part is just amazing.
0:04:11 So it’s like, when I moved over to the maps team,
0:04:14 I was thinking of working on glasses at the time.
0:04:16 And the reason I went to maps is like,
0:04:18 I met this engineer is like,
0:04:21 oh yeah, we write CLs to move satellites around in the sky.
0:04:23 And I was like, wait, what, huh?
0:04:25 You move satellites around the sky.
0:04:27 And it’s like, yeah, like literally orchestrating a fleet.
0:04:29 Like, you know, like most people don’t know this,
0:04:31 like Google owns their own fleet of like,
0:04:33 not just street view cars, but airplanes.
0:04:34 Oh, wow.
0:04:36 And so like the ability to like task those.
0:04:38 So like, hey, we need to, you know,
0:04:41 we’ve got this like Sundar IO thing coming up
0:04:44 and we’re gonna be presenting immersive view.
0:04:47 We got to go capture this high resolution model of London.
0:04:48 And like, not, you know,
0:04:51 and suddenly things in the world of atoms
0:04:52 are moving to make that happen.
0:04:54 I think it’s like absolutely amazing.
0:04:56 I think people deeply underestimate the data mode
0:04:58 that Google has.
0:05:00 Obviously the most complete digital twin of the world
0:05:02 we’re talking about, but like search, right?
0:05:05 Like YouTube, oh my goodness.
0:05:07 All this stuff is available.
0:05:09 And so like, there’s cool things and products
0:05:11 you can build around it.
0:05:13 But along with it comes, you know,
0:05:15 which may not be a surprise to people in tech,
0:05:18 but like a ton of responsibility and sort of guardrails
0:05:20 for how you actually use this data.
0:05:21 So it’s like the size of the prize
0:05:24 and the data sets you get to play with are amazing.
0:05:25 But to be able to do stuff with it,
0:05:28 you really, really have to be exceedingly thoughtful.
0:05:30 And there’s a lot of process involved
0:05:32 in unlocking that innovation.
0:05:33 So yeah, that’s how I would describe it.
0:05:35 I think like it’s just like a,
0:05:38 it’s like, it’s like a Disneyland for nerds to be honest.
0:05:43 When all your marketing team does is put out fires,
0:05:45 they burn out fast.
0:05:46 Sifting through leads,
0:05:48 creating content for infinite channels,
0:05:51 endlessly searching for disparate performance KPIs.
0:05:52 It all takes a toll.
0:05:56 But with HubSpot, you can stop team burnout in its tracks.
0:05:58 Plus your team can achieve their best results
0:06:00 without breaking a sweat.
0:06:02 With HubSpot’s collection of AI tools,
0:06:05 Breeze, you can pinpoint the best leads possible.
0:06:08 Capture prospects attention with clickworthy content
0:06:11 and access all your company’s data in one place.
0:06:14 No sifting through tabs necessary.
0:06:16 It’s all waiting for your team in HubSpot.
0:06:17 Keep your marketers cool
0:06:20 and make your campaign results hotter than ever.
0:06:23 Visit hubspot.com/marketers to learn more.
0:06:28 – So it sounds like you’re still really bullish on Google.
0:06:30 Cause I know we were having like some playful banter
0:06:32 last year about like, you know, I was like,
0:06:34 maybe Google’s going to die.
0:06:36 And you were like, what the hell are you talking about?
0:06:38 – Yeah, yeah, we’ve actually had that conversation
0:06:40 on this podcast before where I’m like, you know what?
0:06:42 I think I give more credit to Google.
0:06:43 I think Nathan’s a little more,
0:06:46 I don’t know if they’re going to be like the top dogs in AI.
0:06:48 Like where do you stand on that?
0:06:49 Do you count Google out?
0:06:52 Do you think Google will pass the Microsoft AI,
0:06:54 you know, Avenger mega team?
0:06:56 – It’s hard to say anything with certainty,
0:06:59 but what I will say is like, you know, after I left Google,
0:07:00 I think I was like one of the few people,
0:07:03 I felt like I was in isolation saying good things
0:07:04 about Google.
0:07:06 Everyone was just like, oh yeah, they’re just too slow.
0:07:09 They foambolt, they came up with a transformer.
0:07:11 All the transformer folks are left.
0:07:15 I think it’s a situation where there was no real disruption
0:07:16 in site for the search base.
0:07:18 Yes, there were talks about like, hey, like kids
0:07:21 are like searching on TikTok and like YouTube like now,
0:07:24 but YouTube is owned by Google on TikTok.
0:07:26 It’s kind of short former people are really going to be like,
0:07:27 is that going to be a resilient thing?
0:07:30 And one might argue now social networks are places
0:07:31 where people do a lot of searching,
0:07:34 but traditional search sort of as like, you know,
0:07:37 a maps guide is to just give the maps analogy.
0:07:40 It’s like, you know, like maps is how you discover stuff
0:07:41 in the real world.
0:07:43 And Google is how you discover stuff in the digital world.
0:07:46 It’s literally your window to the worldwide web, right?
0:07:48 I don’t think anything had like sort of questioned
0:07:51 the strong position Google was in in that regard
0:07:55 until chatGPT came out when suddenly people
0:07:57 could start connecting the dots and see you like,
0:08:00 if you connect large language models with like, you know,
0:08:03 knowledge graph and search index, kind of like perplexity.
0:08:06 And you know, Microsoft co-pilots
0:08:09 and whatever the heck else OpenAI is going to announce
0:08:13 in order to kneecap any Google limelight next week.
0:08:14 Like I think people start saying,
0:08:17 hey, there’s a disruption inside.
0:08:19 And I think combined with the fact that like,
0:08:21 the search ads business model
0:08:24 was just such a money printing machine and still is.
0:08:26 And the fact that, you know, the cost per query
0:08:29 of these generative AI models is obviously going to be higher.
0:08:32 And how do you do advertising and attribution
0:08:34 and all this stuff like that it would like,
0:08:37 kind of represents a, you know, contraction
0:08:40 in the money printing machine and the pie
0:08:41 and the business that Google created
0:08:44 had all the signs of sort of innovators dilemma.
0:08:46 And I think like Google has sort of adopted
0:08:48 the playbook of the innovator solution.
0:08:51 And, you know, initially they had some of these reorgs
0:08:54 that felt more like exec reorgs.
0:08:56 And now they’re actually bringing together
0:08:58 like the brain and the deep mind teams
0:09:01 and they’re actually shipping at a really good cadence.
0:09:04 And I think they still have some of the most unique data sets
0:09:06 that other folks are talking about, you know
0:09:07 that may or may not have been scraped, you know
0:09:11 he’s case in point, the CTO of open AI
0:09:13 being asked by Joanna Stern about,
0:09:14 what does it exactly mean
0:09:16 that you train on publicly available data?
0:09:19 So all this to say, I’m still very bullish on Google
0:09:21 because I think they’ve got the most complete models
0:09:23 of the physical and digital world.
0:09:26 They’ve got ubiquitous distribution
0:09:28 and they’ve got the right infrastructure chops
0:09:31 to basically like bring that cost per query down
0:09:34 and an existing ecosystem of ads and sales
0:09:35 to plug monetization in.
0:09:39 So I think that there’s a like monetizable
0:09:41 sort of like answer engine model.
0:09:43 I think Google is one of the few companies
0:09:44 that could crack it.
0:09:46 That isn’t to say that I think like open AI
0:09:48 and Microsoft can’t take meaningful market share
0:09:50 but let’s be honest, how many of us actually use Bing?
0:09:51 Like I don’t, right?
0:09:53 Like I used it for a little bit
0:09:55 and I probably use perplexity more now.
0:09:58 Yeah, I mean, I am using chat GBT and perplexity
0:09:59 instead of Google a lot these days.
0:10:01 I agree, me too, to be honest, yeah.
0:10:03 And then, you know, I’ve been following,
0:10:04 you know, a long time ago I used to do SEO
0:10:06 like a long, long time ago
0:10:07 and I’ve been kind of following that space
0:10:09 and like in the last two months
0:10:11 and I kind of predicted this a year ago,
0:10:14 they’re like having major changes to the algorithm
0:10:16 where they’re really focusing on authority.
0:10:18 Yeah, domain authority, yeah.
0:10:20 Yeah, the reason they’re having to do that
0:10:23 is because of all the flood of AI content, right?
0:10:26 Like they just can’t deal with the flood of AI content.
0:10:28 So it’s like, okay, how do you deal with that?
0:10:31 Let’s go back to like really valuing the big brands
0:10:34 and the big names or the famous people too.
0:10:36 That’s the other thing is maybe like they’re taking
0:10:37 social signals, like you have a lot of followers
0:10:38 on social media.
0:10:40 Now that’s a signal that you’re a, you know,
0:10:42 an author they should listen to.
0:10:44 Yeah, I mean, why do you think we signed on with HubSpot?
0:10:47 We want that backlink domain authority.
0:10:48 That’s the only reason.
0:10:48 Yeah, yeah, yeah.
0:10:50 (laughing)
0:10:54 I mean, this is like, this is gonna be a meta problem though
0:10:55 for the industry, right?
0:10:57 The just the explosion of synthetic content.
0:10:59 I mean, and some social networks
0:11:01 are almost like incentivizing it.
0:11:03 Like, like on LinkedIn, it gives you,
0:11:06 it uses GPT-4 to suggest the comments.
0:11:08 And now you have just the most cringe like,
0:11:11 like regurgitations and summarizations
0:11:12 of like the original posts from like,
0:11:15 clearly a normal human being would never write this.
0:11:18 But like, if there was a meme about how to respond
0:11:20 to somebody on LinkedIn, I mean,
0:11:22 that’s like encapsulates the style I see.
0:11:22 And so.
0:11:23 But that’s happening on Quora too.
0:11:24 So like right now,
0:11:27 Quora is starting to rank at the top of Google results
0:11:29 and Quora is being dominated
0:11:31 with a chat GPT responses now.
0:11:33 100%, I mean, like books on Amazon too.
0:11:34 And I think the way they came out with a restriction
0:11:37 as well, you can only upload X number of books per day.
0:11:40 Like, I don’t know if that’s the solution.
0:11:42 But like, this is like the deep fake,
0:11:43 shallow fake problem too.
0:11:45 It’s like, everyone’s talking about detecting deep fakes.
0:11:46 And like, how do we figure this out?
0:11:50 It’s like, well, the thing that causes maximum harm today
0:11:51 are aren’t actually deep fakes.
0:11:53 They’re like super shallow fakes
0:11:55 where you take a photo from a different time or a context
0:11:58 and like, you know, kind of put it against another context.
0:11:59 This is exactly the type of stuff.
0:12:01 You’ll see like community noted on Twitter.
0:12:04 And that stuff’s like relatively easier to detect
0:12:06 ’cause you can actually find the source imagery
0:12:08 if you do like reverse image search.
0:12:10 And so like you add in the generative problem
0:12:12 on top of that, it’s like even crazier,
0:12:14 but like most platforms haven’t really even solved
0:12:16 the shallow fake problem, right?
0:12:18 It’s really like when it reaches a certain threshold
0:12:21 of distribution, there’s sort of this retroactive,
0:12:23 let’s go throttle this thing versus like,
0:12:25 how do you get ahead of this?
0:12:26 Anyway, I could talk about that forever
0:12:27 because some of the ways to avoid that is like,
0:12:30 ubiquitous surveillance, which is also not, you know.
0:12:32 Oh yeah, sounds great.
0:12:36 It’s like somehow the solutions to things that sound 1984
0:12:38 is like 1984 technology.
0:12:40 It’s like, it’s kind of weird how that works.
0:12:42 But it’s funny, somebody shared an article with me
0:12:45 just like the other day that was an article about,
0:12:47 well, not just me, but it was like an article
0:12:51 about like these seven AI influencers are, you know,
0:12:54 changing how we see AI or something like that, right?
0:12:56 And then like one of the seven like was my name
0:12:58 and I read the blurb about myself.
0:13:00 And the blurb about myself was like,
0:13:03 I grew up in Louisiana doing real estate and-
0:13:05 – You’re my neighbor.
0:13:08 – And like transitioned into computer programming
0:13:09 and then started teaching AI.
0:13:11 And I’m like, other than the fact that they’re like,
0:13:15 Matt makes content about AI, everything else about that
0:13:17 was just completely wrong.
0:13:18 – I think that’s where also like these models
0:13:21 need to be anchored in some sort of real knowledge graph,
0:13:24 you know, and like, that’s not to say that like, you know,
0:13:27 an approach like search is only gonna give you the truth,
0:13:28 right?
0:13:29 Like there’s like, what is even the truth?
0:13:31 And there’s like differing opinions on it.
0:13:33 But I think these models to be able to like,
0:13:34 just kind of fact check themselves,
0:13:36 at least with known information and come up with,
0:13:39 oh, at least the resources that are reputable are saying,
0:13:43 this is Matt’s bio would be better than, I don’t know.
0:13:46 So I’m like, this is the equivalent of like SEO dribble
0:13:50 that sort of started bleeding into Google around like 2019.
0:13:51 I think like, you know, it’s,
0:13:53 this is gonna be a huge problem.
0:13:55 And not to mention the implications of like,
0:13:57 if we’ve run out of content on the internet
0:14:01 and we are actively disincentivizing human generated content,
0:14:03 like how are we gonna train these models?
0:14:04 Like what’s gonna happen there?
0:14:05 – Yeah.
0:14:08 We’ll be right back.
0:14:11 But first I wanna tell you about another great podcast
0:14:12 you’re gonna wanna listen to.
0:14:15 It’s called “Science of Scaling” hosted by Mark Roberge.
0:14:18 And it’s brought to you by the HubSpot Podcast Network,
0:14:21 the audio destination for business professionals.
0:14:23 Each week host Mark Roberge,
0:14:26 founding chief revenue officer at HubSpot,
0:14:28 senior lecturer at Harvard Business School
0:14:30 and co-founder of Stage Two Capital,
0:14:33 sits down with the most successful sales leaders in tech
0:14:36 to learn the secrets, strategies and tactics
0:14:38 to scaling your company’s growth.
0:14:40 He recently did a great episode called
0:14:44 “How do you solve for a siloed marketing and sales?”
0:14:46 And I personally learned a lot from it.
0:14:47 You’re gonna wanna check out the podcast,
0:14:51 listen to “Science of Scaling” wherever you get your podcasts.
0:14:57 – I wanna talk real quick about search
0:14:59 because just to peek behind the curtain
0:15:02 to anybody who might be listening to this episode,
0:15:05 we’re actually recording it right before Google I/O, right?
0:15:07 Like Google I/O is next week
0:15:09 from the time we’re recording this.
0:15:12 Billavall and I are actually gonna be out at Google I/O
0:15:14 attending in person.
0:15:16 But one of the things that you mentioned
0:15:20 is that OpenAI and Microsoft have a tendency
0:15:23 that whenever Google announces something,
0:15:26 they need to jump in and like sort of one up them.
0:15:28 So by the time this episode comes out,
0:15:32 we’ll probably already know what OpenAI did with search.
0:15:35 But the rumor right now is that OpenAI
0:15:38 is creating some sort of their own search engine
0:15:41 with maybe with Microsoft involved, maybe not.
0:15:44 There’s still a lot of rumors and speculation flying around.
0:15:45 But knowing what you know about Google,
0:15:49 do you think OpenAI and chat GPT can come in and compete?
0:15:52 – I think no, like I think the search index Google has
0:15:53 is a very strong mode.
0:15:56 The fact that they can sort of almost like map the internet
0:16:00 in like almost real time is like just a hard technical
0:16:01 and infrastructure problem.
0:16:04 And they’re really well set up for it.
0:16:05 I’m curious what it is.
0:16:08 Like obviously this is complete pontification rumor mail.
0:16:11 Like what it is OpenAI is going to roll out.
0:16:14 What I think it’s gonna be is like something at parity
0:16:18 with perplexity with maybe a better like search index involved.
0:16:20 Like, and if it’s even if it’s something like that
0:16:23 where you get sort of this like multimodal summary
0:16:25 where it looks at a bunch of links, you get, you know,
0:16:27 some images, maybe some embedded videos
0:16:29 and like a summary of whatever it is you asked for
0:16:32 with citation so you can go validate sort of the quality
0:16:35 of those like the links that were summarized.
0:16:37 I think that would be a huge step up, right?
0:16:40 Like just getting, just being able to invoke like,
0:16:43 like search inside of chat GPT right now is clunky.
0:16:44 You have to be like, hey, well, and look this up,
0:16:48 research this and like explicitly prompted to do that
0:16:49 and being able to do that in a fashion
0:16:54 that is like really about leaning on like sort of a real time
0:16:58 and like sort of, you know, content that has real provenance
0:17:02 along with, you know, like sort of the distilled wisdom,
0:17:03 you know, the wisdom is debatable.
0:17:05 The distilled wisdom that is in,
0:17:07 in these large language models to summarize that,
0:17:09 I think it’s still a magical combination.
0:17:11 And I don’t know if y’all feel like this,
0:17:12 but I think the vibes have been shifting
0:17:14 with regards to just the conversation
0:17:18 and sort of Matt, I know you had this like post about like,
0:17:19 we think things are slowing down,
0:17:22 but here’s a bunch of announcement events coming up,
0:17:25 but doesn’t it feel like just like those leaps
0:17:28 that we hoped for haven’t quite come?
0:17:31 I guess Sora was kind of a leap.
0:17:34 I think the trend from like a million to 10 million
0:17:37 to maybe infinite context is like an interesting leap too,
0:17:40 but maybe we’re just getting too used to it, you know,
0:17:43 like versus the technologies,
0:17:45 like the pace of advancements slowing down.
0:17:46 Curious, which y’all think?
0:17:47 Yeah, I don’t know.
0:17:49 I feel like it’s kind of like it’s on social media,
0:17:52 the perception is, you know, the vibe has shifted,
0:17:53 but I feel like a lot of people
0:17:56 who actually are closer to Sam Altman,
0:17:57 they don’t feel that way.
0:18:00 And so I still believe that, you know,
0:18:01 they have something amazing coming.
0:18:02 – I follow Gary Marcus.
0:18:04 I know I think you actually have Gary Marcus
0:18:06 coming on the TED AI podcast,
0:18:08 so we’ll probably get some more insights from him
0:18:10 in the near future, but, you know,
0:18:12 the sort of Gary Marcus thing
0:18:15 that he’s been sort of all over Twitter about
0:18:20 is that we’re not seeing that same leap from GPT-4 to GPT,
0:18:25 or the same leap from GPT-2 that we saw the GPT-3.
0:18:27 He’s sort of arguing that that exponential curve
0:18:28 that everybody’s talking about
0:18:31 that we’re on with AI is not true, right?
0:18:32 We’re not on this exponential curve.
0:18:36 Otherwise, like, why didn’t we get from GPT-4 to GPT-5?
0:18:40 And half the time we got from GPT-2 to GPT-3, right?
0:18:42 Like, why is it not showing that?
0:18:45 But I also, like, I think my counter argument to that
0:18:46 is just ’cause we’re not seeing it,
0:18:47 doesn’t mean it’s not there, right?
0:18:49 – Yeah, totally.
0:18:51 – I think there’s a lot of stuff happening,
0:18:53 like Nathan sort of alluding to
0:18:57 behind the scenes over at OpenAI that we’re not seeing.
0:19:00 – I think it’s probably more related to, like,
0:19:02 compute requirements to actually use
0:19:05 some of these newer, more advanced models.
0:19:06 If they were to release it right now
0:19:08 with, like, the compute that’s available,
0:19:10 it would be, like, really expensive.
0:19:12 And, you know, the 20 bucks a month
0:19:14 that people are paying to use Jet GPT
0:19:16 is probably not gonna cover the cost of inference to run,
0:19:19 you know, these newer models, same thing with Sora.
0:19:21 – I mean, that’s kind of the leading theory.
0:19:24 I know that I believe with the GPT-2,
0:19:25 like, the mysterious model that came out
0:19:27 is, like, what the hell is that?
0:19:29 Like, maybe that’s what it is, is, like,
0:19:30 they’ve actually, maybe this is something
0:19:32 they actually developed, like, a year or two ago.
0:19:35 And it’s like a, it’s a more efficient architecture
0:19:36 or something like this.
0:19:38 And possibly that’s what GPT-5’s built upon,
0:19:40 then they, you know, they have less issues
0:19:42 with the cost issues in theory, but, yeah.
0:19:45 – I think it’d be hilarious if the GPT-2 stuff
0:19:46 has actually opened AI.
0:19:49 I mean, like, what an interesting way to sort of
0:19:51 test a model in the wild versus, I don’t know,
0:19:54 running some sort of A/B where, like,
0:19:57 there’s some sort of experiments on the chat GPT website
0:19:59 where a subset of users get a certain model
0:20:01 versus another set of users.
0:20:03 Maybe, like, making it explicit that there’s
0:20:04 these two versions of the models
0:20:07 and having people respond to it separately is interesting.
0:20:09 Maybe there’s an intention to create a bit of a PR,
0:20:11 like, sort of, like, you know, kind of,
0:20:14 a seed the conversation and kind of, like,
0:20:16 grease the wheels before the reel,
0:20:17 like, sort of, I don’t know,
0:20:19 race car jump moment happens or whatever.
0:20:22 I don’t know, but it’s like, yeah, like,
0:20:24 I mean, clients agree, like, there’s the compute stuff.
0:20:26 Certainly, Sora hasn’t been rolled out widely
0:20:29 because, like, it’s just so compute-intensive, right?
0:20:31 Like, you need to come up with a completely different,
0:20:34 like, pricing model way beyond the $20 one.
0:20:37 Maybe, hence, them talking to studios and stuff like that.
0:20:39 But all these models will get optimized, too.
0:20:40 To the Gary Marcus point, it’s interesting,
0:20:43 I had a conversation with him last week and it was like,
0:20:46 it’s like, he’s been very consistent about, like,
0:20:48 this not being the right paradigm.
0:20:51 And, you know, I think people liked it,
0:20:53 like, for the lack of, let’s just put it blunt.
0:20:55 Like, people like to shit on Gary a lot.
0:20:57 But, you know, if there’s one thing Gary’s been,
0:20:59 it’s like, it’s been exceedingly consistent.
0:21:01 And so, I don’t know, like, I would like to see
0:21:06 this sort of agentic co-pilot that feels more like an employee.
0:21:08 We certainly haven’t seen it yet, right?
0:21:11 The converse of everything else is the expectations
0:21:13 around AI, like, a year ago,
0:21:15 if we go back to when GPT-4 came out,
0:21:19 we’re just so fricking high that people just thought,
0:21:20 like, whether you were a knowledge worker
0:21:23 or a visual creator, you would look at the narrative
0:21:24 and you’d be like, holy crap,
0:21:26 like, this thing’s gonna take my job.
0:21:27 And then I don’t know if y’all saw the tweet,
0:21:29 I was like, and then you go use the tech
0:21:32 and it feels less like this, like, fricking kaiju Godzilla
0:21:34 that’s gonna stomp you and more like this, like,
0:21:36 chaotic golden retriever that you can kind of coax
0:21:39 to do cool stuff with you.
0:21:41 And I think that delta between expectations
0:21:44 and reality is so stark and, you know,
0:21:46 like, there was all of these,
0:21:48 I think even in a recent Sam Altman interview where he was
0:21:50 asking one of his biggest regrets is like,
0:21:53 GPT-4 didn’t have that, like, economic impact.
0:21:55 Everyone thought it would.
0:21:56 And he’s worried that the pendulum
0:21:58 will swing sort of the other way now,
0:22:00 where if expectations were so high,
0:22:02 people were like, oh yeah, whatever.
0:22:03 And so, I don’t know,
0:22:04 I think the answer is always gonna be in the middle,
0:22:07 but I can’t help but feel like we’ve gone past
0:22:09 the, like, peak of inflated expectations
0:22:12 and we’re going into the trough of disillusionment.
0:22:12 – Well, we’ll see.
0:22:14 I mean, like, Sam Altman also said that, like,
0:22:17 he was surprised that GPT-4 was so successful
0:22:19 and that, you know, it kind of sucks.
0:22:21 – I don’t know, my feeling on that is that Sam Altman
0:22:23 is one of the, like, greatest marketers
0:22:24 of our time right now.
0:22:27 And he’s, you know, he’s really, really, really good
0:22:29 at getting that hype wheel spinning.
0:22:30 – Oh, baby.
0:22:32 – Yeah, I swear, I think Sam Altman
0:22:34 is just really, really smart.
0:22:36 And I think, you know, when you see him speak, right,
0:22:39 when he does interviews, he’s very calculated, right?
0:22:41 He’ll ask a question and he’ll sit there
0:22:43 and he’ll usually pause for a good few seconds
0:22:45 before he responds.
0:22:48 And I think that he’s got that marketer brain.
0:22:49 Like, what can I say?
0:22:52 It’s going to sort of spread the flames
0:22:53 to hype this up a little bit more.
0:22:56 And I think that’s kind of how his brain operates.
0:22:58 So I think, you know, him saying like,
0:23:01 this is going to be the dumbest model
0:23:02 you’ve ever used by a lot.
0:23:04 And we’re going to, you know, we’re going to look at back
0:23:06 at this and be embarrassed by what we put out.
0:23:08 I think that’s all marketing.
0:23:09 – Well, I’m certainly excited.
0:23:11 But, you know, if I could have one request right now,
0:23:15 it’s like just give me GPT-4 from April, last year.
0:23:17 Give me that vintage of GPT-4.
0:23:18 It was better.
0:23:19 It was better, damn it.
0:23:21 – Can you still go into like the open AI playground
0:23:23 and like select the older models?
0:23:24 – I think you can, yeah.
0:23:25 And I feel like just all of these models,
0:23:27 especially in the consumer interface,
0:23:29 follow this trajectory of like when they launched,
0:23:30 they’re really good.
0:23:32 And then over time as like, you know,
0:23:35 various efforts to make sure the output is, you know,
0:23:38 on rails and not harmful kick in,
0:23:40 you see this deterioration happen.
0:23:43 But hey, that’s why we also have open source, right?
0:23:43 – Right.
0:23:44 – Yeah.
0:23:46 – Well, let’s talk about visual effects too,
0:23:48 because that’s like, that’s really your background
0:23:49 over at Google.
0:23:53 I want to go back to like the sort of, you know,
0:23:57 3D imaging 101 for a second here.
0:23:59 Can you sort of like break down the difference
0:24:01 between things like photogrammetry,
0:24:05 LiDAR, NERFs and, you know, Gaussian splats?
0:24:06 – I would love to.
0:24:07 In fact, the thing I was talking about is like,
0:24:10 everyone talks about like generative AI a lot,
0:24:12 but I think like the part that’s getting
0:24:16 not that much attention is this like visual spatial AI space.
0:24:19 And so think about spatial intelligence as like,
0:24:21 really just like a reality capture.
0:24:23 Like the world is in fricking 3D, right?
0:24:25 And so, you know, Matt, you nailed it.
0:24:28 It’s like basically photogrammetry is the art and science
0:24:31 of taking 2D images and other sensor data like LiDAR
0:24:34 and turning it into these 3D representations
0:24:35 of the real world.
0:24:37 So photogrammetry has been around
0:24:39 since like before computers were invented even.
0:24:43 Like this is a way of basically using like math and images
0:24:45 and observations of the world really
0:24:48 to like extract 3D structure from it.
0:24:50 But you should also think of spatial intelligence
0:24:53 as the ability for machines to sort of interpret
0:24:55 the spatial data like maps, 3D models,
0:24:57 like the world as we see it, right?
0:25:00 And so like, to me like photogrammetry
0:25:03 or like reality capture, all these other techniques
0:25:05 are all about recreating reality.
0:25:07 And so photogrammetry isn’t new as I alluded to, right?
0:25:09 But I think what’s gotten a huge boost
0:25:10 in why you hear about all these things
0:25:12 is like, thanks to machine learning,
0:25:15 basically like these learned approaches
0:25:17 to modeling the complexity of reality, right?
0:25:20 Like basically like, how do I take a bunch
0:25:23 of 2D images of the world like this
0:25:25 and essentially have a model do this
0:25:26 inverse rendering problem?
0:25:28 Or it’s like, oh, here’s where these hundred photos
0:25:29 are located in 3D space.
0:25:34 Based on this, I’m literally going to like eyeball ray tracing
0:25:37 like and create a 3D representation that makes sense.
0:25:41 And since you know exactly what the model looks like
0:25:42 at the photos that you’ve taken,
0:25:44 the representation that you get eventually
0:25:46 is like good enough from all viewpoints.
0:25:49 And so like, this basically the first nerve paper
0:25:52 dropped in 2021 called neural radiance fields.
0:25:54 And then there’s just been insane progress.
0:25:56 Like we talked about from like data centers
0:25:59 to like the GPU and your fricking like, you know
0:26:03 Nvidia workstation to like the iPhone in your pocket.
0:26:04 But even this wasn’t new.
0:26:06 There was like spiritual successures
0:26:09 to these like ML based learned representations
0:26:12 to sort of encapsulate the complexity of reality.
0:26:13 Enter radiance fields, right?
0:26:17 Like the way like, think about radiance fields generally
0:26:22 sort of like imagine like a voxel grid, a cube of cubes
0:26:25 where every single cube has like a color value
0:26:28 and an alpha like transparency value.
0:26:30 And like that’s kind of what you end up getting with a nerve.
0:26:32 And then when you do volume rendering,
0:26:35 you can basically like, you know
0:26:37 end up getting these photo realistic renditions
0:26:38 of the world.
0:26:41 And so like the cool part about neural radiance field is
0:26:43 instead of photogrammetry where you get this
0:26:46 like 3D mesh model, this like with surfaces
0:26:48 with textures plastered on it.
0:26:51 Think of it like crappy GTA looking models.
0:26:54 What you get with nerfs is like a radiance field
0:26:57 this voxel grid of like all these voxels
0:26:59 and their various values they’re in
0:27:02 that change based on how the camera is looking at it.
0:27:05 And because of that, you get all these things
0:27:06 that photogrammetry couldn’t do
0:27:10 which is like modeling transparency, translucency
0:27:14 like fricking like glass, like shiny objects
0:27:17 all this stuff can be done fricking fire,
0:27:19 volumetric effects, all the stuff that photogrammetry
0:27:21 can’t do cause imagine needing to come up with like
0:27:24 a cardboard paper mache model of that thing.
0:27:25 It’s gonna look like crap.
0:27:28 How do you model hair, fire, fog, all these things.
0:27:30 And you can do all of that
0:27:32 with these implicit representations.
0:27:35 Now the problem with nerfs were the rendering speed
0:27:37 because you’ve got this voxel grid
0:27:38 and you’re doing this volume rendering
0:27:40 where you’re like first doing like
0:27:41 the training process takes forever
0:27:43 but then when you want to render an image
0:27:44 you got to do volume rendering
0:27:47 and like trace like these rays through that voxel grid
0:27:51 and add up these like values like that takes a lot of time.
0:27:54 And basically it’s like think of it like one frame per second
0:27:57 to render out some of these videos, right?
0:27:58 Along comes Gaussian splatting
0:28:01 which is like, hey, do we even need the neural part
0:28:02 of radiance fields?
0:28:04 Like do we need like ML?
0:28:08 Can we just do this with like all school statistical techniques?
0:28:10 And like, which is kind of wild, right?
0:28:13 And so instead of having this implicit black box representation
0:28:17 where like realities modeled in the weights of this like MLP
0:28:19 this like multi-layer perceptron,
0:28:22 you’ve got this explicit representation
0:28:25 of these like ellipsoidal splat looking things
0:28:26 called Gaussians.
0:28:28 Just think of them like super stretchy like fricking spheres
0:28:33 like turns out you can get like a huge jump in quality
0:28:37 while also being able to render way, way faster.
0:28:40 And so like it’s like from one FPS
0:28:42 you’re getting like a hundred frames per second.
0:28:44 And since it’s an explicit representation
0:28:46 it’s in this like most formats
0:28:48 like all these apps that I’m showing on the screen
0:28:52 it’s in this format called PLY the Stanford PLY file
0:28:53 you can basically bring it
0:28:56 into any industry standard game engine.
0:28:57 Like you can bring it into Blender
0:29:00 you can bring it into Unreal into Unity.
0:29:03 And since it’s not this like like black box
0:29:05 like this neural network that you have to deal with
0:29:07 and it’s explicit you can go and delete
0:29:09 and edit things far more easily.
0:29:13 And so it’s like super crazy to see like what’s happened there
0:29:16 but basically between nerfs and Gaussian splatting
0:29:19 think of Gaussian splatting basically as radiance fields
0:29:21 without that neural rendering part.
0:29:23 And the paper uses terms like training or whatever
0:29:27 but there’s no neural networks involved at all in 3DGS.
0:29:29 So yeah, like how crazy is that?
0:29:30 We went from like cool.
0:29:32 Yeah, you could do like cool fly through videos
0:29:34 if you remember that was what the early days
0:29:36 of like the Luma app was do the scan
0:29:38 and now you can reanimate the camera
0:29:40 and you left this thing render for 20 minutes
0:29:41 and you got back something.
0:29:43 Now you can literally take your scans
0:29:45 and drop them into these real time environments.
0:29:47 And it’s like fricking amazing.
0:29:50 Like I think on the left I’m getting like 400 FPS
0:29:52 on an NVIDIA GPU and on the right
0:29:55 I’ve got this thing in Unreal Engine.
0:29:59 And what the cool part of it is like unlike photogrammetry
0:30:02 like and very similar to, you know, neural radiance fields
0:30:05 they still model these light transport effects.
0:30:07 So like again, like imagine if this was like
0:30:08 a cardboard cut out model
0:30:10 you wouldn’t have had all these light transport effects
0:30:13 of the light going through the tree, et cetera.
0:30:17 And so the way Gaussian splatting does this
0:30:20 is like by using this OG physics concept
0:30:23 called spherical harmonics to model it.
0:30:25 And so like if you’re trying to optimize stuff
0:30:27 you can get rid of some of these view dependent effects
0:30:29 as they’re called view dependent meaning
0:30:30 as you change your view
0:30:32 that like materials look slightly different
0:30:35 but you basically get it all with Gaussian splatting.
0:30:37 So I think it’s super exciting.
0:30:40 And yeah, like you could do this stuff in the cloud
0:30:43 you can do this stuff on your fricking desktop now.
0:30:45 Like I think post shot is a tool
0:30:46 that not many people have used
0:30:48 but like if you’re working on a commercial thing
0:30:50 and you don’t wanna upload your data
0:30:52 with Luma’s terms of service
0:30:53 or Polycam’s terms of service
0:30:58 like you can train this all locally on your desktop
0:31:00 with post shot, with Nerf Studio
0:31:03 the sum of the models Nerf Studio aren’t commercial friendly
0:31:04 and then even in the phone in your pocket, right?
0:31:06 Like so if you’ve got an iPhone like a modern iPhone
0:31:09 like and you just wanna know what 3D
0:31:12 like what radiance fields and reality captures all about
0:31:15 just download the Scaniverse app and like have at it.
0:31:17 So this is maybe a dumb question
0:31:19 but like so with like Nerfs and all this new tech
0:31:22 are you able to make like a really realistic 3D model
0:31:23 of like a city like San Francisco?
0:31:25 I mean, is that what you’re showing me earlier?
0:31:27 Or like, or is it only like a certain scene?
0:31:28 Like how hard is that?
0:31:30 Yeah, I mean, there’s a bunch of new papers outright
0:31:31 the initial radiance fields.
0:31:33 Like so there’s a paper called Block Nerf
0:31:35 that tries to scale Nerfs up to city scale
0:31:37 using Waymo data sets.
0:31:39 And similarly you’re seeing in the Gaussian splatting world
0:31:42 different papers about basically having like
0:31:46 in a kind of like nested hierarchies of splats
0:31:48 that have really good transitions to model
0:31:51 an entire like city and eventually the globe.
0:31:54 So I think like that’s the path that academia
0:31:55 and industry is on.
0:31:58 And I think like already you’re seeing city scale data sets
0:32:00 that are very plausible in research.
0:32:02 And I think it’s only matter of time
0:32:05 before that stuff gets into production.
0:32:06 You think that’s like the future of Google Maps?
0:32:08 I think it’s the future of maps for sure.
0:32:11 Like, you know, in immersive view
0:32:13 there are certain indoor locations
0:32:15 where you get a pre-rendered neural radiance field
0:32:18 that you can kind of like walk around and see.
0:32:20 This is just the evolution of that.
0:32:21 I think those data sets exist
0:32:23 and there’s like a handful of companies
0:32:25 in the world that have it.
0:32:27 So I think like that is the future of geospatial
0:32:29 and like maps in general.
0:32:31 But on the other hand, I think what’s interesting is like,
0:32:33 you know, this technology like building a map
0:32:35 of the world is easy.
0:32:36 Updating it is way harder, right?
0:32:39 Like when people talk about this like
0:32:42 one to one digital twin of reality, it’s like,
0:32:45 oh yeah, well like, by the way, new stuff
0:32:47 has built all the fricking time.
0:32:48 Things change all the time.
0:32:51 Seasonality is a fricking thing, right?
0:32:54 Like so, I think with this technology we’ve got
0:32:56 and since we’ve commoditized capture
0:32:59 because sensors are cheaper, computers cheaper.
0:33:02 And now we’ve got access to the same sort of algorithms
0:33:05 and approaches to model reality.
0:33:07 I think like updating this model of the world
0:33:08 is gonna get a lot, lot easier.
0:33:10 So I think like it’s gonna be very exciting
0:33:12 or in the near future we’re walking around
0:33:14 you know, driving around our cars
0:33:17 and walking around with our like glasses or whatever.
0:33:19 And we’re sort of updating this real time map of the world.
0:33:22 I think we’re very much on that trajectory
0:33:24 and we’re closer now than we’ve ever been.
0:33:26 – What do you think are like the business applications
0:33:27 to this tech?
0:33:28 – I mean, it’s like all the applications
0:33:30 that value stuff in the real world,
0:33:32 there’s utility and there’s delight, right?
0:33:35 I think like being able to not just like,
0:33:37 I mean, if you look at what NVIDIA is doing with Earth too,
0:33:39 right, we’re talking about the physical structure
0:33:39 of the world.
0:33:42 You can think of like the Earth having very facets, right?
0:33:44 Like there’s like the sort of the terrain,
0:33:48 like the natural like physical features of the Earth.
0:33:49 Then it’s all the like, you know,
0:33:51 human built things on top of that,
0:33:52 the structure that we built.
0:33:55 And then you can layer in like human activity
0:33:56 on top of that, right?
0:33:58 Like us moving around in the world,
0:34:00 our sensors, our cars, et cetera.
0:34:03 And then there’s other phenomena like weather, right?
0:34:04 Like tides and things like that
0:34:06 that need to be incorporated.
0:34:08 So Earth too is this really interesting initiative
0:34:11 by NVIDIA to focus on the weather like systems
0:34:13 that govern like, you know,
0:34:16 basically a day-to-day weather in the real world.
0:34:18 And so if you’ve got that understanding of like,
0:34:20 like the structure and geometry of a place
0:34:21 where the sun is going to be,
0:34:23 you can predict already things like,
0:34:25 hey, can I install solar panels here?
0:34:27 Like actually how much like sunlight would I get
0:34:30 if I installed this configuration of panels?
0:34:32 Then when you layer weather on top of that,
0:34:33 things get even more interesting.
0:34:35 So to answer your question,
0:34:37 I think there’s a bunch of applications
0:34:39 across utility and delight.
0:34:42 Like media and entertainment’s obviously in gaming is like,
0:34:45 I think the next GTA is absolutely going to be built
0:34:46 in like a twin of the real world.
0:34:49 Maybe this is the last GTA that we beat
0:34:51 will be built by humans manually
0:34:52 to emulate the real world.
0:34:55 I think that’s certainly exciting.
0:34:57 That said, a bunch of games have already used
0:34:58 reality capture, right?
0:35:00 Like from call of duty to battlefront, et cetera.
0:35:03 But I think the utilitarian aspects
0:35:05 are far, far more interesting.
0:35:07 Whether you’re like anything you’re trying to do
0:35:10 in the world of bits, like from like building stuff
0:35:12 to like disaster planning,
0:35:16 like the range of applications is just immense.
0:35:17 – Well, even just, you know,
0:35:21 one of the things that Jensen showed off at GTC this year
0:35:25 was to create these sort of virtual worlds
0:35:28 and then actually put virtual versions of like
0:35:31 humanoid robots in these worlds
0:35:34 and to sort of train them on this virtual twin
0:35:35 of the real world.
0:35:37 So they know how to navigate the real world
0:35:39 and then once they get that training data
0:35:41 then they can sort of inject that training data
0:35:43 into the real robots.
0:35:46 So like this concept of creating this digital twin
0:35:50 of the earth will allow us to train a lot of these robots
0:35:54 and machinery to operate within that digital twin
0:35:56 before actually deploying it in the real world.
0:35:59 To me, there’s a lot of huge implications there.
0:36:02 – 110%, I mean like these,
0:36:05 it’s like a way of creating all the training data
0:36:07 that these machines and perception models need
0:36:08 to be able to navigate the world, right?
0:36:10 And what better way it’s like,
0:36:12 you can create that like, you know,
0:36:14 you can 3D scan a city block
0:36:17 and then create all these different scenarios
0:36:19 of human activity on top of that
0:36:21 and feed that to, you know, like,
0:36:23 and train like self-driving cars,
0:36:25 like, you know, self-driving AI off of it.
0:36:28 I think like the fact that we’ve got a place
0:36:29 where we can basically like,
0:36:32 we can teleport reality into the digital world
0:36:34 and then also manifest the digital in the real world.
0:36:37 It’s like that bridge I think is just very powerful
0:36:38 for a bunch of different applications.
0:36:41 – Well, I want, let’s talk super quickly about TED.
0:36:45 So I’m, first of all, congrats on even having a TED talk.
0:36:47 Like that’s such an amazing accomplishment.
0:36:50 Like, you know, some people say they’ve had a TED talk.
0:36:51 They’re really talking about a TEDx talk.
0:36:54 And come on, come on, come on.
0:36:57 You’ve actually given a real TED talk, a legit TED talk.
0:36:58 And not only that,
0:37:01 but they asked you to host the TED AI podcast.
0:37:03 So tell us a little bit about that
0:37:04 and what’s going on there.
0:37:06 I mean, maybe share a little bit of your experience
0:37:09 with TED and then tell us about the TED AI podcast.
0:37:10 – Yeah, sure.
0:37:14 I mean, certainly the TED talk was a fun experience last year.
0:37:16 And I would say this year was even more fun.
0:37:18 It’s a side of the opportunity.
0:37:19 It’s a co-session too,
0:37:22 which was all of that AI with Chris Anderson.
0:37:24 And we had some amazing speakers,
0:37:28 like Vinod Kosla, Feifei, you know,
0:37:31 the CEO of GitHub, Helen Toner,
0:37:33 export member, OpenAI.
0:37:36 And even like, I don’t know if you’ve,
0:37:38 if you’ve checked her work out, but nice aunties,
0:37:42 like absolute trip down basically like,
0:37:46 to me what intergalactic social media looks like.
0:37:48 There was a super, super fun experience.
0:37:49 Yeah, I mean, like, look,
0:37:51 the T and TED is all about technology.
0:37:54 And I think right now what’s exciting is to put the,
0:37:58 like over time, TED grew to encompass, you know,
0:38:00 not just technology, entertainment and design,
0:38:03 but a plurality of topics, right?
0:38:05 And I think with AI sort of in technology,
0:38:06 being sort of this horizontal,
0:38:08 like tech is a horizontal,
0:38:11 but it’s impacting so many different verticals
0:38:13 in our daily lives, right?
0:38:15 Like we can talk about all the applications,
0:38:16 whether you’re a creator,
0:38:18 whether you’re a knowledge worker, you know,
0:38:20 whether you’re a musician, you know,
0:38:22 whether you’re thinking about like national security
0:38:25 and defense, whether you’re thinking about relationships.
0:38:30 And often in all of these sort of topics, you know,
0:38:34 there’s like a dichotomy that we as like builders
0:38:36 and consumers have to contend with.
0:38:40 And so the idea of the TED AI show really is to outline
0:38:42 those dichotomies and, you know,
0:38:45 not necessarily take an opinion one way or the other,
0:38:49 but sort of elaborate on the entire gamut of like,
0:38:51 like the good, bad and the ugly
0:38:53 and sort of let people decide for themselves
0:38:56 and do that by talking to people from all walks of life.
0:38:58 Like people whose titles haven’t even been invented yet,
0:39:01 but obviously technologists, journalists, researchers,
0:39:03 artists, you know, the list goes on
0:39:05 and, you know, I’m just super grateful
0:39:08 for the opportunity to be able to, you know,
0:39:10 just bring my excitement into the space.
0:39:12 Like obviously like I want to build,
0:39:14 bring the lens of a creative,
0:39:16 like that’s like built a following
0:39:18 for over a million folks using these tools,
0:39:20 but also as a product builder who shipped a bunch
0:39:22 of this stuff and then just like,
0:39:26 I would say like cautiously optimistic AI enthusiasts.
0:39:28 So I’m going into a bunch of these topics
0:39:30 with those three lenses in mind
0:39:32 and it’s just been a lot of fun.
0:39:35 We’ve got some really cool episodes lined up for y’all
0:39:38 and I can’t wait for y’all to check it out.
0:39:41 – You have any idea of like, you know, launch schedule?
0:39:44 Like is that, are there dates planned out for it yet?
0:39:45 – Yeah, yeah, totally.
0:39:47 So May 21st, first episode drops
0:39:48 and then it’s going to be weekly.
0:39:50 There’s going to be a little bit of a summer break there,
0:39:52 but yeah, 25 episodes in the season.
0:39:55 And let me tell you,
0:39:57 I think there’s something for everyone.
0:39:59 – Yeah, I do wonder like what was the general vibe at Ted?
0:40:03 Like are people optimistic or are they like really fearful
0:40:04 of AI?
0:40:05 – And if you look at Ted also, you know,
0:40:08 you had people like, like the laval.
0:40:10 I know there were some other speakers there.
0:40:11 I think maybe Moustafa Suleiman was there.
0:40:13 Maybe that was a more recent one.
0:40:15 But then you also had guys like Gary Marcus
0:40:20 and I’m going to totally butcher his name, Yadkowski.
0:40:22 – Oh yeah, it is Yadkowski.
0:40:24 – Which are both more on the like,
0:40:26 hey, let’s chill out on the AI side.
0:40:29 So it seems like it’s from a speaker’s front.
0:40:31 It seemed like they had speakers on both sides
0:40:33 of the arguments.
0:40:33 – Definitely.
0:40:35 I mean, the theme for this year was like the brave
0:40:36 and the brilliant and like covering
0:40:38 that gamut of opinions.
0:40:40 I would say overall the vibe is positive.
0:40:42 So I like, I’ll give you a sample size.
0:40:44 Like I taught this discovery session,
0:40:48 which was about the dichotomies of AI is about 50 people.
0:40:49 And sort of what we did is we looked at a bunch
0:40:52 of these verticals in the AI space.
0:40:54 And like, you know, essentially came up with like,
0:40:56 what happens if this goes really well
0:40:59 and what happens if this goes really poorly?
0:41:01 And like, let’s use chat GPT actually
0:41:02 to come up with like a headline,
0:41:06 like a piffy visual depiction of that desirable
0:41:08 and undesirable future.
0:41:10 And honestly, like most folks in the room
0:41:12 are optimistic about it, right?
0:41:14 Like, but they’re not blind to the downsides.
0:41:17 I think like the problem with anything is extremes, right?
0:41:19 And so like, you know, where like Nathan,
0:41:22 I hear your concern of like, if we’re like, you know,
0:41:23 oh, like we can’t have like,
0:41:27 demerism and like, you know, I was like, it’s infectious.
0:41:30 I think the same thing applies to the opposite narrative too,
0:41:32 which is like, well, we just obviously,
0:41:34 we got to keep like accelerating.
0:41:35 We got to keep shipping.
0:41:36 I think it depends, right?
0:41:39 Like, it’s sort of the boring answer to these things.
0:41:42 And I think you can’t understand the nuances
0:41:45 unless you go dissect like the full gamut
0:41:47 of like considerations.
0:41:50 And so the goal is like, really like the editorial perspective
0:41:51 I’m trying to bring.
0:41:55 And of course, Ted has a huge say in this too is like,
0:41:58 look, I’m a 60% optimistic, 70% optimistic,
0:41:59 which is not too dissimilar.
0:42:01 I think Matt, well, you and I have talked about
0:42:03 on most things, but I’m not going to be blind
0:42:06 to all like the downsides of this stuff too, right?
0:42:09 Like, and I think that’s okay to say.
0:42:12 And what I believe is just like the speaker selection,
0:42:15 you know, we’re trying really hard
0:42:17 to have a balanced perspective on the guests too.
0:42:20 So that like, what’s what I think is going to happen
0:42:22 in the real world as well as like,
0:42:24 you’ll be able to hear both sides of that argument.
0:42:27 Like somebody who’s like super stoked and thrilled
0:42:30 on like AI art and just thinks it’s the bee’s knees.
0:42:33 And it’s totally cool to train on copyrighted material.
0:42:35 Somebody who thinks like that is the death of creativity
0:42:36 as we know it too.
0:42:37 And you have to-
0:42:38 – I think it’s good to hear both sides.
0:42:40 I mean, I agree, but I’m concerned.
0:42:41 Like I used to live in San Francisco
0:42:43 and like they’re like pushing for regulation now.
0:42:44 We’re like to-
0:42:45 – Who’s they?
0:42:46 You mean, you mean, Sam Allman?
0:42:47 – The government, yeah.
0:42:48 Well, no, the government.
0:42:49 They’re like, they’re like pushing a bill through right now.
0:42:51 They’re trying to like, they’re trying to fast track it.
0:42:53 I forgot who’s doing the bill,
0:42:55 but we’re basically,
0:42:57 if you launch a new large language model-
0:42:58 – Need approval.
0:43:00 – Yeah, you like need approval,
0:43:02 but also like it doesn’t get to basically sign something
0:43:03 and like it’s perjury if you’re lying
0:43:05 that this model can do no harm.
0:43:06 And it’s like-
0:43:07 – Yeah, like who’s gonna do that?
0:43:08 Yeah.
0:43:09 – Yeah.
0:43:12 And so I agree like nuance is important and like,
0:43:15 I do consider myself kind of part of the EAC movement,
0:43:16 but more generally just like a techno optimist.
0:43:18 – Do you have it in your bio still?
0:43:19 I don’t know.
0:43:20 – I don’t, I don’t.
0:43:21 But I, you know, I like Beth.
0:43:23 I like all the people who are part of that.
0:43:24 – That’s cool.
0:43:25 – I think in general,
0:43:27 I think in general it’s right, you know,
0:43:29 but nuance is important, I agree.
0:43:30 – Let me put it this way.
0:43:31 I think the way I see it is like,
0:43:34 we’ve got enough talented humans out there
0:43:37 that are like pushing for like acceleration
0:43:39 and there’s enough talented people out there
0:43:41 that are pushing for, you know,
0:43:43 I would say pumping the brakes
0:43:46 for the lack of a better way to put it in certain areas.
0:43:48 And I think like in totality,
0:43:52 like we’ll reach like some optimum solution
0:43:53 because of those influences.
0:43:54 And I think it’s always been like that, right?
0:43:58 Like, I mean, just like the early days of music,
0:44:00 everyone’s like, oh yeah, Napster and like peer-to-peer
0:44:01 and let’s just go crazy.
0:44:03 And then things settled down
0:44:05 and we found a business model that worked.
0:44:07 Maybe it’s not perfect, right?
0:44:09 Like people have a lot of gripes with the Apple
0:44:10 and the Spotify business model,
0:44:13 but I think we found this like globally optimum solution.
0:44:15 – I mean, it doesn’t always work out, right?
0:44:16 Though they look at like nuclear plants, right?
0:44:18 Like in the past, the US was gonna build
0:44:21 all these nuclear plants to solve energy problems
0:44:23 and we didn’t do it because of regulations
0:44:24 and because of fear.
0:44:25 And now we’re like trying to solve
0:44:26 all these global warming problems.
0:44:29 Other thing is like, well, we always kind of had nuclear there
0:44:31 that we could have been using and it worked.
0:44:32 So it doesn’t always work out.
0:44:34 Like it often does, but it doesn’t always.
0:44:37 – Totally, I mean, one of the funnest topics
0:44:42 is getting into how do politicians and regulators
0:44:46 even regulate this like sort of nebulous set of technologies.
0:44:48 It’s not just large language models, right?
0:44:50 Like there’s all the perception AI stuff
0:44:52 and like the implications there.
0:44:55 And but like a group of these technologies
0:44:57 that are like sort of permeate and go, my God,
0:45:00 like some of the stuff that I’m like doing research
0:45:04 right now on just the intersection of neuroscience and AI
0:45:07 and what we’re gonna be able to do with just like passive
0:45:10 neural like interfaces with earbuds and things like that.
0:45:14 I mean, there’s gonna be some real big ethical quandaries
0:45:15 that pop up.
0:45:18 And so yeah, yeah, trying really hard to bring like
0:45:19 still be techno-optimist,
0:45:21 but bring that balanced perspective.
0:45:23 And I think folks are gonna like it.
0:45:24 – I think at the end of the day,
0:45:26 the important thing is empathy, right?
0:45:30 Like the perspective I come from is I tend to be
0:45:31 a very empathetic person, right?
0:45:34 I want to hear both sides of the story.
0:45:35 I want to hear both perspectives
0:45:38 and I want to be empathetic to both sides too.
0:45:40 Like if somebody is genuinely worried
0:45:43 that this technology is taking their job,
0:45:44 I want to understand why.
0:45:48 I want to understand what we can do to sort of mitigate
0:45:50 the damages that could be done from this.
0:45:53 Like I’m always gonna come from that place of empathy,
0:45:55 which is why I’ve never sort of identified
0:45:58 with the EAC movement is like,
0:46:00 I don’t necessarily think we should always be pushing
0:46:03 everything forward as fast as possible.
0:46:05 I think we should be listening to the fears.
0:46:06 We should be listening to the concerns.
0:46:09 We should be figuring out sort of middle grounds.
0:46:13 Like you mentioned, there’s always people on both sides
0:46:15 which kind of creates a decent checks and balance
0:46:17 to make sure one side doesn’t go too far
0:46:20 and AI nukes the world,
0:46:22 but also the other side doesn’t go too far
0:46:25 and technology stops advancing completely.
0:46:29 Those checks and balances I think are a net positive overall.
0:46:30 I think those need to be there.
0:46:33 – I agree overall, but I mean, I think the big thing
0:46:36 that was like, the argument with EAC would be making is
0:46:39 that compounding is one of the most important powers
0:46:40 out there, right?
0:46:41 Like an idea that if we build faster
0:46:43 than the technology in the future will be better
0:46:44 and better and better and we’ll start solving
0:46:46 real world problems like cancer
0:46:48 and all these other things that maybe we could have been doing
0:46:52 if we weren’t so like quick to just regulate everything.
0:46:54 And so I think with AI, it’s the same thing.
0:46:56 Like sure, like some regulation in the future
0:46:58 might make sense, but if we just start throwing it
0:47:00 out there right now, we’re gonna slow down the compounding
0:47:03 and like the exponential, we’ll stop the exponential
0:47:05 from happening with our regulations.
0:47:08 And we, you know, yeah, maybe some jobs would be lost
0:47:10 in the short term, but in the long term,
0:47:13 we could have cured cancer, we could have solved, you know
0:47:15 global warming issues, all kinds of other problems
0:47:18 that we could have solved if we would just like weighted
0:47:19 and see what happens with the technology.
0:47:20 And yeah, now there’s a big problem.
0:47:23 Okay, maybe make a regulation, but just don’t do it
0:47:23 like right at the beginning,
0:47:24 like they’re trying to do right now.
0:47:27 – I mean, India totally flipped their decision, right?
0:47:29 Initially they were like, oh, you have to get every model
0:47:31 approved and they’re like, actually we’re gonna retract
0:47:33 this part, which was really interesting.
0:47:36 And I mean, like it’s like a regulation also,
0:47:38 like it could end up in a place where it just only benefits
0:47:41 the incumbent, like the largest AI labs too, right?
0:47:44 Like the regulatory capture like point of view,
0:47:47 it’s like it could end up in a place where like any new
0:47:50 innovation like from a startup can actually happen.
0:47:52 And they’re the ones that get these like owners compliance
0:47:55 requirements and they can’t afford a team of lawyers
0:47:57 unless they’re like super VC backed.
0:47:59 And then like, what an inefficient use of VC capital
0:48:02 instead of innovating, you’re sort of like navigating
0:48:05 like the legal landscape of like a heavily regulated
0:48:05 industry.
0:48:07 So I think like your point about nuclear is well taken too.
0:48:10 It’s like, I mean, like a lot of folks, I mean,
0:48:12 including Gary brings up the example of like, you know,
0:48:16 like basically air travel and airplanes are still well
0:48:19 regulated, but yet we’ve got this whole Boeing fiasco
0:48:20 happening, right?
0:48:23 It’s like where you’ve got one really big incumbent
0:48:25 and there’s probably a revolving door between regulatory
0:48:29 agencies and Boeing and, you know, so it’s-
0:48:30 – And when the Wright brothers got started, I mean,
0:48:31 they weren’t being heavily regulated as they were
0:48:33 like inventing the plane.
0:48:34 – Totally.
0:48:35 – They were out there just like out in Ohio,
0:48:37 just, you know, trying shit out.
0:48:37 So I mean-
0:48:39 – I think one thing it’s like a lot of people talk about
0:48:42 is like just like technology, sunsets, like regulations
0:48:45 need to sunset rather than us adding up more and more
0:48:46 regulations.
0:48:48 So I think this is where things get geopolitical too.
0:48:51 It’s like, I think China is so much savvier about AI
0:48:53 regulation than the US is right now.
0:48:57 And I feel for the politicians, I think they’re like asking
0:48:59 for this type of engagement.
0:49:01 And I think it’d be good if we engage with them on this
0:49:05 and like bring those perspectives to bear rather than,
0:49:07 I don’t know, just being like a regulation, bad,
0:49:10 innovation, good, let’s keep innovating.
0:49:13 And so it’s like, it’s nuanced, but then again, like,
0:49:18 look, I’m a, I’ve always been a Libra and like, you know,
0:49:21 kind of trying to build bridges between two worlds.
0:49:25 – Yeah, no, I mean, I think this being a super nuanced
0:49:28 conversation is like the understatement of the episode here.
0:49:31 I think there’s just so many different like rabbit holes
0:49:33 that we could potentially go down when it comes to the
0:49:34 regulation thing.
0:49:37 I think you’re going to have to be one of our sort of
0:49:38 recurring guests.
0:49:41 Maybe every few months jump on and nerd out about this stuff.
0:49:44 But, you know, I do want to give you the opportunity to
0:49:46 tell us what else you’re working on.
0:49:48 If there’s a place you think people should go check you
0:49:51 out, your Twitter, your YouTube, obviously the TED AI
0:49:53 podcast coming out later in May.
0:49:56 – Yeah, so just please follow me on Twitter @belavosadoo.
0:50:01 You can also follow me on YouTube and TikTok @billyfx.
0:50:03 If you’re interested in some more long form expositions
0:50:05 that I do, check out the Creative Tech Digest.
0:50:08 It’s both a newsletter as well as a YouTube channel.
0:50:10 And yeah, of course, check out the TED AI show.
0:50:14 Maybe the one last thing I’ll say is like if you’re a
0:50:16 founder and a builder in this space building with any of
0:50:19 the technologies that we talked about and you’re looking
0:50:21 for early stage investment, I’m also a scout for
0:50:23 A16Z Games.
0:50:26 So just hit me up on Twitter or you can email me.
0:50:28 We’ll put the email in the show notes as well.
0:50:30 And I really appreciate you guys having me on.
0:50:32 I’m wishing you all the success for your podcast.
0:50:36 And Matt, I will see you at I/O.
0:50:39 And Nathan, I hope to see you in 3D sometime soon.
0:50:42 – Oh, come out the Kyoto, come on.
0:50:43 – I gotta make it happen.
0:50:44 – Awesome, Bill of All.
0:50:45 Well, it’s been a blast.
0:50:47 This has been one of my favorite conversations we’ve had
0:50:47 so far, so fun.
0:50:50 Excited to see you in person next week.
0:50:51 – Cool, cheers.
0:50:53 (upbeat music)
0:50:56 (upbeat music)
0:50:59 (upbeat music)
0:51:01 (upbeat music)
0:51:04 (upbeat music)
0:51:06 [MUSIC]

0:00:02 (upbeat music)
0:00:06 – Hey, welcome to the Next Wave podcast.
0:00:07 I’m Matt Wolf.
0:00:09 I’m here with my co-host, Nathan Lanz.
0:00:12 And in this show, it is our goal to keep you looped in
0:00:15 on all the latest AI news, all the coolest AI tools,
0:00:18 and just generally what’s going on in the AI world.
0:00:20 And the last couple of weeks
0:00:23 have been absolutely insane in the AI world.
0:00:24 There have been so many announcements.
0:00:28 We had Google I/O, we had OpenAI’s announcements.
0:00:30 We had two different keynotes from Microsoft,
0:00:32 and all of these announcements
0:00:34 had so much going on around AI.
0:00:38 So we thought we’d do a fun little bonus episode,
0:00:39 maybe a little bit shorter than normal,
0:00:41 and just kind of riff and talk about
0:00:43 some of these announcements and, you know,
0:00:45 get you looped in on what’s going on
0:00:46 in the world of AI right now.
0:00:50 So the first event that came up last week
0:00:52 was the OpenAI event, which is kind of funny,
0:00:55 because we knew Google I/O was happening
0:00:56 last week on Tuesday.
0:00:58 So what does OpenAI do?
0:01:00 They go and make their announcement on Monday,
0:01:03 the day before the big Google I/O event.
0:01:06 That was sort of the kickoff to this announcement fest
0:01:09 of all of these AI announcements from these big companies.
0:01:14 And of course, the big OpenAI announcement was GPT-40.
0:01:15 And during this announcement,
0:01:18 they showed off some demos of GPT-40,
0:01:22 being able to sort of have conversations with you,
0:01:24 the inflections of the voices change,
0:01:28 the voices sound eerily similar to Scarlett Johansson,
0:01:31 which is the voice of the AI in her.
0:01:34 So there’s some drama going around about that.
0:01:36 But I figured let’s kick off this conversation
0:01:38 talking about GPT-40.
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0:02:11 – So, I mean, Nathan, like what are your initial thoughts?
0:02:13 When you watch that keynote, like,
0:02:15 were you blown away by it?
0:02:17 Were you underwhelmed by it?
0:02:19 Like what were your thoughts when you first watched it?
0:02:20 – I was honestly blown away by it.
0:02:21 Like just like, you know,
0:02:22 in one of our previous videos,
0:02:25 we talked about how I think in a year from now,
0:02:27 voice will be the main way that you interact with AI.
0:02:29 And it’s like, okay, well, now here it is.
0:02:32 Like they’re showing you can actually just talk to the AI.
0:02:33 You can actually even interrupt it.
0:02:35 It can be talking and you can just like interrupt it
0:02:36 and start talking again.
0:02:37 It’s not like, it’s not like the old one
0:02:41 where you had to like record and then like processes
0:02:43 and then it says something and you had to wait till it’s done.
0:02:45 No, you can just like talk back and forth with it.
0:02:47 And it wasn’t perfect,
0:02:50 but damn it was pretty good for like a first version
0:02:52 of like this kind of voice interact with AI.
0:02:54 But yeah, I was pretty blown away by it personally.
0:02:55 – You know, one of the big announcements
0:02:57 that came out with the GPT-40
0:03:00 is that pretty much the latest state of the art models
0:03:02 that, you know, the general consumers
0:03:04 are going to get access to,
0:03:05 they’re going to give them access free, right?
0:03:09 So like the GPT-40, people are going to get,
0:03:10 they’re going to get access to that
0:03:12 just in the free chat GPT now before, you know,
0:03:15 if you had the free chat GPT, you were using, you know,
0:03:17 GPT 3.5 and older model.
0:03:20 If you were on the chat GPT plus subscription,
0:03:23 you got chat, you got GPT-4 turbo.
0:03:25 The naming conventions are all, you know, weird
0:03:30 ’cause you got GPT-4, GPT-4 turbo, GPT-40, GPT-3.5.
0:03:33 Like it’s all confusing, but you know,
0:03:35 Sam Altman actually made a comment
0:03:36 in one of the recent interviews
0:03:38 that he’s probably going to stop, you know,
0:03:41 naming them GPT-4, GPT-5, GPT-6, right?
0:03:43 They’re going to just sort of land on a name
0:03:46 and just keep on improving on that version
0:03:47 over and over again.
0:03:49 But I thought it was really cool
0:03:51 that they’re basically saying our most state-of-the-art
0:03:53 model, the best models that we’re putting out,
0:03:55 you’re going to be able to use just for free now
0:03:57 in the free version of chat GPT.
0:03:59 I thought, I thought that was really, really cool.
0:04:01 And then if you’re a plus subscriber,
0:04:02 then you just get more use, right?
0:04:04 You get, you’re going to get some of the features
0:04:06 a little bit earlier than everybody else,
0:04:08 but you’re going to get like five times more
0:04:10 input/output with the model.
0:04:11 – I think it’s a big deal
0:04:13 because you know, most people when they think of AI,
0:04:15 they’re thinking of chat GPT
0:04:17 and they’re typically thinking of the free model, right?
0:04:20 Which has been 3.5, which you know,
0:04:22 compared to 4 is really, really bad.
0:04:24 And so the fact now that someone gets,
0:04:26 you know, I think 4.0 in some ways
0:04:28 is not as good as 4 in some ways,
0:04:31 but it’s pretty darn close and it’s way, way faster.
0:04:34 So for most people, that’s going to be such a, you know,
0:04:35 step forward in terms of what they believe
0:04:36 is possible with AI.
0:04:37 Like, and so I think that’s going to lead
0:04:39 to like a lot more awakening around like,
0:04:42 oh, AI is actually here, it’s really powerful.
0:04:44 But, you know, I think one thing worth thinking about though
0:04:46 is like, apparently they were training this model
0:04:49 with a separate team ever since 2022.
0:04:50 So my understanding is like, yeah,
0:04:53 this is kind of their state-of-the-art model,
0:04:55 but I don’t think it’s their like flagship model.
0:04:57 I think it’s just like another model
0:04:58 that they were developing.
0:05:00 And so they put it out there for free.
0:05:02 My theory is it’s probably built on like a better architecture
0:05:03 where it’s more cost efficient.
0:05:05 That’s why they’re able to give away for free.
0:05:07 That’s why it’s faster.
0:05:09 And then five is probably going to be built
0:05:10 on top of that as well.
0:05:12 So I think we’re still going to see GPT-5 quite soon.
0:05:14 And it may not be multimodal.
0:05:15 That’s my big question.
0:05:17 Like, okay, so if it’s a different model,
0:05:19 are we going to get something that’s dramatically smarter
0:05:21 with GPT-5, but it’s not multimodal yet.
0:05:22 It’s just text.
0:05:25 – Yeah, but this new model, GPT-4O was, you know,
0:05:27 pretty multimodal, right?
0:05:29 They were, they were inputting video,
0:05:31 although I think the video they were showing,
0:05:33 it was just sort of looking at screenshots from the video.
0:05:35 It wasn’t actually watching the video
0:05:37 because there was one moment in their demo
0:05:39 where he picked up the phone and like smiled
0:05:40 into the camera and it was like,
0:05:42 oh, I’m looking at something wood.
0:05:43 And he was like, no, no, that was before.
0:05:45 Now look at my face, right?
0:05:47 So it obviously sort of like took a snapshot
0:05:49 of the table or whatever.
0:05:51 And then when he looked at his face,
0:05:53 it still was like thinking about the picture
0:05:54 of the table or something.
0:05:56 So I don’t think it’s actually using video,
0:05:59 but it does seem to be ingesting audio.
0:06:01 You can put images into it.
0:06:04 So I mean, it’s pretty multimodal already.
0:06:05 I think the real question is,
0:06:08 are we going to get like actual video input with GPT-5?
0:06:11 – Yeah, I guess we’ll see.
0:06:12 – So there were some other announcements
0:06:13 during the OpenAI event.
0:06:15 So I’ll just kind of rattle off some of them.
0:06:17 I’ve got my notes here in front of me.
0:06:19 They talked about a new desktop app,
0:06:22 which it’s pretty cool.
0:06:24 It’s only available on Mac right now.
0:06:27 They didn’t make it available on PC right away.
0:06:30 And I think I’m at the Microsoft event right now.
0:06:31 If you’re watching on video,
0:06:33 you can see I’ve got a different background than normal.
0:06:37 I think we found out why they didn’t release a Mac version
0:06:38 while I’m at the Microsoft event,
0:06:39 but we’ll get into that
0:06:42 when we start talking about the Microsoft event here.
0:06:44 But the desktop app, it’s pretty cool.
0:06:45 I tested it out on my Mac.
0:06:47 It doesn’t have the voice features in it yet.
0:06:49 It doesn’t have the feature
0:06:51 where you can view your desktop yet.
0:06:54 You can take a screenshot, drag the image in,
0:06:57 and chat with the screenshot essentially,
0:06:58 but it doesn’t just look at your desktop
0:07:00 like they showed in the demo yet.
0:07:02 It’s pretty much the same thing
0:07:04 you get inside of the chat GPT web app,
0:07:05 just on your desktop.
0:07:10 Now we also learned that that GPT-2 chatbot
0:07:12 that was all over Limsis on the chatbot arena,
0:07:15 you know, apparently that was GPT-4O.
0:07:17 That was them kind of testing that out
0:07:20 to see how people would work with it.
0:07:23 And you know, the other big thing was like
0:07:24 the voices in it, right?
0:07:28 Like the GPT-4O, it feels like a marginal improvement
0:07:31 with like the intelligence of it, in my opinion, right?
0:07:33 It doesn’t seem like huge leaps
0:07:34 above what we were getting before.
0:07:36 Other than in coding, it seems to work really well
0:07:39 with coding, but the like the voice stuff
0:07:41 was I think the thing that most people
0:07:43 were going nuts about from that keynote, right?
0:07:46 When you speak to it, you can tell it
0:07:49 to give you more emotion, get more excited about it,
0:07:52 talk like a robot, do all that sort of stuff.
0:07:53 And then when they were demoing it,
0:07:55 that’s also where we heard the voice,
0:07:58 which sounded very similar to Scarlett Johansson.
0:08:00 But I think that was the thing
0:08:03 that people really went nuts over was that voice thing.
0:08:05 And like you mentioned earlier in this episode,
0:08:07 we did a whole episode about how like
0:08:09 voice is that next thing, right?
0:08:12 Voice is what’s going to be the sort of input
0:08:15 of all of these large language models.
0:08:17 And when chat GPT showed off that voice
0:08:19 and there was really like no latency,
0:08:21 they would ask a question, it would respond
0:08:22 almost in the same amount of time,
0:08:23 a real human would respond.
0:08:26 You know, that was the thing that was probably
0:08:29 the biggest sort of differentiator about,
0:08:31 you know, that from what came before it.
0:08:32 – Yeah, I mean, I tweeted about the whole
0:08:34 Scarlett Johansson thing yesterday
0:08:35 and it got a lot of attention,
0:08:37 especially on LinkedIn for some reason.
0:08:38 People, you know, seem pretty upset about it.
0:08:40 You know, I have mixed feelings.
0:08:41 I mean, I guess to give people context,
0:08:44 like Scarlett Johansson put out a statement
0:08:45 or I’m not sure if it was officially from her,
0:08:48 but her publicist, you know, said that it really happened
0:08:50 where openly I contacted Scarlett Johansson,
0:08:52 asked like, can we use your voice?
0:08:53 She’s like, no, you can’t.
0:08:57 And apparently they kept trying and she just refused.
0:09:00 And they kind of picked a voice that seemed similar to hers.
0:09:01 And then she’s saying, not only that,
0:09:03 but then like they threw it in my face
0:09:04 ’cause like Sam Altman like tweeted to somebody
0:09:06 like the word her, you know,
0:09:09 and like referencing the movie where she’s like the,
0:09:11 you know, the main voice for the AI system.
0:09:12 I have mixed feelings about it.
0:09:14 ‘Cause like when I, when you actually,
0:09:16 somebody else shared a, you know,
0:09:18 side-by-side comparison of the voices, you know,
0:09:20 like here’s one, here’s the sky voice,
0:09:23 the open AI voice, and then here’s Scarlett Johansson’s voice.
0:09:24 You know, they’re quite different.
0:09:26 I mean, like they don’t sound like,
0:09:28 sure it sounds like an attractive woman talking
0:09:29 or something, but it doesn’t sound
0:09:31 really like Scarlett Johansson.
0:09:33 And then like, so can she really like,
0:09:34 what does she own?
0:09:37 Like AI, like feminine AI voices forever, right?
0:09:39 Like that’s kind of, you know,
0:09:40 that’s kind of like a wild statement to make
0:09:42 that you own that, but they, but who knows?
0:09:45 They’ll probably still end up having to settle with her
0:09:48 for the fact that like he said her, if I had to guess.
0:09:49 – Yeah, yeah, that’s true.
0:09:51 I mean, open AI did put out their own statement
0:09:52 around what was going on.
0:09:54 They said that they hired a different voice actor,
0:09:55 not Scarlett Johansson.
0:09:57 They trained on hours and hours
0:10:01 of this other voice actors work to get this in.
0:10:03 But from what I understand,
0:10:05 they actually are not planning on launching
0:10:07 with that sky voice now that, you know,
0:10:08 just to avoid all the controversy
0:10:10 and all the issues that might come up.
0:10:13 I think that, you know, right now they’re just saying,
0:10:14 we’re just not going to launch with that voice.
0:10:16 You know, we don’t want to deal with all that.
0:10:18 So we’ll see how that plays out.
0:10:20 So HubSpot just put out this really cool checklist.
0:10:22 It’s called the AI adoption checklist.
0:10:25 And if you’re trying to implement AI into your business
0:10:29 in any way whatsoever, this checklist has you covered
0:10:33 from security to privacy to planning to training.
0:10:34 This has you covered.
0:10:36 Click the link in the description below
0:10:38 and grab the checklist today.
0:10:40 – Yeah, so then the very next day
0:10:41 after this open AI keynote
0:10:43 where they made those announcements
0:10:45 was the Google IO event
0:10:48 where that’s Google’s developer conference
0:10:50 where they typically make all of their announcements.
0:10:53 And this year it was once again, all about AI.
0:10:55 In fact, at the end of the conference,
0:10:58 Sundar, the CEO of Google actually counted up
0:11:00 how many times they said AI.
0:11:02 And it was like 121 times
0:11:04 or something throughout the presentation.
0:11:06 One thing that I find interesting
0:11:09 between the two keynote presentations
0:11:12 was that I feel like ChatGPT and open AI,
0:11:16 they really sort of like honed in on like the one thing,
0:11:17 right?
0:11:19 They really sort of honed in on like the voice feature
0:11:22 and the chatting and the conversational element of it
0:11:25 and the tone and the intonations of the voice.
0:11:28 It was very, very focused on that thing.
0:11:31 The Google event in contrast to it was like,
0:11:33 here’s an announcement, here’s an announcement,
0:11:35 here’s an announcement, here’s an announcement.
0:11:36 It was just two hours of an announcement
0:11:39 after announcement, after announcement.
0:11:40 I was at the event
0:11:43 and I’m actually kind of struggling right now
0:11:46 to remember what were all the announcements Google made, right?
0:11:51 So like ChatGPT or open AI had like one big announcement
0:11:54 that everybody remembers, everybody talked about.
0:11:57 Google just like bombarded us with announcements
0:11:59 but they were all kind of so marginal
0:12:01 that I almost forget them.
0:12:03 Like I know I’ve got my notes in front of me,
0:12:06 but like there’s nothing that stands out in my mind
0:12:10 of like Google talked about this and that is game changing.
0:12:12 But I’m curious, Nathan, like from you,
0:12:14 was there anything from the Google keynote
0:12:18 that specifically stood out that was like,
0:12:19 okay, wow, that’s something that Google did
0:12:21 that I thought was impressive?
0:12:23 – No, I mean, I think it was like information overload.
0:12:25 Like they put out so many things
0:12:29 and if you look at the open AI event in comparison,
0:12:32 it was way more like Steve Jobs like, right?
0:12:34 Where there’s like, here’s this one thing that we have
0:12:37 and they just demonstrate in a beautiful way.
0:12:39 And I think open AI did a really good job too
0:12:40 where they even humanize it more
0:12:42 by having all these different team members
0:12:45 show the same thing in different ways.
0:12:49 Here’s the AI voice, our CTO co-founders showing it to you,
0:12:51 presenting it to you, and then here’s people from the team
0:12:53 and here’s how they’re using it.
0:12:55 And they showed like these six, seven different use cases
0:12:58 all with the same product, the same AI voice.
0:12:59 And I thought that was such a great way
0:13:02 to like reiterate the one thing over and over and over.
0:13:04 So by the end of it, it was like really ingrained
0:13:06 in your head like, oh, they’ve done an amazing job
0:13:08 with AI voice, whereas with, you know, with Google,
0:13:11 it’s, they release so many things and it’s like,
0:13:13 it’s not clear when a lot of it’s actually gonna come out.
0:13:15 That’s really hard to like pinpoint like,
0:13:16 oh yeah, what’s the one thing?
0:13:17 And I was like, it sounds like, oh yeah,
0:13:18 they made a lot of progress.
0:13:20 There’s a lot of cool things they did.
0:13:21 You know, like I put out Twitter threads
0:13:23 about both companies’ announcements.
0:13:26 And, you know, my Twitter thread about OpenAI
0:13:28 got like 5.9 million views.
0:13:30 And my tweet thread about Google,
0:13:33 I think it got maybe like 50,000 views just in comparisons.
0:13:36 It kind of showed you the general interest level
0:13:39 in OpenAI’s announcement versus Google’s announcement.
0:13:40 – Yeah, one thing that I found like really interesting
0:13:43 about the OpenAI event was that they had so much more
0:13:45 that they could have talked about as well, right?
0:13:48 Like they put out a blog post about all of the stuff
0:13:51 that they were rolling out with their new rollout.
0:13:54 This GPT-40 is its own image generator.
0:13:55 It’s not using Dali.
0:13:58 It’s like using its own built-in image generator.
0:14:00 It can do text to like 3D object.
0:14:03 It’s got like a ton of features on their blog post.
0:14:06 But in that keynote, they focused in on like the one thing
0:14:09 that I thought maybe they felt was gonna have
0:14:12 the most impact on people from watching that event.
0:14:13 So I thought that was really interesting
0:14:16 that they just, they could have themselves
0:14:18 done a two-hour keynote where they bombarded us
0:14:21 with OpenAI announcements, but they chose to focus
0:14:23 on just like one or two key things.
0:14:25 So I felt that was really, really interesting as well.
0:14:28 – Yeah, and I thought it was fascinating too
0:14:31 that, you know, Sam Altman didn’t appear.
0:14:33 And so for me, that’s like, okay, he didn’t appear
0:14:36 because he’s going to appear when GPT-5 comes out
0:14:37 in like three months.
0:14:39 – I’m at the Microsoft event now.
0:14:41 He was here. He was part of that keynote.
0:14:43 But we’ll get to Microsoft in a minute.
0:14:43 He’s like…
0:14:47 We’ll be right back.
0:14:49 But first, I want to tell you about another great podcast
0:14:50 you’re going to want to listen to.
0:14:54 It’s called Science of Scaling, hosted by Mark Roberge.
0:14:56 And it’s brought to you by the HubSpot Podcast Network,
0:15:00 the audio destination for business professionals.
0:15:02 Each week, host Mark Roberge,
0:15:04 founding chief revenue officer at HubSpot,
0:15:07 senior lecturer at Harvard Business School
0:15:09 and co-founder of Stage 2 Capital,
0:15:12 sits down with the most successful sales leaders in tech
0:15:15 to learn the secrets, strategies, and tactics
0:15:17 to scaling your company’s growth.
0:15:20 He recently did a great episode called How Do You Sol
0:15:22 for a Siloed Marketing and Sales?
0:15:24 And I personally learned a lot from it.
0:15:26 You’re going to want to check out the podcast,
0:15:27 listen to Science of Scaling
0:15:30 wherever you get your podcasts.
0:15:34 – I do want to talk about a few more
0:15:35 of the Google things that they announced
0:15:37 ’cause there was something I thought was cool
0:15:38 while I was there.
0:15:41 But they’re also like, if I’m being honest,
0:15:43 they’re kind of like, they’re sort of gimmicky
0:15:46 and they’re kind of like almost forgettable,
0:15:47 but they’re still kind of cool, right?
0:15:50 Like they showed off this feature called Ask Photos
0:15:54 where you can basically use like an AI search
0:15:55 to search through your photos.
0:15:56 And some of the examples they gave was like,
0:15:58 when did my daughter learn how to swim?
0:16:00 And it would look through all of your photos,
0:16:02 all of the timestamps, try to find photos
0:16:04 where your daughter is swimming
0:16:07 and then tell you your daughter learned to swim
0:16:09 based on all of your photos, right?
0:16:13 So it uses the photos as context to answer your questions.
0:16:15 That I thought was pretty cool.
0:16:16 Like I can see that being really useful
0:16:19 if you have a giant database of photos on your computer
0:16:21 with like thousands of photos
0:16:24 and you’re trying to find like one specific thing
0:16:26 or maybe you’re making a video online
0:16:29 and you need like some B-roll for your video
0:16:31 and you want the B-roll to just be like shots
0:16:33 of the ocean or something.
0:16:35 You could go in there and let the AI find
0:16:37 like just the shots that you’re looking for.
0:16:40 So I thought Ask Photos was a pretty cool feature.
0:16:42 – When I saw that demo, I was like, oh, that was amazing.
0:16:44 They probably should have made that better
0:16:46 and really focus on something like that
0:16:48 ’cause it’s like, they announced like 10 things.
0:16:50 And most of it seemed like they were just kind of like
0:16:52 tacking on AI onto existing products, right?
0:16:53 It’s like a whole joke about like–
0:16:54 – I think a lot of it was.
0:16:56 – If you see like the little three stars,
0:16:58 that means you’re just like adding AI on
0:17:00 for like the sake of it, right?
0:17:03 And it felt like a lot of their stuff was that.
0:17:04 And there was this engineer who made a statement
0:17:06 about that the other day.
0:17:08 Apparently he worked at Google for like 20 something years.
0:17:10 He was a pretty, you know, top engineer at Google.
0:17:12 And he said, they’re doing the same (beep)
0:17:14 they did with Google Plus when like Facebook came out
0:17:16 where like, they’re like panicking.
0:17:17 They had to create something else and they’re just like,
0:17:20 start, okay, we have to have a social network.
0:17:22 Well, let’s just put all Google’s existing stuff
0:17:24 into a social network and like it just doesn’t work.
0:17:28 And you know, they’re also changing search too,
0:17:29 which I mean, is a big deal.
0:17:31 You know, where they’re like using AI
0:17:33 to like analyze the results of a lot of search terms.
0:17:36 I guess it’s only like 1% or so of searches
0:17:37 are currently using that feature,
0:17:40 but it rolled out like two days ago and you know,
0:17:42 it’s apparently some people in SEO land
0:17:45 are already seeing like 20% drop in traffic from that.
0:17:46 Like in the last week.
0:17:50 And so it’s, you know, they’re in a tough situation
0:17:51 ’cause like all the stuff they released,
0:17:54 they’re gonna like cause issues
0:17:56 if they just start dramatically changing Google search,
0:17:57 you know.
0:17:58 – Well, I mean, their revenue is all from,
0:18:00 from ad revenue from search, right?
0:18:02 Like that’s the biggest portion of the revenue
0:18:03 for the business.
0:18:06 So if people stop clicking on those search ads,
0:18:08 well, what happens to Google’s business?
0:18:11 I’ve actually noticed that pop up a lot more often.
0:18:14 Like almost every search I’ve done in the last like a week,
0:18:15 I don’t search Google a lot anymore,
0:18:18 but like I would say almost all of the searches
0:18:19 I’ve done in the last week,
0:18:23 I’ve seen that AI sort of summary thing come up at the top.
0:18:24 I still end up clicking on the links though.
0:18:27 Like usually if I’m Googling something,
0:18:28 I’m trying to find a website.
0:18:30 I’m not trying to find an answer to a question
0:18:32 because if I’m trying to find an answer to a question,
0:18:35 I’m just going straight to chat GPT these days, you know,
0:18:36 or Claude or something like that.
0:18:38 – You know, people are making a good point too.
0:18:39 It’s like almost like Google is like violating
0:18:41 this social contract that always existed
0:18:43 with the open web, right?
0:18:46 Where it’s like, hey, we’re like searching all your stuff.
0:18:49 We are taking your data and we’re making money off of it,
0:18:51 but we’re going to also send people to you.
0:18:53 And so that’s always been this kind of like social
0:18:54 contract that existed.
0:18:57 So now if they are taking in people’s data,
0:18:59 but then they’re just giving the answer,
0:19:00 how are they, and then they’re like,
0:19:02 how could they possibly criticize chat GPT?
0:19:04 (laughing)
0:19:08 How could they criticize chat GPT if open AI actually did
0:19:10 crawl all of YouTube’s data, like it’s, you know,
0:19:12 the rumor that they did.
0:19:13 I think they have a hard argument there.
0:19:14 That’s probably why they haven’t like really
0:19:17 went after it yet, because like they’re doing similar.
0:19:20 – Google’s a web crawler scraping company, right?
0:19:23 Like it scrapes the entire web’s data also.
0:19:26 The only difference is like if when Google scrapes the web,
0:19:28 it’s actually beneficial to the creators
0:19:30 and when chat GPT scrapes the web,
0:19:32 it sort of disincentivizes creators, right?
0:19:35 There’s definitely a big differentiator there.
0:19:39 – For now, for now, but it’s changing almost every month
0:19:39 right now.
0:19:41 So it’s like every month it’s like, you know,
0:19:43 people are going less to websites,
0:19:44 they’re just getting the answer from Google.
0:19:48 So yeah, I think Google’s in a very tough situation there.
0:19:49 And I don’t know how they’re going to get out of it.
0:19:51 – Yeah, well, the other thing is, you know,
0:19:53 when it comes to like context windows,
0:19:55 Google is currently the king, right?
0:19:59 Like the Gemini now has a one million token context window
0:20:01 and they said that’s jumping to two million tokens
0:20:02 within the year.
0:20:04 And just for, you know, context,
0:20:09 one million tokens is about 750,000 words input and output.
0:20:11 So the amount of words that you can put into the prompt
0:20:13 and get out is 750,000.
0:20:15 So they go to two million.
0:20:18 That’s 1.5 million words in and out context.
0:20:22 That’s enough to put in the entire Harry Potter book series
0:20:23 and ask questions about it.
0:20:24 – Yeah, talk about Steve Jobs again.
0:20:25 Like, you know, it’s like Steve Jobs
0:20:26 wouldn’t talk about all the specs, you know,
0:20:28 which now Apple’s doing that crap too.
0:20:29 Like Steve Jobs would talk about
0:20:31 how this is an amazing new thing.
0:20:32 He wouldn’t talk much about the specs.
0:20:34 You know, Google’s doing that same thing where like,
0:20:36 here’s the specs, it’s all these, you know,
0:20:38 here’s the context window, how big it is.
0:20:41 And versus open AI, not even talking about that stuff.
0:20:43 And I think it’s a trap because, you know,
0:20:45 one of my friends was at the open AI event
0:20:48 and the rumor, you know, around town in Silicon Valley
0:20:52 is that GPT-5 don’t really worry about the context window.
0:20:53 There’s like some major breakthrough
0:20:55 where I’m not sure if the context window
0:20:57 is gonna be dramatically larger,
0:20:58 but apparently something has changed
0:21:01 and they’re like that’s not gonna be much of an issue in GPT-5.
0:21:04 And so I think with like Google trying to play that game
0:21:06 of like we have the largest context window.
0:21:08 I mean, maybe GPT-5 is gonna have like 10 million
0:21:10 or 100 million or something ridiculous.
0:21:11 Maybe they’ve made a breakthrough there.
0:21:13 And so like, the Google’s gonna look pretty silly.
0:21:15 Like we’ve been playing this like stats game
0:21:17 where we have the best, you know, whatever
0:21:20 and the best specs and that’s not even,
0:21:21 they’re gonna lose in that game as well, I think.
0:21:24 – Yeah, I honestly think we’re gonna hit a point pretty soon
0:21:26 where people just don’t even talk about context windows.
0:21:28 This is gonna be like a non-issue.
0:21:29 They’re gonna be so big that the context window
0:21:33 is essentially more than you need, like always.
0:21:35 The other thing that they talked about
0:21:38 that was like pretty big news was their project Astra,
0:21:39 which I don’t remember.
0:21:40 I don’t know if you remember the demo,
0:21:43 but they walked around with like an iPhone out
0:21:45 and the iPhone was seeing things
0:21:48 and they were having a conversation with the phone
0:21:49 with what they were seeing, right?
0:21:51 The example they showed in their demo,
0:21:54 was the video footage went to a speaker
0:21:57 and it was like, let me know when you see something
0:21:58 that makes sound, right?
0:22:00 And it was like, oh, I see a speaker on the table.
0:22:02 And then they drew a little arrow on the camera
0:22:03 and said, what’s this part of the speaker called?
0:22:05 And it was like, oh, that’s called the tweeter, right?
0:22:07 And then they walked around the room
0:22:10 a little bit more with the camera
0:22:12 and then the girl in the demo was like,
0:22:14 do you remember where my glasses were?
0:22:16 And it actually remembered from earlier video footage,
0:22:19 yes, your glasses were on that other desk over by the Apple.
0:22:22 So she went over to where her glasses were,
0:22:24 put on the glasses and it was like this little Easter egg
0:22:27 moment where she put on glasses,
0:22:29 which looked like a hint at maybe a new version
0:22:31 of Google Glass or something, right?
0:22:34 ‘Cause she put on these glasses, sent her phone down
0:22:38 and then continued to have a conversation with the AI bot,
0:22:40 but now it was seeing what the glasses saw
0:22:43 and it also looked like it had a little tiny heads up display.
0:22:47 So whatever she was asking and whatever it was responding with,
0:22:50 it was almost like captioning it in front of her face
0:22:52 on the heads up display.
0:22:54 And Project Astra was actually one of the things
0:22:56 that they had demos available.
0:22:59 So I was actually able to demo Astra
0:23:00 while I was at Google IO.
0:23:03 And I mean, it worked pretty much the way
0:23:04 they showed it did in the demo.
0:23:08 It wasn’t like previous Google demos
0:23:10 where they made it look like real time,
0:23:11 but it wasn’t really real time.
0:23:14 It worked just like the demo.
0:23:16 And I thought that was actually pretty impressive.
0:23:17 I can see that being useful,
0:23:19 especially when it gets into like glasses and stuff.
0:23:21 – So since you really used it,
0:23:23 so I’m curious for like, from my perception was
0:23:27 that the open AI voice was more responsive than the Google,
0:23:29 but maybe the Google seemed to be taking more video input
0:23:31 ’cause it seemed to actually understand the surroundings
0:23:34 a bit better than the open AI demo.
0:23:35 So is that kind of like–
0:23:36 – There’s definitely more of a delay, right?
0:23:38 So when you were using the Google one,
0:23:39 you would ask it a question
0:23:41 and then there would be like a, you know,
0:23:45 one, two, three, four, it would respond.
0:23:48 The new version of chat GPT, it was like almost instant.
0:23:51 But if you pay attention,
0:23:55 it uses like filler words to make it feel more instant, right?
0:23:57 So what it would kind of do is you would ask it a question
0:24:00 and it would almost like repeat the question back to you.
0:24:03 And while it’s repeating the question back to you,
0:24:04 that’s where that sort of delay,
0:24:06 that latency would normally be.
0:24:08 So you would say like, “Hey, what am I looking at?”
0:24:11 And it would say, “Okay, let me take a look.”
0:24:12 It looks like you’re looking at
0:24:14 and then it would go into, you know, its response.
0:24:15 – Which is brilliant.
0:24:16 – So it was using that like filler.
0:24:17 – Yeah, it’s brilliant.
0:24:19 – But it makes it feel more natural
0:24:20 ’cause we talk like that too.
0:24:22 – Yeah, and you know, engineers,
0:24:23 there have been a few engineers on Twitter
0:24:25 that have been speculating that the reason
0:24:28 that the OpenAI model is so much more responsive
0:24:31 is because it actually is a breakthrough
0:24:32 in terms of being multimodal,
0:24:34 whereas Google is basically kind of stitching
0:24:36 these different models together behind the scenes.
0:24:37 You know, they got like a video model.
0:24:40 They got a, you know, text one, all this, right?
0:24:40 In audio.
0:24:42 And then OpenAI actually announced it.
0:24:43 They’re like, maybe people don’t realize it
0:24:45 ’cause we don’t really talk about the technical side
0:24:47 much on the stage, but yeah, that’s the big thing here.
0:24:49 It’s like, this is a model where literally
0:24:52 it’s doing all three at one time.
0:24:53 It’s not just doing text and then do,
0:24:55 it’s not doing text or doing image
0:24:57 and then like kind of like sending it to another model.
0:24:59 No, this is all happening within the same model.
0:25:00 That’s why it’s so fast.
0:25:01 And so I think that was the thing
0:25:03 that maybe a lot of people didn’t realize.
0:25:04 – Yeah, yeah, I mean, you mentioned a video model.
0:25:05 That was another thing that like,
0:25:07 we’re not gonna cover everything
0:25:08 that they covered at the Google event.
0:25:10 There was just way too much, right?
0:25:11 It was like two hours of announcements,
0:25:14 but another one that was kind of interesting, I guess,
0:25:16 was Veo or VEO, right?
0:25:17 Like they were basically acting like
0:25:19 this was their Sora competitor,
0:25:21 but if you put them side by side,
0:25:23 Sora’s still quite a bit better,
0:25:24 but Veo, I think they said that
0:25:27 can generate over one minute long videos
0:25:29 in 1080p resolution.
0:25:31 So, you know, it’s got the length
0:25:33 and the kind of quality going for it,
0:25:36 but it’s not like as realistic as what we saw out of Sora.
0:25:39 It was something where, you know, people saw it, right?
0:25:42 But everybody’s like first thing
0:25:44 is they’re gonna look at it and compare it to Sora, right?
0:25:45 Sora’s the best we’ve seen.
0:25:48 Like that set the bar for AI video.
0:25:50 And now you look at something like Veo
0:25:51 and you’re like, oh, that’s pretty cool.
0:25:53 But because we’ve already seen Sora,
0:25:55 it’s hard to be impressed by it.
0:25:57 – Yeah, that’s, and I wasn’t impressed.
0:25:59 And, you know, and Sora set the bar so high
0:26:01 that like it’s even,
0:26:03 it’s actually heard all the other AI video companies, right?
0:26:04 Like Runway and all the other ones, Pika.
0:26:07 ‘Cause like I used to share all these AI video threads
0:26:09 and they would get millions of views.
0:26:10 And then now people are just not interested.
0:26:12 Like you share it and like people are like,
0:26:13 this is like garbage.
0:26:15 – So hard to impress people now.
0:26:16 – So hard to impress people.
0:26:17 – Yeah, yeah.
0:26:19 Well, one last thing that I will say about Google
0:26:21 and I did sort of like a recap video
0:26:23 of my experience of Google I/O.
0:26:24 And I said this in that video,
0:26:28 is that going to events like the Google I/O event,
0:26:31 you know, it’s, it is really easy to look at Google.
0:26:34 Is this like big, huge corporate, you know,
0:26:37 faceless company that just wants to harvest
0:26:39 everybody’s data and get as much money
0:26:40 out of everybody as possible, right?
0:26:43 Like I think that’s the perception of the Googles
0:26:46 and the Microsofts and the metas of the world, right?
0:26:48 But when I went to events like this,
0:26:51 I got to meet so many of the people at Google, right?
0:26:53 I got to meet like the various engineers
0:26:54 and I got to meet, you know,
0:26:57 project leaders on different projects
0:27:00 that were working on a lot of this software.
0:27:03 And the thing that kind of really struck me
0:27:04 at this event was like,
0:27:06 these people are really, really excited
0:27:08 and really, really passionate about the tools
0:27:09 that they’re building.
0:27:12 And so even though Google itself is like this big,
0:27:15 faceless, massive mega corporation,
0:27:17 the individuals working on these projects
0:27:18 are really, really excited
0:27:20 and really passionate about what they do.
0:27:25 And it really sort of added to the humanity of Google for me
0:27:27 like actually getting to meet these people
0:27:28 and talk with them.
0:27:31 So, you know, that’s kind of the last little wrap up thing
0:27:34 that I wanted to say about Google is the people at Google
0:27:36 do care about the products that they’re developing.
0:27:39 They do care about what people think of these projects.
0:27:42 They do want to make them the best they can make them.
0:27:45 And that was the overwhelming sense
0:27:46 that I got at that event.
0:27:48 Now, fast forward to this week,
0:27:52 I’m actually at Microsoft Build out in Seattle right now.
0:27:53 Same kind of thing.
0:27:57 I’ve got to talk to the CTO of Microsoft.
0:27:59 I’ve gotten to talk to a whole bunch of project leaders
0:28:02 on different projects at Microsoft
0:28:04 and actually getting to talk to the humans
0:28:05 underneath these projects
0:28:07 that are actually building these projects
0:28:11 has been really interesting to me.
0:28:15 It really, really does make me feel more connected
0:28:16 to the company as a whole
0:28:19 just because I see the excitement of the people
0:28:21 that are building these things.
0:28:24 And so while at this Google event,
0:28:26 there was really two keynotes that happened.
0:28:28 There was the Monday keynote
0:28:31 which was like a co-pilot slash surface keynote
0:28:33 like the consumer facing products.
0:28:35 And then on Tuesday was Microsoft Build.
0:28:38 And Microsoft Build was the developer conference
0:28:40 which was really geared towards software engineers
0:28:42 and people building the software.
0:28:45 Not a whole lot of huge, exciting, crazy announcements
0:28:47 that came out of Microsoft Build
0:28:49 but the event that happened yesterday
0:28:50 was really, really interesting.
0:28:53 They announced a new feature called Recall
0:28:56 which is really interesting.
0:28:59 Basically what Recall does is it watches everything
0:29:02 that’s happening on your computer and it saves it all.
0:29:06 So it’s like the history inside of your Chrome Bowser
0:29:07 but for your entire computer.
0:29:09 So anything you built in Photoshop,
0:29:13 anything that you made with DaVinci Resolve,
0:29:16 any tool that you used on your computer,
0:29:19 it actually saved a history of all of that
0:29:21 and you can go back and find all of that history.
0:29:24 All of your browsing, all of your internet browsing,
0:29:26 it saves all of that as well.
0:29:28 It saves it all and you can go back through your history,
0:29:31 scrub through it and find very, very specific points
0:29:33 throughout your day.
0:29:34 And I thought that feature was pretty cool
0:29:37 but it obviously brings up some like security,
0:29:41 some privacy issues like oh, if it’s recording everything
0:29:45 I do on my computer, is Microsoft getting that data?
0:29:46 Where does that go?
0:29:49 What if there’s websites that I don’t want to be saved
0:29:52 into my storage and remembered that I visited?
0:29:55 Well, the cool thing about the Microsoft event
0:29:57 and one of the other announcements that they made
0:29:59 was that they’re actually developing new computers
0:30:01 to be AI first.
0:30:04 So a computer typically has a CPU and a GPU in it.
0:30:08 These new Microsoft computers have a CPU, a GPU
0:30:11 and now what they call an MPU, a neural processing unit.
0:30:15 So it’s like a separate card just to process the AI.
0:30:18 So all of the AI that it’s using to record your computer
0:30:21 and help you find what you did throughout the day,
0:30:24 that is all happening locally on your computer.
0:30:26 It’s not actually going out to the cloud
0:30:29 and Microsoft isn’t getting any of this data from you.
0:30:31 You can be not connected to the internet
0:30:33 and still save all this history.
0:30:36 Plus, they have the ability to go back through
0:30:38 and delete history that you don’t want in there.
0:30:40 So let’s say you visited a website
0:30:41 that you don’t want other people to visit.
0:30:43 Maybe you’re gift shopping or something.
0:30:45 Let’s just use that as an example.
0:30:47 I’m sure there’s other examples we can go with
0:30:49 but let’s use the example of gift shopping.
0:30:50 You don’t want somebody to come back,
0:30:52 look at the history of your computer
0:30:55 and see what gifts you were looking at for them.
0:30:57 So you can go and delete that from your history.
0:31:01 So it’s pretty secure, pretty private.
0:31:02 They say they never are gonna train
0:31:04 on any of your data that it’s saving.
0:31:09 And supposedly it all stays local right on your computer.
0:31:12 So that was one of the big announcements that they made.
0:31:13 Well, two of the big announcements that they made.
0:31:17 One was that they’re making their PCs AI first.
0:31:19 And the second one is that you’re gonna have
0:31:23 this recall feature built directly into Windows.
0:31:24 So everything you do on the computer,
0:31:26 there’s like a history of it that you can go back
0:31:31 and find really, really easily using your AI search.
0:31:33 The other big announcement they made at this event
0:31:37 was that co-pilot is kind of getting an overhaul.
0:31:38 If you use Windows right now,
0:31:41 you might notice co-pilot is like a little pop-up thing
0:31:44 that shows up on the right sidebar of your desktop.
0:31:45 Well, now it’s an actual app
0:31:48 that can actually be snapped to Windows
0:31:52 or float in front of other Windows.
0:31:54 And they showed off this really cool demo
0:31:56 where you can actually chat with the bot
0:31:59 and it will actually know what’s going on
0:32:01 with your computer and actually speak back to you.
0:32:03 So going all the way back to what we were talking about
0:32:05 at the beginning of this podcast,
0:32:10 OpenAI released a Mac app for ChatGPT
0:32:12 that’s going to have the voice in it.
0:32:15 And I think the reason that they didn’t release
0:32:16 the Windows app along with it
0:32:19 is because they knew Microsoft was going to release
0:32:21 this new version of co-pilot,
0:32:23 which kind of does all the same stuff.
0:32:26 That was the reason I think that OpenAI
0:32:27 didn’t announce a Windows app
0:32:29 because co-pilot does that stuff.
0:32:31 It can actually see what’s going on on your computer.
0:32:33 You can talk to it with your voice.
0:32:35 It will respond with a voice.
0:32:37 It does that stuff as well.
0:32:40 One of the really cool examples they showed off
0:32:42 was they had co-pilot open
0:32:44 and then somebody was playing Minecraft.
0:32:45 And supposedly they were playing Minecraft
0:32:46 for the first time.
0:32:47 They didn’t know how to play.
0:32:50 And they were having a conversation with the bot
0:32:54 and the bot was explaining to them how to play Minecraft
0:32:55 based on what it saw on their screen.
0:32:58 So it was like, they opened up their inventory
0:33:01 and asked the bot, “What do I build with this inventory?”
0:33:03 And it’s like, “Oh, you need to build an axe.”
0:33:04 And he’s like, “Okay, I’ll build an axe.”
0:33:07 And then it closes an inventory and the zombie pops up.
0:33:08 And he’s like, “What’s that? What do I do?”
0:33:10 And the AI was like, “Run, run, it’s a zombie.
0:33:11 Get out of here.”
0:33:14 So the AI was watching in real time
0:33:15 as he was playing this game
0:33:17 and actually giving feedback
0:33:20 and telling him what to do next in the game.
0:33:22 And that was also a really cool feature
0:33:25 that they showed off at the Microsoft event.
0:33:30 But it has been a whirlwind of AI announcements
0:33:31 over the last couple of weeks.
0:33:33 We’ve just been absolutely bombarded
0:33:36 between open AI, Google, and Microsoft.
0:33:41 And then in June, we also have a Cisco event coming up
0:33:42 where they’re gonna be talking
0:33:44 about how they’re leveraging AI for cybersecurity.
0:33:46 We have a Qualcomm event coming up,
0:33:50 which is starting to make a lot of the AI chips
0:33:51 that a lot of these products are using.
0:33:53 In fact, at the Microsoft event,
0:33:54 a lot of the Surface Pros are using
0:33:57 Snapdragon trips from Qualcomm.
0:33:59 So Qualcomm has a bunch of AI announcements coming up.
0:34:03 And then also in June, we have WWDC from Apple,
0:34:06 which is the Worldwide Developer Conference.
0:34:07 This is their big event
0:34:10 where they announce all of their big new features
0:34:11 that are coming out.
0:34:13 That’s last year, we got the announcement
0:34:14 of the Apple Vision Pro.
0:34:17 This year, we’re expecting a whole bunch of AI announcements,
0:34:19 possibly a new AI series.
0:34:22 But it has just been a crazy few weeks
0:34:25 and we have a few more crazy weeks coming up
0:34:28 with these additional events that are happening.
0:34:31 And hopefully, Nathan and I are gonna be able
0:34:33 to keep you looped in and chatting
0:34:35 about all of these upcoming events
0:34:38 and filling you in on all of the big announcements
0:34:39 that are happening.
0:34:41 So if you’re not subscribed to this podcast,
0:34:43 make sure you’re subscribed.
0:34:45 We put out new episodes every Tuesday
0:34:46 and every once in a while,
0:34:48 when we have really, really exciting events
0:34:49 happening in the AI world,
0:34:51 we’re gonna drop these bonus episodes
0:34:53 in between our normal episodes
0:34:55 to make sure that you’re looped in
0:34:59 and keeping your finger on the pulse of the latest news.
0:35:02 So that’s the goal, a lot of exciting things happening
0:35:05 and hopefully you’re here for it ’cause we’re here for it.
0:35:08 And thank you so much for tuning in to this episode today.
0:35:11 (upbeat music)
0:35:14 (upbeat music)
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