0:00:01 (upbeat music)
0:00:04 Support for the show comes from Into the Mix,
0:00:07 a Ben and Jerry’s podcast about joy and justice
0:00:09 produced with Vox Creative.
0:00:12 Ainez Bordeaux is a self-described hellraiser,
0:00:15 and she became an activist after being caught up
0:00:16 in the criminal legal system
0:00:19 when she couldn’t afford her bond.
0:00:20 And without a trial,
0:00:23 Ainez was sent to a St. Louis detention facility
0:00:25 known as the Workhouse,
0:00:28 notorious for its poor living conditions.
0:00:31 Here how she and other advocates fought to shut it down
0:00:33 and won on the first episode
0:00:36 of this special three-part series out now.
0:00:39 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:00:45 Support for the show comes from Into the Mix,
0:00:48 a Ben and Jerry’s podcast about joy and justice
0:00:50 produced with Vox Creative.
0:00:53 Ainez Bordeaux is a self-described hellraiser,
0:00:56 and she became an activist after being caught up
0:00:58 in the criminal legal system
0:01:00 when she couldn’t afford her bond.
0:01:01 And without a trial,
0:01:04 Ainez was sent to a St. Louis detention facility
0:01:06 known as the Workhouse,
0:01:09 notorious for its poor living conditions.
0:01:12 Here how she and other advocates fought to shut it down
0:01:14 and won on the first episode
0:01:17 of this special three-part series out now.
0:01:20 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:01:24 – Scott, have you ever made a significant pivot
0:01:25 at one of your businesses?
0:01:28 And if so, how did you know is the right time
0:01:29 to make that change?
0:01:31 – Yeah, I’m not sure there is a significant business
0:01:35 that’s ever been built without something resembling a pivot
0:01:38 or iterating the business strategy.
0:01:42 So my first firm, Profit Brand Strategy,
0:01:44 was initially profit market research.
0:01:45 And we used to go out and do surveys
0:01:46 with the internet and computers
0:01:48 and try and find a different way to collect data.
0:01:53 And what we found is that what brands and clients appreciated
0:01:54 was the interpretation.
0:01:57 So we turned to Profit Brand Strategy
0:01:59 and we became a consulting firm at L2.
0:02:01 We were totally focused on the luxury space.
0:02:02 And then P&G called us and said,
0:02:04 “Would you ever do this for P&G?”
0:02:06 And the name of the company was Luxury Lab.
0:02:08 And I hung up the phone and said,
0:02:10 “Our new name is L2.”
0:02:15 And pivoted to or into consumer products at section,
0:02:17 my online education started up.
0:02:20 We initially thought we were gonna be the Netflix of business
0:02:23 that it would be short form videos for B2B.
0:02:25 And that was gonna be so expensive
0:02:26 to produce that kind of content.
0:02:29 So much of that content was available elsewhere
0:02:31 that we pivoted straight into online education
0:02:35 focusing on upskilling the enterprise or AI skills.
0:02:38 So I don’t think I’ve had a business where we didn’t pivot.
0:02:41 I think you just look at the data
0:02:45 and you are thoughtful about what are the opportunities?
0:02:49 And there’s nothing like facing the enemy.
0:02:51 There’s just no market research like launching a business
0:02:54 and seeing what people are actually willing to pay for
0:02:56 to inform your decision making.
0:02:59 And a lot of times clients will come to you and say,
0:03:01 “We’d love it if you could do this.”
0:03:05 And so you’ll get signals from the market.
0:03:09 And what I would suggest is have a solid board
0:03:10 and have your kitchen cabinet of people
0:03:14 that you can propose stuff to and bounce stuff off of them.
0:03:16 And also talk to your colleagues and your employees.
0:03:20 And I’m trying to think if we’ve done a pivot here,
0:03:24 I guess we’re sort of we had our adventures in television.
0:03:26 Now we’re kind of, I wouldn’t say all in on podcasts,
0:03:28 but I think we’re devoting the majority
0:03:32 of the human capital property media now to podcasts.
0:03:37 So the market is an unbelievable muse and advisor.
0:03:39 And you just wanna surround yourself with smart people
0:03:40 who can help you interpret the data
0:03:44 and make sure that you’re not speaking to yourself.
0:03:45 It’s very hard to read the label
0:03:47 from inside of the bottle sometimes.
0:03:50 (upbeat music)
0:03:54 – Welcome to First Time Founders.
0:03:59 One of the most promising use cases for AI is code generation.
0:04:02 That is doing the work of a software engineer.
0:04:06 Already in the US, an estimated nine in 10 software developers
0:04:08 are using AI coding tools.
0:04:11 My next guests created one of those tools.
0:04:13 And less than two years after launch,
0:04:16 it’s already one of the most popular AI coding assistants
0:04:18 in the world.
0:04:21 Last year, they had less than a thousand users.
0:04:24 Today, they have more than 600,000.
0:04:27 Now, after raising a $65 million funding round
0:04:31 at a $500 million valuation,
0:04:33 they’re looking to take over the industry.
0:04:37 Next up, compete with the likes of Microsoft and OpenAI.
0:04:40 This is my conversation with Varun Mohan,
0:04:42 CEO and co-founder of Codium,
0:04:44 and Jeff Wang, Codium’s head of business.
0:04:47 Varun, Jeff, welcome.
0:04:47 – Thanks for having us.
0:04:48 – How was the flight?
0:04:49 You just got in today, right?
0:04:50 – Yeah, we took a red eye
0:04:53 and we I think slept one hour each maybe.
0:04:55 And then when we got to the hotel earlier today,
0:04:56 maybe we slept another hour.
0:05:00 So we’re in perfect condition to do this podcast.
0:05:02 New York code spells are super fun.
0:05:04 You get like this matchbox room.
0:05:06 You know, you’re right next to the wall
0:05:08 every location you are, so perfect.
0:05:10 – Well, I appreciate you being here
0:05:11 and appreciate you joining,
0:05:15 despite getting one hour of sleep last night.
0:05:17 – It’s like two, I suppose.
0:05:19 – Yeah, yeah, good enough.
0:05:22 So you guys are the second AI company
0:05:23 that I’ve had on this podcast.
0:05:28 The previous one I had was an AI for finance company,
0:05:31 more or less replacing bankers,
0:05:35 though his argument is that he’s not replacing bankers.
0:05:37 I’m just gonna start this with the same question
0:05:39 that I asked him, which is,
0:05:42 are you guys at Codium replacing programmers?
0:05:46 – Our vision is actually to give developers
0:05:48 the ability to dream bigger.
0:05:50 And I know that that sounds very vague,
0:05:52 but I think there’s one way of looking at it
0:05:54 that we could just go out and replace
0:05:57 like low-skill labor or low-skill developers.
0:05:59 But I think that that’s not a very rich idea.
0:06:01 We wanna take the best developers
0:06:03 and make them 10 times as leveraged.
0:06:06 And the reason why we think that this is only going to lead
0:06:09 to more developers existing is unlike other professions,
0:06:11 there’s no limit to the amount of technology
0:06:12 the world can actually consume.
0:06:13 – Yeah. – Right?
0:06:15 I don’t think you would ever just be like,
0:06:18 hey, guys, stop making technology.
0:06:19 If we can actually make it so that
0:06:22 the next great invention happens 10 times faster,
0:06:23 we will just only get 10 times
0:06:25 the amount of invention in the world.
0:06:29 – So a program is generally fans of yours, would you say?
0:06:30 – I hope so.
0:06:33 Yeah, I mean, our message is not to replace developers,
0:06:34 I would say.
0:06:36 The Wave Room actually got me on board
0:06:40 ’cause he said like everyone that touches a product,
0:06:42 almost half the people continue using it.
0:06:45 So when you have that, you know there’s something there,
0:06:46 you know there’s some value, right?
0:06:47 And some excitement.
0:06:49 – Is that higher within the industry?
0:06:52 I mean, 50% retention basically of the customers.
0:06:56 That’s, do we know what it’s like for other AI tools
0:06:57 or is it too early?
0:06:59 – Yeah, I think for a lot of consumer products,
0:07:02 it’s usually in the, if you can get it above 10%
0:07:05 at the long tail that is considered very good.
0:07:07 That’s largely because consumers,
0:07:10 unlike companies, if they get bored of something,
0:07:12 they throw it away very quickly.
0:07:14 And these products are not collaborative also.
0:07:16 This is like a single player product.
0:07:18 So it’s actually very easy to churn off of the product
0:07:20 because you aren’t chatting with other people.
0:07:23 So it does mean it is providing a lot of leverage
0:07:25 and developers stay more in flow state
0:07:27 using products like Kodium.
0:07:29 But yeah, hopefully we can make it even better.
0:07:31 – I mean, you’re up against a lot of different tools.
0:07:34 And I mean, I feel like code generation
0:07:35 was one of the first things that people said,
0:07:37 “Oh, AI is going to take over this thing.”
0:07:41 But I feel like the biggest competitor in your space
0:07:43 is GitHub Copilot.
0:07:45 What does the competitive landscape look like
0:07:48 in the AI code generation space?
0:07:50 – There are reasons why we are able to compete directly
0:07:51 with Copilot.
0:07:54 One of them is that we have full repo context awareness.
0:07:56 So as the user is typing,
0:07:58 the results are highly personalized
0:08:01 and we’re seeing like a 30 to 40% boost in accuracy
0:08:03 just having that code base be available
0:08:06 and giving tools for the user to point to
0:08:09 what they’re working on and trying to figure out their intent.
0:08:12 So just the quality of our code suggestions
0:08:14 are very competitive.
0:08:16 And then the thing that we’re really kind of trying
0:08:19 to lean in on though is our ability to deploy
0:08:21 onto like a private server.
0:08:24 And people can host Kodium inside their company
0:08:26 or in their work environment.
0:08:29 And for example, if you’re like in the defense space
0:08:31 or like the finance or healthcare space,
0:08:33 they can’t use Copilot at all.
0:08:35 And that’s kind of where we are focusing right now,
0:08:38 our efforts, but then we have some things down the pipe
0:08:40 where we’ll just be competitive
0:08:41 even on the cloud front too.
0:08:43 – What does it look like for a programmer?
0:08:46 I mean, it sounds like you’re sort of typing in
0:08:49 and then it gives you a list of auto suggestions
0:08:51 for what comes next.
0:08:53 What does it actually look like if you’re a programmer?
0:08:56 And please explain it to me as if I’m five
0:08:59 ’cause I don’t program, I don’t, not a coder.
0:09:02 – Yeah, so a little bit about like the way software
0:09:03 sort of gets built.
0:09:06 So developers write code and what’s called an ID.
0:09:09 It’s this application that enables you to debug code.
0:09:11 So if there are bugs, you could run it.
0:09:14 You can actually see what the errors are, iterate on it, right?
0:09:18 And then right before the code gets pushed into production,
0:09:20 it goes through a review process.
0:09:22 And other people in the company take a look at the code
0:09:23 and actually review it.
0:09:26 And then after that, it goes and it actually gets deployed
0:09:28 into production and it’s on a website or whatever,
0:09:32 where end users can actually touch the product in the end.
0:09:36 And right now where codium is mostly focused is in the ID.
0:09:38 So that’s where developers actually write the code.
0:09:40 It provides value in multiple ways.
0:09:42 So as developers are writing code,
0:09:46 it fills in passively starts filling in more and more code.
0:09:48 And because of the fact that we actually do train
0:09:51 our own models for that passive AI,
0:09:54 we actually found that around 50% of all software
0:09:57 that is getting committed by a developer
0:10:00 is actually accepted and generated by codium.
0:10:02 So that’s the amount of leverage
0:10:05 that just autocomplete is providing to end users.
0:10:08 But to add to that, we also provide a couple of other pieces
0:10:10 of functionality that is super valuable,
0:10:13 despite what level you are as a programmer.
0:10:15 So you can even chat with your code base.
0:10:17 And this probably seems like a very basic piece
0:10:20 of functionality, but when you’re a new developer
0:10:21 and you’re coming into a company
0:10:23 and you have millions of lines of code,
0:10:25 it takes a while to actually onboard
0:10:26 onto that new code base.
0:10:29 And what we’re finding is even at the largest enterprises,
0:10:32 the time it takes to onboard onto a code base
0:10:35 goes down from four to six months to four to six weeks
0:10:37 with a product like codium.
0:10:40 – I wanna focus on how you started this company.
0:10:45 You were a software engineer at a self-driving vehicle company.
0:10:48 So you were kind of working on AI there, I feel like.
0:10:53 And you originally had an idea to start a company
0:10:55 not for writing code with AI,
0:11:00 but for something called GPU virtualization,
0:11:02 completely different company from codium.
0:11:03 It also had a completely different name.
0:11:05 The name was Exa Function.
0:11:09 Can you explain the first iteration of this company
0:11:11 before it became what is now known as codium?
0:11:12 – So to add a little color there.
0:11:14 So I graduated from MIT,
0:11:16 worked at this company called Nero.
0:11:18 It’s an autonomous goods delivery company.
0:11:19 And actually a lot of the learnings
0:11:20 that I had from autonomous vehicles
0:11:23 are actually making their way into the space
0:11:24 we’re in right now.
0:11:25 – Oh wow.
0:11:28 – And maybe to paint some clarity on that.
0:11:30 In 2015, TechRunch basically wrote,
0:11:32 this is the year of AVs.
0:11:34 And in 2024 now, the quote is,
0:11:36 is this the year of AVs?
0:11:38 And you can see how there’s probably going to be
0:11:39 a lot of parallels to generative AI
0:11:42 where we are going to severely overestimate
0:11:44 what is going to happen in a year.
0:11:46 And one of the cool parts about generative AI
0:11:48 is how easy it is to make a demo,
0:11:50 but it is tremendously hard
0:11:51 to make something production ready.
0:11:52 And if you make a claim
0:11:54 that you are going to get rid of a developer,
0:11:56 that is a massive, massive claim.
0:11:57 And in fact, I would actually argue
0:12:00 that is a harder problem than autonomous vehicles.
0:12:01 Because ultimately,
0:12:02 if you look at autonomous vehicles,
0:12:04 all you need to do is press the accelerator
0:12:06 or decelerator or turn a steering wheel.
0:12:07 – That’s a great point.
0:12:08 – Think about the number of different things
0:12:09 a developer actually needs to do.
0:12:11 So I actually led a team
0:12:13 to build large scale deep learning infrastructure.
0:12:16 So how do you run these models at scale
0:12:18 and sort of left the company
0:12:19 with this vision of deep learning
0:12:22 and the idea of running these large models
0:12:24 was going to affect many, many industries.
0:12:25 And we had a small team of people.
0:12:28 We had eight people managing upwards of 10,000 GPUs.
0:12:32 We managed close to 20 to 30% of an entire data center.
0:12:34 And we worked with a lot
0:12:36 of these large autonomous vehicle companies
0:12:37 when we started this company, Exafunction.
0:12:38 Because our mission was,
0:12:41 how do we make it easier to run deep learning models?
0:12:42 But what ended up happening?
0:12:44 This is where startups can always get disrupted.
0:12:46 And it sounds silly to get disrupted.
0:12:48 We were making seven figures in ARR,
0:12:51 but we realized actually most of the models
0:12:53 would probably become these transformer based models.
0:12:56 And these are the models that underpin the GPTs,
0:12:57 the models that open AI has.
0:12:59 – What is a transformer based model?
0:13:00 If you could explain for us, yeah.
0:13:02 – So the basic idea is,
0:13:04 so we now know of prompting, right?
0:13:06 You know, use chat GPT, you pass in a prompt
0:13:10 and notice how it streams tokens one at a time, right?
0:13:12 That’s actually a property of these models
0:13:13 that are called transformer models,
0:13:15 that they are what are called auto aggressive.
0:13:17 They actually generate one token at a time.
0:13:19 And this is very different
0:13:21 than a lot of other classification tasks in the past
0:13:22 where you pass in an input
0:13:25 and it just gives you the entire answer all in one shot.
0:13:28 But this actually like slowly generates the entire thing,
0:13:30 sort of one word, one token at a time.
0:13:31 And we started noticing actually
0:13:34 that that was how a lot of models were starting
0:13:37 to look like once open AI came out with GPT-3.
0:13:39 And the beautiful thing about the model
0:13:41 that is truly crazy is because of the way it is trained,
0:13:43 it can do it in an unsupervised way.
0:13:45 So one of the things that was very different
0:13:49 about models in the past is you needed a lot of label data.
0:13:51 But these models are trained on the entire public internet.
0:13:53 The label data is the internet.
0:13:55 So because of that, you suddenly got these models
0:14:00 that could take in basically trillions of tokens of code
0:14:03 or text and this was not possible in the past
0:14:05 and this created these new sort of generative models.
0:14:06 And in the middle of 2022,
0:14:09 we had this business that was a GPU virtualization business.
0:14:11 The idea was we made it simpler
0:14:14 to run applications on GPUs.
0:14:16 And we found out that most applications
0:14:19 would probably be these transformer models.
0:14:21 And if all of what we were doing
0:14:22 was running transformer models,
0:14:24 we would largely become a commodity
0:14:26 because they would become a race to the bottom, right?
0:14:28 It would be the equivalent of asking,
0:14:31 like they would ask Varun how cheaply can you run this model?
0:14:33 I’d say I can do it for a dollar.
0:14:34 Then they would ask Jeff how cheaply you can do it.
0:14:36 He’d say 50 cents and we’d go back and forth
0:14:37 until no one made any money.
0:14:40 And this is the commodification of this entire space.
0:14:43 But what we did see was we felt that this technology
0:14:45 would be like the early coming of the internet.
0:14:47 There would be a brand new set of applications
0:14:48 that would be created.
0:14:50 And we were early adopters of GitHub’s product,
0:14:52 GitHub Copilot, and we thought that that was just scratching
0:14:55 the tip of the iceberg of what the future would look like.
0:14:57 And that’s where Codium sort of came about.
0:15:00 But it was, as you can imagine, a very rough experience
0:15:03 because we basically said buy to all the revenue that we had
0:15:05 and we had to start all the way back down to zero.
0:15:10 So, I mean, that to me is like the mother of all pivots
0:15:14 where not only are you changing the entire business
0:15:16 as you know it, you’re also doing it at a time
0:15:17 when things are going really well.
0:15:20 I mean, you said seven figures ARR.
0:15:22 My understanding is that you’d also raise $22 million
0:15:24 for this company.
0:15:26 Like things are going right.
0:15:30 And then you turn around and you tell all your employees,
0:15:32 actually would scrap that.
0:15:34 We’re going to do a whole different thing.
0:15:38 If I were a software engineer who worked at Big Tech
0:15:40 and had quit to go work at ExoFunction
0:15:45 and the CEO told me that, I’d be a mixture of like pissed off,
0:15:46 freaked out, concerned.
0:15:49 How did you rally the team
0:15:52 and how were you able to make that pivot so successfully?
0:15:53 – So I’ll say a couple of things
0:15:55 about the composition of the team.
0:15:57 Largely they were people that we knew.
0:15:58 And that’s actually very important
0:16:00 because they would be people that would go
0:16:02 into the trenches with us.
0:16:04 They were people that knew the caliber of people
0:16:07 that both me and my co-founder were.
0:16:08 And also on top of that,
0:16:10 we picked a problem space
0:16:13 where we were all passionate about it.
0:16:15 And I 100% knew at the time
0:16:19 there were products like mid-journey that were taking off.
0:16:20 Small team of people, eight people
0:16:23 that were making tens of millions of dollars in revenue.
0:16:24 And frankly speaking,
0:16:26 when we decided to pivot the company,
0:16:27 we knew for a fact,
0:16:29 none of us were that passionate about image generation
0:16:31 despite the fact that it is a very cool area.
0:16:32 And if we had picked it,
0:16:35 our team wouldn’t have had I guess the mental fortitude
0:16:38 to dig deep enough to actually build the problem space.
0:16:41 And then I guess the sort of third part
0:16:43 is actually that we actually were able to take
0:16:45 a lot of the infrastructure expertise
0:16:46 that we had as a company
0:16:48 to actually go out and build the application
0:16:49 significantly faster.
0:16:51 We were very quickly able to train our own models
0:16:52 and run them at massive scale.
0:16:54 And right now, Codium is one of the top five
0:16:56 largest generative AI apps
0:16:57 in terms of text in the world.
0:17:00 And that largely is because the original composition
0:17:02 of the team was these people
0:17:05 who are effectively GPU infrastructure experts.
0:17:07 But all said and done, everything that I said,
0:17:11 it comes down to you need a very truth seeking company.
0:17:13 And at the time,
0:17:15 even if we were at seven figures in revenue,
0:17:18 I did not know how we would 10x the amount of revenue.
0:17:20 And we could continue to lie to ourselves
0:17:23 and have a slow but certain death as a company
0:17:25 as the technology commoditizes, right?
0:17:27 And we all run the same kind of models.
0:17:28 Or we could just say,
0:17:31 there is a high probability that we will die,
0:17:33 but there’s a space that we could be very passionate about
0:17:34 and it could be very big.
0:17:37 I think we just decided the latter was
0:17:39 the more rational choice it is very hard to make.
0:17:43 But in retrospect, it was the obvious choice, right?
0:17:45 – Did you have any data showing you
0:17:47 that you were going to crash and burn at that point?
0:17:48 Or was it just a hunch?
0:17:50 And part of the reason I asked that
0:17:53 is because if I were your investor,
0:17:55 I would wanna be like, oh yeah, yeah.
0:17:58 It’s very clear to me that you guys have to pivot.
0:18:01 – We were cashflow positive then.
0:18:02 We were cashflow positive then.
0:18:04 – So you just had a feeling?
0:18:06 – We had a feeling.
0:18:08 It’s just because, and this is a little bit of a curse
0:18:11 of being a venture capital, venture-based business.
0:18:13 If you’re making millions of dollars in revenue,
0:18:15 that is not a venture-backable business.
0:18:19 And if we can’t figure out a path to get that to 100,
0:18:21 then that is not a business that we could build.
0:18:25 We could continue to keep it as an eight to 10% team.
0:18:26 We have another mentality in the company
0:18:27 beyond being truth-seeking
0:18:29 that we are a very lean company.
0:18:30 By the time we raised our Series B,
0:18:32 we had barely spent our seed round.
0:18:35 And I think that’s just because we don’t think capital
0:18:38 is a limiting factor in building a good business.
0:18:41 It’s you have to build a great product that customers love.
0:18:43 And that is usually not just you had more money.
0:18:46 – We’ll be right back.
0:18:48 (upbeat music)
0:18:51 (upbeat music)
0:19:02 – Support for the show comes from Into the Mix,
0:19:05 a Ben and Jerry’s podcast about joy and justice
0:19:07 produced with Vox Creative.
0:19:10 Would you have $25,000 to post bill?
0:19:13 That’s how much Inez Bordeaux had to pay
0:19:15 when she was arrested in 2016.
0:19:17 And since she couldn’t afford it,
0:19:18 she was sent to the workhouse,
0:19:21 a pretrial detention center in St. Louis.
0:19:23 Inez and the other detainees weren’t locked up
0:19:26 because they’d been convicted,
0:19:29 but because they couldn’t afford their bail.
0:19:31 – Experiencing what I experienced
0:19:34 and watching other women go through it
0:19:38 and know that there were thousands before us
0:19:41 and there were thousands after us
0:19:46 who had experienced those same things.
0:19:48 That’s where I was radicalized.
0:19:50 – She spent a month at the workhouse
0:19:52 and witnessed abject conditions,
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0:21:18 – We’re back with First Time Founders.
0:21:20 One of the things you mentioned
0:21:23 is that you are training your own models.
0:21:25 I mean, this is an AI application,
0:21:28 but most AI applications that I am aware of,
0:21:32 they’re purely building the application layer,
0:21:35 and that is they’re basically using someone else’s model,
0:21:38 usually open AI, and they’re tweaking
0:21:39 and they’re building off of that model
0:21:41 and creating their own application.
0:21:42 You guys are different.
0:21:44 It sounds like you guys are,
0:21:45 I don’t know what you’d call it,
0:21:48 full stack AI from the model to the application.
0:21:49 Is that right?
0:21:50 – That is correct.
0:21:52 Actually, even at the kernel layer,
0:21:55 we’ve done some, like we’ve written some code
0:21:57 even at the infrastructure layer
0:21:58 so that we could set the models on top
0:21:59 in an efficient manner.
0:22:01 And the reason we have to do that
0:22:03 is because of the latency issues we talked about.
0:22:05 For example, if you are a passive AI
0:22:07 and you take, let’s say one second
0:22:09 to show up the suggested code,
0:22:10 people are just going to stop using that.
0:22:12 They don’t want to get out of flow state
0:22:14 and pause and wait for results.
0:22:18 – How many other AI startups are doing,
0:22:19 what should we call it, the full stack,
0:22:23 the infrastructure to application?
0:22:24 Are there many others?
0:22:26 I just, I mean, off the top of my head,
0:22:29 I’m like anthropic like open AI,
0:22:32 but I guess they’re mainly kind of infrastructure layer, right?
0:22:34 I mean, isn’t this super rare?
0:22:36 – I think in my mind,
0:22:39 there’s maybe a couple of unique things about code
0:22:41 that make it so that you can actually do this here.
0:22:42 And you’re totally right.
0:22:44 Most of the large companies that are even successful
0:22:46 are largely built on top of an API,
0:22:49 but we genuinely felt to build a best in class app here.
0:22:51 We needed to become vertically integrated.
0:22:55 And for us, it was also not a complex thing for us to do
0:22:58 in that we have the technical talent inside the company
0:22:59 to actually go ahead and do that.
0:23:02 Maybe one of the unique aspects of code
0:23:05 on why we can do this is code can actually be run.
0:23:08 Like let’s say I am a illegal AI tool
0:23:10 and I’m redlining a bunch of documents.
0:23:12 The only way to know if that is good
0:23:14 is for a human to go in afterwards
0:23:16 and actually take a look at it.
0:23:17 For code, you can actually,
0:23:19 if you make an edit to a code base,
0:23:21 you can actually run the code and validate
0:23:22 it is doing the right thing
0:23:24 without a human in the loop at all.
0:23:26 And what that means is there are ways in which
0:23:29 you can close the loop in intelligent ways
0:23:30 that you can actually,
0:23:32 if you specialize on that application
0:23:34 and you are vertically integrated,
0:23:37 you can build an even better app for code.
0:23:40 And we’ve taken advantage of this in many, many ways.
0:23:42 And we realized if we didn’t do this,
0:23:43 we’d be shooting ourselves in the foot.
0:23:45 And I’ll give you even a simple example
0:23:47 of how this manifests itself.
0:23:49 Right now, I mentioned this.
0:23:51 Codium is, processes over a hundred billion tokens
0:23:53 of code every day, which is over 10 billion lines
0:23:54 of code every day.
0:23:56 If we passed that through OpenAI,
0:23:57 we would have gone bankrupt.
0:24:00 And there was a recent article from the Wall Street Journal.
0:24:01 – And why is that, sorry,
0:24:02 because you would have to pay for it.
0:24:03 – Because it would be too expensive.
0:24:04 – Exactly.
0:24:08 – And not the best for our particular application
0:24:09 on top of that.
0:24:11 And if you look, there was a recent article
0:24:13 on the Wall Street Journal about how GitHub Copilot
0:24:16 was spending tens of dollars per user per month.
0:24:18 And that’s actually because even GitHub,
0:24:20 Microsoft’s product is not vertically integrated.
0:24:22 They are relying on external models
0:24:24 to build their application.
0:24:27 And we view that as, hey, the model and the product
0:24:28 and the infrastructure are so critical
0:24:30 to delivering a great experience,
0:24:32 why would we not have control over every piece of that?
0:24:35 So my understanding is you guys don’t use
0:24:38 the actual data of your individual users.
0:24:42 So how is the model getting trained then?
0:24:45 – So we actually do sort of two different things.
0:24:48 And I’ll let Jeff add on how this affects our enterprises
0:24:50 and the customers that use the product.
0:24:52 So first of all, we use permissively licensed code
0:24:54 that is available on the public internet.
0:24:56 And we also attribute it on generation time.
0:24:59 So we actually take sort of copyright
0:25:01 and licensing very seriously as a company.
0:25:03 But on top of that, when we release product
0:25:04 from our user data, you’re right,
0:25:06 we don’t take the data from our users,
0:25:08 like let’s say when they’re auto-completing stuff
0:25:10 and copy that code and put it into our training set.
0:25:13 But we can see, hey, users are accepting
0:25:14 these types of suggestions more
0:25:16 and these types of suggestions less.
0:25:19 So we have preferences on what users and humans like.
0:25:21 And that actually informs us to actually build products
0:25:23 that are better and more willing to use.
0:25:25 And then that actually has a virtuous cycle
0:25:26 and that now people are willing to try
0:25:28 more complex things on our product
0:25:29 because the easier things they have,
0:25:31 high confidence that they work.
0:25:33 And suddenly the frontier of what we are actually able
0:25:36 to experience as we are able to give the user
0:25:37 increase more and more,
0:25:39 largely because we have a product that is so well beloved.
0:25:42 We now have over 600,000 users that use our product.
0:25:43 – Yeah, it’s unbelievable.
0:25:45 – I think one thing we might have glossed over
0:25:48 in the beginning was codeon made a very conscious decision
0:25:51 to make the product free for individuals.
0:25:53 And if you think about, you know,
0:25:57 Varun just said co-pilot loses $10 to $20 a month per user.
0:26:00 That’s after they’ve been paying a subscription to, right?
0:26:02 So having that infrastructure background,
0:26:05 being able to make it efficient to deploy these models
0:26:07 and then giving it out for free for individuals,
0:26:09 allowed us to build this very large user base,
0:26:12 probably the largest user base for a coding assistant.
0:26:14 – Yeah, I mean, just the data here,
0:26:17 you started out last year with less than 1,000 users,
0:26:19 by the end of the year, you had half a million.
0:26:21 – Yeah, and we have over a million,
0:26:23 millions of downloads across all the plugins.
0:26:24 And the reason why that’s very important
0:26:26 is because of what we just talked about.
0:26:27 If we roll out multiple models,
0:26:29 if we are changing the temperature
0:26:31 of the thresholds here and there,
0:26:33 we are getting so many signals
0:26:35 as to what is the appropriate settings to tweak.
0:26:38 And I think every hour we’re getting like a million signals.
0:26:41 So we can run all these experiments on these free users
0:26:43 of all these models we train
0:26:44 to really, really get the best results
0:26:45 that you could possibly get.
0:26:48 And then only when we’ve validated like, okay,
0:26:49 we’ve trained this model,
0:26:51 this is better than all the other ones we’ve trained.
0:26:53 These are the settings that makes the best results.
0:26:55 Then we could deploy that to our on-prem
0:26:57 or enterprise users, right?
0:26:59 Because we can’t, after we’ve deployed it,
0:27:00 we can’t really get that much more information from it.
0:27:01 It’s completely,
0:27:04 it can be hosted even in an air-gapped environment.
0:27:06 So I think that’s a big element
0:27:07 of why we are successful
0:27:09 of being able to deploy these models.
0:27:12 Because if somebody’s trying to start from scratch right now,
0:27:14 how are they gonna know that their model is good?
0:27:16 How are they gonna tweak the model, right?
0:27:18 Without a very large user base.
0:27:19 So that’s part of the secret sauce
0:27:21 is having that free user base.
0:27:24 – Yeah, and you, it’s still free,
0:27:26 which is what I find pretty fascinating.
0:27:28 And you said, I was just reading your state,
0:27:30 your like mission statement,
0:27:33 you are quote committed to having a free tier forever.
0:27:36 The natural next question is,
0:27:39 how is it gonna get properly monetized?
0:27:41 And how are you gonna maintain that,
0:27:43 that free tier into perpetuity?
0:27:45 – I think people underestimate kind of the demand
0:27:47 for both just the on-prem instance,
0:27:49 but also some of the teams features we add
0:27:50 on the SaaS product.
0:27:52 So we have a free individual tier,
0:27:56 but if you create a team and add on-board users to it,
0:27:57 that is a paid product.
0:27:59 And there are things like analytics
0:28:01 and actually bigger models and seat management
0:28:04 that are going to be better than the free product.
0:28:06 But we are committed to making the free product
0:28:08 the best coding assistant out there, no matter what.
0:28:10 So whatever other coding assistants come to market,
0:28:13 we will make sure our free product is still the best one.
0:28:14 We wanna make sure, you know,
0:28:16 disincentivize others from entering,
0:28:18 but we want people that always have the option.
0:28:20 We don’t want them to get forced to buy a co-pilot,
0:28:21 for example.
0:28:22 – And then maybe one thing to add to Jeff,
0:28:24 like we monetize enterprises, right?
0:28:27 So we have some of the largest Fortune 100s,
0:28:30 F-thousands, even over 10,000 developers on our product.
0:28:33 And those companies, obviously they want security guarantees,
0:28:34 they want personalization
0:28:36 for many, many repositories that exist.
0:28:37 And they also want support
0:28:40 across all source code management tools.
0:28:44 Less than 10% of Fortune 500 companies are on GitHub cloud.
0:28:45 And that is the competitor that we have,
0:28:46 that is GitHub co-pilot.
0:28:48 And they have committed to making their product
0:28:52 differentially better if you are on GitHub cloud, right?
0:28:55 So we want to take the approach of almost being Switzerland.
0:28:58 We don’t care what programming language you write.
0:29:00 We don’t care what ID is you use.
0:29:03 We don’t care where you store your source code.
0:29:06 And ultimately, we also just don’t really care
0:29:07 what seniority the developer is.
0:29:10 We will provide the maximum amount of leverage there.
0:29:13 Whereas a lot of the larger players in the space
0:29:15 are focused on being tied to another brand.
0:29:17 And the reason why we don’t think that that makes sense is
0:29:20 we think AI is such an up-leveler.
0:29:23 We think it deserves to be in a category of its own.
0:29:26 – You recently raised $65 million
0:29:29 in a round led by Kleiner Perkins.
0:29:32 It valued you at half a billion dollars.
0:29:35 Congratulations.
0:29:37 What is that money going to be used for?
0:29:39 – I think the way we would like to think about it is
0:29:41 we have ways of spending cash,
0:29:42 not only to train models,
0:29:44 but to also make it so that we can build
0:29:46 a better user experience for the end user.
0:29:48 But one of the cool things for us is our product
0:29:50 has such high ROI that we think that there will be
0:29:52 a real payback period on that.
0:29:55 Enterprises and companies will see enough value there
0:29:57 that they will be able to eat the cost
0:29:58 that we will need to spend upfront.
0:29:59 But also on top of that,
0:30:01 we want to spend a lot on making sure
0:30:03 that we can become better partners for our customers.
0:30:05 We’re onboarding some of the world’s largest companies
0:30:08 and we’re onboarding tens of thousands of developers.
0:30:09 That’s going to take a little bit of effort
0:30:11 to make sure that we do that properly.
0:30:13 One company that we’re working with right now
0:30:15 that we have a multi-year engagement with,
0:30:18 they account for 0.15% of all developers in the world,
0:30:20 it’s just that one company, right?
0:30:23 So, I’m a little bit of a different type of founder
0:30:24 in that I do not like the idea
0:30:26 of spending money unnecessarily,
0:30:28 but if it comes down to we are doing it
0:30:29 because we make our customers more successful
0:30:32 and our users more happy, we’ll do it any day.
0:30:35 – How have you guys restrained yourselves
0:30:36 in terms of spending?
0:30:40 Because I mean, yeah, the story, the narrative in AI
0:30:42 has been that it is an arms race.
0:30:45 And the thing that I hear about in the venture industry,
0:30:47 or at least what AI founders are being told,
0:30:50 is just go out and raise a shit ton of money
0:30:53 as much as is even possible.
0:30:56 One, because you just want to develop a war chest.
0:31:00 And two, you want to get the headlines.
0:31:02 You want to be the AI company that’s working
0:31:05 on co-generation, the AI company for finance,
0:31:06 whatever it is.
0:31:09 So I guess sort of two questions for me here.
0:31:12 One, is that accurate to your experience?
0:31:16 And two, how have you been so responsible
0:31:19 in terms of spending while you see all of these headlines
0:31:21 of other companies spending so much money
0:31:23 on talent and training their models?
0:31:26 – I think Varun mentioned earlier that we run very lean.
0:31:28 And the reason we’re able to do that
0:31:31 is we hire people that are generalists or ex-founders
0:31:33 and they’re capable of doing many job roles at once.
0:31:37 So our company size is probably like a little misleading.
0:31:39 It’s probably way more effective,
0:31:41 not just infrastructure, but the headcount also.
0:31:42 – What is the headcount?
0:31:44 – So right now we’ll be almost about 55
0:31:45 at the end of the month, I think.
0:31:47 And then the thing is like the people we hire
0:31:49 are able to just slot into different roles,
0:31:50 almost out of moments notice.
0:31:52 It’s like, oh, we don’t even have a marketing team,
0:31:53 for example.
0:31:55 The product’s growth has been organic,
0:31:57 but we do want to do some marketing experiments
0:31:59 to make sure that we are getting ourselves out there,
0:32:00 just as an example.
0:32:02 And then people, randomly someone will be like,
0:32:04 I have an idea, okay, go do it.
0:32:07 And then we all of a sudden have a Google ad strategy.
0:32:09 All of a sudden we have a bunch of blog posts.
0:32:12 We’re on podcasts like with you and Elson.
0:32:14 But I think that my point is,
0:32:16 part of the function of not spending the money
0:32:19 is just being very, I guess, practical
0:32:21 of where the money goes and running lean.
0:32:23 And I think when there is a moment that says like,
0:32:25 hey, we need to train a much bigger model
0:32:26 and we need to spend this much money,
0:32:28 we’re all for it, actually.
0:32:31 We actually are very conscious about what the ROI is
0:32:32 of everything we do.
0:32:35 – Yeah, how do you maintain that culture of leanness
0:32:38 and what would be your recommendation to other companies
0:32:41 that are maybe not as big as you, but trying to be?
0:32:44 – This is quite probably the hardest problem
0:32:46 that we’re trying to solve right now.
0:32:49 ‘Cause we wanna hire people that are very good,
0:32:52 very technical, maybe they’re generalists,
0:32:54 like I said earlier, but it’s very hard
0:32:55 to hire those people.
0:32:57 So actually, this is probably one of the things
0:32:59 we focus on in the next month
0:33:01 is what is our recruiting strategy?
0:33:03 How do we hire the best people?
0:33:05 Maybe part of that is getting Kodium’s brand name
0:33:06 much more aware.
0:33:09 Maybe it’s like a big push of user adoption.
0:33:11 Maybe we’re just gonna have to be scrappy
0:33:14 and be very creative of how we hire people.
0:33:15 For example, I don’t know if other companies
0:33:18 are just like pinging every ex-founder on LinkedIn,
0:33:19 but we are, right?
0:33:23 So we are trying to scale with creative means.
0:33:25 – One other thing is like as a company,
0:33:28 I think culture is, we have some cultural principles
0:33:30 and we run lean as one of them,
0:33:33 but who would wanna say you don’t run lean?
0:33:36 So I think, how do you actually live that out?
0:33:38 We are a five days a week in-person company,
0:33:40 so we don’t do remote work.
0:33:42 We don’t really do hybrid work either.
0:33:45 So people see what it’s like to work at the company
0:33:49 and until very recently, our CTO was ordering snacks.
0:33:51 And that’s not to say that’s a great use of his time.
0:33:53 It’s more just that no one is high enough
0:33:56 to not do some work to test a hypothesis.
0:33:58 And we don’t hire specialists at the company
0:34:01 until generalists outgrow that role.
0:34:03 And I’ll give you another example of this.
0:34:06 When we ran that GPU virtualization company,
0:34:07 even though we were making money,
0:34:09 we never hired a sales rep.
0:34:11 And that’s not because I don’t believe in enterprise selling.
0:34:13 No, we have a great VP of sales now at the company
0:34:15 and I think we might have in terms of talent density,
0:34:18 one of the strongest enterprise sales teams in the world,
0:34:20 actually, but why didn’t we hire someone?
0:34:23 I just didn’t believe that if we added one new person,
0:34:25 I would be setting them up for success
0:34:28 because the reality is if I could not get $1 of additional
0:34:33 sales, I cannot expect someone else to get $10.
0:34:35 So this is one of those things where we have a mentality
0:34:38 of we try to do it ourselves and then we try to eliminate
0:34:39 ourselves from the role.
0:34:41 We give away our Legos.
0:34:43 We let someone else take that over that understands
0:34:46 the role much more, but we don’t do things prematurely.
0:34:50 And I think there’s a tendency across people that the idea
0:34:52 of building a scalable organization is really valuable.
0:34:54 And I do see that that you do want to build
0:34:57 a scalable organization, but sometimes people get too excited
0:35:00 about this notion of org building or fundraising rather
0:35:03 than the idea of having customers, having users.
0:35:05 Because ultimately, people that join our company
0:35:07 don’t care about how much money we raised,
0:35:09 as long as we will survive.
0:35:11 And our customers genuinely don’t care.
0:35:12 Let’s look at it this way, right?
0:35:14 If you look at a company as big as JPMC
0:35:16 that makes hundreds of billions of dollars,
0:35:20 to them, does it make sense if we raised $100 or $200 million?
0:35:21 It all looks like peanuts to them.
0:35:23 It’s all like 10 basis points of the amount of revenue
0:35:25 that they make a year.
0:35:26 So to them, what they really care about
0:35:28 or companies of this size is,
0:35:30 are we the best partner for them?
0:35:32 Are we the best product to them?
0:35:34 And as long as we’re laser focused on that,
0:35:36 we should do whatever it takes to build that up.
0:35:39 We’ll be right back.
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0:37:22 – We’re back with first time founders.
0:37:24 Sort of a more personal question.
0:37:29 I mean, you started this company in 2021
0:37:31 sort of just as the AI hype was bubbling up
0:37:35 and you now find yourself at the epicenter
0:37:37 of the hardest industry
0:37:39 and you are one of the hardest companies
0:37:41 in the hardest industry.
0:37:43 Just a personal question for both of you.
0:37:44 How does that feel?
0:37:47 Like what has it been like getting used to
0:37:50 being the guy in AI?
0:37:52 – I told this to the company.
0:37:56 I tell everyone just get ready to get destroyed.
0:37:59 Assume that something very bad is going to happen always.
0:38:02 And this is where us having gone through that pivot
0:38:03 is very critical.
0:38:05 Things are going very well for us as a company.
0:38:07 A lot of the reason why we haven’t spent a lot of money
0:38:09 is now we make money, which is a unique property
0:38:12 about a lot of companies apparently in this space
0:38:13 where most companies talk about vision
0:38:15 rather than actually building a product that people use.
0:38:18 But I just, I tell everyone get ready
0:38:20 for something really bad to happen.
0:38:22 And this is why it’s like very important
0:38:26 that we hire people that are truly in it for the long run.
0:38:28 And I tell people this when they joined the company,
0:38:30 I think we could be a company
0:38:32 that’s worth over a hundred billion dollars.
0:38:33 I think we can.
0:38:35 And that’s largely because the total adjustable market
0:38:37 of what we’re building
0:38:38 and the amount of impact that this can have
0:38:41 given how important technology is could be massive.
0:38:44 But also a series of bad decisions that we make
0:38:46 could completely kill the company.
0:38:48 And that will happen very fast.
0:38:49 And I think this is where us building
0:38:51 a very truth seeking company.
0:38:53 And that actually is very hard
0:38:55 because people want to believe
0:38:56 that what they’re doing is correct.
0:38:59 And they want to embrace psychological safety.
0:39:01 And what I tell people is, hey,
0:39:04 if you feel something is wrong,
0:39:07 lean into what you think is wrong and tell everyone.
0:39:10 Tell everyone, because we should not have pockets of people
0:39:12 that want to report up the chain
0:39:14 and tell their manager or tell me,
0:39:16 we have a very flat company or tell me,
0:39:17 things are going fine.
0:39:19 I would much rather hear everything is on fire
0:39:21 and have paranoid people at the company
0:39:23 than people who are just happily going to work.
0:39:25 And this is why I think startups
0:39:27 are so much harder than big companies.
0:39:29 It’s actually not that, you know,
0:39:31 you’re taking a massive risk on the monetary side.
0:39:34 You still can make a six figure salary, right?
0:39:36 These are not people that are living hand to mouth.
0:39:40 But the really hard part is the lack of psychological safety.
0:39:42 We make a bunch of people at the company
0:39:43 make a series of bad decisions
0:39:46 and the entire thing can go to zero.
0:39:48 Whereas if you’re at Google,
0:39:49 you have very little accountability.
0:39:51 If your team doesn’t perform well,
0:39:55 Google makes so much money that you are a rounding error.
0:39:57 You will be shuffled to some other part of the company.
0:39:59 You never really need to deal with the impact
0:40:02 of your decisions and consequences of your decisions.
0:40:04 And that’s why it’s always a little bit of a funny statement
0:40:06 when someone at a big company is like,
0:40:08 I work at a startup at a big company.
0:40:10 No, no you don’t.
0:40:14 Imagine the idea of you potentially losing your job
0:40:16 every quarter or every month.
0:40:17 Exactly.
0:40:19 One thing that the way I think about it
0:40:21 is radical transparency.
0:40:23 And we have a lot of conversations within our company
0:40:26 of let’s be super transparent about everything.
0:40:28 And even in my personal life,
0:40:30 I’m like, I’m just gonna be like totally upfront.
0:40:35 That’s the cleanest, most kind of hygienic way to operate.
0:40:41 Do you ever feel that there could be too much truth?
0:40:44 Do you feel that there’s a possibility
0:40:46 that if you’re encouraging everyone
0:40:48 to tell the truth, tell the truth, be transparent,
0:40:52 tell me everything, that they’ll kind of go overboard?
0:40:54 I think this is the hardest part about a startup.
0:40:57 The two things that I say is a startup is really hard
0:41:00 because you need to be both irrationally optimistic.
0:41:02 Because if you’re not optimistic,
0:41:04 the answer is always Microsoft is gonna beat you, right?
0:41:04 Right.
0:41:06 It’s the biggest company of all time.
0:41:07 They have the most capital.
0:41:08 They have the most people.
0:41:09 They have the most distribution.
0:41:10 Why does any company win?
0:41:11 But clearly that’s wrong, right?
0:41:12 There are companies that have beat Microsoft
0:41:13 at different areas.
0:41:14 We always say this,
0:41:16 oh, they have the most capital they’re gonna win.
0:41:18 Yes, yes, it’s very easy from my perspective to say that.
0:41:19 Exactly, right?
0:41:22 And then HBS, I try to think about what Harvard Business
0:41:25 School would say 10 years from now for us as a company.
0:41:28 And I tell people this, it’s like, we fail.
0:41:31 And what they write is in a world
0:41:34 in which technology was changing,
0:41:36 Microsoft had all the distribution in the world.
0:41:38 They had this property called GitHub.
0:41:40 It was inevitable that they would win.
0:41:41 And because of that, they won.
0:41:42 They won the entire space.
0:41:45 And all of these startups, it was a fool’s errand.
0:41:46 Why did they even try?
0:41:48 And then the world in which we win,
0:41:50 they were going to write in a world
0:41:54 in which the technology was getting disrupted so materially.
0:41:56 There were a set of companies,
0:41:57 and one of which was Codium,
0:42:00 that had such a technological advantage
0:42:02 that there was no way a slow-moving gorilla
0:42:03 like Microsoft could even compete.
0:42:05 So what I think is very hard–
0:42:06 – Very hard, yeah.
0:42:07 – Yeah, exactly.
0:42:08 They will write whatever the future looks like
0:42:10 and the history will be written by the victor.
0:42:12 And no one will know exactly
0:42:14 what the pages of the book look like.
0:42:18 And I think the hardest part about a startup is,
0:42:19 you do need to be irrationally optimistic
0:42:21 to believe that you can win.
0:42:24 Because by default, if you don’t, you will definitely lose.
0:42:26 But then also uncompromisingly realistic,
0:42:29 which is that sometimes, actually,
0:42:33 there’s no point continuing in a particular direction.
0:42:36 This is where I think it comes down to what you just said,
0:42:38 which is that if you were too truth-seeking
0:42:41 and everyone is paranoid all the time,
0:42:43 it could lead to paralysis.
0:42:45 And I think there’s a fine line there.
0:42:48 There’s a fine line where one time we lost a deal,
0:42:49 and we actually, every day for dinner,
0:42:52 talked about it for two weeks in a row for multiple hours.
0:42:54 We talked about the implications as a company.
0:42:55 And that was very useful.
0:42:58 But if we extended that out to an entire year,
0:43:00 we would not go anywhere.
0:43:01 – Yeah.
0:43:02 – So you’re totally right.
0:43:03 There’s a level here.
0:43:05 But what I do feel most companies do
0:43:08 is probably err on the side of not being truth-seeking enough.
0:43:11 They become too complacent with what they’re doing.
0:43:14 And I think the thing to really think about,
0:43:15 and this is not true at a big company,
0:43:17 which is why you really need to think about it
0:43:19 at a startup is you do not win an award
0:43:21 for doing the wrong thing for longer.
0:43:24 So the sooner you can rip the band-aid off,
0:43:25 the better your company will be.
0:43:27 You will be way happier that you did it.
0:43:30 It is going to be incredibly painful for a week,
0:43:31 but just do it.
0:43:32 – I love that.
0:43:34 You guys have been generous with your time,
0:43:36 so we’ll begin to wrap up here.
0:43:39 Jeff, I’ll ask you this question.
0:43:41 What do you think has been the greatest challenge
0:43:44 that this company has faced in the past couple of years?
0:43:48 – I think the pace at which things switch
0:43:50 is really challenging.
0:43:53 We relied on some technology features
0:43:54 to be the selling point.
0:43:56 And then our competitors would come out
0:43:58 and it’s like the same thing all of a sudden.
0:44:01 And every time that there’s a news release
0:44:02 for one of our competitors,
0:44:04 we immediately go into like a code red
0:44:06 and go into a competence room.
0:44:08 Reverse engineer what they’re doing.
0:44:09 And this is constant.
0:44:12 This is like every month this is happening.
0:44:13 The question is like, will this last forever?
0:44:16 Like will we just always be panicking?
0:44:18 And the question that answers probably yes, right?
0:44:21 – I think for people listening to this podcast,
0:44:26 you too are the closest thing to AI experts as we’ve had.
0:44:30 You’re kind of on the front lines of this.
0:44:33 What would be your advice to anyone
0:44:35 who is working in the AI industry
0:44:37 or who wants to work in the AI industry?
0:44:39 And I think that doesn’t just have to be founders
0:44:43 but engineers, product managers,
0:44:44 business operators, et cetera.
0:44:46 What’s the most important thing
0:44:49 that they should understand about AI right now?
0:44:51 – There’s an interesting property about AI right now
0:44:54 in that it is actually imperfect.
0:44:56 You know, when you use the products,
0:44:58 sometimes says the wrong thing.
0:45:00 And despite that, it is actually very useful
0:45:01 in some domains.
0:45:03 That’s not like anything in the past.
0:45:05 When you used the internet
0:45:08 and you ordered something off Amazon in 2002,
0:45:10 it’s not like they would ship you something incorrectly
0:45:12 or maybe they would do that, but that’s not,
0:45:13 there was no expectation going in.
0:45:16 You would buy one book and you would get a different one.
0:45:18 And somehow that is still fine right now,
0:45:20 which is a cool part of the technology,
0:45:22 which is that it actually gets perfect.
0:45:24 It’s going to usher in a brand new set
0:45:26 of applications as well.
0:45:29 But I think the key thing to really think about
0:45:31 is not to think about, go back from a demo
0:45:33 and try to build that today.
0:45:36 So think about what products can you build today
0:45:38 that are actually imperfect,
0:45:41 but still can generate a lot of value.
0:45:43 And that is a lot harder than you would think
0:45:46 because in a lot of domains, if you are imperfect,
0:45:49 like let’s say you’re reviewing a legal document
0:45:51 and it actually completely reviews the document,
0:45:53 but 10% of the time it’s wrong.
0:45:55 You can’t give that to an end customer.
0:45:58 So actually thinking about the trade-offs of
0:46:02 how good does the quality need to be to ship your product?
0:46:04 How fast does the experience need to be?
0:46:06 In a world in which the quality is not perfect,
0:46:07 it better be fast.
0:46:09 There’s no world in which I’m going to wait 24 hours
0:46:12 for something, and the quality is imperfect, right?
0:46:16 And then if the quality is imperfect and it is fast,
0:46:18 how quickly can I correct it?
0:46:20 And these are all important factors of a product.
0:46:22 If you don’t hit the sweet spot here,
0:46:24 you will have a product that’s a cool demo,
0:46:26 but no one will ever use it.
0:46:28 I think this is the most important thing
0:46:29 to really think about.
0:46:32 Adding AI to just any field that exists
0:46:34 doesn’t just suddenly make the product usable.
0:46:37 It needs to be a product that is useful in its own right.
0:46:40 – I think if you give away a product for free
0:46:42 and everybody keeps using it
0:46:45 and a lot of people keep trying to get it,
0:46:47 then you know there’s something of value
0:46:48 and there’s product market fit.
0:46:50 And I think if you look at a lot of these AI tools
0:46:52 and AI demos, maybe they’re not realizing that.
0:46:53 Maybe they’re just building something
0:46:56 that is a cool demo or it’s like a really,
0:46:58 it pushes the limits of the technology,
0:46:59 but it’s not actually building something
0:47:02 that people want or will find value from.
0:47:03 I think that’s maybe our biggest message
0:47:05 to other founders or other people
0:47:06 that are building products in the area.
0:47:08 It’s just think like if I gave this away for free,
0:47:11 is everybody gonna wanna use it and keep using it?
0:47:13 I think that’s maybe something people miss.
0:47:15 – Do you think maybe that’s the model that,
0:47:17 I mean, I was gonna say software founders,
0:47:19 but maybe all founders that you should just start
0:47:22 with giving the product out for free
0:47:24 and see where things take you from there.
0:47:26 – It worked really well for chat GBT, right?
0:47:27 – Yeah, yeah, exactly.
0:47:28 – And it worked well for you, yeah.
0:47:30 – That’s actually an interesting principle
0:47:31 that Jeff just said.
0:47:33 Obviously, in some scenarios,
0:47:35 the reason why chat GBT could do that and open it,
0:47:37 it could do that is they own the infrastructure.
0:47:38 And if another company did that,
0:47:39 they would have gone bankrupt.
0:47:43 So you do need advantages in particular places
0:47:44 to be able to do that, but at the very least,
0:47:47 if you did burn money and you gave it away for free,
0:47:49 if no one runs to use the product,
0:47:51 you’re probably in a world of trouble.
0:47:55 – That’s a great place to end.
0:47:57 Varun Mohan is the founder and CEO of Codium.
0:48:00 Jeff Wang is the company’s head of business.
0:48:01 Guys, thank you for joining us.
0:48:02 That was awesome.
0:48:03 – Yeah, thanks for having us.
0:48:04 – Thanks for having us.
0:48:09 – Our producer is Claire Miller,
0:48:11 our associate producer is Allison Weiss,
0:48:13 and our engineer is Benjamin Spencer.
0:48:15 Jason Stavis and Catherine Dillon
0:48:17 are our executive producers.
0:48:18 Thank you for listening to First Time Founders
0:48:20 from the Vox Media Podcast Network.
0:48:22 Tune in tomorrow for ProfG Markets.
0:48:25 (upbeat music)
0:48:50 – Support for the show comes from Into the Mix,
0:48:53 a Ben and Jerry’s podcast about joy and justice
0:48:55 produced with Vox Creative.
0:48:57 Into the Mix is back for a new season
0:48:59 and welcomes you in with four new stories
0:49:02 that take listeners beyond the headlines
0:49:04 and into the lives of ordinary people
0:49:07 fighting for justice in their communities.
0:49:09 Starting with Ainez Bordeaux,
0:49:10 an activist and St. Louis native
0:49:13 who fought to shut down the workhouse,
0:49:15 a notorious pretrial detention center
0:49:18 that she says functioned like a debtor’s prison.
0:49:21 Subscribe to Into the Mix, a Ben and Jerry’s podcast
0:49:23 to listen to the first episode
0:49:25 of this special three-part series out now.
0:49:35 [BLANK_AUDIO]

0:00:01 (upbeat music)
0:00:04 Support for the show comes from Into the Mix,
0:00:07 a Ben and Jerry’s podcast about joy and justice
0:00:09 produced with Vox Creative.
0:00:12 Ainez Bordeaux is a self-described hellraiser,
0:00:14 and she became an activist
0:00:16 after being caught up in the criminal legal system
0:00:19 when she couldn’t afford her bond.
0:00:20 And without a trial,
0:00:23 Ainez was sent to a St. Louis detention facility
0:00:25 known as the Workhouse,
0:00:28 notorious for its poor living conditions.
0:00:31 Here how she and other advocates fought to shut it down
0:00:33 and won on the first episode
0:00:36 of this special three-part series out now.
0:00:39 Subscribe to Into the Mix, a Ben and Jerry’s podcast.
0:00:42 – It’s almost time.
0:00:45 Verizon Small Business Days are coming
0:00:47 from August 5th to the 11th.
0:00:50 Small and mid-sized businesses can get a tech check
0:00:53 and advice on how to get the most out of Verizon Business
0:00:55 with guidance on the best solutions
0:00:57 for your specific needs.
0:00:59 Meet with their experts, get one-on-one advice,
0:01:02 three tech checks, and other special offers.
0:01:06 Give your business the VIP treatment it deserves.
0:01:10 Call 1-800-483-4428,
0:01:13 or go to Verizon.com/smallbusiness.
0:01:17 That’s 1-800-483-4428,
0:01:21 or go to Verizon.com/smallbusiness.
0:01:23 – Episode 310.
0:01:26 Three-1-0-0 could belong in Los Angeles County in 1910,
0:01:28 the first public radio broadcast was conducted
0:01:30 from the Metropolitan Opera House in New York City.
0:01:33 Having sex with me is like the opera.
0:01:35 No one has any idea what the fuck is going on
0:01:39 and at the end, there’s a fat guy sweating and yelling.
0:01:44 ♪ Go, go, go ♪
0:01:46 (upbeat music)
0:01:54 Welcome to the 310th episode of the Prop G pod.
0:01:57 By the way, our first joke, actually in 1910,
0:01:59 the Boy Scouts of America was established.
0:02:00 That’s just too easy.
0:02:04 There’s just too many jokes about Scout leader Patrick,
0:02:07 and the bottom line is I was a Boy Scout,
0:02:09 and it was one of the nicest experiences I had as a kid.
0:02:12 The Boy Scouts is taking an immense amount of shit.
0:02:13 It is a wonderful organization,
0:02:15 or I should say it was a wonderful organization for me.
0:02:17 I was raised by a single mother,
0:02:19 and every Wednesday night, she would drop me off
0:02:22 at, I think, it was a junior high school in Culver City.
0:02:23 I was 42.
0:02:24 I was a wee below.
0:02:27 I was a Boy Scout, and then there’s a transition period.
0:02:29 It’s like puberty scouts where you’re a wee below
0:02:30 and you wear a different scarf.
0:02:33 And true story, I used to wear my Boy Scout uniform
0:02:34 to school, including in junior high,
0:02:37 which was just such a big hit
0:02:39 with the ladies and the cool crowd.
0:02:42 It really sort of established my social currency
0:02:44 showing up in my Boy Scout uniform,
0:02:46 but they were really good people.
0:02:48 The crew, if you will, everyone needs to find their crew.
0:02:51 And Boy Scouts for me was a group of kids
0:02:55 who maybe weren’t the coolest, so to speak.
0:02:56 Maybe weren’t the most social.
0:02:58 Maybe weren’t the most athletic,
0:03:00 but wanted to find their own crew.
0:03:03 We used to go camping once a month outside of LA County.
0:03:07 I gave them an appreciation for nature, leadership.
0:03:10 The Scout leaders there were incredibly generous
0:03:11 and thoughtful and nice.
0:03:15 And we used to have to do things like plan out your backpack.
0:03:16 And I used to do that with my mom.
0:03:20 And then at the end of the weekend of camping,
0:03:22 we would go through, we’d make these lines
0:03:25 and make sure that there was absolutely no sign of us
0:03:27 that we had been at that campsite.
0:03:30 And we used to study for and take tests for our mare bed.
0:03:31 It’s fire safety and not tying.
0:03:35 By the way, both those things have come in real handy for me.
0:03:37 I had a joke lined up, as you can imagine,
0:03:38 incredibly crude and inappropriate.
0:03:40 And then I thought about just how wonderful
0:03:41 the Boy Scouts were to me.
0:03:45 Anyways, so again, welcome to the 310th episode.
0:03:47 In today’s episode, we speak with Matthew Ball,
0:03:50 the CEO of Apilion, a startup advisor
0:03:53 and the former head of strategy for Amazon Studios.
0:03:54 Matthew has sort of, not sort of,
0:03:56 Matthew’s developed a following
0:03:59 just ’cause he’s got such a big fucking brain about tech.
0:04:01 And he speaks in sort of this,
0:04:04 almost like you’re asking chat GPT a question,
0:04:07 except it comes back not with an anodyne answer,
0:04:09 but with a really thoughtful nuanced answer.
0:04:11 He reminds me a little bit of Josh Wolf
0:04:13 ’cause Josh Wolf has one of those brains
0:04:16 that’s just like, I’m on a 286 Intel
0:04:19 and he’s on a Pentium or a GPU.
0:04:20 And they have different styles,
0:04:22 but they’re both these incredibly bright people
0:04:24 who have this incredible range around technology.
0:04:27 Anyways, I had not heard of Matthew
0:04:28 and then I interviewed him
0:04:29 and I immediately went on YouTube and found out
0:04:31 this is gonna be a resource for me
0:04:33 around any question I have around technology.
0:04:37 Okay, before we get to that, let’s bring all of this back
0:04:39 to our favorite subject, me.
0:04:41 I am an Aspen and I absolutely love it here.
0:04:42 I used to come here in the winter,
0:04:44 now we only come in the summers.
0:04:46 My strategy is the following.
0:04:49 I’m pretty much taking not all, but most of my money
0:04:52 and I’m buying these beautiful places around the world
0:04:55 where I hope my sons will just find irresistible
0:04:57 and they’ll come spend a lot of time with me.
0:05:00 In addition, I’m going after a 0.1% strategy.
0:05:01 I think it’s terrible and I’ll fight it,
0:05:03 but I think it’s going to happen.
0:05:05 I think income inequality is only gonna get worse
0:05:06 around the world.
0:05:08 And what’s interesting about people I find it interesting
0:05:10 is that the poor and the middle class
0:05:12 are much more interesting in the sense
0:05:13 that they’re much more heterogeneous.
0:05:15 If you look at their apparel they wear,
0:05:18 if you look at their culture, their food,
0:05:19 it’s pretty local.
0:05:24 So the middle class and Laurentian people in France
0:05:29 dress French, eat French food, vacation in French places.
0:05:32 The very wealthy or the wealthy are incredibly homogenous.
0:05:34 They all party in St. Barthes, they all wear Hermès
0:05:37 and they all send their kids to American universities.
0:05:40 There’s definitely sort of an elite lifestyle
0:05:41 that has been globalized
0:05:43 and there’s two real global consumers.
0:05:47 There’s the wealthy person who buys the same products
0:05:50 and has the same experiences and then there’s teenagers.
0:05:51 That’s also a global cohort.
0:05:56 They listen to Taylor Swift and where Nike,
0:06:00 actually they’re wearing Adidas or Adidas recently
0:06:04 or Hoka or on, Nike’s really shit the bed lately.
0:06:05 But those are the two cohorts
0:06:09 that have emerged globally until about 20 years ago.
0:06:13 Another cohort emerged globally and that is the tech buyer.
0:06:15 That is the MIS or the head of operations
0:06:17 typically are the same person who went to the same schools
0:06:18 and buy the same products.
0:06:20 So what do we have here?
0:06:22 We have the emergence of global brands
0:06:24 that typically are in one of three categories,
0:06:29 technology, Microsoft and NVIDIA are global brands.
0:06:32 Brands that target teens, see above Adidas
0:06:33 or even the North face.
0:06:36 And then brands that target the very wealthy,
0:06:39 almond hotels or Chanel.
0:06:41 Anyways, fascinating, total right turn
0:06:43 from what the script is here.
0:06:45 And my producer is just sort of sitting there
0:06:47 shaking your head like, what the fuck is he doing now?
0:06:50 Anyways, I also saw last weekend,
0:06:52 and I’m super excited about this,
0:06:54 got tickets, took my kids and their friends
0:06:57 to see Deadpool and Wolverine.
0:06:59 I think it’s called Deadpool and Wolverine anyways.
0:07:02 And it amassed $205 million in domestic ticket sales
0:07:03 during its opening weekend.
0:07:06 The most money this year and a historic record
0:07:08 for an R rated film.
0:07:09 Wow, didn’t know that.
0:07:10 I loved it by the way.
0:07:12 I absolutely loved the one-liners.
0:07:14 I think Ryan Reynolds is incredibly talented.
0:07:16 Actually, so is Hugh Jackman.
0:07:17 They’re both crazy fucking talented.
0:07:21 Hugh Jackman can sing like no one’s business.
0:07:23 What was that movie, “The Great Entertainer”
0:07:26 where he played Barnum or Bailey or whatever it was
0:07:27 and then died, was in that movie?
0:07:29 God, “Watchings and Dies.”
0:07:30 Zach Braff, who knew Zach Braff could sing?
0:07:31 Did you know that?
0:07:34 I did not know that Zach Braff could sing.
0:07:35 That was an outstanding movie.
0:07:37 I think musicals are especially impressive.
0:07:39 That’s gotta be really hard to pull off.
0:07:41 Anyways, absolutely loved “Deadpool.”
0:07:42 But I’m struck a little bit.
0:07:45 One, Hollywood will pretend that the movie’s business
0:07:46 is back, it’s not.
0:07:49 It’s still off 20% from its pre-pandemic levels.
0:07:52 And I think the majority of the interesting content now
0:07:54 is on the medium or the small screen,
0:07:56 specifically your television or your phone.
0:07:57 Why is that?
0:08:00 Because the type of money that’s required
0:08:03 to make a feature motion picture is so extraordinary now
0:08:06 that everybody just goes to these 10-pull franchises.
0:08:07 I mean, I think this is the third
0:08:09 or the fourth “Deadpool” movie.
0:08:11 And there’s not as much what I call
0:08:13 license for creative content.
0:08:15 And I even think about, what other franchises
0:08:17 that have been launched in the last few years
0:08:19 that’ll get three or four sequels might be frozen?
0:08:20 I don’t know, there’s probably something else.
0:08:24 But my son at camp just went and saw Minions 4
0:08:25 or Minions 5.
0:08:28 I mean, there just isn’t, there isn’t a ton
0:08:30 of originality, whereas when I tune in,
0:08:31 I’m about to watch “Presumed Innocent.”
0:08:33 Everyone says, “That’s totally binge-worthy.”
0:08:36 But I do think you’re gonna continue to see
0:08:39 a leaking of influence and return on investment.
0:08:40 And one of my pieces of advice,
0:08:43 reductive generalizations in terms of advising young people
0:08:46 and on a career media is the return on your invested capital
0:08:48 is gonna be inversely correlated
0:08:49 to the size of the screen.
0:08:51 And if you wanna be on the screen,
0:08:52 everyone’s like, “Well, I’ll start doing
0:08:55 cute little videos, but then hopefully I’ll get a TV show.
0:08:57 And then who knows, I’ll hit the big time
0:08:58 with a big, and be on the big screen
0:09:01 so I can see my face really, really fucking big.”
0:09:04 So there’s a certain prestige or vanity aspect
0:09:07 or a psycho, if you will, or a psychic return.
0:09:09 What is really interesting or I find interesting
0:09:13 is I get 20 to 30 emails a day asking for advice.
0:09:15 And it’s wonderful that people would reach out to me.
0:09:17 It’s also a little bit frustrating
0:09:19 ’cause I think that this is a really thoughtful email
0:09:20 from someone who’s very sincere
0:09:21 and I can never get to all of them.
0:09:23 By the way, if you’re out there, I apologize.
0:09:25 I just can’t get to all of them.
0:09:27 But I’m increasingly over the last two years
0:09:28 getting a lot of emails from people
0:09:31 in the media industry asking what do they do next?
0:09:34 That they say I’ve been very critical of the rider’s strike.
0:09:37 I thought that was literally like the head up your ass
0:09:38 shit for brains.
0:09:42 I don’t understand strategy negotiation of the ages.
0:09:44 And I’ve said all along that this industry
0:09:45 attracts way too much human capital.
0:09:47 There’s 180,000 people in Sagaftra.
0:09:49 There should probably be 10,000.
0:09:52 And as evidence of that, 83% of them didn’t qualify
0:09:53 for health insurance last year
0:09:55 ’cause they made less than $23,000.
0:09:56 I wanna crush your dreams.
0:09:59 If you wanna go into a vanity industry, fine.
0:10:01 You wanna go into modeling, fashion, sports.
0:10:03 You want your own jewelry design level.
0:10:04 You wanna be a fashion designer.
0:10:05 I mean, seriously, you know
0:10:08 if you’re trying to go into a vanity industry, that’s fine.
0:10:12 But you have to set up guideposts for yourself or metrics
0:10:15 that if you’re not in the top 10% pretty quickly,
0:10:18 you should get out the quote unquote top 10%.
0:10:20 If you’re in the 90th percentile of actors,
0:10:22 that means you’re an Uber driver.
0:10:24 If you’re in the 99th percentile,
0:10:26 that means you make a living, not even a great living.
0:10:29 I know some actors who you would all know.
0:10:31 You think, wow, they’ve been in series.
0:10:33 They make a good living, not a great living.
0:10:35 Unless you’re in the 0.1%,
0:10:37 it is a very difficult way to make a living.
0:10:40 Whereas most industries and non-romance industries,
0:10:42 just being the top half and you can make a decent living.
0:10:45 And if you’re in the top 10% much less the top 1%,
0:10:47 boy, oh boy, are you going to kill it?
0:10:50 But anyways, back to Deadpool and Wolverine.
0:10:52 What else is popping off the screen?
0:10:53 What are we watching?
0:10:55 The Olympics, who would have thunk it?
0:10:57 I didn’t even know the Olympics were on.
0:10:59 And my feeds on my platforms
0:11:03 are all these amazing people doing amazing things.
0:11:04 By the way, by the way,
0:11:06 speaking of opening ceremonies at the Olympics,
0:11:09 I love Celine Dion.
0:11:12 I did not know this.
0:11:12 I did not know this.
0:11:15 I see her visage or image and I think,
0:11:19 oh God, lame Canadian, lame Canadian coming my way.
0:11:21 And then when they’re about 15 seconds, I’m thinking,
0:11:22 wow, she’s pretty good.
0:11:25 And then within 30 seconds, I’m fucking crying.
0:11:27 (upbeat music)
0:11:30 Wow, is she talented?
0:11:35 And by the way, France, Parisians, oh my gosh.
0:11:38 Generally speaking, a group of very disagreeable people.
0:11:40 I used to go to France a lot for business.
0:11:42 My company L2 focused on luxury brands.
0:11:44 The home of luxury is France.
0:11:44 I used to go to Paris.
0:11:47 No joke, have a series of meetings with everyone
0:11:50 from LVMH to Chanel to Clarence.
0:11:53 Just a ton of brands, right?
0:11:56 Dior, Chloe, we would spend a week and have jam-pack.
0:11:58 And almost every meeting I’d come out of,
0:12:00 I think, Jesus Christ, that was a shitty meeting.
0:12:03 Basically, French people who would cross their arms,
0:12:05 we would say something and they would argue with us
0:12:06 and then speak to each other in French
0:12:07 and there’s disdainful tones.
0:12:09 Like, who is this stupid fucking American?
0:12:11 And we’d be on the way to the airport.
0:12:12 And I would say to my colleague,
0:12:14 I always went with the same people,
0:12:17 usually who were covering Europe without reason or luxury.
0:12:19 I’m like, God, that was just the worst meeting I’ve ever had.
0:12:20 And then I’m not exaggerating,
0:12:22 we’d get a call from the client saying,
0:12:24 that was amazing, we wanna see you again.
0:12:26 They just have a different mentality.
0:12:28 Also, people will say that Parisians
0:12:29 are different than the French,
0:12:32 but I have come to appreciate one thing
0:12:34 or more than one thing about France.
0:12:36 There is something in the DNA of the French,
0:12:37 there’s something in the water
0:12:40 where they have an easier time
0:12:42 crafting the most beautiful things in the world.
0:12:44 If you just look at the panache, the style,
0:12:47 the touch points of the Olympics and the opening ceremonies,
0:12:49 I think, wow, I wish I was there.
0:12:50 I actually got invited to the Olympics
0:12:52 and I said to my kids, do you wanna go to the Olympics?
0:12:54 ‘Cause I thought, gotta take your kids to the Olympics
0:12:55 at least once.
0:12:57 And they said, no, we have no interest.
0:12:58 And it struck me that the World Cup
0:13:00 has become so dominant the last four years
0:13:03 and slowly but surely the Olympics
0:13:05 have actually decreased in popularity.
0:13:07 Although from a business standpoint,
0:13:09 it seems to be enjoying a little bit of a bump.
0:13:12 An April MBCU had already sold more than 1.2 billion
0:13:14 in advertising for this year’s games.
0:13:16 That’s a record for Olympic ad spending.
0:13:18 A lot of this should be adjusted for inflation
0:13:20 ’cause I think a lot of these numbers are a little bit,
0:13:21 I don’t know exactly.
0:13:23 A lot of this doesn’t feel Apple’s Apple’s.
0:13:24 And it was back to the Olympics.
0:13:25 The other thing that’s really struck me about the Olympics
0:13:28 is you can get is the difference between streaming
0:13:31 and broadcast or linear.
0:13:34 Watching the Olympics I find on MBC
0:13:36 is actually a quite frustrating experience
0:13:38 because they say, and now we’re headed to three meter diving.
0:13:41 You’re like, well, I’m not sure I’m into three meter diving.
0:13:43 Whereas if you watch it on Peacock,
0:13:45 you can actually sign up and pick a sport.
0:13:47 So if you just really wanna see surfing all day long,
0:13:48 you can watch it.
0:13:50 Speaking of streaming, it is beginning
0:13:53 to kind of consolidate, if you will.
0:13:55 So there’s this great chart from Antenna
0:13:58 looking at committed versus curious.
0:14:00 And that is people who are just trying it
0:14:02 versus the people who are committed customers.
0:14:04 And it’s interesting, you would expect Netflix
0:14:07 to be at the top and their ratio is 2/3 to 1/3.
0:14:11 So 2/3 of people are committed, 1/3 are curious.
0:14:13 I think curious is a polite way of saying people
0:14:15 who might churn out, who sign up to download
0:14:17 all of Ted Lasso and then churn out.
0:14:18 Next, and this really shocked me,
0:14:22 was Hulu at a ratio of 35 to 65.
0:14:24 So if you wanna think about a market capitalization
0:14:27 or a dominant player, Netflix is two to one,
0:14:31 basically hardcore customers who are likely renew,
0:14:33 versus the next player, which is one to two,
0:14:35 which has got a dramatically impact margins
0:14:38 because Hulu has to reinvent its customer base
0:14:39 every goddamn 18 months.
0:14:44 Paramount Plus comes in about the same level at 36.64.
0:14:49 Disney is 40, 60, some more committed.
0:14:51 Peacock is at 35.
0:14:52 Max is at 28.
0:14:53 That really shocked me.
0:14:55 I always think of Max and specifically HBO
0:14:57 as having me able to tap into the zeitgeist.
0:15:01 And Apple TV Plus, who I think has spent 20 billion so far
0:15:03 on programming for Apple,
0:15:05 TV Plus for their effort here is 32.68.
0:15:07 I wonder if they kind of regret it.
0:15:11 I wonder if Apple TV Plus is not nearly the kind of,
0:15:15 I don’t know, train wreck that the mixed reality headset is.
0:15:16 But I wonder if they had to do it again
0:15:20 if they would spend $20 billion original scripted drama.
0:15:22 Anyways, the market continues to consolidate.
0:15:23 I am loving the Olympics,
0:15:26 but also what I found is I’m spending most of my time
0:15:28 watching it on TikTok.
0:15:30 But I love the idea of amateur athletes.
0:15:33 Things have happened since the Olympics
0:15:34 over the last 20 years or 30 years
0:15:37 and make me wonder if why it has not done as well.
0:15:39 Is it because professional athletes are involved?
0:15:40 I don’t know.
0:15:42 Is it because they’ve brought in things like,
0:15:43 I don’t know, mountain biking,
0:15:45 which I think is important to establish
0:15:49 a younger customer base, but it does lose the purity.
0:15:51 But more than anything in our editor-in-chief,
0:15:53 point of the south Jason Stavros,
0:15:55 I think the key to a luxury brand going back to France
0:15:57 and luxury brand is the following.
0:15:58 It’s scarcity.
0:16:01 It’s the illusion that you are part of a tribe
0:16:02 that says something about you.
0:16:03 It’s self-expressive benefit.
0:16:06 Actually, there are really two things that luxury offers.
0:16:07 Only two things.
0:16:09 The first is it makes you feel closer to God.
0:16:10 Why?
0:16:13 Because the majority of these very artisanal handcrafted
0:16:16 illusive products with a domain of religious institutions.
0:16:18 The religious elites figured out a way
0:16:19 that they needed to manipulate the masses
0:16:22 and make them feel like we are closer to God
0:16:24 and you need to do what we tell you to do
0:16:26 and also to provide them with comfort.
0:16:27 So what we’re gonna do is we’re gonna invite you
0:16:30 to these places of worship, these temples, these mosques,
0:16:32 these churches, these chapels,
0:16:33 and we’re gonna fill them
0:16:34 with the most beautiful things in the world.
0:16:38 We’re gonna engage the most incredible, sophisticated,
0:16:41 impressive artisans to build frescoes on the ceiling.
0:16:42 We’re gonna have incredible music.
0:16:45 We’re gonna have the most gorgeous pageantry
0:16:47 and candles and smells.
0:16:48 And you’re gonna get the sense
0:16:50 that there’s a decent chance of God hangs out here.
0:16:51 And we’ve been doing this for hundreds,
0:16:52 if not thousands of years.
0:16:55 And as a result, we associate fine things,
0:16:57 artisanal things with being closer to God.
0:17:00 And when you see the mesh on a boutique of a net-a-bag
0:17:01 or the slip on the back of a 9/11,
0:17:02 you feel closer to God.
0:17:03 It stills you.
0:17:06 It’s a very rewarding experience to be in the company
0:17:07 of this type of artisanship.
0:17:09 In addition, the second thing
0:17:11 is that it increases the likelihood
0:17:13 that you’re gonna procreate.
0:17:14 Why?
0:17:15 Because it says something about you.
0:17:17 Ergonomically impossible menolablonics
0:17:19 make your legs seem longer.
0:17:22 This makes you seem more elegant, more feminine.
0:17:25 Having a Panerai watch or a Porsche means your kids
0:17:27 or the kids that you or mate and you decide to have
0:17:29 are more likely to survive
0:17:30 than someone who is wearing a swatch watch
0:17:32 and driving a Hyundai.
0:17:35 So it’s the ultimate expressive, self-expressive benefit.
0:17:38 And by the way, this has been the best performing asset class
0:17:41 over the last 30 or 40 years, whether it’s modern art
0:17:42 or whether it’s a luxury business itself.
0:17:45 On a risk-adjusted basis, luxury has performed better
0:17:47 than even, yes, you guessed it, tech.
0:17:48 And it’s produced, I think,
0:17:50 the second or third most billionaires.
0:17:52 This is an unbelievable business.
0:17:54 And it has huge motes by virtue of the fact
0:17:55 that it has heritage.
0:17:58 You cannot recreate Chanel right now.
0:17:59 You just can’t.
0:18:01 You can’t have that story.
0:18:03 You can’t have that heritage.
0:18:06 And if you’re able to establish that illusion of scarcity
0:18:07 and artificially constrict supply,
0:18:10 I go into the Panerai store here in Aspen,
0:18:12 see above, Douchebag, Prilish Douchebag,
0:18:13 but they always say to me,
0:18:16 oh, that’s a limited run or we don’t have that one.
0:18:18 These are not difficult items to manufacture,
0:18:20 but they create the illusion of scarcity.
0:18:21 Who’s best at this?
0:18:22 Who’s best at this?
0:18:25 Hermes, who get this as double the market cap of Nike.
0:18:27 Jesus Christ, that blows my mind.
0:18:30 Anyways, the illusion of scarcity.
0:18:32 Also the learning here, personally,
0:18:35 there is the illusion of scarcity that you want to create.
0:18:37 You want to have boundaries.
0:18:40 In my brand, I absolutely say no to 95%.
0:18:43 Now granted, I’m in a position of privilege,
0:18:46 but creating a sense that you’re, I don’t know,
0:18:47 your brand or your person, if you will,
0:18:49 has a touch of exclusivity to it
0:18:52 once you’ve established some domain expertise
0:18:53 and some credibility.
0:18:56 I think it’s key to creating margin, if you will.
0:18:58 So it’s the same way with a services company.
0:18:59 Let me translate this to B2B.
0:19:00 What are you doing B2B?
0:19:02 In my opinion, what’s the best way to market?
0:19:04 You put out thought leadership.
0:19:05 They get some awareness.
0:19:07 With L2, we put out a ranking
0:19:09 and you create a reverse inquiry model, if you can.
0:19:12 That way it changes the entire tone of the conversation,
0:19:13 right?
0:19:15 And you try and create an illusion of scarcity
0:19:16 that you’re doing them a favor
0:19:17 by them signing up as membership.
0:19:20 The entire membership model and hospitality right now,
0:19:22 whether it’s Maison Estelle or Soho House
0:19:25 or Casa Chiprione, that entire thing has just exploded,
0:19:28 although I think it’s probably saturated at this point,
0:19:29 is all based on the illusion of scarcity.
0:19:31 Gee, can you recommend me?
0:19:34 So I can pay $7,000 a year to then go buy drinks
0:19:36 at what is essentially a nice restaurant.
0:19:38 This again is the master of illusion of scarcity.
0:19:41 This is what has become a branding.
0:19:44 The ultimate, ultimate rejectionist exclusionary
0:19:46 artisanal brand is U.S. higher education.
0:19:48 To a certain extent, the U.S. has become a luxury brand
0:19:50 because of our fucked up immigration policies.
0:19:51 But you get the point.
0:19:54 Scarcity, luxury brands equals margin.
0:19:55 And let’s bring it home.
0:19:57 Some wonderful moments from the Olympics.
0:19:58 Simone Viles, Jesus Christ.
0:20:00 That shit’s just inspiring.
0:20:02 She gets a lot of attention, so I’ll move on.
0:20:04 Two best friends from America,
0:20:06 I think they’re called Cookin’ and Bacon,
0:20:09 or best friends who’ve been going to the Olympics
0:20:12 three or four times or one just made her like fourth trial,
0:20:13 finally made the Olympics won a medal.
0:20:14 That was a nice moment.
0:20:16 The Philippines won its first gold medal.
0:20:18 And finally, finally, there was a gymnast from North Korea
0:20:19 who won a silver medal in the Olympics.
0:20:23 She didn’t win gold, but her execution was flawless.
0:20:24 Get it?
0:20:27 Anyways, go six rings, go Olympics.
0:20:32 We’ll be right back for our conversation with Matthew Ball.
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0:24:00 (upbeat music)
0:24:09 Welcome back, here’s our conversation with Matthew Ball,
0:24:12 the CEO of Opelion and author of the revised book,
0:24:16 The Metaverse, Building the Spatial Internet.
0:24:17 Matthew, where does this podcast find you?
0:24:19 – In Midtown Manhattan.
0:24:20 – So let’s bust right into it.
0:24:23 You’re one of the go-to experts on the metaverse,
0:24:26 a topic that we just haven’t paid much attention to
0:24:28 since some of the hype faded.
0:24:29 Can you give us a state of play?
0:24:32 Where does the metaverse and spatial computing stand today
0:24:34 in 2024?
0:24:36 – So overall, those in the industry talk
0:24:38 about these three different peaks for the theme.
0:24:41 The first happened in the late 80s, the early 90s,
0:24:43 that’s where you had really all of the terms
0:24:44 that we talk about today.
0:24:48 Spatial computing came onto the scene roughly ’91, ’92,
0:24:52 the metaverse in ’92, you had the advent of virtual reality,
0:24:56 artificial reality, certainly cyberspace, the matrix,
0:24:58 they all came out of that early period.
0:25:01 And that was sparked by the emergence
0:25:05 of graphical user interfaces of the internet at large,
0:25:08 of 3D computing, simulation and video games.
0:25:12 And they all attempted to capture these terms,
0:25:14 what the future might look like.
0:25:15 And we very quickly realized
0:25:17 that those technologies were premature.
0:25:21 15 years later, we had this second burst of activity.
0:25:24 Second life ends up on the cover of Time Magazine,
0:25:26 and there’s a belief that we’re going to see
0:25:28 the metaverse finally come to fruition.
0:25:30 And then the following two to three years
0:25:32 after that peak for second life,
0:25:35 you have the starting of nearly all of the modern efforts
0:25:38 to build wearable glasses and goggles,
0:25:41 magic leap, you have the Snapchat acquisition
0:25:43 of Virgins Labs, you have HoloLens,
0:25:45 you have Oculus VR.
0:25:49 And then we kind of encountered this 10 to 15 year stagnation
0:25:51 in the hardware side.
0:25:53 And then in 21 and 22, we had this other burst
0:25:56 where there was general consensus that finally,
0:25:59 the technologies had matured,
0:26:01 the internet infrastructure, computing technologies,
0:26:03 even some of the wearables that we imagined
0:26:05 we might one day wear,
0:26:08 that they had all matured to the point in which finally,
0:26:12 this 30 year old term, roughly 70 year old conquest
0:26:15 and 100 year old idea was ready for prime time.
0:26:18 And then it got hoisted onto the front page of the news
0:26:19 by Mark Zuckerberg.
0:26:23 So we had this long progress of technology and progress
0:26:27 suddenly lead us to this belief that it was imminently here,
0:26:29 if not changing the world already.
0:26:32 And so where are we in 2024?
0:26:36 I think the focus on that hype, the name,
0:26:39 and the relative un-success or general lack of success
0:26:41 of meta suite of metaverse products
0:26:43 has led to a belief that the idea
0:26:47 has come and gone, been Julie rejected by consumers,
0:26:50 but actually the progress of all of the constituent parts
0:26:54 has continued, not just with more child
0:26:57 and leisure oriented activities, Roblox and Fortnite,
0:27:00 but indeed had mounted displays at large,
0:27:02 general computing simulation,
0:27:03 and the creation of virtual worlds
0:27:05 using artificial intelligence.
0:27:09 But now at scrutiny has shifted elsewhere.
0:27:12 – So give us the tax work definition of the metaverse.
0:27:14 What is the metaverse?
0:27:15 – The best and easiest way to understand it
0:27:20 is a 3D shared and live version of the internet.
0:27:23 The internet as we have it today is best understood
0:27:27 as a dozen or two common protocols and a suite of standards
0:27:29 that enable the consistent, comprehensive,
0:27:34 and coherent exchange of data across 110,000 autonomous
0:27:37 and independent networks,
0:27:38 hundreds of millions of different servers,
0:27:40 billions of different devices,
0:27:42 supporting about 5 million applications,
0:27:46 billions of websites, all exchanging information.
0:27:48 And yet what that internet lacks
0:27:50 is really three fundamental elements.
0:27:53 First is the ability to transmit again,
0:27:54 coherently, comprehensively,
0:27:58 and consistently 3D information for it to be shared.
0:28:02 What you and I are doing right now, live Zoom,
0:28:04 is essentially one of the few things we ever do
0:28:06 on the internet that’s truly shared.
0:28:07 And essentially everything that we do on the internet
0:28:09 is not actually live.
0:28:11 When you and I go to theNewYorkTimes.com,
0:28:14 not only are we disconnected from the New York Times server,
0:28:16 but even when the New York Times updates,
0:28:18 we’re still looking at the old version of it.
0:28:20 And so the metaverse is best understood
0:28:24 as a shared, live, and 3D augmentation
0:28:27 to the existing internet as we experience it today.
0:28:29 – So technology is generally speaking,
0:28:33 everyone was happy to kind of pronounce crypto dead
0:28:36 about a year ago, and it’s come roaring back.
0:28:39 Voice was super hyped, it’s come down a bit,
0:28:40 it might come back.
0:28:44 This does feel as if it’s been, I wouldn’t say forgotten,
0:28:45 but it feels like there probably
0:28:47 is still some opportunity there.
0:28:48 Where do you see the greatest opportunity?
0:28:51 What industries do you think will register
0:28:53 the greatest leverage or success
0:28:56 around metaverse applications?
0:28:57 – Well, I think to start,
0:29:00 one of the unfortunate consequences of Meta’s name change
0:29:04 was the strong association with these technologies
0:29:06 and their concepts with virtual reality
0:29:09 or social workrooms that we would use to engage
0:29:12 in lieu of Zoom call or physical meeting.
0:29:14 Most of the pioneers in the category
0:29:16 strongly separate the two.
0:29:18 Some don’t even believe that virtual reality
0:29:19 has much of a future.
0:29:21 Neil Stevenson, who coined the term,
0:29:23 talks about it being central to his idea
0:29:24 of the future in the ’80s,
0:29:27 but he has essentially disavowed the requirement
0:29:30 of virtual reality or augmented reality from the metaverse.
0:29:33 So when you go to some of the larger businesses
0:29:37 in the category, whether that’s of Epic Games or Nvidia,
0:29:39 they have no requirement nor expectation
0:29:41 of a near-term solution for this hardware.
0:29:43 But if you’re gonna talk about
0:29:45 where we’re seeing these imminent opportunities
0:29:48 that are perhaps not covered extensively,
0:29:50 I think there’s two great examples.
0:29:55 The first is in the use of actually these headsets
0:29:57 in more industrial use cases.
0:29:59 Four years ago, the United States performed
0:30:00 its first ever live patient surgery
0:30:02 using a mixed reality headset.
0:30:04 The first was spinal fusion.
0:30:07 The second was the removal of a cancerous tumor
0:30:09 on a spinal column.
0:30:10 The United States is now performing
0:30:14 between four to 600 surgeries a year using these devices.
0:30:17 And the results, they’ll preliminary, right?
0:30:20 We haven’t seen a decade of patient outcomes,
0:30:23 do show that the surgeries are typically performed faster.
0:30:25 They’re more accurate.
0:30:27 They are, in some instances, much cheaper.
0:30:30 And most of the surgeons that perform this talk about it
0:30:33 in the same way that they did GPS in the early ’90s,
0:30:35 are revolution in how they perform
0:30:38 a relatively complex and yet routine process.
0:30:41 And yet one in which we’re still not able to do nearly
0:30:43 what we can with the technology today
0:30:46 that we imagined a few decades ago.
0:30:49 – It does feel like a healthcare is an obvious example.
0:30:52 And so talk to me a little bit about gaming.
0:30:53 I’m an investor.
0:30:55 I’ve made one of my largest investments
0:30:58 about three years ago in epic games.
0:31:01 It’s not much of this is around syntax or nomenclature
0:31:04 ’cause I think of, I think of Fortnite as the metaverse,
0:31:06 to a certain extent, I don’t,
0:31:08 I’m trying to figure out where gaming ends
0:31:10 and the metaverse begins.
0:31:14 And give me a sense for, now speaking as a,
0:31:16 advise me as a shareholder of epic,
0:31:19 how the metaverse will impact gaming
0:31:22 and who you see as sort of the winners in that space.
0:31:24 – So you’re right that a lot of this is a debate
0:31:25 over terminology.
0:31:28 In fact, even Spatial, which Apple has embraced,
0:31:30 has its origins, as I mentioned, in the early ’90s,
0:31:32 but it was never contemplated to actually connect
0:31:33 to the physical world.
0:31:36 It was just a description of a 3D space in a computer.
0:31:38 And so all of these terms, the metaverse included,
0:31:41 have kind of been perverted, reapplied in scenarios
0:31:43 it was originally not intended for
0:31:45 and become a part of corporate propaganda, right?
0:31:49 We’re Spatial, not metaverse, we’re metaverse, not Spatial.
0:31:51 I interviewed Tim Sweeney,
0:31:53 the founder and CEO of Epic recently,
0:31:55 and he likened the metaverse to a stock price.
0:31:57 He said, when something cool comes out, it goes up.
0:31:59 When something lame comes out, it goes down.
0:32:01 And more often than not over the last three years,
0:32:03 lame things have come out.
0:32:04 And certainly when you take a look
0:32:07 at those leading use cases, Fortnite is one such example.
0:32:10 They at least don’t capture the pop culture imagination,
0:32:13 the way that it did three to four years ago.
0:32:15 But it’s a good way of understanding the proliferation
0:32:17 of these technologies and trends.
0:32:20 Roblox, as an example, it has an advantage over Epic,
0:32:21 as you know, as being on mobile,
0:32:24 has about 375 million monthly active users.
0:32:28 That’s more than the entire active user base
0:32:30 of the Switch platform, the Xbox platform,
0:32:32 and the PlayStation platform.
0:32:35 Nearly all of its users are under 18.
0:32:36 And so you’re seeing something that,
0:32:39 despite being concentrated at a younger demo,
0:32:42 is nevertheless larger than another category
0:32:45 that spans all age demographics.
0:32:47 The other interesting thing about that category is,
0:32:50 of course, those younger users have no interest
0:32:54 in the capital M, M word, its trends, its significance.
0:32:58 It’s just a form of habit and how they socialize.
0:33:00 But when you talk about the companies such as Epic,
0:33:03 when people talk about the internet,
0:33:04 the internet is in some regard,
0:33:08 not unlike the constitution in the States,
0:33:12 in the sense that it was never meant to say static,
0:33:16 and yet it hasn’t really been updated for several decades.
0:33:18 The consensus is that the standards
0:33:22 which would support a shared live 3D internet
0:33:24 have to come from private business.
0:33:26 And therefore you need other private businesses
0:33:30 to willingly adopt standards and technologies
0:33:33 another entity owns and operates.
0:33:36 And therefore you need to trust Epic looks like
0:33:39 through its strength of existing platform,
0:33:42 its economic engine, and then its stewardship
0:33:45 by a more philosophical controlling shareholder
0:33:47 looks like one of the most likely entities
0:33:48 to pioneer those changes.
0:33:52 – There’s a chapter, I guess it’s an updated chapter
0:33:54 in your book that explores the century-long history
0:33:57 of AI and AI philosophy.
0:33:59 And also the six ways this technology controls
0:34:01 the metaverse, walk us through those.
0:34:03 – So I think when you take a look at many
0:34:05 of the technological impediments to building
0:34:07 what many have imagined, whether that’s a headset
0:34:10 or just a digital twin, a persistent simulation
0:34:13 of San Francisco as Tesla is now seeking to build,
0:34:17 a lot of the time we are facing literal laws
0:34:18 of physics constraints.
0:34:21 That’s actually why the Vision Pro is so expensive
0:34:26 and yet so unrewarding for many users.
0:34:27 And so we’re now starting to see these different ways
0:34:31 in which our dreams are being made real through AI.
0:34:34 Number one is that when you take a look at an HMD
0:34:36 head mounted display like the Vision Pro,
0:34:39 the best way to talk about what you can’t do
0:34:41 is to compare it to the device many of us have.
0:34:44 A Xbox Series X, a PlayStation 5,
0:34:46 those are 10 pound devices.
0:34:49 They’re the size of two or three different shoe boxes.
0:34:51 That’s despite the fact they don’t need a battery.
0:34:54 That’s despite the fact they don’t need a screen.
0:34:57 And yet they don’t need a mobile connection.
0:35:00 We don’t worry about the heat that they generate too much
0:35:02 because they’re feet and feet away from you.
0:35:06 They don’t need cameras to understand the world around you.
0:35:09 And they don’t need to take safety precautions, right?
0:35:11 To understand that there’s tax returns on the table
0:35:13 or that you’re about to stumble over an object.
0:35:18 Shrinking a 10 pound relatively underpowered device
0:35:19 that doesn’t need two of the heaviest things
0:35:22 that can have a screen and a battery
0:35:24 into something portable and wearable.
0:35:26 We haven’t found the science
0:35:30 that would allow us to overcome those challenges.
0:35:31 And yet through artificial intelligence,
0:35:35 we are actually starting to kind of co-opt that system, right?
0:35:37 We’re starting to come up with smarter ways
0:35:40 to have the system predict what you’re going to do
0:35:42 so that it doesn’t have to process it.
0:35:44 That processing requires battery, for example.
0:35:48 It requires tax on a limited GPU.
0:35:50 In fact, when you’re wearing a headset,
0:35:52 one of the biggest challenges
0:35:55 of just power reservation or preservation
0:35:58 is when you see the Vision Pro,
0:36:00 you’re actually looking at a reproduction of the world
0:36:04 around you from three to four different external cameras
0:36:06 that have to be stitched together.
0:36:07 But those cameras are actually captured
0:36:09 about an inch and a half in front of your eyes
0:36:12 and on an obtuse angle.
0:36:13 It’s artificial intelligence
0:36:16 that is bringing all of those images together,
0:36:19 shifting it back onto your eyes
0:36:22 and then making it seem like it’s coming from your eyes.
0:36:24 So that’s just one such example
0:36:28 of literally if we want to have lightweight portable devices
0:36:31 that are comfortable, powerful, able to do what we want,
0:36:34 it’s actually not a question of lithium ion advances,
0:36:35 not entirely.
0:36:38 It’s not about how many nanometers we have
0:36:39 for how many different transistors.
0:36:41 A lot of the time it’s how much smarter our systems
0:36:44 can be with scarce information.
0:36:45 The two bigger elements
0:36:48 are just about actually producing the world.
0:36:49 There was a lot of scrutiny,
0:36:51 and I know you’ve covered this around Galaxy’s Edge
0:36:55 at Disneyland and as expensive as that was,
0:36:57 it’s shocking to most people to realize
0:37:00 that the cost of making a virtual Galaxy’s Edge
0:37:02 is actually not necessarily less
0:37:06 than it was to produce a physical theme park.
0:37:09 And if you actually want to staff that with individuals
0:37:12 who can bring to life Naboo or Navarro
0:37:16 or the planet of Hoth, it becomes more expensive still.
0:37:17 And so with artificial intelligence,
0:37:19 we’re starting to see this reality
0:37:23 that if you wanted to produce the Disneyland of your dreams,
0:37:26 have it populated as you might imagine
0:37:28 and also allow you to do essentially everything
0:37:28 that you would want to do
0:37:31 and by extension can’t do in a theme park.
0:37:32 We’re talking about billions of dollars
0:37:36 in annual investment that is starting to shrink down
0:37:37 into the hundreds of millions
0:37:40 and where the cost curve might bring it even lower still.
0:37:42 – Something that I don’t think gets enough attention
0:37:47 is the application or applications of the metaverse and AI
0:37:51 in terms of simulation or its use on the battlefield.
0:37:53 And you have a chapter on this,
0:37:56 give a sense for where you think this intersects
0:37:58 with military strategy.
0:38:00 – So the best way to do this is to talk about
0:38:03 one of those terms that has kind of been forgotten
0:38:05 and even Microsoft moved away from,
0:38:06 which is digital twins.
0:38:10 Digital twins a few years ago became so common
0:38:13 because every company that felt obliged
0:38:14 to have a quote unquote metaverse strategy
0:38:16 just said, let’s make a digital twin.
0:38:18 And they very quickly realized
0:38:20 that sure it had some signaling value.
0:38:22 They got their employees to feel good about it.
0:38:23 They tested some new technology,
0:38:25 but they realized they didn’t really know
0:38:27 what they were going to do with it.
0:38:29 And one of the problems, and this comes back to AI is,
0:38:33 there are really five different levels of digital twins
0:38:34 that we talk about in the industry.
0:38:37 And the advanced ones require artificial intelligence.
0:38:39 And most of them were level one.
0:38:40 Level one is a digital twin.
0:38:42 It’s like a physical miniature.
0:38:44 It’s a model, a diorama.
0:38:45 Teams feel good about them.
0:38:48 Executives like having a diorama of their corporate campus,
0:38:50 but it reflects a statement.
0:38:52 It’s a point in time.
0:38:54 And it doesn’t have much applied value.
0:38:58 Level two digital twins take that original digital twin
0:39:00 and they make them real time using IoT
0:39:01 and other simulated systems.
0:39:04 You’re now having a live reproduction of that environment.
0:39:07 Level three are predictive digital twins.
0:39:09 They can tell you what’s likely to happen.
0:39:11 Level four are prescriptive.
0:39:14 They provide actual recommendations to the individuals.
0:39:18 And then level five, we talk about autonomous digital twins.
0:39:21 Those that can produce prescriptions and predictions
0:39:25 at such a high velocity that a human agent
0:39:28 can’t actually effectuate those changes effectively.
0:39:30 So that’s level one to five.
0:39:33 And by three, four, five, we start to get actual utility,
0:39:36 but we require high levels of accuracy,
0:39:39 sophistication, and velocity from AI systems.
0:39:41 We have two other axes.
0:39:43 One is the volume of data.
0:39:44 Obviously you can have a digital twin
0:39:47 that captures individual vehicles or fleets,
0:39:48 and that’s a very big distinction.
0:39:51 And then we have the amount of other network
0:39:52 digital twins you have.
0:39:54 Are we talking about a factory plant
0:39:56 or a McDonald’s in Manhattan?
0:39:59 Or are we talking about one plugging into the entire corpus
0:40:02 of a simulated environment of a Manhattan?
0:40:03 So once we understand this scope,
0:40:06 you start to talk about how these technologies
0:40:07 are being used today,
0:40:10 in particular in battlefield testing,
0:40:13 where you’re saying we have all of these systems
0:40:15 that can today do a decent job
0:40:17 of predicting and prescribing activities
0:40:19 for a relatively stable system
0:40:21 with relatively low cost of failure.
0:40:24 And by that I mean a production facility.
0:40:26 Pretty stable in what it’s going to do.
0:40:28 And the consequence of a line pause
0:40:31 is real for General Motors or Tesla,
0:40:33 but it’s not life-threatening.
0:40:35 There’s still a belief that we don’t have the level
0:40:36 of prediction or prescription,
0:40:40 let alone autonomy, to bring that into an active battlefield.
0:40:42 And what we are however seeing,
0:40:44 in the UK as a pioneer here,
0:40:47 is the use of this in active training,
0:40:52 in better simulation of what may or may not go right or wrong.
0:40:54 And in general, this connects to your earlier point,
0:40:57 which is the technologies that are almost always used
0:41:01 to actually test this, especially with human agents,
0:41:03 is the Unreal Engine out of Epic.
0:41:07 – You also had an edition of the book
0:41:08 where you’re talking about big techs fight
0:41:10 over undersea cable infrastructure
0:41:13 and Starlink versus Amazon’s project.
0:41:15 Kuiper, I’d love just,
0:41:17 you have such a big brain around,
0:41:18 I don’t even think he’s the metaverse guy,
0:41:22 I think he’s more like kind of like the cutting edge tech guy.
0:41:24 I look at Starlink and I see something
0:41:27 that has the width of the Amazon
0:41:28 and that this thing could be potentially
0:41:31 one of the most valuable companies in the world.
0:41:32 And some of this is just,
0:41:35 I’ve had such an incredible experience with a product
0:41:37 when it’s offered on planes.
0:41:39 Talk to me about Starlink,
0:41:44 if you agree that it’s got that sort of potential
0:41:47 and product excellence and moats
0:41:48 and who are the competitors
0:41:51 and where are they relative to Starlink?
0:41:52 – So I love this question
0:41:54 and it actually gets to the earlier point
0:41:56 around updating or supplementing
0:41:59 the internet protocol suite as we know it.
0:42:03 There was a largely under covered fight
0:42:05 going on between the big giants
0:42:07 to actually own the submarine cable infrastructure
0:42:09 of the internet.
0:42:12 Meta, as you called out in 2018,
0:42:16 they owned 0% of what we call the internet backbone
0:42:19 or the oceanic backbone.
0:42:22 By the end of this year, the free internet foundation
0:42:27 estimates that Meta will own 12 to 13%
0:42:31 or own, co-own, or be the capacity owner, right?
0:42:33 Essentially a leasehold like a wireless tower
0:42:35 of all submarine cable infrastructure,
0:42:40 about 170,000 kilometers of cable.
0:42:43 They will own the cables that connect 47
0:42:47 to 55 different African continental countries.
0:42:49 And it’s believed that out of the 12 to 13%
0:42:53 they own worldwide, 40 to 50%
0:42:57 of all of the African continental internet infrastructure.
0:42:59 That has led to additional escalation
0:43:01 from Google and Amazon companies
0:43:04 that were much farther ahead in purchasing
0:43:06 and owning these fiber optic connections.
0:43:08 When you talk about Starlink,
0:43:10 you’re again talking about another system
0:43:13 that we don’t have a traditional competition
0:43:17 or comparison for, but is now roughly 70%
0:43:21 of all low earth satellites that we have globally,
0:43:23 including all of those of China and NASA,
0:43:27 where they’re expected to put up another 12,000
0:43:30 in the next 12 months, up to 30 to 40,000 more.
0:43:33 And the cost and velocity advantages
0:43:38 they have over any other competitor is astonishing.
0:43:40 And so I’ll bring that back, which is you say,
0:43:42 okay, so what’s the challenge
0:43:44 with updating the internet protocol suite?
0:43:45 The challenge with the internet protocol suite
0:43:46 is it’s decentralized.
0:43:49 No one mandates a protocol’s adoption.
0:43:50 We’ve proposed many.
0:43:54 And so one classic example is the internet protocol suite
0:43:56 does not differentiate between any packet of data.
0:43:59 It doesn’t know what’s real time you and I talking
0:44:03 and it doesn’t know what’s an email or a Netflix stream.
0:44:06 And so you and I may have our call dumped
0:44:08 because there’s congestion in the network
0:44:10 and a network hop just says,
0:44:12 well, we’ve got to pick between these two.
0:44:15 So let’s dump Scott and Matt to let the email through,
0:44:19 severing the connection, not just delaying ours.
0:44:21 To get everyone to agree,
0:44:25 you need 110,000 networks,
0:44:27 millions and millions of different routers
0:44:29 to all say, let’s accept it.
0:44:32 And there’s no simple, let’s classify this versus that
0:44:35 because all data has different demand needs.
0:44:36 And so when you start to talk about the scope
0:44:39 of Meta’s ownership of cable infrastructure
0:44:43 or Starlink, you start to have a private party
0:44:48 that can forcibly or effectively produce new protocols
0:44:50 that reshape how the internet manages
0:44:51 and discriminates traffic.
0:44:53 I’m not talking about net neutrality.
0:44:56 I just mean like the fundamental understanding
0:44:59 of data and routing to start to change
0:45:02 the way the most profound technology
0:45:05 the last 50 years operates in a way that
0:45:08 at least in some regions of the world
0:45:11 and potentially globally through Starlink,
0:45:14 nothing else can even propose an alternative.
0:45:16 And that’s where you get into something truly remarkable.
0:45:19 And that’s a moat that would perhaps take
0:45:23 50 years to even try to chip away at.
0:45:25 – So you’re bullish on Starlink.
0:45:28 – I think it’s remarkably hard not to be.
0:45:30 – Yeah, that’s my sense too.
0:45:32 What other, okay, so Starlink, what other companies
0:45:34 when you look at how all the moons are converging
0:45:36 or not converging here, what other companies
0:45:39 are you especially optimistic about?
0:45:42 – So before I shifted over to interactivity
0:45:45 and gaming at large, I was primarily focused
0:45:47 on Hollywood and media.
0:45:50 I was the head of strategy for Amazon Studios,
0:45:52 which ran at the time, essentially what users
0:45:54 think of to be as prime video.
0:45:56 And I’m very familiar with your perspective
0:45:57 on generative AI.
0:46:00 Look, I think that technology is remarkable.
0:46:04 And I think you can kind of tell the general fears
0:46:08 around that technology by how the criticisms have changed.
0:46:10 A year and a half ago, it was the number of digits
0:46:11 that were on a finger.
0:46:15 Right now, most of the criticisms that I see are that
0:46:18 it looks great, yes, but it doesn’t have the nuance
0:46:21 of a human expression, of a human performance.
0:46:22 They say it’s plugey, right?
0:46:26 The lighting is bad, it’s not dramatic.
0:46:31 And just the fact that we have gone from visual deformities
0:46:37 to a normative sense of like taste is extraordinary.
0:46:42 And of course, the funny thing about that is
0:46:45 to even believe that the visual presentation
0:46:48 or the performance is flawed is to assume
0:46:51 that there’s a uniform human response to those things
0:46:52 when we know that there isn’t.
0:46:55 Which is to say, an expert may say that doesn’t land
0:46:58 the way that cinema or Scorsese would,
0:47:01 but that assumes that every viewer would.
0:47:03 The pace in which that technology is improving
0:47:04 is remarkable.
0:47:07 I think the ethics of how a lot of the training data
0:47:10 has been used are often reprehensible
0:47:15 or at worst, willfully ignorant of the ramifications.
0:47:17 But having gone through this fire wave
0:47:20 of virtual production and real-time production,
0:47:23 which we realized was probably 10 to 15 years
0:47:26 ahead of schedule, I think that we are very quickly
0:47:29 coming to that fundamental change point
0:47:32 for how generative AI is used in workflows
0:47:35 for video game, for music, for cinema at large.
0:47:38 And I use cinema deliberately
0:47:40 as opposed to just movies or content.
0:47:43 – So it’s had a strategy for Amazon Studios.
0:47:46 How do you think AI, if you will,
0:47:48 is gonna sort of crawl up to stack a Hollywood?
0:47:52 Is it the existential threat
0:47:55 that the WGA claimed it was and yet got no protections
0:47:56 from it, as far as I can tell?
0:47:59 Or do you think it’s actual?
0:48:03 Or is it a productivity tool that potentially lowers costs
0:48:06 and some media companies adapt, others don’t,
0:48:10 but on the whole, the media ecosystem stays robust
0:48:11 and some there are winners and losers?
0:48:12 Or is it really gonna start,
0:48:15 is it gonna disrupt Hollywood?
0:48:19 Is Hollywood the next Detroit at sort of the feet of AI?
0:48:21 What are your thoughts here?
0:48:23 And if you were still advising Amazon
0:48:26 or traditional studio, where do you think,
0:48:30 how do they best defend or go on offense here and leverage AI?
0:48:31 – Well, we have to keep in mind
0:48:33 that one of the reasons I think that Hollywood
0:48:36 has been more skeptical around generative AI
0:48:39 is the lessons of the last few supposed waves.
0:48:41 When you take a look at Netflix,
0:48:43 Netflix in many ways or streaming video,
0:48:45 democratize video distribution
0:48:47 and it changed the monetization,
0:48:50 but it did nothing to alter the cost structure of production.
0:48:52 It’s one of the reasons why fans decry
0:48:55 the fact that streaming has replicated the cable bundle,
0:48:56 but it’s more expensive.
0:48:58 Well, of course, we haven’t come up
0:49:01 with any real innovations to the production cost.
0:49:03 We produce more expensively than ever before,
0:49:06 in part due to the competitive intensity
0:49:09 brought about by the democratization of distribution.
0:49:11 You go back 15 years earlier, you get to VHS,
0:49:13 a new channel, a new monetization scheme,
0:49:18 but it didn’t again change how we produced.
0:49:21 Digital film and the advent of computer generated imagery
0:49:24 in the early ’90s, in many ways,
0:49:28 was expected to change production and democratize it
0:49:30 by eliminating sound stages,
0:49:34 but the cost of digital cameras at the time,
0:49:37 the cost of CGI, actually elevated budgets
0:49:39 to the point in which anyone who wants to have an epic
0:49:42 or a spectacle, the films that do best in movie theaters,
0:49:45 requires often, not exclusively,
0:49:47 but often hundreds of millions, if not more.
0:49:49 Hollywood is therefore kind of attuned
0:49:52 to this idea of the new disruptive technology,
0:49:54 doesn’t change production,
0:49:57 therefore maintains the merits of project financing,
0:50:02 of distribution slates to diversify risk of sound stages.
0:50:04 And in many ways, the actual cost
0:50:07 of running generative AI systems right now,
0:50:10 plus the importance of distribution
0:50:12 that they’ve spent 15 years trying to build up
0:50:14 through streaming, has led many to believe
0:50:16 that yes, it’s a disruptive force,
0:50:19 it is more likely than not going to affect
0:50:22 below-the-line workers and supporting systems,
0:50:26 but many believe that especially with the law on their side,
0:50:29 that it’s still gonna shake out mostly for them.
0:50:33 I’m skeptical because I think that we have never before seen
0:50:38 an actual massive disruptive force on the production side,
0:50:41 and one that in classic disruption theory,
0:50:45 suggests that many of their existing resources
0:50:49 become at best distractions
0:50:53 and at worst cumbersome cost hurdles for them.
0:50:56 And so this is to say, it’s a little bit difficult
0:50:59 to predict the outcomes, but I do think that everything
0:51:02 that we expected from YouTube that we didn’t get,
0:51:06 which is to say a massive volume of independent creatives
0:51:10 that have never touched nor gone through a traditional pipeline,
0:51:12 and yet are producing content that doesn’t look
0:51:14 like a $300 million Marvel film,
0:51:17 but looks like a 40 or $50 million Marvel film,
0:51:21 only it is more easily updated and edited,
0:51:24 changed, customized, frankly, transplanted,
0:51:27 and re-imported into an immersive environment,
0:51:31 into a storybook form, that’s gonna be really hard to slow.
0:51:34 And crucially, because Hollywood will no longer
0:51:37 own the distribution levers, can’t stymie either.
0:51:42 – The only place I would take exception is that,
0:51:43 I do think on the production side,
0:51:45 there has been a globalization, right?
0:51:47 They’ve brought down some production of the RIs
0:51:51 gone up by producing stuff in South Korea and Spain.
0:51:53 I think Netflix has done a pretty good job with that.
0:51:55 Would you agree with that?
0:51:56 – Depends on how you wanna define that.
0:51:59 Do I think that Netflix has done an outstanding job
0:52:02 in Spain and South Korea, in Australia?
0:52:06 Absolutely, I think investors often overlooked
0:52:08 Netflix’s advantages because they compared it
0:52:11 to HBO domestically, a business that had 50 years
0:52:13 of investment competing against one
0:52:14 that had a few years of investment,
0:52:18 without appreciating that in many foreign territories,
0:52:20 Netflix is HBO, not just to the consumers,
0:52:22 but to talent, to production expertise.
0:52:25 They own sound stages, they pre-booked sound stages
0:52:29 that they financed the construction of for years.
0:52:33 At the same point, there isn’t much evidence
0:52:35 of the routine repeatability, low-loan,
0:52:38 efficient production investment
0:52:40 of those foreign internationals hitting over here.
0:52:43 We have Squid Game, but Squid Game
0:52:45 was now three plus years ago.
0:52:47 We had Money Heist before that,
0:52:49 a title that they didn’t actually produce,
0:52:50 but purchased the license to.
0:52:53 I think that is to say, Scott,
0:52:54 I think that by American standards,
0:52:57 where we’re used to five to $15 million per hour,
0:52:58 Netflix has excelled in diversifying
0:53:00 their international production
0:53:02 to the two to $5 million budget level
0:53:05 when servicing those regional customers.
0:53:07 But I haven’t yet seen so much evidence
0:53:08 that they’ve been able to substitute
0:53:12 the American diet for high-cost scripted shows,
0:53:13 which much lower,
0:53:17 more efficient international scripted shows on balance.
0:53:19 We’ll be right back.
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0:55:34 (upbeat music)
0:55:39 – It feels as if we’ve written about this
0:55:41 at the kind of the streaming wars, if you will,
0:55:45 are just this great case study and economics.
0:55:49 Overinvestment because the markets are willing to replace
0:55:52 or say, well, we want growth over profits,
0:55:55 so there’s a massive overinvestment.
0:55:56 And now we’re going through a shakeout.
0:55:59 Cost-cutting and consolidation.
0:56:01 As you look at the landscape here,
0:56:02 of all the different streamers,
0:56:04 who do you think the winners and losers are?
0:56:07 Who are the consolidated oars and the consolidated ease
0:56:10 and any kind of off-market predictions
0:56:13 about what might play out in the next 24 months?
0:56:14 – Well, I think we have to start from the fact
0:56:17 that even as recently as 2020,
0:56:20 it’s remarkable how profitable that category was.
0:56:21 People talk about pay TV,
0:56:23 but I think it’s generally underappreciated
0:56:25 that if you can believe it,
0:56:28 pay TV or network television distribution
0:56:33 was a top-decile EBITDA business in the United States.
0:56:38 The median industry has a roughly 13, 14, 15% EBITDA margin.
0:56:43 Network distribution was around 37 to 40% in 2020.
0:56:48 That compared with renewables, nicotine, and oil and gas.
0:56:49 Why?
0:56:51 Because the amortization that you netted
0:56:53 against your operating income was enormous
0:56:55 because you had to build pipelines.
0:57:00 Any system that said just shifting from a top-decile
0:57:05 to a top-quartile category,
0:57:07 meant that you were gonna lose roughly one-third
0:57:09 of your profit margins,
0:57:11 that you probably had two times the cost structure
0:57:12 that you needed.
0:57:14 And that’s before accounting for the fact
0:57:16 that your two biggest competitors,
0:57:18 non-traditionally, are Amazon and Apple,
0:57:20 which need not a dollar of direct margin,
0:57:23 and you’re competing against a business Netflix
0:57:25 that said we don’t care for 20 years.
0:57:28 There is no way, there has never been,
0:57:31 a way to run away from that system.
0:57:33 And so all of the outcomes
0:57:35 that I think have long been predicted,
0:57:36 seem as inevitable now.
0:57:40 There’s too many players, the cost structures remain too high.
0:57:42 And that’s before you even take into account
0:57:45 the aforementioned generative AI displacement.
0:57:48 There’s nothing the average American still,
0:57:52 in 2024, does with their free time more than watch TV.
0:57:54 And I don’t think that that share of time
0:57:56 is even going to last as a result of video gaming,
0:57:58 social media, and other practices
0:58:01 that we see from the younger generation.
0:58:04 And so we’re going to see more companies go belly up.
0:58:06 We’re going to see more companies merge
0:58:09 and like Paramount and Viacom,
0:58:12 find out that despite their doubled size,
0:58:15 they’re gonna end up half the size they were.
0:58:17 – So take it a step further.
0:58:19 I’ll put this out there.
0:58:23 Time Warner survives, Disney survives, Netflix survives.
0:58:25 Other than that, I feel like all bets are off.
0:58:26 What are your thoughts?
0:58:27 – How do you mean survive?
0:58:31 Like as going concerns or direct to consumer business?
0:58:33 – My sense is they’re all recognizing,
0:58:35 even the deep pockets of Amazon and Apple realize
0:58:38 they don’t have the appetite to make the requisite investments
0:58:41 to be kind of standalone big competitors here.
0:58:43 And everyone’s looking for a dance partner
0:58:45 or to get acquired.
0:58:47 It just feels like the whole,
0:58:49 there just isn’t enough room for all of these players.
0:58:52 And what I’m putting to you is who do you think
0:58:55 it’s acquired sooner rather than later?
0:58:58 Might we see one of them actually get unplugged?
0:59:01 – Well, look, I think it remains very hard
0:59:03 to imagine what the independent future
0:59:05 of Alliance Gate or stars will be,
0:59:07 especially as a separated entity.
0:59:09 They kind of have all of the drawbacks
0:59:11 they had as a combined entity,
0:59:13 plus none of the narrative and none of the ability
0:59:16 to at least tap into two segments of the value chain.
0:59:20 AMC has been looking for a dance partner for 15 years,
0:59:23 clearly overestimated its value over and over
0:59:25 to the point in which there’s no dance partner
0:59:26 to find for them.
0:59:29 But the more important aspect is,
0:59:31 look, if you take a look at WBD,
0:59:34 these days it’s circling less than $7 per share.
0:59:36 It’s a collection of assets
0:59:38 that seem increasingly out of whack.
0:59:40 You have the Turner sports regime
0:59:43 that’s apparently about to lose its NBA assets.
0:59:45 You have CNN, you have HBO,
0:59:48 which as of now is decoupling further still
0:59:50 from the rest of Macs.
0:59:51 I think it’s important to recognize
0:59:55 that under current leadership,
0:59:57 WBD has actually sold off
1:00:00 most of their plausible growth story.
1:00:05 They’ve renewed a deep into 2030s distribution agreement
1:00:06 with Bel-Canada.
1:00:09 They’re apparently renewing their sky distribution deal
1:00:12 in Germany, in Italy, in France.
1:00:14 They’ve renewed a South Korean distribution agreement,
1:00:17 an Australian distribution agreement with Stan,
1:00:18 at the point in which you’re saying
1:00:22 we’re gonna downsize our domestic business in HBO.
1:00:24 We’re going to start licensing all of our content
1:00:27 to Netflix and anyone else who will buy it.
1:00:29 In all of the international territories
1:00:31 that have the highest streaming penetration,
1:00:33 we’re going to retreat and license
1:00:35 for the next decade to come.
1:00:38 And then you’re giving up your most valuable rights
1:00:39 on the Turner side.
1:00:42 CNN has no strategic adjacency
1:00:44 and the stock price has lost 75%
1:00:48 since it debuted only two and a half years ago.
1:00:50 It’s very hard to imagine
1:00:53 that that current structure can endure.
1:00:54 And that’s not even talking
1:00:55 about the video game side of this.
1:00:58 – And Matthew, before we go here,
1:01:00 we have a lot of young people who listen to the pod
1:01:03 and are working hard,
1:01:06 trying to establish currency in a professional marketplace.
1:01:08 And I think anybody that looks at your background
1:01:09 and what you’ve achieved
1:01:11 and the seat you’ve sort of created for yourself.
1:01:15 And I think that is a really cool profession.
1:01:17 Can you give us a little bit of the backstory
1:01:19 about how you got to where you are now
1:01:22 and any advice you might have for young men and women
1:01:27 who are looking to establish what feels, smells
1:01:29 and looks like a really cool, well-compensated career?
1:01:32 – So I’d say two things.
1:01:35 Growing up in the early 90s,
1:01:39 I was a relentless user of these really hard to use systems.
1:01:41 I was a big pirate in the 90s.
1:01:42 I was on IRC chats.
1:01:44 I was using MS-DOS.
1:01:48 The use of those products often provided, I think,
1:01:51 a intuitive understanding of what was around the corner.
1:01:52 Why?
1:01:55 Because often the systems that,
1:01:57 especially Hollywood starts to bring,
1:01:59 feel regressive at the time, right?
1:02:00 I’ll give you an example.
1:02:02 Like TV everywhere is one of the biggest disasters
1:02:04 that Hollywood has ever invested.
1:02:06 Do you remember ultraviolet, Scott?
1:02:07 – Mm-hmm, yeah.
1:02:10 – And it was one of those things where
1:02:13 if you had been a pirate and I don’t endorse piracy,
1:02:15 I’m talking about the products
1:02:17 of using these experimental technologies,
1:02:20 you all of a sudden realized that what you were being asked
1:02:23 to use was a woefully inadequate version
1:02:25 of the already-cluge systems
1:02:27 that you were doing 10, 15 years ago.
1:02:29 And then when that’s put in parallel
1:02:31 with a product like Netflix that, yes,
1:02:32 came from an independent company
1:02:33 that didn’t own its destiny,
1:02:36 that was licensing content that had all of its flaws,
1:02:39 that didn’t have live sports and live news,
1:02:41 it provided me with a much clearer understanding
1:02:44 of this is at minimum a better model
1:02:46 and at maximum a better model
1:02:47 that is competing with companies
1:02:50 that don’t even know what a good model looks like
1:02:52 and are to some extent ignorant
1:02:54 of what consumers are already doing.
1:02:58 And so I do think that using those technologies constantly,
1:02:59 which in the case of crypto
1:03:02 means going through truly terrible systems
1:03:04 and often losing your money as a result of it,
1:03:06 not saying that you should speculatively invest,
1:03:07 there’s no substitute for that.
1:03:09 You cannot learn it by reading blog posts
1:03:11 and going on Twitter.
1:03:14 The second thing is, I would say I’ve done a good job
1:03:18 in my career of constantly switching out of a category
1:03:22 where I believe the big strategic problems have solved
1:03:23 and then focusing on the categories
1:03:26 where you only have hard
1:03:28 and sometimes intractable questions.
1:03:30 In the case of the metaverse or VR,
1:03:32 that means going after a field
1:03:34 that you’re gonna get wrong a lot of the time.
1:03:36 It’s part of the reason why I’ve updated this book,
1:03:39 it’s a 70% remake from only two and a half years ago.
1:03:43 You can’t think of the metaverse the same way in 2024
1:03:44 after the Vision Pro,
1:03:47 after the crypto crash and resurgence
1:03:49 and after the advent of AI.
1:03:53 But if you can be relatively unsentimental
1:03:54 about going for, in my case,
1:03:57 streaming video was really hard in 2013.
1:03:58 You didn’t know who to hire,
1:03:59 you didn’t know the business model.
1:04:03 It was darn hard to get an app on a Samsung TV,
1:04:04 any television.
1:04:06 But by 2017, 2018,
1:04:08 we essentially figured it out,
1:04:09 which is why 2019,
1:04:13 we saw every single service on earth come to market.
1:04:16 I pivoted out to an uncertain category.
1:04:19 And when you have the opportunity to learn,
1:04:20 go to labs,
1:04:23 talk to entrepreneurs on Slack day in and day out
1:04:25 about something no one has figured out yet,
1:04:29 but most people think is about to become significant,
1:04:31 you end up with a multi-year advantage
1:04:33 that you can continue to compound for.
1:04:37 Matthew Ball is a CEO of Apelian,
1:04:38 a diversified holding company
1:04:39 that makes angel investments,
1:04:41 provides advisory services
1:04:43 and produces television, films and video games.
1:04:45 He’s also a venture partner at Makers Fund,
1:04:47 Senior Advisor to KKR,
1:04:48 Senior Advisor to McKinsey and Company
1:04:51 and sits on the board of numerous startups.
1:04:53 The fully revised and updated edition of his book,
1:04:56 “The Metaverse” is out now.
1:04:58 He joins us from Midtown, Manhattan.
1:05:01 Matthew, you’re one of these guys.
1:05:03 You remind me a little bit of Josh Wolf.
1:05:06 I don’t know if you know him from Lux Capital.
1:05:11 But I feel like I’m working with a 286 or a 386 ship
1:05:13 and the way you guys are able to process
1:05:15 and distill information is just,
1:05:18 it’s not only impressive, it’s really inspiring.
1:05:20 Appreciate you sharing our thoughts with our audience
1:05:22 and congratulations on building
1:05:24 such an impressive career for yourself.
1:05:26 – Thank you. It’s very kind.
1:05:28 (upbeat music)
1:05:31 (upbeat music)
1:05:37 – Algebra of Happiness.
1:05:40 I was invited to speak at something called
1:05:42 White Dudes for Harris,
1:05:45 which was a Zoom call that Garner get this,
1:05:48 160,000 people and raised about four million bucks.
1:05:49 So I got to speak for two or three minutes.
1:05:52 And my favorite thing is I got to speak
1:05:54 after the governor of Minnesota.
1:05:56 And before, Luke Skywalker, that’s right,
1:05:59 Mark Hamill spoke after me.
1:06:02 Initially, I thought I’m so sick of identity politics.
1:06:04 I don’t want to be associated with an event
1:06:08 that identifies me based on my bage-ness
1:06:10 and the fact I have outdoor plumbing.
1:06:12 But I signed up for it because,
1:06:14 and of course, all the Trumpers weighed in and said,
1:06:17 “If we did this, it would be accused of being racist
1:06:18 “and bigoted and blah, blah, blah.”
1:06:20 I think you have to take gestures
1:06:21 with the intent that they’re given.
1:06:23 And this was, let’s be honest,
1:06:27 this was non-whites and women have absolutely been ignited,
1:06:31 enthralled, motivated, inspired
1:06:34 by the prospect of a president Harris.
1:06:35 I love that.
1:06:38 I think it’s been very difficult not to get swept up
1:06:39 and come a lot, if you will.
1:06:41 And regardless, I want to be clear,
1:06:42 she was not my chosen candidate,
1:06:43 but neither was Bill Clinton.
1:06:46 I was supporting Michael Dukakis, remember him?
1:06:48 But I’m all in.
1:06:49 I think she’s a competent person.
1:06:51 And I think the person she’s running against
1:06:53 is not a great role model for young men,
1:06:55 and that’s not what I’m here to talk about.
1:06:58 Vice President Harris has received a lot of grief
1:07:02 from Vice President nominee, J.D. Vance,
1:07:03 for not having kids.
1:07:06 And that’s just not true.
1:07:09 Vice President Harris is a stepmom, if you will,
1:07:10 to two kids.
1:07:13 And my stepmother just played
1:07:16 such a positive role in my life.
1:07:18 My dad’s been married and divorced four times.
1:07:20 He had a daughter by his third marriage,
1:07:23 but his wife, Linda, his third marriage,
1:07:26 was the first person to spoil me.
1:07:28 Do you remember that, the first person?
1:07:30 For most people, it’s their grandparents, right?
1:07:32 And my grandparents were not around.
1:07:34 So some background, Linda had been told
1:07:36 that she could never have her own children.
1:07:38 And so when this little,
1:07:40 when this eight-year-old and Levi’s corduroys
1:07:42 and an OP shirt and missing his two frontiers showed up,
1:07:46 she was just in love, like moment one,
1:07:47 and used to spoil me rotten.
1:07:50 I’d come over and she’d have like chocolate
1:07:52 hidden around the house.
1:07:54 She’d take me to Toys R Us,
1:07:57 and she’d see me eyeing the remote-controlled P-51 plane
1:07:59 and say, “Well, what about this?”
1:08:00 Even though I was too embarrassed to ask
1:08:01 ’cause it looked expensive.
1:08:03 The first person who spoils you,
1:08:04 you just love the rest of your life.
1:08:06 Anyways, my stepmom, Linda, spoiled me.
1:08:10 She was also really good in terms of encouraging my father
1:08:12 to be more involved in my life.
1:08:13 She and I spent a lot of time together
1:08:15 ’cause my dad was on the road,
1:08:17 so I would go out to my father’s every other weekend
1:08:19 and basically hang out with Linda.
1:08:21 And she was such a positive role model for me
1:08:23 and was such a loving person.
1:08:26 Reason I bring this up is I think stepparents
1:08:29 are very much underrated and overlooked,
1:08:30 including the vice president.
1:08:33 I think that it is an especially strong signal
1:08:35 of your humanity, your generosity.
1:08:38 And generally speaking, your capacity to love
1:08:40 when you do what most stepparents do,
1:08:42 and that is love those children like they’re your own.
1:08:44 (upbeat music)
1:08:46 This episode was produced by Caroline Shagren.
1:08:49 Jennifer Sanchez is our associate producer
1:08:52 and Drew Burroughs is our technical director.
1:08:54 Thank you for listening to the Propg Pod
1:08:56 from the Vox Media Podcast Network.
1:08:58 We will catch you on Saturday
1:09:00 for No Mercy, No Malice, as read by George Hahn.
1:09:03 And please follow our Propg Markets Pod
1:09:05 wherever you get your pods for new episodes
1:09:07 every Monday and Thursday.

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0:00:39 sweet and spicy sauce. You’ll wish this spectacle of flavor never ended. Try the new Fire Cracker
0:00:46 McRispy today at Participating McDonald’s restaurants. Welcome to the Prof. Jude Pod’s
0:00:49 office hours. This is the part of the show where we answer your questions about business
0:00:55 big-tech entrepreneurship and whatever else is on your mind. Hey, Prof. Jude. Hey, Scott and team.
0:00:59 Hey, Scott. Hi, Prof. Jude. Hey, Prof. Jude. Hey, Prof. Jude. Hi, Professor G. Last week’s
0:01:02 office hours, we answered your questions surrounding sheen’s design practices,
0:01:07 qualities to look for when hiring, and how to pivot when you’re a mid-career professional.
0:01:15 IP protection be increased? I think you could argue that the final frontier of that or the
0:01:21 next frontier is AI. The key to being successful, I think, is to develop allies along the way.
0:01:30 Don’t let perfect be the enemy of good. Every day, three or four emails to strangers, contacts,
0:01:34 colleagues from your alma mater who are working in investor relations, comms,
0:01:40 video production, content strategy, and sort of get on it and just get back into the ecosystem,
0:01:44 if you will. Today, we’ll answer your questions about the current pharmacy staffing shortage,
0:01:49 whether the U.S. college price tag is worth it and how to navigate life transitions.
0:01:52 I’m already intimidated. You know what? I don’t know any more about this
0:01:56 shit than you, but I don’t know any less. First question.
0:02:02 Hi, Professor Galloway. My name is Mann. I currently live in Washington State.
0:02:06 I have been a fan since I listened to your interview with Barry Holmes,
0:02:12 in which you mentioned your book, The Ford. My question to you is about the pharmacy’s
0:02:17 workforce because I’m a pharmacist. The pharmacy world is dealing with the shortest of technicians
0:02:23 due to low wages. What do you think corporate need to do to provide incentives for the pharmacy
0:02:31 technician? I enjoy watching all your polls. Enjoy all your dad joke on the show. Thank you.
0:02:35 So, boss, we really need to be friends. Such that every time I see you, I can say, “Hey, man.
0:02:44 Hey, man. I love that. I love that.” I say, “I respond to texts from other men, I would say,
0:02:47 “Hey, man, and if I like them or I’m close to them, I’m like, ‘Hey, brother.’”
0:02:52 Anyways, what do I think? Supposedly, and I’ve read something about this, there is supposedly a
0:02:57 looming pharmacy crisis in America, specifically staffing shortage due to increasing burnout
0:03:02 among pharmacists. I guess a lot of boomers are just sick of this shit and retiring. According
0:03:07 to the American Association of Colleges of Pharmacy, applications to pharmacy schools have
0:03:15 declined 64% from nearly 100,000 in 2012 to about 36,000 in 2022. Data from the Philadelphia College
0:03:20 of Osteopathic Medicine revealed that there were about 61,000 job postings for pharmacists in the
0:03:27 first three quarters of 2023, but only about 13,000 pharmacists graduated in 2022. Why is this
0:03:33 happening? What’s going on here? Some workers have staged walkouts, including well-known protests
0:03:41 called Farmageddon, which involve three days of nationwide walkouts in CVS and Walgreens.
0:03:46 What’s being done to navigate the pharmacy shortage? National retailers, including Walgreens and CVS
0:03:50 Health, are investing heavily in automation and micro-fulfillment centers where robots handle
0:03:55 most of the tasks to streamline and reduce the workload. In February of this year, Walgreens
0:03:59 announced a partnership with pharmacy school deans at 17 universities to increase student
0:04:08 enrollment in pharmacy schools. What’s going on here? Theoretically speaking, if there’s a crisis
0:04:14 in a shortage, that would mean the market would naturally, on its own, intrinsically, need to
0:04:20 offer greater wages and you would see an increase in wages. Just as through the pandemic, we couldn’t
0:04:27 get any frontline workers or any staff or service workers back to, people just got sick of trying
0:04:31 to get people to put their masks on. Meanwhile, putting their own health at risk for nine bucks
0:04:39 an hour. I was on the board of Panera Bread and wages went up, I think 30 or 40%, just in a
0:04:44 probably a six or a 12-month period. Not because we’re good people, although I do think they’re
0:04:49 good people, but because we had to. It was just striking. I remember this one stat that the CEO
0:04:55 was saying that usually they have a job fair and they get 100 applicants and they might hire 20 of
0:05:01 them. 18 would show up day one. They would say, two, just don’t show up. It went down to something
0:05:06 like 20 people would show up at the job fair. They’d make 10 offers and of those 10, only two
0:05:11 or three would show up the first day of work, which just struck me as, where are people getting
0:05:17 money? It does feel, and I think this is a good thing, that at the lower end of the wage scale,
0:05:23 there was all this pent up bullshit or wages were too low and all of a sudden, I don’t want to
0:05:27 say the dam broke, but basically these people said, this just isn’t worth it. I’m not going to work
0:05:32 this hard and put up with this bullshit to live below the poverty line. There was a massive,
0:05:39 massively overdue increase in wage pressure, which led to higher wages at the lower income level,
0:05:43 which is a wonderful thing. At the end of the day, it’s supply and demand. I would think that over
0:05:50 time, you’re going to see wages rise among pharmacists, just as if you’ve seen wages rise
0:05:57 among nurses. Now, if I were to say, what is the culprit here? It’s that an industry is too
0:06:01 concentrated. One, I would argue, and I don’t have the data here, but I would argue if I were to
0:06:05 put forward a thesis around what’s happened. It’s one, regulatory capture by the pharmaceutical
0:06:09 companies and hospital networks that have essentially starched out all the margin,
0:06:14 and the frontline workers, the doctors, and the pharmacists and the nurses have not kept
0:06:22 anything near the pace of the increase in healthcare costs. It has gone to insurance companies
0:06:27 who get 45 cents on the dollar for admin and profits. The best argument in my opinion for
0:06:34 nationalizing medicine is 45 cents on the dollar gets starched out of the system by insurance
0:06:40 companies. If you pay a dollar in insurance, you get 55 cents in care back, too, there’s a pretty
0:06:46 serious concentration around the front end. That is, I think between CVS Health and Walgreens,
0:06:53 I would imagine that it’s pretty concentrated. There’s not enough people bidding on the labor
0:06:59 here. If there’s really only two, and they themselves are struggling on the front end,
0:07:03 they’re facing some of the same pressures, I think, as frontline healthcare workers are facing,
0:07:09 that they’re not in a mood to be super generous. Quite frankly, they don’t need to because if
0:07:15 they control the majority of the job listings around pharmacists, they set the price. Again,
0:07:20 I think it’s another example of the concentration of power in an industry is not a good thing.
0:07:26 I would argue that it’s an interesting profession. I would think over the long term that the
0:07:30 market will largely self-correct. It may take longer than it should because of this regulatory
0:07:36 capture and this concentration of power that I was talking about. So there you go, man. Next question.
0:07:43 Hi, Scott. This is Florian from Zurich, Switzerland. I love your podcast. Your candor and humor are
0:07:47 refreshing, and I often find myself returning to your work when looking for interesting content.
0:07:52 Here’s my question. I’m a father of two teenage boys about to graduate from the Swiss public school
0:07:58 system. Their high school degrees will allow them to attend Swiss universities, where education is
0:08:05 excellent, and tuition is very affordable, between $1,000 and $2,000 a year. Given this,
0:08:09 would you still consider sending your sons to a U.S. college despite the high tuition fees?
0:08:16 Is the differential in tuition fees warranted in your view? As a pro bono professor at NYU,
0:08:21 I look forward to receiving your honest opinion. Regards, Florian.
0:08:27 Thanks, Florian. First off, let’s just take stock of your blessings. You live in Zurich,
0:08:30 which I think is one of the most beautiful, civilized,
0:08:34 just generally pleasant cities in the world. I think it would be wonderful to be raising boys
0:08:40 there. The father of two teenage boys. I’m a father of two teenage boys, and I’m not exaggerating.
0:08:45 Every day I have a moment where I think, God, I’m just so blessed. I just think about my boys,
0:08:51 and I just think, Jesus, I have experienced something that just has made it all worthwhile.
0:08:55 So anyways, back to your question. According to the College Board, the average 2023-2024
0:09:01 price to tuition fees, housing, and food of private non-profit four-year colleges is $56,000.
0:09:08 I think at NYU, it’s actually about $100,000. I think tuition is $72,000. I think it’s well
0:09:12 above $100,000. It’s $510,000. In a four-year public college, as in-state students face an
0:09:17 average cost of about $24,000, I think those numbers are low. But anyways, according to the
0:09:20 National Center for Education Statistics, the average price of college tuition fees in room
0:09:26 and board has increased 155% between 1980 and 2023. Why? Because me and my colleagues every day
0:09:30 look in the mirror. When we wake up in the morning, we ask ourselves one question.
0:09:35 How can I increase my compensation while decreasing my accountability? There’s this
0:09:40 notion that somehow we’re more noble than your average bear. We’re not. We’re not any less noble,
0:09:47 and there’s a lot of good people in education. But be clear. We want to have a home in the
0:09:51 Hamptons and have a nice life and pay for our own kids’ overpriced college education as much as
0:09:56 anybody else. We have discovered the ultimate business strategy and CLVMH strategy. Let’s
0:10:02 reject so many people through artificial scarcity by constraining supply unnecessarily such that we
0:10:06 can position ourselves as an aspirational luxury brand and raise our prices faster than inflation,
0:10:10 and then hire a bunch of administrative people, administrators who do interesting work that
0:10:16 has absolutely no fucking impact on anything, see above DEI, sustainability, leadership, ethics,
0:10:21 Jesus fucking Christ. I’m going to teach my son, or I’m going to teach a kid at the age of 27
0:10:26 how to be more ethical. Yeah, good luck with that. Anyways, where are we? Okay, so this is
0:10:31 the bottom line in what I would do. America does a small number of things really well. We make the
0:10:37 best weapons in the world. Looking to kill a bunch of people? We’re your retailer of choice.
0:10:42 We make incredible software. When I say software, I’m encompassing all technology.
0:10:47 Another thing America does really well, really well, distinct of the price,
0:10:52 is the college experience. I’ve spoken at Oxford and Cambridge and spent time in the
0:10:59 Baconi. I taught at Instituto Impressa in Madrid for a semester back in 2007, I think,
0:11:05 but anyways, I’m pretty familiar with European universities. They’re fine. They’re better value.
0:11:11 They give you the skills you need. They do not have the same brand equity, right? Michigan,
0:11:16 Stanford, and Carnegie Mellon are global brands, right? The Baconi is sort of,
0:11:22 Essex, sort of. Cambridge and Oxford, definitely, but the other several thousand universities in
0:11:27 Europe no one’s ever heard of. And I do think it’s an advantage. We live in a LinkedIn information
0:11:33 economy and having a brand name US University does give your kids an edge. Also, also, in terms of
0:11:39 the experience, oh my gosh, we’re so good at that. College football games, fraternities and
0:11:42 sororities. Yeah, I said fraternities and sororities are a wonderful experience for people. They shrink
0:11:46 a big university down to a small number of people. By the way, fun fact that I used to tell people
0:11:50 when I was the Interfraternity and Counsel President at UCLA, no joke, that’s right, I was king of the
0:11:55 jarheads. Was it the moment a kid joins a fraternity or sorority, they become much more likely to
0:12:02 graduate. It’s important to immediately find a group of people or a tribe or whatever to create
0:12:07 that connective tissue. Anyways, the university experience, the US University experience, land
0:12:15 and grand schools, it is singular. It is singular. So what should you do? One, if your kids are up
0:12:21 for it, apply to several US colleges. Hopefully, hopefully this is what happens. Your son or your
0:12:26 daughter get into three or four, actually you said sons, teenage boys, plural, get into three or four
0:12:30 universities and then this is what you do. You play them off against each other because the
0:12:35 interesting thing about the university admissions process is we all want to get in, right? We’re
0:12:40 desperate to get in. But once we get in, they all want your kid because they have something called
0:12:45 yield rates that has a huge impact on their rankings. And that is if someone gets into Duke and UVA,
0:12:50 they will announce or they will publish what the yield is. What do I mean by that? The yield between
0:12:54 Columbia and NYU, that is people that got them to both schools, used to be like 90-10. Everyone
0:12:59 went for the big brand prestige of Columbia. And then Ross and Rachel, friends, basically,
0:13:06 and Will and Grace, everyone wanted to be in SOHO. And so now our yield, I think it’s like 55-60 to
0:13:10 45-40. In other words, Columbia still gets a higher yield than us, but we’re within striking
0:13:14 distance of being a parody. Through no fault of our own, the faculty and administrators will take
0:13:18 credit for the amazing work we’ve done at NYU. Some of that is true, but it’s mostly because we
0:13:22 live in the coolest neighborhood in the world. I’ll stick to that. I think SOHO is an amazing
0:13:27 neighborhood. Anyways, ideally, ideally, and one, best laid plans and then your teenage boys will
0:13:31 tell you what they are doing. I like to think it’s so funny with parents. We think that we have so
0:13:35 much influence over our kids and the reality is they kind of come doing the makeup of their own
0:13:41 mind. And if it is affordable and it’s all else being equal, by all means, and again, it’s up to
0:13:47 them, the U.S. university experience is singular. I would recommend it to anyone globally. It’s
0:13:51 an amazing experience, something that would treasure the rest of their lives. Thanks for the question.
0:13:55 We have one quick break before our final question. Stay with us.
0:14:04 Support for this podcast comes from Grammarly. Your team spends half their time writing
0:14:09 and not productive writing, annoying writing, clarifying writing, just following up writing.
0:14:14 And we all know how that happens. When confusing email turns into 12 confused replies and a
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0:14:27 But it’s more than just a grammar check. Grammarly can help generate AI prompts or even
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0:14:36 We here at the PropG team use Grammarly and all I have to say is it makes our writing better and
0:14:42 more efficient. Plus, Grammarly integrates seamlessly across a half a million apps and sites,
0:14:47 no cutting, no pacing, no context switching. Personalized on-brand writing help is built
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0:14:56 hit your goals while keeping your data secure. Learn more at Grammarly.com.
0:15:06 Support for PropG comes from Fundrise. Artificial intelligence is poised to be one of the biggest
0:15:11 wealth creation events in history. Some experts expect AI to add more than $15 trillion to the
0:15:16 global economy by 2030. Unfortunately, your portfolio probably doesn’t own the biggest
0:15:21 names in AI. That’s because most of the AI revolution is largely being built and funded in
0:15:26 private markets, which means the vast majority of AI startups are going to be backed and owned by
0:15:33 venture capitalists, not public investors. So until the AIPO, you can’t get a piece of their success,
0:15:38 but the Fundrise Innovation Fund is changing that. The Innovation Fund pairs a $100 million
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0:16:10 Support for this podcast comes from Huntress. Keeping your data safe is important, however you’re a
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0:16:50 or learn more. Welcome back question number three. Hello Scott. I’m Thomas. I recently moved out of
0:16:57 my hometown in Quebec to a new city, Montreal. This move allowed me to transfer to my company HQ,
0:17:03 work on more interesting projects, and experience new and exciting things as I approached my mid-20s.
0:17:08 I’m here with my girlfriend and we live in a nice apartment downtown. It’s great.
0:17:15 However, I won’t hide the fact that it’s a significant change to absorb. I am particularly
0:17:20 stressed about maintaining my close relationships from a distance and creating bonds with new people
0:17:26 in Montreal. Since you have moved to multiple cities throughout your life and strongly advise
0:17:32 young people like me to move to a city, step out of their comfort zones, and seek new experiences,
0:17:37 what advice would you have for someone like me who’s in the middle of a life transition?
0:17:42 Thanks so much for your help. Love in your book. So first off, Thomas, one of the pieces of advice
0:17:46 I give to young people about how to create the atmosphere, it’s your success. It’s simple and
0:17:51 that has moved to a city and you’ve done that. You can be good in Montreal and get much further
0:17:56 faster than if you were great in your hometown in Quebec. So moving to Montreal, moving to the
0:18:02 big city, if you will, is an investment in yourself and is going to better leverage your
0:18:06 skill set. Also, the fact that you moved there with your girlfriend, you’re in a relationship,
0:18:10 do you realize only one out of three men under the age of 30 has a girlfriend? Two out of three
0:18:14 women under the age of 30 have a boyfriend that you think, well, that’s not mathematically
0:18:19 impossible. It’s not because women are dating older as they’re pursuing more economically
0:18:25 and emotionally viable men. Another talk show. So, boss, I just have one word of advice for how to
0:18:30 integrate and develop that kind of social capital you’re looking for as a young man in a new city.
0:18:38 Yes. Say yes to everything for a while. Say yes to drinks with coworkers, a coffee, ask people out,
0:18:44 get your girlfriend’s friends, invite other couples out, whatever it might be, do a dinner
0:18:50 party. Just kind of say yes to everything and you’re so fortunate to kind of hit the ground
0:18:55 running there with a partner. That just makes things so much easier and you’re not going to get as
0:19:02 lonely. But just my brother, you’re obviously a shit-together guy and you’ve got a partner in
0:19:08 crime here. Just go out. Be friendly. Introduce yourself. Get involved. Maybe if you play sports
0:19:14 in a local league, I don’t know if you attend a church or a temple or a mosque, but get involved
0:19:20 in the local chapter, what have you. And you kind of work through to get your sort of your squad,
0:19:24 if you will. But the key is getting out of the house, saying yes to everything. Try to resist
0:19:28 the temptation to just hang out with your girlfriend and watch Netflix all the time after
0:19:33 a hard day’s work. Get out, do stuff, join groups. But my brother, let’s finish where we started.
0:19:39 You’re living in Montreal with your girlfriend after getting a job. It is good to be you, Thomas.
0:19:44 Congratulations and thanks for the question. That’s all for this episode. If you’d like to
0:19:48 submit a question, please email a voice recording to officehours@propertymedia.com. Again,
0:20:04 that’s officehours@propertymedia.com. This episode was produced by Caroline Shagren. Jennifer
0:20:09 Sanchez is our Associate Producer and Drew Burroughs is our Technical Director. Thank you for listening
0:20:13 to the PropG pod from the Vox Media Podcast Network. We will catch you on Saturday for No
0:20:19 Mercino Malice as read by George Hahn. And please follow our PropG Markets pod wherever you get
0:20:28 your pods for new episodes every Monday and Thursday. Daddy was a tall drink of lemonade
0:20:31 right there. Hello. Give me a little bit more sky.

0:00:03 Support for property comes from better help.
0:00:05 Social media has made it really easy to peer
0:00:06 into other people’s lives,
0:00:08 but when you start comparing yourself, that’s a trap.
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0:00:12 instead of what others have
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0:00:41 – McCrispy fans, there is a new jar
0:00:43 dropping McCrispy at McDonald’s.
0:00:46 It’s called the Fire Cracker McCrispy.
0:00:51 It has the crispy, juicy tender chicken you love,
0:00:54 topped with crispy jalapenos
0:00:56 and a super tasty sweet and spicy sauce.
0:01:01 You wish the spectacle of flavor never ended.
0:01:04 Try the new Fire Cracker McCrispy today
0:01:07 and participate in McDonald’s restaurants.
0:01:10 – Today’s number $10.
0:01:13 That’s the value of the Uber Eats gift card
0:01:16 that CrowdStrike offered customers as an apology
0:01:18 for its worldwide outage.
0:01:20 Ed, I just can’t take much anymore.
0:01:22 I’m divorcing my wife.
0:01:23 First it was some guy in a drunk party.
0:01:26 Then it was her ex-boyfriend, her boss, my best friend,
0:01:29 even an Uber driver.
0:01:32 I just can’t stop sucking other men’s cocks, Ed.
0:01:44 – That was bad, even for me.
0:01:45 Here we are, Ed.
0:01:49 Proph-G, our producer just went off camera.
0:01:50 She’s calling her lawyer.
0:01:56 – Hello.
0:01:58 – Hey Dina, it’s Claire again.
0:02:00 – What’s going on, Ed?
0:02:02 – I’m doing very well.
0:02:04 By the way, I saw a nice headline in the news this week,
0:02:08 which is that you’re donating $12 million to UCLA
0:02:09 and UC Berkeley.
0:02:10 – Oh, that’s an interesting segue
0:02:12 for me giving random oral sex to men.
0:02:15 Yes, I am, Ed.
0:02:17 – I’m trying to portray you in a better light here.
0:02:19 – We definitely changed altitudes pretty quickly there.
0:02:21 – Do you want to stay on sucking dick?
0:02:24 Do you want to remain there for a little bit longer?
0:02:26 – Let’s try and pivot out of that.
0:02:28 Even I’m feeling a bit cringed out right now.
0:02:31 Even I’m feeling a bit cringed out.
0:02:32 Back to me in my virtue signaling,
0:02:33 what would you like to know, Ed?
0:02:37 You know me, I don’t like to talk much about myself.
0:02:38 What’s on your mind?
0:02:40 – Well, you just talk about it.
0:02:43 I shared it on Twitter, which you’re not on,
0:02:44 so you didn’t see this,
0:02:46 but I just sort of gave you a little shout out
0:02:48 for putting your money where your mouth is.
0:02:49 – That’s nice, that makes me feel good.
0:02:51 – And people just loved it.
0:02:54 I mean, it’s gone, I wouldn’t say viral,
0:02:56 but semi-viral.
0:02:59 I think people are just very impressed with that donation.
0:03:02 So maybe explain what it’s for, what you’re doing.
0:03:06 I just like when you follow through with your ideas,
0:03:07 and that’s what you’ve done here.
0:03:09 – Okay, well, first off, thanks for asking.
0:03:11 So it’s a lot of things.
0:03:13 It’s a culmination of a lot of things.
0:03:15 One, it’s an overdue nod to the generosity
0:03:18 of California taxpayers that gave me a shot.
0:03:20 The reason I’m here with you today
0:03:22 is the generosity of California taxpayers
0:03:26 and the visions of the Regents of the University of California.
0:03:27 I’m not being humble.
0:03:29 I’m a remarkably talented person,
0:03:31 but without the certification contacts
0:03:34 and job opportunities that I got
0:03:37 from the University of California, I just wouldn’t be here.
0:03:40 And the thing about UC back in the ’80s
0:03:43 was that it was not only affordable, it was accessible.
0:03:46 Yeah, 76% admissions rate, $1,200 per year.
0:03:48 And I feel that people who are successful
0:03:51 and have gathered some wealth have an obligation,
0:03:54 especially UC grads, to try and return it
0:03:56 to that level of affordability and accessibility.
0:03:58 In addition, I saw an opportunity,
0:04:02 and that is we have this incredible infrastructure
0:04:03 across the UC campuses.
0:04:05 We don’t take advantage of the facilities at night
0:04:07 or during the summer.
0:04:08 And also our product doesn’t evolve.
0:04:09 Not everyone should be shoved
0:04:13 through a traditional four-year liberal arts degree.
0:04:16 And because five people are leaving the trades
0:04:18 for every two that are going in over the next 10 years,
0:04:20 we’ve seen a dramatic escalation
0:04:22 in the salaries and compensation
0:04:26 of plumbers, electricians, cybersecurity professionals,
0:04:28 specialty nursing, specialty construction.
0:04:31 So I approached the chancellors at UCLA and Berkeley
0:04:34 and said, if I funded a program,
0:04:36 that was more vocational in nature.
0:04:38 They gave maybe young adults and adults
0:04:40 a chance to take courses, very specialized courses
0:04:42 over the course of a year.
0:04:46 They gave them access to this incredible up swell
0:04:48 and compensation and job opportunities
0:04:49 in the main street economy.
0:04:50 Would you be interested?
0:04:51 – They were interested and they were very generous with me,
0:04:54 even though they hate using the term vocational.
0:04:56 So we talk about non-traditional students.
0:04:58 – Why do you think they hate the term?
0:05:00 Does it just sound not elite enough or something?
0:05:01 – Yeah, I think they see themselves
0:05:04 as wanting to higher education
0:05:07 as about giving a kid a chance to explore different disciplines
0:05:10 such that it rounds out the kind of the brain is a muscle,
0:05:12 whether it’s history or philosophy,
0:05:14 and that maybe our junior colleges
0:05:16 or other trade schools are really for that,
0:05:18 that that erodes kind of the mission
0:05:21 and somewhat of the elite status of higher ed.
0:05:23 So they are very, they have been,
0:05:24 that was the hardest part about this gift
0:05:28 was getting them to somehow move to the notion
0:05:32 that we need to offer an opportunity here
0:05:35 over one or two years that would help kids
0:05:37 have the skills that foot to the main street economy
0:05:38 right now.
0:05:41 And my vision is I want it to be free
0:05:43 and I don’t want there to be an admissions process.
0:05:46 I want it to be if you’re smart, not that I’m smart.
0:05:49 You’re a good person who wants to be a part of our economy,
0:05:52 wants to be in the middle class, wants to, or higher,
0:05:54 wants to pay taxes,
0:05:56 but isn’t cut out like two thirds of Americans
0:05:58 for traditional four year liberal arts degree
0:06:03 that you have opportunities and free and accessible.
0:06:05 Those are my two call signs here,
0:06:08 but this is, I’m super excited about it.
0:06:12 Both UCLA and Berkeley were really supportive of the idea.
0:06:14 And also for me, it’s not even philanthropy,
0:06:17 it’s consumption, it makes me feel really fucking awesome.
0:06:19 I feel like a baller doing it.
0:06:20 – I think it accomplished another goal,
0:06:24 which is that many of the comments I saw on Twitter were,
0:06:26 I didn’t know Scott had $12 million.
0:06:30 – I have 12 million and one, it’s all gone now.
0:06:31 – That’s what I said.
0:06:32 Someone said, how much does he have?
0:06:33 I said, more than 12 million.
0:06:36 – It’s super exciting.
0:06:39 I’m happy to be, you know, I don’t know, dad.
0:06:42 It’s like you get to a point in your life
0:06:46 and what I wanna do is,
0:06:48 I love the difference between an opinion
0:06:50 and a principle or a value.
0:06:51 And the difference between an opinion
0:06:53 of which I vomit out to everybody on this
0:06:56 and other podcasts is that, okay,
0:06:58 are you really passionate about struggling young men?
0:06:59 I think I am.
0:07:00 Well, is it an opinion or is it a value?
0:07:02 I’m really passionate about higher ed
0:07:04 and making it more affordable and accessible.
0:07:07 Well, is that just an opinion or isn’t a value?
0:07:08 And the way you show it’s a value
0:07:10 is that you sacrifice for it.
0:07:13 And so I’m sort of overdue closing the gap
0:07:15 between everything I say and everything I do.
0:07:18 I need to, you know, I definitely talk the talk.
0:07:20 I need to walk the walk more.
0:07:22 And this is an attempt to do that.
0:07:24 – And with that, let’s share our opinions on the news.
0:07:26 Let’s start with a clear review of market vitals.
0:07:29 (upbeat music)
0:07:36 The S&P 500 had its worst stay since 2022.
0:07:39 The dollar was flat, Bitcoin declined,
0:07:40 and the yield on tenure treasuries fell,
0:07:42 shifting to the headlines.
0:07:44 Google reported second quarter earnings
0:07:47 beating analyst expectations on the top and bottom lines.
0:07:50 Operating profit crossed $1 billion for the first time ever.
0:07:53 However, the stock still fell 5%
0:07:54 due to concerns over heavy AI spending
0:07:57 and slowing YouTube ad sales.
0:07:59 Louis Vuitton and Dior owner LVMH
0:08:03 reported only a 1% increase in sales for the second quarter.
0:08:06 That is its lowest growth rate since 2009,
0:08:07 excluding the pandemic,
0:08:10 sales for fashion and leather goods also only rose 1%.
0:08:12 Nearly half of what analysts expected,
0:08:15 the stock fell more than 4% following that news.
0:08:19 And finally, Spotify hit 246 million premium subscribers
0:08:20 in the second quarter.
0:08:23 That’s up 12% from a year earlier.
0:08:25 Those subscriber numbers helped deliver a record profit
0:08:28 of just under $300 million.
0:08:31 Spotify stock rose as much as 16%.
0:08:34 Scott, your thoughts starting with Google earnings.
0:08:35 – I’ve been thinking a lot about Alphabet,
0:08:39 and I wonder if they’re still sort of semi stuck
0:08:40 in the innovators dilemma.
0:08:43 And that is the company’s LLM Gemini
0:08:47 gets about an eighth of the traffic of chat GPT.
0:08:49 When you think about the captive audience they have
0:08:52 between Android and search,
0:08:54 and the fact that a lot of the IP for AI
0:08:58 was actually developed at Alphabet,
0:09:01 are they really, have they really turned the fire hose
0:09:06 of their 3 billion captive consumer base to Gemini?
0:09:08 Or do they wanna have their cake and eat it too?
0:09:10 And that is the majority of the AI efforts
0:09:12 I have seen from Alphabet have been in the context
0:09:15 of a Google search and it has that kind of summary at the top.
0:09:18 But I don’t feel like I’ve had that much marketing
0:09:21 or that much incentive to use Gemini.
0:09:24 And I wonder if they’re still sort of protecting
0:09:25 or not going full force.
0:09:30 They haven’t burned the boats, so to speak.
0:09:34 And they’re busy sending out $23 billion offers to whiz
0:09:36 and buying back shares and issuing dividends, yeah.
0:09:38 – Their catbacks got hit hard this quarter
0:09:40 and what struck me immediately thought of Apple
0:09:42 that’s so smart not getting into this arms race.
0:09:45 They’re just gonna make sure they own access
0:09:46 to the billion wealthiest consumers
0:09:48 and then they’re gonna charge someone
0:09:50 like Alphabet or open AI ridiculous amount of money
0:09:53 to be the AI of iOS.
0:09:57 But their catbacks was hit 13 billion up 91%
0:09:59 from a year earlier.
0:10:01 Their total catbacks this year could be around 50 billion
0:10:04 which would be 84% higher than when the company
0:10:06 has averaged annually over the past five years.
0:10:09 I gotta think most of that was on AI
0:10:13 which was mentioned, get this 89 times on the earnings call.
0:10:17 YouTube, you know, Ad revenue still climbed 13%
0:10:19 so I think it’s pretty striking.
0:10:22 The thing we have to remember here is that Alphabet
0:10:25 and this is our big tech stock pick of 2024
0:10:26 so I’ve been tracking it.
0:10:28 Microsoft year to date is up 16%
0:10:30 for all of the excitement about that stock.
0:10:34 Amazon’s up 21% but Alphabet ad is up 25%.
0:10:37 So they’re doing really well
0:10:39 and it just strikes me when the analysts,
0:10:42 the analysts zero in on the negatives here
0:10:44 but the company is still doing really well.
0:10:45 What are your thoughts?
0:10:46 – I completely agree with you.
0:10:48 I think people are so obsessed with this idea
0:10:52 that they’re behind on AI which is probably true
0:10:54 when you compare it to Microsoft.
0:10:56 But as with anything, you have to look at the big picture
0:11:00 here and the big picture for Google is extremely compelling.
0:11:02 Search revenue is up 14%.
0:11:05 People thought that chat, GBT and AI
0:11:07 would be eating into that revenue.
0:11:08 It hasn’t hurt it at all.
0:11:12 In fact, you know, search is chugging along just fine,
0:11:13 better than fine.
0:11:16 Cloud revenue up 29%.
0:11:18 I think that was expected.
0:11:20 And as you mentioned the YouTube revenue,
0:11:24 people didn’t like the 13% jump in YouTube revenue.
0:11:27 It’s coming off an insanely high base.
0:11:28 And I think they’re just comparing it
0:11:29 to the previous quarters
0:11:33 where they were getting 20 plus percent growth
0:11:34 which is already insane.
0:11:36 I just wanna point this start out.
0:11:39 YouTube ads, just the ads alone,
0:11:42 they are now bringing in on an annualized basis,
0:11:45 $35 billion per year,
0:11:50 which is higher than Netflix’s total revenue last year.
0:11:52 And it doesn’t even include all the paid subscriptions
0:11:56 they get from YouTube premium and YouTube TV.
0:12:00 So I just think it’s remarkable what YouTube has done.
0:12:02 We have been saying this for a while.
0:12:04 I continue to believe that YouTube
0:12:07 is the most underrated media asset in the world.
0:12:10 And I think if you just stack all those things up,
0:12:14 there’s so much reason to be optimistic about Google.
0:12:14 – Well, the market agrees with you.
0:12:17 And I’ve always, the thing I’ve said about Alphabet
0:12:20 for a long time is that it has the greatest concentration
0:12:22 of IQ since NASA.
0:12:24 And the team of the best players wins
0:12:28 and Alphabet consistently finds the tracks
0:12:31 and retains some of the best players.
0:12:32 It’s an incredible company.
0:12:36 I think it’s, you have to admire their management
0:12:38 and what they built there.
0:12:41 – As we went to LVMH, thoughts on these earnings
0:12:42 that were a disappointment.
0:12:47 – LVMH is sort of the quote unquote bellwether for luxury.
0:12:51 And what’s ailing them is kind of what’s ailing
0:12:52 every luxury firm.
0:12:55 And that is that Asia or specifically China
0:12:58 is no longer the gift that keeps on giving.
0:13:00 And if you were overexposed to China,
0:13:05 it was champagne and cocaine from like 2000 to 2018.
0:13:08 And Estee Lauder went through the roof and, you know,
0:13:11 North Face, it took North Face, I think 20 years
0:13:12 or 30 years to get to a billion in sales.
0:13:14 It took him 18 months in China.
0:13:18 I mean, the shit was just selling before it even got
0:13:20 offloaded from ships, right?
0:13:24 And last year, it’s about one in six purchases globally
0:13:27 of luxury happened in China.
0:13:30 But the Chinese economy is showing signs of weakness.
0:13:32 High net worth families in China reduced their annual
0:13:34 spending by 11% last year.
0:13:37 And you want to talk about just an incredible shift
0:13:39 in fortunes, Chinese stocks have lost 6 trillion
0:13:40 over the past three years.
0:13:43 That’s twice the GDP of the United Kingdom.
0:13:45 The S&P over the last five years has doubled.
0:13:46 It’s up 100%.
0:13:49 India 65, Japan 25, Europe 24.
0:13:52 China is down 30%.
0:13:56 So if, I don’t know what it was, if China was 10 trillion
0:14:00 and we were 25 trillion, we went to 50 and they went to seven.
0:14:03 I mean, LVMH gets about a third of its revenues from China.
0:14:06 So if that’s down 15%, that means of our revenues
0:14:08 are going to be down 5%.
0:14:09 I wonder if it’s a buying opportunity.
0:14:11 It’s such a well-run company.
0:14:13 They have such incredible brands.
0:14:15 But this is just simply put, their biggest customer,
0:14:18 it doesn’t have as much money as they used to.
0:14:20 I’ll also add, it’s very interesting.
0:14:25 I think this is another nice example of these ripple effects
0:14:27 that we often talk about in the markets,
0:14:32 where what started out as basically a real estate crisis
0:14:34 in China that began with Everground
0:14:37 has morphed into a larger issue in China.
0:14:40 It has reverberated throughout the world.
0:14:44 And it’s now worming its way onto the income statement
0:14:49 of a French luxury fashion house, which is LVMH.
0:14:51 And so it’s a very interesting dynamic going on here.
0:14:54 Having said all that, I think your point
0:14:56 that it could be a buy is a good one,
0:14:58 because this company is not in crisis.
0:15:01 I mean, the stock is down this year,
0:15:05 down 10% year to date, coming off some crazy highs
0:15:08 where you saw or know becoming the wealthiest man
0:15:09 in the world.
0:15:11 So yeah, I don’t think this is an organizational issue
0:15:13 with LVMH.
0:15:14 This is a regional issue.
0:15:15 It’s a problem with China.
0:15:17 – So, but let’s just look at the stock.
0:15:21 Over the last five years, the stock’s up 66%.
0:15:24 I mean, it’s just, and then the one
0:15:28 that just absolutely flummoxes me as Hermes
0:15:32 has a market cap of 213 billion euros,
0:15:34 which is about 240 billion.
0:15:35 – Unbelievable.
0:15:37 – So I think luxury is gonna continue.
0:15:39 I think it’s ridiculous.
0:15:41 This notion that young people aren’t as fascinated
0:15:43 by luxury as my generation,
0:15:44 and their ability to command margins
0:15:46 once they get to sort of that iconic status.
0:15:48 And they also, and I’ll wrap up here,
0:15:49 they have an incredible mode
0:15:53 ’cause the majority of luxury brands have heritage.
0:15:55 You just can’t spin up heritage.
0:15:56 You can have a brand like Supreme
0:15:59 that becomes aspirational for a while.
0:16:03 But these brands, Panerai was initially crafted
0:16:07 for Italian submariners.
0:16:09 I mean, this shit is just Louis Vuitton
0:16:12 trekked into Paris on barefoot and said,
0:16:16 “Okay, it makes no sense that these carriages
0:16:18 “are carrying suitcases that are rounded at the top
0:16:21 “and have leather that attracts moisture and mold.”
0:16:24 So luxury is really rooted in innovation.
0:16:27 I think it was at L’Oreal or was it,
0:16:31 I forget who, initially, it was a German chemist
0:16:35 who went to the fields of the South of France
0:16:37 and found a way to crush these flowers
0:16:39 and turn them into a fragrance.
0:16:40 I mean, this shit, it really is rooted.
0:16:43 It was innovation before there was innovation
0:16:46 as we saw it in terms of technology wasn’t fact luxury.
0:16:47 Anyways, that’s my rant on luxury.
0:16:50 – Coco Chanel defined luxury as the following.
0:16:54 Luxury is a necessity that begins when necessity ends.
0:16:57 I thought that was sort of the perfect encapsulation
0:17:00 and a great explanation of why, yes,
0:17:03 we will always worship luxury no matter what we say.
0:17:07 We’ll find a way to find necessities when necessity ends.
0:17:11 – Yeah, she also said the opposite of luxury is not poverty,
0:17:14 it’s vulgarity, which I love.
0:17:16 And she also said, “I love that Nazi dick.”
0:17:20 She said that too, and she said that too.
0:17:21 – Oh, okay.
0:17:22 – Is that fair?
0:17:23 Is that fair?
0:17:25 It’s pretty easy to tell I’m no longer working
0:17:27 for a company that caters to luxury brands.
0:17:29 By the way, Chanel’s an amazing company
0:17:31 with amazing people, sorry about that.
0:17:33 – Yeah, that’s why you’re getting sent clothes
0:17:35 from Nike and not Louis Vuitton.
0:17:37 – I’ve used Chanel moisturizer.
0:17:38 I use Chanel blue.
0:17:39 It’s what I bought actually
0:17:41 when my son was headed back to boarding school.
0:17:44 I always do a little bit of a shopping ritual for him.
0:17:46 And I’m like, this shit is gangster.
0:17:48 You gotta put a little of this on.
0:17:52 And I use Chanel blue moisturizer.
0:17:53 Anyway, it sells lovely.
0:17:55 Masculine, yet feminine at the same time.
0:17:56 – It’s fascinating.
0:17:59 I’m glad everyone’s getting to hear this.
0:18:03 Let’s move on to Spotify, who had a great quarter.
0:18:06 Monthly active uses up 14%, revenue up 20%,
0:18:09 profits up 45%, record profits for the company,
0:18:11 your thoughts on Spotify.
0:18:13 – If you think about what Spotify has accomplished,
0:18:14 it’s singular.
0:18:16 They’ve taken an entire medium
0:18:20 and distilled it to a single icon on your phone
0:18:22 that is searchable and very user friendly.
0:18:23 No one’s done that on TV.
0:18:26 No one’s done that in books.
0:18:27 I think it’s a great value.
0:18:29 I think they do a fantastic job.
0:18:30 In sum, I think it’s a great company.
0:18:31 And they were also pretty bold.
0:18:34 They went all in and gave the artists and labels
0:18:35 a disproportionate amount of the revenues.
0:18:36 They basically lost money.
0:18:39 They were more like a collective or cooperative,
0:18:40 just taking money and distributing it
0:18:42 to the record labels and the artists.
0:18:43 But once they got scale,
0:18:45 and once they kind of not consolidated the industry,
0:18:47 but had a large enough share where they could start,
0:18:51 they had the pricing power to improve or increase prices
0:18:52 and their subscribers can go down.
0:18:55 And basically, essentially what they have figured out
0:18:58 is that they have more pricing power than they thought.
0:19:00 And despite increasing prices,
0:19:03 they have increased their revenue.
0:19:07 So revenue from premium users increased 21%.
0:19:09 And premium subscribers accounted for 95%
0:19:12 of Spotify’s gross profit over the last 12 months.
0:19:13 The thing that doesn’t work
0:19:16 or the thing I saw in this earnings call
0:19:20 or in these numbers is I think both Netflix and Spotify,
0:19:23 I think the advertising does not work for them.
0:19:27 And I remember being like in 2000,
0:19:30 like the early 2000s, I think I was on a date or whatever.
0:19:32 I had some people over
0:19:33 and I was trying to impress these people
0:19:36 and I was at my loft.
0:19:39 I know it’s horrifying to think of me as single.
0:19:41 And I remember I had music on
0:19:43 and things were going really well.
0:19:46 And all of a sudden it dawned on me
0:19:50 like some really bad ad for like pets.com or something
0:19:50 that came up. – Oh no.
0:19:51 – And I’m like, oh my God,
0:19:53 no one’s ever gonna have sex
0:19:55 with the ad supported Pandora guy.
0:19:58 And I literally thought having ad supported Pandora
0:20:01 was just gonna ruin no matter
0:20:04 how many Panoras I had or how I was trying.
0:20:09 When the pets.com ad comes on on Pandora radio, it’s over.
0:20:13 Everyone’s like, well, it’s getting late, it’s getting late.
0:20:16 But what I saw in the Netflix earnings call
0:20:21 and in this one is that it’s just the ad supported ecosystem
0:20:24 is having a really difficult time.
0:20:26 I think it gets in the way of storytelling.
0:20:28 And I think this earnings show is just that
0:20:31 basically it’s subscribers that are
0:20:34 what 95% of Spotify’s gross profit.
0:20:36 – One other thing I found really interesting
0:20:39 was how the CEO, this guy Daniel Eck,
0:20:40 announced these earnings.
0:20:43 And that is before the official earnings call,
0:20:46 he posted on Twitter and on Instagram
0:20:48 what was essentially like a TikTok video.
0:20:50 It was like a two minute selfie video
0:20:53 where he just spoke directly at the camera
0:20:55 and ran through all of the headline numbers
0:20:57 in the earnings report.
0:21:00 I think he started doing this around Q4 of last year.
0:21:03 This is kind of his calm strategy.
0:21:04 I’d like to get your take.
0:21:07 I will just say, I think it’s such a good idea
0:21:09 because in a weird way,
0:21:13 the way most people consume earnings news,
0:21:16 it isn’t actually from the company earnings calls.
0:21:17 It’s from media companies.
0:21:20 It’s from like CNBC or the Wall Street Journal
0:21:23 or even you might get it from listening to this podcast.
0:21:25 You’re rarely hearing from the CEO.
0:21:27 But this strategy is such an obvious one.
0:21:29 Just post directly to social media.
0:21:31 That sort of fixes it.
0:21:35 It’s a small detail, it’s a small innovation.
0:21:38 But I would predict that this is gonna become the norm.
0:21:40 I think you’re gonna see lots more CEOs
0:21:42 posting on social media these selfie videos
0:21:44 about their earnings in the next few months.
0:21:45 – I think that’s really interesting.
0:21:46 I didn’t know that.
0:21:49 You can see them bypassing kind of the
0:21:50 analyst industrial complex
0:21:52 with the CNBC industrial complex
0:21:57 and doing a video kind of timed well, choreograph tweets.
0:21:59 And then maybe doing like Instagram live
0:22:01 to do their analyst calls, right?
0:22:04 To say, all right, I’m going live to answer your questions.
0:22:06 There’s some choreography around SEC
0:22:11 and when you release non-public material information
0:22:12 that they gotta be careful of.
0:22:13 But I think you’re right.
0:22:15 I think that that might be,
0:22:18 ’cause what you want is you wanna get more people
0:22:21 just as you wanna garner more consumers,
0:22:23 so a consumer brand wants to get new consumers
0:22:26 into the franchise, get new customers.
0:22:28 The company wants to get new investors.
0:22:31 And they also, what never goes out of style
0:22:32 is they all want to be known for having
0:22:34 an innovative product that’s differentiated
0:22:36 and that they’re good at what they do
0:22:37 and they’re competent.
0:22:39 But what they really want more than anything
0:22:41 is they want some of that innovative pixie dust
0:22:42 poured all over them.
0:22:45 So communicating your earnings via a video
0:22:48 that’s posted to YouTube and then spliced up
0:22:51 for TikTok or what have you.
0:22:52 And then doing some of this live stuff
0:22:53 on some of these platforms
0:22:55 that just sort of screams of innovation.
0:22:59 – Yeah, I can’t understand how PR firms or PR teams,
0:23:00 I should say, at these public companies
0:23:01 haven’t gotten on this.
0:23:02 – It’s weird to think this,
0:23:07 but I would bet within five years, 10 years max,
0:23:10 a key component of your, of boards deciding
0:23:12 whether they’re making someone CEO
0:23:15 is how strong is their following.
0:23:17 Basically as the CEO, your job is to attract
0:23:18 and retain the best talent
0:23:20 and set a vision for the company.
0:23:22 But as much or more than anything now,
0:23:25 it’s your ability to tell a story or craft a narrative.
0:23:28 The results and access to cheaper capitals
0:23:30 such that you can invest at a greater rate
0:23:32 than your competitors and pull away from them.
0:23:35 Anyways, I’m 100% with you
0:23:39 and I would bet your, the next generation of CEOs
0:23:40 are ones that come armed
0:23:43 with pretty decent followings on social media.
0:23:46 – We’ll be right back after the break
0:23:47 with a look at Tesla.
0:23:50 (upbeat music)
0:23:59 Support for property markets comes from Fundrise.
0:24:00 Venture Capital is widely seen
0:24:03 as one of the most lucrative asset classes in the world.
0:24:04 Go look at the S&P 500,
0:24:07 nearly every major tech company on that list
0:24:09 was once funded by venture capital firms
0:24:13 producing billions of dollars in profits in the process.
0:24:14 The hard truth, however,
0:24:15 is that the biggest venture funds
0:24:18 are almost entirely funded by institutional investors
0:24:20 like endowments and sovereign wealth funds.
0:24:22 So unless you knew a guy who knew a guy,
0:24:25 you and 99.9% of individual investors
0:24:28 did not get to participate in the pre IPO growth
0:24:31 of any of those blue chip companies.
0:24:32 And it’s happening again.
0:24:34 AI is making waves everywhere right now,
0:24:36 except your portfolio.
0:24:38 Some of the biggest names in AI
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0:24:56 Go to fundrise.com/markets to learn more.
0:24:58 Carefully consider the investment material
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0:25:03 This and other information can be found
0:25:05 in the Innovation Funds Prospectus
0:25:07 at fundrise.com/innovation.
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0:26:55 – We’re back with ProfG Markets.
0:26:58 Tesla’s second quarter profits fell 45% year-over-year,
0:27:01 declining for the second quarter in a row.
0:27:02 The company also posted its lowest
0:27:05 quarterly profit margin in five years
0:27:07 and its second consecutive sales decline.
0:27:10 Tesla did not offer a fresh sales target for the year,
0:27:13 but it did warn that its vehicle volume growth rate
0:27:16 would be, quote, “notably lower than 2023.”
0:27:20 The stock fell 12% after the earnings call,
0:27:22 Scott reaction to Tesla’s earnings.
0:27:26 – I think the analogy here is this market feels very similar
0:27:29 in some ways and not in others to the streaming market.
0:27:32 And that is Tesla basically had the market
0:27:33 to themselves similar to Netflix
0:27:37 through the odds in the 2010s.
0:27:39 And that is, if you were gonna buy an EV,
0:27:40 you were really gonna buy a Tesla.
0:27:42 It was kind of like Tesla in the ’70s.
0:27:44 No one was gonna buy a Pontiac Leaf
0:27:46 or whatever the heck it was called, right?
0:27:48 And so they sort of owned it.
0:27:51 And then the stock market just reacted so positively
0:27:56 to Tesla and gave them sass-like, tech-like multiples
0:27:59 that everyone in the auto industry said,
0:28:01 “Okay, we gotta get into this.”
0:28:03 And they announced, you know, Mary Barra announced
0:28:07 that half the cars sold from GM were gonna be electric
0:28:11 within a certain time, Rivian spin up, you know,
0:28:14 Fisker, all these startups kind of spun up.
0:28:18 And there was essentially what happened in the EV race
0:28:19 is what happened in streaming.
0:28:22 That is, it would became over-invested.
0:28:25 And the manifestation of that over-investment
0:28:29 is that a year ago, an EV, an electric-powered vehicle,
0:28:31 was $8,500 more expensive
0:28:33 than its internal combustion equivalent.
0:28:37 As of today, it’s only $1,500 more expensive.
0:28:39 And in some instances, it’s less expensive.
0:28:43 So the F-150 Lightning, that is now $10,000.
0:28:46 The electric version is $10,000 less
0:28:48 than its internal combustion brother.
0:28:49 And I will say brother,
0:28:51 that’s a pretty much a fucking car.
0:28:52 That shit has real balls, Ed.
0:28:54 That shit has balls.
0:28:57 Bottom line is this is classic economics.
0:28:59 Over-investment, because of the market
0:29:01 giving an above market multiples,
0:29:04 that over-investment results in a price war.
0:29:06 And then I think you combine that with,
0:29:09 Tesla’s products feel a little bit dusty right now.
0:29:10 They don’t feel that.
0:29:14 I mean, by the way, I drove in a matte black Cybertruck.
0:29:15 – No way.
0:29:17 – Yeah, a friend of mine is this total master,
0:29:19 the universe baller hedge fund guy,
0:29:20 and he invited me out to his house.
0:29:24 I went out there last weekend and his house manager
0:29:27 picked me up in a matte black Cybertruck.
0:29:28 – No way.
0:29:29 – And I’m like, I am literally
0:29:32 the douchiest douche in Douchville right now.
0:29:33 – How did it feel on the inside?
0:29:34 ‘Cause I kind of agree with you.
0:29:38 I think Tesla’s feel very cheap on the inside.
0:29:41 Did it feel cheap on the inside or did it feel cool?
0:29:42 – No, I felt modern and very techy,
0:29:46 but on the way back, we drove in his Range Rover
0:29:48 and I thought that was just much nicer.
0:29:50 I think the car, quite frankly,
0:29:51 I think the Cybertruck is fucking ridiculous.
0:29:54 I think it looks like something Homer Simpson
0:29:55 would have designed after watching
0:29:58 Battlestar Galactica for 48 hours straight.
0:30:02 I think it’s just so stupid looking and weird looking.
0:30:05 And the inside was very,
0:30:08 it felt like you’re on a set of a movie about the future,
0:30:12 but you would never fucking actually own this car.
0:30:15 And people were coming up and stopping and talking to us
0:30:18 because they were so interested.
0:30:20 It looked like the Batmobile,
0:30:23 but I don’t, I think that thing is a giant thought,
0:30:25 although I guess, have you heard anything
0:30:26 about the sales of this thing?
0:30:29 – I don’t think they’ve broken out the sales
0:30:30 for the Cybertruck yet,
0:30:34 but I think the consensus is that orders are underwhelming
0:30:36 and they’re sort of struggling to keep up.
0:30:39 – The other thing that strikes me about Tesla is that,
0:30:41 if you think about pure meme stocks,
0:30:43 like the memiest of meme stocks,
0:30:45 a meme stock is a stock who’s, in my opinion,
0:30:48 is stock is totally disassociated
0:30:50 from the underlying fundamentals of a company.
0:30:53 It’s like the ketamine of the market, if you will.
0:30:56 And the ultimate meme stock is, hands down,
0:30:58 Donald Trump media.
0:31:01 It’s got a $6 billion market cap,
0:31:04 even after declining 30% in the last week,
0:31:07 and it’s like 7 million in revenues and 300 million.
0:31:08 The company makes no fucking sense.
0:31:11 It’s basically people have decided it’s a proxy
0:31:14 for your support of or your belief
0:31:18 or the probability that Trump is elected president.
0:31:20 And it trades on kind of sentiment and emotion
0:31:22 as nothing to do with the underlying business.
0:31:24 Halfway between a stock that trades
0:31:25 on its underlying fundamentals,
0:31:28 like an alphabet or 99% of stocks,
0:31:30 and Trump, which is a Trump media,
0:31:32 which is a total meme stock,
0:31:35 I think in near meme stocks would be like AMC and GameStop.
0:31:36 They’re shitty businesses,
0:31:38 and they trade much greater multiples than they should
0:31:40 ’cause people think there’s a chance they’ll go crazy again
0:31:43 because of Roaring Kitty or whatever.
0:31:46 I think perfectly in the middle of that continuum
0:31:50 is Tesla, because to be fair, it’s an amazing company.
0:31:54 It inspired the EV race, they do have great products.
0:31:57 Their energy unit is making money.
0:32:00 The idea of a robotex is compelling,
0:32:01 we’ll come back to that.
0:32:05 But Tesla trades at 99 times forward earnings.
0:32:08 This is in contrast to Ferrari,
0:32:10 an amazing brand that a lot of people want
0:32:12 to kind of singular in terms of prestige
0:32:13 and self-expressive benefit.
0:32:16 That trades at 50 times.
0:32:18 Ford trades at seven times and GM get this ad,
0:32:20 trades at five times forward earnings.
0:32:24 So great company, but should it trade
0:32:26 at double the multiple of Ferrari
0:32:29 and 20 times the multiple of General Motors?
0:32:33 So this is sort of the term I would use,
0:32:35 is it as it relates to meme stocks
0:32:37 that Tesla is a hybrid?
0:32:38 – To Prius.
0:32:38 – Yeah, it’s a great company,
0:32:42 but it can’t really justify the multiple it’s at.
0:32:43 And then what I’ll end up with,
0:32:45 and this will come back to our prediction,
0:32:49 is that just as Donald J. Trump media became
0:32:52 an index for whether or not Trump got reelected,
0:32:55 I think these guys, these techno-libertarian weirdos,
0:32:57 really fucked up by coming out
0:33:00 so forcefully in favor of Trump.
0:33:01 Because what they’ve done is,
0:33:04 is they’ve tied themselves and their businesses
0:33:07 to the re-election of Donald Trump.
0:33:11 And as the likelihood of a vice president,
0:33:15 a Kamala Harris becomes more likely,
0:33:16 and it’s become much more likely
0:33:18 just in the last five days,
0:33:19 I think people are gonna go,
0:33:21 well, who is this gonna hurt?
0:33:22 And I think one,
0:33:24 it’ll put pressure on Bitcoin prices,
0:33:25 because they’ll say, okay, maybe Bitcoin
0:33:27 isn’t gonna be totally deregulated
0:33:29 and become the ultimate stablecoin,
0:33:33 or whatever the right term would be good for Bitcoin.
0:33:35 But also I think people are gonna soon learn
0:33:37 or soon figure out,
0:33:38 if it’s a Harris administration,
0:33:43 they may not be inclined to put tariffs on BYD.
0:33:47 They may not be as inclined to give subsidies
0:33:49 that would include Tesla,
0:33:51 or give subsidies that might exclude
0:33:52 some of the Tesla models.
0:33:55 I just, I think people are gonna start connecting the dots
0:33:58 that when you go all MAGA Musk,
0:34:00 there’s some risks there.
0:34:02 And I think that risk will start to show up
0:34:04 in some pressure on the stock
0:34:06 as a little bit of a meme stock
0:34:10 tracking Trump’s election or lack thereup to the White House.
0:34:12 – You mentioned the RoboTaxi,
0:34:13 which we should definitely talk about.
0:34:15 It was supposed to come out,
0:34:19 or the RoboTaxi model was supposed to be unveiled in August.
0:34:21 And then on this earnings call,
0:34:23 Elon delayed it to October.
0:34:28 And that’s, I think, a big reason why the stock fell.
0:34:31 He’s been saying that full self-driving
0:34:35 is coming next year for literally a decade.
0:34:39 So, he’s delayed the unveiling again.
0:34:41 Supposedly it’s coming out in October now.
0:34:43 One sort of tangential point
0:34:46 I’d like to get your reaction to in terms of this,
0:34:50 when will this RoboTaxi ever arrive discussion?
0:34:53 I was speaking with an AI founder recently,
0:34:55 and he actually started his career
0:34:57 as an engineer at an autonomous vehicle company.
0:35:01 And that episode will be coming out in first time founders.
0:35:03 And he made a really interesting point,
0:35:07 which is that we tend to think of self-driving cars
0:35:11 as its own sort of separate, very specific technology.
0:35:13 But in reality, as he pointed out,
0:35:16 self-driving cars is just AI.
0:35:18 And his point is that, you know,
0:35:23 right now is the big AI moment, 2024 is the year of AI.
0:35:24 And so logically speaking,
0:35:26 you would think that if we’re in the AI moment,
0:35:30 we’re about to witness the self-driving moment too.
0:35:32 I think it’s a strong case for why
0:35:35 the Tesla RoboTaxi might actually,
0:35:37 it actually will arrive this year,
0:35:38 despite all of Elon’s bullshit.
0:35:40 And I’m wondering if you agree.
0:35:42 I have no idea.
0:35:43 I just know that it’s the thing
0:35:45 that’s supposed to be around the corner.
0:35:47 And then you look around the corner and it’s not there.
0:35:48 And you also have Waymo,
0:35:51 you also have a lot of competitors in the space
0:35:54 in order to really, I’m taking this through,
0:35:58 in order to capture incremental margin
0:36:01 that results in this type of increase in earnings,
0:36:06 you would have to have Teslas that were more AI enabled,
0:36:09 or had more automated driving technology
0:36:10 than any other car.
0:36:14 Is Tesla that far ahead of the other self-driving technology
0:36:16 such that they could capture that innovation
0:36:17 just for Teslas?
0:36:19 I don’t, there’s two things here.
0:36:20 When does this happen?
0:36:23 And also, what would Tesla’s ability be
0:36:26 to capture the economics of that innovation
0:36:29 versus any other company?
0:36:31 Just before we wrap up on this,
0:36:33 we spend all this time ragging on Tesla.
0:36:36 Let’s try to think a bit more positively.
0:36:39 Say you were on the board of Tesla.
0:36:42 And let’s be clear, the business is struggling.
0:36:45 Revenue rose, but it only rose 2%
0:36:47 and profits fell 45%.
0:36:49 It’s dealing with a lot of issues.
0:36:52 You know, it’s market share in the EV space in America
0:36:54 is down to 50%.
0:36:56 Four years ago, that number was 80%.
0:36:59 So we’re not being biased by saying that Tesla’s,
0:37:02 Tesla as a business is struggling.
0:37:04 What would you be focusing on
0:37:06 if you were trying to improve this business
0:37:07 and you were on the board?
0:37:08 Okay, so if we’re gonna imagine we’re on the board,
0:37:10 I’m gonna imagine that I’m dating Tom Brady
0:37:13 and he runs his hands through my share like thick hair.
0:37:15 I mean, if we’re really gonna imagine,
0:37:17 if we’re really gonna hallucinate, let’s go full.
0:37:20 Let’s go full psilocybin and with a kicker
0:37:22 of like nine shots of something.
0:37:25 Okay, I’m on the board of Tesla.
0:37:28 Oh, that’s a good one.
0:37:29 Where would I be focused?
0:37:32 I think I’d be, I mean, this sounds boring,
0:37:35 but I think their energy stuff is pretty cool.
0:37:37 Totally, by the way, that business doubled.
0:37:39 Yeah, doing pretty well there.
0:37:42 I mean, it sounds really base.
0:37:44 I guess I don’t have anything creative here.
0:37:47 I’d be focused on freshening the model lineup
0:37:49 and then I would probably,
0:37:52 I would probably, for the robotaxi stuff,
0:37:55 I would have probably acquired Lyft
0:37:56 and have a built-in base and user base
0:37:58 of people who are comfortable with ride hailing.
0:38:00 They should acquire pellets all in there.
0:38:01 Yeah, there you go.
0:38:03 That’s right, that was my favorite for a while.
0:38:06 They’re definitely being acquired, says ProcG.
0:38:09 We’ll be right back after the break
0:38:12 with a look at a tobacco company’s recent success.
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0:38:59 on your nightstand.
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0:39:03 and it’s an even better thing
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0:39:23 – We’re back with ProcG Markets.
0:39:25 Shares of Philip Morris International
0:39:27 hit their highest level in more than two years
0:39:30 after a red hot product propelled the tobacco company
0:39:32 to a better than expected earnings report.
0:39:34 That product is ZIN.
0:39:37 ZIN is a nicotine pouch that you absorb through your gums
0:39:39 and they’re so popular that there’s been
0:39:41 a nationwide shortage of them this summer.
0:39:44 Philip Morris, which acquired ZIN in 2022,
0:39:47 said sales of the pouches rose 50% year over year.
0:39:51 Overall sales in its smoke-free category rose 24%
0:39:54 and total revenue for the company rose 10%.
0:39:58 Scott, what do you make of this new ZIN trend
0:40:00 that Philip Morris has managed to capture
0:40:02 and that is benefiting this company?
0:40:02 – I think it’s really interesting.
0:40:06 I think all the ZIN guys are trying to figure out a way
0:40:09 to go sort of near ZIN and that is,
0:40:11 my understanding of ZIN is that I want to be clear,
0:40:13 this shit is not good for you.
0:40:18 Don’t pick it up if you don’t have an addiction to nicotine,
0:40:23 but it’s a much less damaging means of delivering nicotine
0:40:26 than chewing tobacco.
0:40:29 And just full disclosure, I have some background here.
0:40:31 I invested in a company being pulled out of bankruptcy
0:40:35 called EnJoy, which is an electronic nicotine delivery
0:40:37 system better known as vaping.
0:40:42 And I think I did it in 2015 or ’16, a long time ago.
0:40:45 And one of the reasons I invested was my mother died
0:40:48 of a smoking-related illness and I’d had two friends
0:40:50 who’d quit smoking using EnJoy.
0:40:53 And just as combustibles are going away,
0:40:55 every year they’re down like five or eight percent.
0:40:57 One in three people who buy a pack of cigarettes,
0:41:00 let’s get this, says this is their last pack
0:41:02 they’re ever gonna buy, one in three.
0:41:04 It’s the largest source of preventable death
0:41:06 in the United States and it’s going away.
0:41:08 People are getting the memo here.
0:41:11 Long story short, we pulled this company out of bankruptcy.
0:41:13 I think we bought it for 60 or 70 million,
0:41:14 put a bunch of money into it.
0:41:16 It was basically a regulatory play.
0:41:18 I think we invested another 100 million in it
0:41:20 to try and get FDA approval and show that
0:41:22 we’re good players, we’re not jewel,
0:41:23 we don’t have a youth problem.
0:41:27 Anyways, seven, what it was, seven, nine years later,
0:41:31 we got acquired for 2.8 billion by Philip Morris.
0:41:34 – Sorry, was it, ’cause there’s Altria,
0:41:36 which used to be Philip Morris,
0:41:38 and then there’s Philip Morris International,
0:41:41 which is the international segment
0:41:44 that was spun out of Altria several years ago.
0:41:47 So that’s just one little wrinkle in this story.
0:41:49 Do you know if it was Altria or Philip Morris International
0:41:50 that acquired you?
0:41:51 – It was Altria, so you’re right,
0:41:53 it’s technically a different group,
0:41:54 ’cause there’s different dynamics
0:41:56 and I guess they figured they could get more money.
0:41:58 – Yeah, and they’re totally separate companies now,
0:41:59 but at one point it was–
0:42:01 – They were the same people.
0:42:02 My favorite though is they changed the name to Altria,
0:42:04 thinking that people would like them more.
0:42:05 They would forget about all the death disease
0:42:07 and disability that they’d spread around the world.
0:42:08 – You don’t think it worked?
0:42:11 – I don’t like name changes
0:42:13 when you’re trying to escape from something.
0:42:16 I don’t think it made any sense.
0:42:19 Anyways, but the thing that really struck me,
0:42:21 I think I told you this, I went to Summit at Sea
0:42:23 with all these young and up-and-coming,
0:42:28 vertical farming, it’s like, I call it learning man,
0:42:29 it was TED Talks during the day
0:42:31 and then at night everyone did their drugs
0:42:33 with a DJ and pretended they were interesting
0:42:35 and thoughtful people, ’cause they’d gone to a talk
0:42:40 during the day on like AI and fashion.
0:42:41 That’ll be riveting.
0:42:46 Anyways, so, but the thing that struck me
0:42:48 was it was on this Virgin cruise ship
0:42:50 and I went up in order to make her some ginger at the bar
0:42:52 and he was like, “Oh my God, finally someone’s drinking.”
0:42:53 And I said, “What do you mean?”
0:42:55 None of these kids drank, they’re all doing drugs.
0:42:57 And I noticed that everybody,
0:43:00 the drug of choice was mushroom chocolates
0:43:01 and then everyone buys one drink
0:43:03 and just nurses it all night
0:43:05 and that alcohol is really,
0:43:08 well, Axel, I’ll turn this question back to you.
0:43:12 You’re young and now for a young person,
0:43:15 what is going on with the trend of substance abuse,
0:43:18 both tobacco and alcohol and drugs
0:43:21 and I won’t ask you to say what you do,
0:43:22 but what do your friends do?
0:43:24 – Yeah, that’s exactly right.
0:43:25 Everyone stopped drinking.
0:43:27 I mean, here are the statistics.
0:43:32 Non-alcoholic beer sales increased 28% last year
0:43:33 and then two, probably more importantly,
0:43:38 Gen Z drinks 20% less alcohol per capita
0:43:39 than millennials did at their age.
0:43:41 I’d love to see the difference between the millennials
0:43:44 and the boomers, probably like 100% less.
0:43:46 But the thing that, you know,
0:43:48 what we should be talking about with this story
0:43:50 is this new obsession with Zinn.
0:43:52 And yeah, it’s a nicotine pouch.
0:43:55 It’s similar to chewing tobacco, but without the tobacco.
0:43:58 Supposedly it doesn’t cause cancer,
0:44:01 but like the vapes, we just don’t have enough data
0:44:04 to say it causes or doesn’t cause it,
0:44:07 but it’s extremely popular everywhere.
0:44:09 Zinn sales are up 80% earlier this year.
0:44:11 It’s now around 50%.
0:44:15 An expected 580 million cans will be sold this year.
0:44:18 And as I mentioned, there is a Zinn shortage in the US.
0:44:21 So now Philip Morris is spending $600 million
0:44:24 on a manufacturing facility in Colorado
0:44:26 just to keep up with demand.
0:44:28 Final anecdotal evidence I will offer,
0:44:30 most of my friends use Zinn.
0:44:31 – Really?
0:44:35 – Yes, none of the women, all the men,
0:44:38 especially the tech bros and especially the bankers.
0:44:43 This is sort of a phenomenon in the world of nicotine.
0:44:48 So it’s massively popular.
0:44:51 I think the question is, do you wanna get in on it
0:44:52 as an investment?
0:44:54 I mean, Philip Morris International is trading
0:44:58 at 20 times earnings, which is pretty high.
0:45:01 It’s double alters PE ratio at the moment.
0:45:03 I think the market is correctly recognizing
0:45:08 that Zinn is an absolute rocket in the nicotine industry.
0:45:10 But I will throw this back to you.
0:45:12 One, do you like this as an investment?
0:45:15 Two, do you have any ethical concerns
0:45:17 about investing in a company
0:45:20 that sure offers tobacco alternatives,
0:45:22 that also sells tobacco?
0:45:23 – I think it’s easy to be a purist
0:45:26 and lecture other people after you’re already rich.
0:45:28 I think people have an obligation
0:45:31 to develop economic security for themselves.
0:45:32 Like I used to own Facebook stock
0:45:34 and I got so much shit for it
0:45:35 ’cause I’m constantly saying, you know,
0:45:38 Mark and Cheryl have done more damage to the world
0:45:40 or teens and anyone like, but you own the stock.
0:45:41 So I sold the stock.
0:45:43 But I don’t have a problem with owning Zinn stocks.
0:45:47 I don’t, my attitude is, you know,
0:45:49 if you really have a moral,
0:45:53 if you really are against it, then fine, do what you want.
0:45:57 But my observation is that the companies
0:45:58 that are, quote unquote, ruining the world
0:46:00 generally have the nicest people
0:46:02 and are the best run companies.
0:46:04 So I did work for fossil fuel companies
0:46:07 and my first company, Profit, the people at Chevron,
0:46:12 the people at Exxon, so nice, such a well run company.
0:46:14 I’ve worked with people at gaming companies,
0:46:16 you know, the casino guys,
0:46:19 incredibly professional, incredibly well run.
0:46:21 Walk into Altria, do work at Altria
0:46:23 and you’re gonna see some of the most talented,
0:46:25 disciplined managers.
0:46:28 They massively invest in their human capital.
0:46:31 – I think it’s got some of the happiest employees
0:46:32 in the world based on service.
0:46:36 – They invest a tremendous amount of money and training.
0:46:39 They have great employee profit sharing.
0:46:41 These are just really well run companies
0:46:43 and they’re typically, in terms of evaluation,
0:46:45 somewhat depressed relative to peers
0:46:47 ’cause there’s a large segment of the population
0:46:48 that won’t invest in them.
0:46:52 So long term, just, I’m not gonna make a moral argument
0:46:53 for or against them.
0:46:56 I mean, you know, I’m a capitalist and, you know,
0:46:59 have at it, it’s your capital, do what you want.
0:47:01 But I would invest in it.
0:47:03 I’m an investor in a,
0:47:04 am I an investor in a fossil fuel company?
0:47:07 I’m an investor actually in a small fossil fuel company
0:47:09 in Switzerland, but let me put it this way.
0:47:10 I think it’s a personal choice,
0:47:13 but I don’t look down on people who invest in this stuff.
0:47:16 I think economic security is really the thing
0:47:17 you should be pursuing
0:47:19 and I think we should be voting for people
0:47:20 that put in place regulations
0:47:25 that think about the well-being of people.
0:47:27 – Let’s take a look at the week ahead.
0:47:29 We’ll hear the Fed’s interest rate decision for July
0:47:31 and we’ll also see earnings from Microsoft,
0:47:33 Meta, Apple and Amazon.
0:47:33 Big earnings week.
0:47:35 Do you have any predictions, Scott?
0:47:38 – Tesla’s about to become a bit of a meme sock
0:47:40 that is an updraft or a downward draft
0:47:43 based on Vice President Harris’s likelihood
0:47:46 or where she is in the polls.
0:47:49 And I think these guys a couple of weeks ago,
0:47:52 this big list of tech bros that again,
0:47:56 seem like literally the lamest club in San Jose,
0:47:59 thought that they were smart to go all in on Trump
0:48:01 and that it would pay off for them.
0:48:03 They didn’t do the math on what’s gonna happen
0:48:06 if all of a sudden a Harris presidency
0:48:07 becomes more and more likely
0:48:09 that I do think it’s gonna actually impact
0:48:11 the companies they’re involved in
0:48:14 and Musk has turned Tesla red pill
0:48:18 and it appears as if he’s gone all in on Trump.
0:48:19 He said he was giving $45 million a month
0:48:21 now he’s backtracked on that.
0:48:22 – Well, he argues that it was made up
0:48:24 and I don’t think there’s any way that we’ll know.
0:48:26 – Well, okay, it was the Wall Street Journal reporting it.
0:48:27 So who do you trust more,
0:48:30 the Wall Street Journal or Elon Musk?
0:48:35 Anyways, this is about to become another,
0:48:36 not as much as Donald Trump media
0:48:38 but it’s about to become a tracking stock
0:48:40 and it become inversely correlated
0:48:42 to Harris’s poll numbers.
0:48:45 – This episode was produced by Claire Miller
0:48:46 and engineered by Benjamin Spencer.
0:48:48 Our associate producer is Alison Weiss
0:48:49 our executive producer is Jason Stavars
0:48:50 and Catherine Dillon.
0:48:52 Mia Silverio is our research lead
0:48:54 and Drew Burroughs is our technical director.
0:48:55 Thank you for listening to Prof.G Markets
0:48:57 from the Vox Media Podcast Network.
0:49:00 Join us on Thursday for a conversation with Dan Ives
0:49:02 only on Prof.G Markets.
0:49:08 ♪ Lifetimes ♪
0:49:16 ♪ You help me ♪
0:49:21 ♪ In kind reunion ♪
0:49:28 ♪ As the world turns ♪
0:49:32 ♪ And the dark lights ♪
0:49:35 ♪ In love, love, love ♪
0:49:39 ♪ Love, love, love ♪
0:49:48 [BLANK_AUDIO]