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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN.
Speaker 2:Today is Thursday, 05/21/2026. We are live from the TV from Ultradome. The temple of technology, the fortress of finance, the capital of capital. Yeah. We have a massive show.
Speaker 2:There's so much tech news. People said the technology industry, they were out of news. They weren't. There's plenty of news. They lied to you.
Speaker 2:All over The Wall Street Journal, AI companies are duking it out for prime placement in the journal. SpaceX got top billing in the journal with the IPO filing. SpaceX sets its IPO in motion. The SEC filing starts move to raise tens of billions of dollars in record debut. We've talked about this a lot on the show.
Speaker 2:Clock is officially ticking on SpaceX's huge stock offering. What are laughing about?
Speaker 1:Ryan says, I knew Jordy
Speaker 3:would be
Speaker 1:a dispute
Speaker 4:two days in
Speaker 1:a row. Did I not do two days in a row?
Speaker 2:Nope. Haven't done two days in a row in months. We can roll the tape. I mean, after reading the that piece about us, I feel like some brand differentiation is actually to our benefit since some people can't tell us apart. And so I've become a fan of the the the the split
Speaker 1:in Casual Friday Yeah. Thursday.
Speaker 2:Of just a of a casual look over there, more buttoned down, buttoned up, buttoned left and right over
Speaker 1:gotta be buttoned up.
Speaker 2:Someone's gotta do it. SpaceX on Wednesday revealed new details about how its about its financials and how Chief Executive Officer Elon Musk will try to grow a sprawling enterprise dedicated to advancing cutting edge technologies in space and back on Earth. The company disclosed the information in an investor prospectus. Publication
Speaker 5:of
Speaker 2:the document sets SpaceX on course to potentially raise $80,000,000,000 or more for a stock sale as soon as next month. The rumored date is what? June? July?
Speaker 1:It June 12?
Speaker 2:June 12. That's just twenty days away, basically. They're gonna beat out Saudi Aramco that raised 26,000,000,000 when it went public in 2019. Musk has touted out of this world objectives for the company from deploying a huge number of artificial intelligence satellites in the future to colonizing Mars, Texas based SpaceX, has distinct businesses ranging from rocket launch to satellite operations to a nascent AI unit that its rivals that is racing to catch up with rivals founded by Musk nearly a quarter century ago. Yeah, it has been a long time.
Speaker 2:SpaceX revolutionized the commercial space industry. The company has grown from a start up with a handful of employees that almost went out of business to one of the world's most valuable private companies with over 22,000 workers as of March 31. It controls technologies that competitors and even nation states haven't been able to fully match. SpaceX reported its revenue last year at 18,670,000,000, and Dan Primak had a post saying that the business was smaller than he expected. He's going on CNBC today to talk about the IPO, has had a couple of interesting takes.
Speaker 2:People are going back and forth. Overall, the reception has been the S1 is an extremely enjoyable read. Kevin Kwok says it's the most enjoyable S1 read in a long time. Reads so easy like sci fi or fiction. And
Speaker 1:It's kind of the perfect post Or just regular if you're pro tech, you like space, you're excited about space
Speaker 2:Yes.
Speaker 1:That could be a positive. Yes. But if you're if you're a bear Yeah. You can say it reads almost like science Of
Speaker 3:course
Speaker 1:The TAM slide ever?
Speaker 2:Probably the best TAM slide ever. Sawyer Merritt has the screenshot here. SpaceX and IPO filing. We believe we have identified the largest actionable total addressable market in human history. We estimate that our quantifiable TAM is $28,500,000,000,000 consisting of 370,000,000,000 in space from space enabled solutions, 1,600,000,000,000 in connectivity across 870,000,000,000 in Starlink broadband and 740,000,000,000 in Starlink mobile, as well as additional opportunities in enterprise and government, $2,026,500,000,000,000
Speaker 6:in AI across 2,400,000,000,000 in AI infrastructure, 760,000,000,000 in consumer subscriptions, 600,000,000,000 in digital advertising.
Speaker 2:That's massive.
Speaker 1:Well, is that for X?
Speaker 2:I
Speaker 1:don't The idea so so
Speaker 2:And 2020
Speaker 1:is more believable. Everything else is more believable to me than X getting meaningful digital advertising penetration.
Speaker 2:Yeah. I guess I guess the time the time matters here because a lot of these markets aren't aren't aren't this big currently, I think. I I don't know. But I guess over time, you know, if you think about the next twenty five years, the next hundred years, I don't know if these are inflation adjusted, but there's lots of things that could happen. For illustrative purposes of sizing our addressable market, SpaceX excluded China and Russia from global estimates.
Speaker 2:I feel like you might wanna put in China and Russia over the next couple decades. Who knows? Maybe we become best buds with both companies with both countries. You know? Anything can Great.
Speaker 2:World peace might come, and that's going to expand TAM. That's an economic incentive for world peace. I like to see it. There were some beautiful photos that were shared in the start of the Lots of pictures. Lots of pictures to start, and then it gets very text dense.
Speaker 2:But the photos were I I I liked them. I thought that they were unique. I hadn't seen them, like, that often. They felt like they were kept in the back pocket for a while. And they I don't know.
Speaker 2:They just like remind you of SpaceX. It's like a beautiful thing. Dan Primak says, incredible that Goldman beat out Morgan Stanley for the SpaceX IPO left lead left. Given that Michael Grimes returned to Morgan Stanley in part for this deal, of course, Morgan Stanley is on the deal, but that is it is a big win for Goldman that DJ SpaceX is at the helm. Goldman Sachs and Co, LLC lead left in the joint book running managers, but everyone's getting a piece of the SpaceX IPO at this size.
Speaker 2:Will Bitsky says, Shout out to the Goldman analyst that was originally sacrificed to win this lead left IPO. It must have been an incredible amount of work. It's not just the biggest IPO of all time. It's not just this incredibly complex structure with multiple businesses. It's also you're reporting to Elon Musk.
Speaker 2:Elon Musk is your client and he's going to ask for things probably more aggressively than anyone who's a CEO of a company that's going public. So lots of of things. Lots of winners from the SpaceX IPO. Luke Nosek is a huge one. He was at Founders Fund, co founded Founders Fund with Peter Thiel.
Speaker 2:His next role will be leading. This is from a long time ago. He left to start Gigafund, which was built at the time as a new investment firm that initially will be focused on raising capital for Elon Musk's SpaceX, a founder's fund portfolio company where Nosek is a director. And so David Quan says, Today, learned Luke Nosek left FF to fund to start a fund exclusively focused on investing in SpaceX. There are a few of those that we're hearing about these days.
Speaker 2:Of course, exclusive does not mean 100% of the capital went into SpaceX. It just means that they were very, very focused on that. Gigafund has a lot of different companies in the portfolio, cover. We've had a bunch of founders on the show who have raised money from Gigafund. But SpaceX is where Luke is a director, deeply involved and has focused on participating in many, many rounds.
Speaker 2:And so conviction will do that to an MF, says Pocket Jack's Capital. Lots of big winners. Frank asked, Codex for SpaceX fair value based on the S one should be an interesting buildup to the IPO. What was the result from cap
Speaker 1:Sid Landstrom 1.1 to one and a half It's not bad. In?
Speaker 2:That's not bad. Bull case gets to 1.7 to 1.9 if investors assume anthropic sticks, AI infrastructure margins are strong, Starship unlocks major new markets, and public market scarcity drives demand. But $2,000,000,000,000 means the market is effectively assigning something like $8,800,000,000,000 to $1,000,000,000,000 to the AI orbital compute story on top of an already rich Starlink valuation possible as an IPO mania print, but that's not what I'd call for fair. So we'll see what happens. I mean, the big the big news was the partnership with with Anthropic where Anthropic is spending over $1,000,000,000 a month, I think.
Speaker 2:It's ramping $15,000,000,000. A year. And that's huge for SpaceX given that they did 18 and a half or something last year. This is a huge jump up in in I mean, they have to be one of the biggest neo clouds like overnight with this.
Speaker 1:Yeah. Was trying to find Huge, huge I was trying to find some of our conversations from last year Yeah. Where we were, you know, x Yeah. Sorry, x AI and Grok was was growing, but maybe not at the rate that not close to the rate that would require that much infrastructure.
Speaker 2:Yeah. Finding product market fit on the actual distribution side, obviously we love that. But it's not the biggest platform.
Speaker 1:Yeah. Wasn't it's certainly, you know, for the stars. Yeah. And if you miss, you have a pretty great Neo Cloud business. Right?
Speaker 1:Anthropic has to pay way above traditional Neo Cloud pricing for this compute. And so ends up being a great outcome for SpaceX.
Speaker 2:Yes. Well, Antonio Gracias is another investor who's absolutely printing off the SpaceX IPO. Antonio Gracias at Valor has 30 entities invested in SpaceX, in case you were wondering what truly going long looks like. He added some corrections saying that some people were assigning like, oh, he's the only investor. And he says, no, no.
Speaker 2:Have a lot of LPs. I do a whole bunch of different funds. Like, this is not just his windfall, although, of course, he's going to be doing very, very well personally. But so many different Valor for Space Holdings LLC, Valor M33, six, like so many different investment vehicles because Elon has raised money so many times both for primary capital and for tender offers for employees who had worked at SpaceX for fifteen years and needed to buy houses, needed some liquidity. Elon was very good about never doing a down round, growing the valuation very gradually over decades to get to this point.
Speaker 2:And Peter Haig says, just reading the SpaceX SEC document, one thing that sticks out is the capital spend on AI is 3x that on space. It's an AI company with some rockets, which is a wild wild pivot at the at the it's the eleventh hour. You know, this has been a rocket company for for twenty years or fifteen years, then an Internet company with Starlink, but that was still so tied and so clear and so quick to get to like a logical link. Like you needed the launch capacity to build StarLink. And so we have this new capability, satellite Internet.
Speaker 2:It was amazing. And it went from idea to launching the satellites to consumers actually using it when they're traveling, camping, off the grid, real and then showing up in planes and all sorts of different applications. It became very, very relevant, very real, very quickly. And Colossus x AI, that felt like a different company because it was. It felt like a different initiative, but it has just become so so so big so quickly.
Speaker 1:Yeah. And and looking back at the plays Elon and his investors have made around this over the last year. Right? There was that felt like somewhat of a coordinated effort at the was it beginning of this year or late last year when suddenly everyone started talking about space data centers very suddenly. Remember Gavin Baker Yeah.
Speaker 1:Started coming out talking about it. That's around the time when they sort of floated the I believe it was December of last year. Started floating floating the idea of like what the potential valuation Yeah. Would be. Started building that AI narrative.
Speaker 1:Started, you know, made a play for Cursor, you know, partnered with Anthropic even though, you know, only a few months ago they were much more combative.
Speaker 2:Yeah. So Name calling
Speaker 1:So, yeah. He You know, I think this is why Elon has been able to accumulate so much capital. Yeah. It's like he is the pretty much the best in the world at like making just making place.
Speaker 2:Yeah. Making place.
Speaker 1:And doing whatever it takes.
Speaker 2:Yeah. So the most recent play unrelated to the news that made the front page of The Wall Street Journal, Anthropic revenue surges set to post first profit. Sales seen reaching $10,900,000,000 in the second quarter, up 130 percent over previous quarter. Truly, in the title of the in the actual URL of The Wall Street Journal article, they call it mind blowing growth about to propel Anthropic to its first profit. Absolutely fantastic execution.
Speaker 2:So Tom Brown, cofounder of Anthropic says, We're expanding our partnership with SpaceX and we'll be scaling up GB 200 capacity on Colossus 2 throughout June. Appreciate Elon Musk and the team helping us find find good homes for the Claude's. Is Claude plural? I thought it was all one Claude and the purpose of Anthropic was to build Claude and Claude will eventually build Claude. But I guess you have multiple instances of Claude running on different servers on different GB200s.
Speaker 2:Ray Wang over at Semi Analysis shares a little bit more. Anthropics Q2 revenue is set to increase by over 200%. We'll post an operating profit. The AI will never be profitable. Group is in absolute shambles right now.
Speaker 2:There have been a lot of folks who have been just doubting time and time again, will this ever make money, will this ever make sense? And Dylan Patel sort of laid out on the Dor Kesh Patel show this idea that at a certain point the leading models might actually be able to raise money because they're or raise prices because they're driving so much economic value. Semi analysis also put out a table showing for particular workflows that would take them, you know, a thousand dollars of human time that they would have to hire more people for, they were able to use AI and actually get an equivalent result for a tenth of the cost or a one hundredth of the cost or even, you know, a 30% saving sometimes.
Speaker 1:San Agaib says, can someone check on Gary 02/23/2026? He said turns out Gen AI was a scam.
Speaker 2:I had to check the date on this because this seems like something he would have written in like 2024 and I would have been like, yeah. Okay. Yeah. Maybe the usages are a little limited. Maybe where there is some sort of wall here, the data wall or, maybe we won't be able to maybe we'll need new paradigm.
Speaker 2:But to write this in 2026 when we're in like the fastest period of acceleration in terms of actual value from these models is pretty remarkable. I'm interested to see where he goes from this. Is he gonna double down? Is he gonna stick with this? It has been a couple months since
Speaker 1:I've heard
Speaker 4:I I think there's
Speaker 1:I think I think the the entire crypto boom and NFTs in particular just broke a lot of people's brains.
Speaker 2:Yeah. And VR, metaverse too. Metaverse. There's another thing that
Speaker 1:was Metaverse like and Under delivery. Metaverse, yeah, potentially even more.
Speaker 2:Yeah. Yeah. Yeah. There was a lot of discussion about this will destroy Hollywood, this will destroy movies, like
Speaker 1:the metaverse, there was never there was never a moment where you could use a product and have a mind blowing experience.
Speaker 2:Well, without paying for it.
Speaker 1:Like you had to No. No. I I'm just saying I'm just saying like period.
Speaker 2:No. No. No. The Apple Vision Pro demo, like there was a day Yeah. You called me and you were like, why is everyone losing their mind on the timeline over the Apple Vision Pro?
Speaker 2:Do I need to buy one of these? And I was like, it's kind of like a previous, not like perfectly there. I like it but
Speaker 1:it's I don't even think I I I But there wasn't I don't think you're remembering correctly because was good thing. There was no moment where I wanted to buy one.
Speaker 2:No. No. No. You didn't want to but you recognized that it was the current thing when the Apple Vision Pro launched. For like that week, when everyone got them delivered and they tried them, there were a lot of people
Speaker 1:They had vision pro psychosis.
Speaker 2:They had vision pro psychosis. A lot of people had NFT psychosis, all sorts of psychosis. We'll see how the AI psychosis develops. It goes both ways.
Speaker 1:Yeah. But anyways, comparing it to anyone can have
Speaker 2:Yes.
Speaker 1:A pretty wild experience with AI
Speaker 2:Yes.
Speaker 1:In, you know, on like a ton of different a ton of different services
Speaker 2:Yeah.
Speaker 1:You could never do that with Metaverse. Yeah.
Speaker 2:So Lisan Al Gayib is contrasting Gary Marcus' Sub Sack post with what's happened in the AI industry. Anthropic valuation up 173% since the start of the year, posting profits in Q2 according to The Wall Street Journal. OpenAI valuation, up 67% since the start of the year. And OpenAI general purpose model solves long standing and well known problem. Is it Erdish or Erdos?
Speaker 2:I believe it's Erdosche. Erdosche. Erdosche problem. The two dots over the o get me on the pronunciation. Without a scaffold.
Speaker 2:And so there was a lot of questions what would do, you know, how hard is it to solve these problems. But fortunately, we have Tyler Cosgrove who's going to take us through what actually happened with this solution to this math problem that people are very excited about. Noam Brown said, Today, we are sharing that a general purpose internal OpenAI model achieved a breakthrough on one of the best known combinatorial geometry problems. Less than one year ago, Frontier AI models were at IMO gold level performance. I expect this pace of progress to continue.
Speaker 2:And Sidhar Ramesh, I don't know if he was joking about this bet, but he says I have lost my $30,000 bet that AI would never solve the planar unit distance. I believe that was joke. That's a joke. Yeah.
Speaker 7:I think if you got
Speaker 2:a a lot, but no. But a lot of people were surprised and a lot of people were excited about this. So take us through what actually happened.
Speaker 7:Okay. Yeah. So so I can basically go through like a simple explanation of what the problem actually is.
Speaker 2:Okay.
Speaker 7:So so so just for some context, Paul Erdos, kind of this legendary mathematician, throughout twentieth century, he basically proposes I I think the number is, like, a little over 1,200 different, like, little problems. Mhmm. These are the Erdos problems. People talk a lot about these as like goals for AI to solve. And you've heard, like, time, there's been kind of like small iterative kind of solutions to a lot of these problems.
Speaker 7:Yeah.
Speaker 2:Sort of like collaborative mathematician working alongside the Yeah. AI model or an easy one just getting
Speaker 7:There's like a main kind of like place where all of the solutions go. So sometimes people will will will find like AI will like find a different paper that wasn't actually put on the website and then they they're like, oh, AI solved it. But Okay. It's honestly true. But this is kind of the the first time we've really seen kind of a big step change.
Speaker 7:Like, this is actually a new solution. Mhmm. This is using, like, you know, kind of novel
Speaker 2:Yeah. Ideas here. Out there already.
Speaker 7:Yeah. So so this was problem number 90. So so can kind of read Please. Read the question, then I can explain what it means. Yeah.
Speaker 7:So so it's does every set of n distinct points in the real plane contain at most n to the one plus o of one over log log n many pairs which are one apart? Okay. So, like, what does that mean? Yeah. Basically, we have, like, the real plane.
Speaker 7:Right? Two d. Mhmm. And we have a bunch of points on it. Mhmm.
Speaker 7:What is basically the the the how many, like, pairs of those will be basically one unit apart? Mhmm. And what's, like, the max number? Like, how do we basically organize those points such that we have the max number of them? Right?
Speaker 2:So the grid?
Speaker 7:No. So so you would think that,
Speaker 2:but I
Speaker 7:I can basically explain why. So so let let's kind of, like, formalize this better. So we have u of n. Right? And this is basically the largest number of unit distance pairs among endpoints in the plane.
Speaker 7:Mhmm. Okay. So so, basically, like, we're we're thinking about, like, how do we solve this? Naively, it's like, okay. What what if we just take all the points?
Speaker 7:We have endpoints Yep. And we just put them in a line Yep. And unit distance apart. Right? So so it looks something like
Speaker 2:this. Yep.
Speaker 7:Right? So for this example, we have four points, but it doesn't matter. It's just n. Mhmm. So 12, 34.
Speaker 7:How many pairs are there? There's three. Right?
Speaker 1:Okay.
Speaker 7:Yeah. So basically, this scales with n minus one. Yeah. Right? So you could have a billion
Speaker 2:Yep.
Speaker 7:Points and there's nine nine nine nine whatever. Yep. N minus one. Yeah. Okay.
Speaker 7:So now if we put it in a grid
Speaker 2:Yeah.
Speaker 7:What happens? Right? So if we have a square grid here
Speaker 2:Okay.
Speaker 7:There's nine points here. Yep. And then how many how many pairs are there? I believe there's 12. Mhmm.
Speaker 7:And basically, as this number scales up, it's still linear.
Speaker 2:Mhmm.
Speaker 7:So it's two n. Okay. Basically, if you do a billion points, it's it's 2,000,000,000 pairs.
Speaker 2:2,000,000,000 pairs.
Speaker 5:Yeah.
Speaker 2:Okay.
Speaker 7:So then basically The
Speaker 2:pair is specifically that line. Line that Correct. Represents the
Speaker 7:because it's one unit distance. Right?
Speaker 2:And you Diagonal just doesn't count because
Speaker 7:it's not one unit distance.
Speaker 1:Got
Speaker 7:it. So so then okay. What's the next thing we can do? The next kind of configuration is is what's called the the lattice construction.
Speaker 1:Okay.
Speaker 7:And so if we can pull up picture a of it, it's this kind of crazy looking grid
Speaker 8:Mhmm.
Speaker 7:That has all these super, like, intricate, you know, lines in between. Mhmm. You can see it on the this is from the OpenAI blog. Mhmm. If we can pull it up here.
Speaker 2:Oh, I think I saw this.
Speaker 7:So so this is what it looks like. Okay. So if you can, like, zoom in on on any of these points, you see that, you know, it it it somehow it looks like a grid. Right? But Yeah.
Speaker 7:It there's not just kind of pairs at the at the edges. Right? There's, like, way more.
Speaker 2:Okay.
Speaker 7:So this scales at n Interesting. To the one plus o one over log log n. Right? This is this is basically the the best kind of example that we know works.
Speaker 2:Yes. But not a proof.
Speaker 7:So so so we we know we can find this, but is this the upper bound? We don't know. Right? So this is basically the lower bound.
Speaker 2:Okay.
Speaker 7:So so then the the question is, like, we have the lower bound Yep. Which is the this is the best one we found. Yep. This is the most number of of pairs.
Speaker 2:Mhmm.
Speaker 7:And then we we've theorized that the the high bound, upper bound, is scales with n to the four thirds.
Speaker 3:Mhmm.
Speaker 7:And then so Erdos, the original conjecture that he thought that that it the upper bound is still gonna be less than n to the one plus o of one. Mhmm. So this means o of one, it's like as it scales as n scales to infinity. Right? So o of one basically scaled to zero.
Speaker 7:Mhmm. It go to zero as n goes to infinity. And then, basically, OpenAI figured out that this is not true
Speaker 1:Mhmm.
Speaker 7:And that there there actually are some are some n's for which this kind of max number of pairs is greater than the original Erdos conjecture. Mhmm. So for infinitely many n, this is not for every single n, right, so it's not like five points or whatever, but there are infinitely many n's for which this is true Okay. That it scales with that it's greater than n plus n to the one plus some constant. Interesting.
Speaker 7:Okay. So that was basically the big thing. Right? This is like Yeah. You know
Speaker 2:Huge if you're into math.
Speaker 7:Decades old problem. Right? Yep. This is incredible thing. Terence Tao is like, wow, this is incredible.
Speaker 2:Yeah. Yeah.
Speaker 7:But yeah, that's basically the overview of the problem.
Speaker 1:Okay.
Speaker 7:But yeah, I think it's very exciting because this is not like a math model. This is just an internal model. Sure. General like reasoning. Yeah.
Speaker 4:You could
Speaker 1:say it's, like, generally intelligent.
Speaker 7:Yes. I I think you could say that. And then I think it's it's interesting because from, like, public perception, it seems like this didn't take that many tokens. This was not millions of dollars of inference time.
Speaker 2:Sure.
Speaker 7:It was maybe something like hundreds to thousands of dollars of inference compute spend.
Speaker 2:Very interesting because we were talking about Gorn's conjecture about novel ideas coming from just, like, brute forcing different connections between things, and this is more token efficient.
Speaker 7:Yeah. This is not just taking some solution to a different Erdos problem and just, like Trans spamming it on all 1,200 of the problems Sure. Sure. One of them works.
Speaker 2:Okay.
Speaker 7:This is, like, a kind of a new novel idea. Like maybe this solution is the way that they found this, it's like super complex. You can read the proof. It's like 18 pages long. Wow.
Speaker 7:I don't really know what it means. But but like there's a lot of mathematicians are saying, okay, this is actually could be useful to a lot of other problems. That's cool. This is like a new way to do things. Interesting.
Speaker 7:I think it's it's very exciting. This is like Yeah. Maybe similar to a, you know, alpha fold moment or something That's where now this is like a real kind of step change in Yeah. In math capabilities.
Speaker 2:Do are people gonna run out of problems? How many more problems do we have?
Speaker 7:I I don't know the exact number. I I think so there's 1,200 in total
Speaker 2:Okay.
Speaker 7:Of just Erdrich problems. I I believe the number is around 500, 600, ones that have been solved.
Speaker 3:Mhmm.
Speaker 7:But there there there I mean, there's so many of these like famous open math problems. Yeah. There's like the Millennium Prize. Right? Sure.
Speaker 7:A million dollars that you win.
Speaker 2:Much did OpenAI win if you get a million dollars for the Millennium Prize Yeah. How should they get for cracking this
Speaker 7:puppy out So all every single Erdos Prize Yes. If you solve a problem, there is a prize. Yes. And so these I'm
Speaker 2:angry at a million. So
Speaker 7:Yes. So these are gonna be slightly less. I think this one was around $500.
Speaker 1:500 smack a
Speaker 7:reel. I I believe Erdos sum up scale. There's 25, $100, and $500. Okay. This was kind of the big one.
Speaker 7:Yeah.
Speaker 1:Non dilutive financing.
Speaker 2:Yeah. Non dilutive financing.
Speaker 7:Yeah. Yeah. So so it could be a revenue pathway for OpenAI.
Speaker 2:I I have to imagine that the that the inference bill for this was over $500.
Speaker 7:I think so. Yeah.
Speaker 2:So the mathematician that just works with a coffee still.
Speaker 7:So obviously, like, okay, what does this actually impact? Does this, you know, bring
Speaker 3:us I would back my
Speaker 7:office. Maybe not,
Speaker 3:but but
Speaker 7:it does show that, like, okay, these models are not just, you know, the average of all their training data. Sure. They can actually make novel ideas.
Speaker 2:They're outside of distribution, outside of the training Yes. It's not just knowledge retrieval.
Speaker 7:Yeah. I think this is very much contrary to, you know, kind of the the Gary Marcus take. Sure. These are just, you know, parrots. These are just predicting the next token.
Speaker 7:Yeah. Aren't actually intelligent. Yeah. Yeah. Yeah.
Speaker 7:Think it's very exciting. Yeah.
Speaker 2:Cool.
Speaker 1:Well, thanks
Speaker 2:for breaking up.
Speaker 1:Why don't you hit the gong for Yeah. The researchers?
Speaker 2:Yes. Boom. Thank
Speaker 1:you for breaking that down. Universities Yes. Classes become live podcast settings, podcasts are becoming This is where we're going. Universities.
Speaker 2:This is where we're going. Well, let's take everyone through our lineup today because we have Alex Tabarrok from George Mason University and cohost of the Marginal Revolution podcast with good friend of the show, Tyler Cowen Tabarrok coming inator. A minute. Bill Clerico from Collective Capital is coming on. Alex Norstr Convective.
Speaker 2:Convective Capital from Spotify. The co CEO of Spotify is coming on. Then we have Jordan Schneider back from China Talk going to probably spend a few minutes talking about the underwhelming summit in China and then move on to a bunch of other talks, a bunch of other topics. And then we have Christina Lee Storm from Secret Level joining at one p. M.
Speaker 2:Pacific. So the other news, rumors about OpenAI is being close closing in on the IPO funding filing and that pushed out NVIDIA's results which is normally something I would expect on the front page but there was too much AI news. NVIDIA results skyrocket on rise of AI agents. We talked a little bit about it yesterday. But the big news is that they're doing an $80,000,000,000 share buyback authorization.
Speaker 2:And Take was bullish. People were wondering where he would sit on NVIDIA. He laid out pretty convincing case. You can go listen to the interview. It aired yesterday on TBPN.
Speaker 2:But without further ado, we have Alex Tabarrok in the waiting room. Let's bring him in to the TBPN UltraDome. Alex, how are you doing? I think we don't have audio. Can we check your microphone, make sure it's working?
Speaker 2:We're good. Okay. We are. It was something on our end. How are you doing?
Speaker 5:I'm still doing great.
Speaker 2:Fantastic. Perfect. It's
Speaker 1:to have you on the show.
Speaker 2:It's been far too long. I'm a huge fan. I've read Marginal Revolution since I studied economics back in 2010 and a huge fan of the Marginal Revolution podcast. I very much enjoyed your debate with Tyler Cowen all about the cost disease or Balmol effect. And I think we should start there and then I we can go all over the place in AI and labor and the economy broadly.
Speaker 2:But do you want to start with an introduction on the Balmol effect? Maybe why it captured your interest and some of the work that you've done around it?
Speaker 5:Sure. I mean, probably a lot of people have seen this famous chart where you have a bunch of things going up in price and a bunch of things going down in price. Yeah. And the question is why. I mean, the things that are going up in price, I think we all know, is like healthcare, education, right?
Speaker 5:Yep. And then things are going down in price, often manufactured goods like automobiles, quality adjusted, or televisions, computers, things like that. And question is like, why? Why do we see these big differences? And what Vamil pointed to was that there's a problem with service industries, you know, like education.
Speaker 5:You know, think about what I do, which is teaching students, and you think about what Pythagoras did. Like Pythagoras, he's got 10 or 12 students around him and he puts a triangle in the sand and some math there. It's more or less what I do, right? I mean thousands of years later, maybe I'm using Chalk or maybe I'm using PowerPoint. But basically, it's me and a few students and productivity really has not gone up at all in the education industry.
Speaker 5:Because of that, prices have to go up because you take an industry where productivity is flat and you might say, Okay. Prices are going to be flat. But, no. No. Because all the other industries are improving in productivity and the education industry, they have to attract labor from those industries which are getting better.
Speaker 5:So they still have to pay me as much as I would earn, you know, in another industry. But my productivity hasn't gone up, You know? Yeah. So that means prices have to go up. Yeah.
Speaker 5:So that's the basic bommel effect is that industries, especially services, where productivity is not going up, prices have to go up.
Speaker 2:Yeah. We have the chart here and I imagine that there are a few logical pushbacks. One is regulation. Everyone will say that the number of licenses to practice medicine is restricted. It's a taxi cab medallion system.
Speaker 2:It's a regulatory capture situation. Does that not play into this chart as much as people think? Is that to be disregarded or is overregulation still something worth contending with if you want to avoid runaway inflation in or or just disproportionate inflation in important services that people have demand for but are maybe paying through the nose for and not happy about?
Speaker 5:Right. Yeah. Look, I'm a free market guy. You know? I'm anti regulation, anti bureaucracy, all that kind of stuff.
Speaker 5:But you have to understand with these trends, we're talking about increases in prices which have happened over one hundred years. Sure. Yeah. Medical care, people were complaining about medical care going up in price in like 1920, 1930. This is before you know, Medicaid, Medicare, before a lot of government involvement.
Speaker 5:Education has been going up in price. So I think it's deeper than just regulation. And let me give you just one other example is think about car repair, okay? You know, or cobblers. Was the last time you took your shoes to a cobbler?
Speaker 3:Right?
Speaker 5:You know, my mother will say, oh, the new generation, they just don't care about repairing things, you know? Yeah. And I'd say, no, no, mom. I love you, but look, it's that the cost of repair has just gone up so much Mhmm. Compared to just the cost of buying a new pair of shoes.
Speaker 1:Yeah. Would you like to, you know, spend $70 to fix your $60 pair of shoes?
Speaker 5:Exactly. Exactly. So, you know, I had a my car had some I I bashed it in the in the parking lot, you know, and it was like, not not a serious, you you know, just a a surface injury. Mhmm. But it was like a third the price of the car, the value of the car just to side.
Speaker 5:You know? And that's pretty typical.
Speaker 2:Yeah. So I mean a lot of people in in the AI world are saying that AI will do to services what technology has done previously to manufacture to goods, to manufacture products. Does that mean that the Baumel effect goes away? Is it more pronounced in the industries that are AI resistant and you see some sort of runaway inflation in the things that can't be automated? Because when I think about teaching a college course I do see the sort of maybe linear scaling that you're discussing but we have microphones now.
Speaker 2:We have amphitheaters. You can teach more students. There's online resources. There's ways to delegate and manage teams of homework reviewers and dislike sort of disaggregate the works. And so you would imagine that technology would be a lever on services in some ways, but I'm wondering how you think it will change in the age of AI.
Speaker 5:Yeah. So the big question is robots, right? Mhmm. If you can replace labor with capital then a lot of the bomb effect goes away, which would be great. I mean, that would be great.
Speaker 5:Basically, anything that improves productivity is good. But, I think people also get a little bit too upset about the bommel effect because, really, why another way of putting it is, why are services getting more expensive? It's because manufactured goods are getting cheaper. Right? Yeah.
Speaker 5:It's because what we have to pay for the services in terms of giving up other goods has gone up in price. But still, we're richer than ever before, which is why people keep buying more education and more health care. Right? So that's another reason why I don't buy entirely the regulation story. Yeah.
Speaker 5:Because if it was sort of regulation and the price of healthcare was going up, people would buy less of it. Yeah. But actually, they're buying more of it. Yeah. So, it's the fact that, you know, our productivity is going up.
Speaker 5:We can afford more of it. That's really why the price of medical care is going up is because the price of computers and other things is going down.
Speaker 2:Yeah. How are you processing the the latest and greatest in behavioral economics around maybe this concept of the vibe session, this idea that, yes, we are richer than we have been in history. And yet, I mean, now consumer confidence is very low. There seems to be a lot of dissatisfaction with the with the progress that the economy is making. How much of that is grounded in in real economic data versus psychological factors?
Speaker 5:I've I'm amazed at the amount of psychological factors. It's something I've changed my mind on, how big those psychological factors can be. Yeah. I mean, if you just look around the world today, no other country has done as well from globalization as The United States. I mean, it was it it was us which kept open the sea lanes
Speaker 2:Yeah.
Speaker 5:And globalized the world to our benefit. And we're the richest country in the history of the world, the richest at at any point in our history, and yet somehow we're upset about free trade and globalization. And again, no other country has done as well at assimilating immigrants and doing well with immigrants than The United States, And yet, we're upset about immigrants. Yeah. So I think it's very disappointing.
Speaker 5:I hope we I hope we get over the bad vibes because The US has a lot to be proud of
Speaker 2:Yeah.
Speaker 5:And a lot to be feel good about.
Speaker 2:Yeah. Is one of those psychological factors, you know, the average American's perception of debt to GDP? We seem to anchor debt like nominal values of debt to GDP, which is a sort of an income stream and we get very irritated or anxious when debt sort of touches GDP and relative values. How are you thinking about the level of indebtedness that is appropriate for a modern economy to sustain itself?
Speaker 5:I'm not happy about the debt. You know, we still don't know. The US has a big choice. Do they want higher taxes or do they want less spending?
Speaker 6:Mhmm.
Speaker 5:And The US voter just keeps saying, how about neither? You know? Sorry. Is not working. Right?
Speaker 2:Yeah.
Speaker 5:You know? Have your cake and eat it too. No. You cannot do that. So the American public has just not decided which way it it it go.
Speaker 5:Yeah. But that is what is driving the malaise. I don't know. I'm not I'm not sure. See, I don't know whether I don't know whether it's cell phones.
Speaker 5:I don't know whether it's Instagram. Yeah. You know? But it does seem that there is an anger, a grievance culture in The United States. At first, you know, I thought it was just on the left.
Speaker 5:Mhmm. Right? You know, when we had everyone's complaining, oh, African Americans are treated so poorly. The women are treated so poorly. The poor are treated so poorly.
Speaker 5:You know? And then with Trump, we've just changed our set of grievances.
Speaker 2:Mhmm.
Speaker 5:You know? And so now, oh, it's the foreigners who are ripping us off, you know, crime is terrible, and of course it's not. You know, all of these things. We've just changed our set of grievances without actually focusing on
Speaker 1:Is that yeah. That you think how much does the fact that, you know, so many people are downwardly mobile? I mean, I I was born in the nineties and and I remember as a as probably a an early teenager hearing like, you know, statistically, this is the first generation where you're more likely to to do less well economically than than your parents did. And I feel like part of the challenge with that is that America's culture is so progress oriented. Right?
Speaker 1:Like the American dream is just centered around doing doing doing more, doing better. You know, if your if your father was a was a cobbler, like you own a shoe store, that that kind of thing. And and so Mhmm. Now when you have, you know, still this like massive wealth and and as you said, you know, the richest country in history, there's this constant comparison to to the past, and I think frustration from that, which is making, like, you know, huge swaths of the country frustrated. And you wanna you wanna blame it you wanna blame it on on, like you said, foreigners or or free trade, etcetera.
Speaker 1:But but it's just like this sort of latent frustration.
Speaker 5:Yeah. There's definitely frustration. I agree with that. Compared to the past, we are doing better. Yeah.
Speaker 5:There's no question of that. Now, to be sure, there are some key areas like housing. Right? Housing is much more expensive, you know, than it should be. You know, that's zoning problem.
Speaker 5:That's a choice people have been making, I think, a bad choice. I think we ought to do something about it. But even with housing, you know, houses are so much better today. They're larger. Kids have their own rooms.
Speaker 5:Know? There's a parking Yeah. In 1960 structures. Yeah. A large fraction of the housing stock in 1960 didn't have indoor toilet, didn't have indoor plumbing.
Speaker 5:Right? That was still pretty common not to have indoor plumbing. So, I don't think it's compared I think when if people are saying that we are worse off in the past, I think that's incorrect. Maybe what's going on is that inequality has gone up somewhat, not as much as people often think, but it has gone up somewhat. And, of course, we have more access to seeing inequality.
Speaker 5:So, you know, Instagram and stuff like that, which is sort of a fake, you know, it's a
Speaker 2:The Lamborghini might be No. I completely agree. People.
Speaker 1:Yeah, other factor is that the forms of entertainment that are constantly being chosen today, like doomscrolling, right? You maybe had the hippie generation, it was like, hey, we don't have jobs, let's go to Yosemite and just live there. Surf. And like what that what that would do to your sense of well-being versus like I don't have a job, I'm gonna sit on my phone That's a yeah. All day long.
Speaker 1:Yeah. Right? Or or you know last week
Speaker 2:hitchhikes across America when they're in between gigs anymore. Yeah. Happened? Yeah.
Speaker 1:Yeah. But like just just I don't have anything going on. I don't have opportunity. I'm gonna go outside Yeah. And touch grass.
Speaker 1:Yeah. It's like gonna have a wildly different impact on your psyche.
Speaker 2:I know a super successful corporate lawyer today that like was in the middle of a career transition, spent a year like surfing in Southern in South America and like that is unheard of by today's standards. Like that just doesn't happen. Sorry. Did you
Speaker 1:have Yeah. No.
Speaker 2:Yeah. Yeah. I have also been thinking about like if there was a if there was an alien that showed up and had a quadrillion dollars, like if you include that alien in the Gini coefficient it skyrockets it. But the existence of that alien doesn't affect your perception until you're made aware of the the diamond spaceship that the alien comes to town with and starts flexing on you on Instagram. But the mere existence doesn't change your your economic well-being or anything real but it does change your psychology once you see them flexing on you.
Speaker 2:I'm I'm interested in the housing thing though. I want to go back to a bommel effect because housing seems to potentially fall in the middle like there's manufactured goods that go into building a house. There are also services that go into a house. Like how do we apply the thinking of the Baumel effect and what you've learned to what would happen to housing? Like is there a second step?
Speaker 2:Everyone, when they talk about housing, will say, let's fix the zoning rules. Let's make it easier to build. But is that enough?
Speaker 5:Yeah. I mean, look. With housing, it's not the construction of housing which has gotten so much more, you know, expensive. It's almost 100 percent the land.
Speaker 2:Okay.
Speaker 5:The cost of the land. Yeah. And you look, I mean, you just go to, you know, San Francisco or San Jose, which ought to be, right, some glorious metropolis, you know, of the future with, you know, sky high buildings and people traveling around in, you know, fantastic Yeah.
Speaker 2:Should look like a Chinese city where there's LED walls and yeah. We have that on Salesforce Tower, but outside of that, there aren't these massive skyscrapers. And it just it just has It's
Speaker 5:a a land of strip malls. Yeah. You know, Silicon Valley is a land of strip malls.
Speaker 2:It really is.
Speaker 5:And strip malls are just extremely extremely expensive. They're just lying on Yeah. You know, this very valuable land where people are not allowed to go. Yeah. So I'm hopeful of something like California Forever, you know, where they're trying to get permission to, you know, start a new city.
Speaker 5:I'm hopeful for things of that nature. But none of this this is all policy. This is all of this is under our control. Yeah. In some sense.
Speaker 5:This is not like we've we haven't been hit by, you know, or a tornado and we're all poor and have no housing is because we've said no, you cannot build.
Speaker 2:Yeah. I've I've I've been thinking about the the the push into cities which which makes so much sense in the sense that the economic opportunity is in the cities And so we've seen successful college graduates leave their hometowns, go to San Francisco, Los Angeles, New York, Miami, Austin, these mega hubs that have been very expensive if they aren't building. But I was I was really optimistic that between remote work, self driving cars, like faster highways, like we would get just an extension because I think as you look through history, the forty five minute commute is sort of a sweet spot where before the horse and carriage would live a couple miles because that's where they could walk in forty five minutes. We got the horse and carriage. Once we went to 60 miles an hour it became okay you live you know 30 miles away from your from your workplace.
Speaker 2:But I was hoping that we would get another leg up on that and maybe it's coming but we certainly haven't seen it yet. Have you been surprised by any of the fallout or lack thereof of the COVID era, the shift to remote work? Any changes, technology or otherwise, in just the housing and labor markets?
Speaker 5:Yeah. I agree with you. I've been a little bit surprised that we haven't seen another city really take off. I mean, we used to build new cities. Yeah.
Speaker 5:Right? You know, like, you know, Chicago, you know, not that long ago was a city of 50,000 people. Yeah. And Trump briefly talked about freedom cities for a while, which I thought was a good idea. Yeah.
Speaker 5:But it's sort of gone away.
Speaker 2:Okay.
Speaker 5:It does tell you that there's something very strong about these so called agglomeration, the technical term in economics, agglomeration effects. Yeah. That, like, people just get more productive when they are near other productive people.
Speaker 2:Yeah.
Speaker 5:And you really need this big push to try and get this into the new city. I mean, Miami briefly, you know, seemed to be jumping ahead, but that that trend seemed to have gone away. Las Vegas tried it with Zappos, but that modestly only took off modestly. I am somewhat surprised that we can't plant our flag and say the new city is going to be here and have a lot of companies all agree to move in at once.
Speaker 2:Yeah. Yeah. The I've heard it referred to as like the rainforest theory that why San Francisco is so resilient because you have so many different participants and the VCs can go to Miami but they're just a phone call away while so many other key pieces of the economy are still chugging along. And so San Francisco clearly made it through a trough and is on a major major upswing. Jordy?
Speaker 1:What data are you most obsessed with following to try to understand the current moment? We see AI in the GDP data primarily through CapEx right now. But what kind of productivity data are you looking at? You know, we've been very excited about, you know, what what what we've seen from Stripe. They have this incorporation product and they're seeing companies, you know, more companies formed, growing revenue faster, that's very exciting.
Speaker 1:But it's also like a certain type of person finds himself incorporating, you know, their business with with Stripe and is not perfectly a reflection of of the economy more broadly. So what are you looking at to try to understand the impact and and and try to ignore maybe the headlines from CEOs that say, oh, well, we we we we laid off this 20% of people because of AI because, you know, as we know, oftentimes it's marketing.
Speaker 5:Yeah. It's very interesting. There's a lot of theories, you know, about is this going to be a job apocalypse or Not something like much data. Of course, all of the data we have so far is that AI is increasing the number of jobs, not decreasing the number of jobs. What I'm most excited about and most interested in seeing is the effect of AI on medical care.
Speaker 2:We
Speaker 5:just saw yesterday that AI had you just had it on your had proved a new mathematical theorem or a counterproof. Yeah. So, AI is making these inroads into the highest levels of mathematics. If we could do that for drug discovery, you know, if we could have, you know, a five percent reduction in cancer mortality, that would be worth trillions.
Speaker 3:You
Speaker 5:know, that would be worth trillions. So, the opportunities there for AI to make tremendous leaps in human welfare by improving medical care, healthcare, I think are really exciting and well within the realm of possibility. You know, one new drug like solving an air dose problem, that would be incredible.
Speaker 2:And what does that mean in the labor market? I'm just I'm thinking back to like there was a time when there was sort of only one track for doctors. He was just like a generic doctor. Now there's much more specialization. There's a dermatologist, a podiatrist, all sorts of different doctors.
Speaker 2:Is this like there's fracturing and further employment creation from the administration distribution advisory around new treatments as it rolls out? Because you could imagine, okay, there's a new drug. That's great. That helps everyone live longer. But I'm unclear on how it interfaces with the labor market.
Speaker 5:Yeah. I mean, I think the trend is, you know, the division increases in the division of labor. Mhmm. You know, it's talked which Adam Smith talked about from the pin factory. Yeah.
Speaker 5:And, when you apply that idea of the pin factory, you know, somebody shapes the pin, somebody puts it on, and that's how you get pieces in the inside. When you apply that to the knowledge economy, then it's exactly as you said, you no longer have a physician. You have a podiatrist and you have an optometrist
Speaker 2:and you
Speaker 5:have an ear, nose, throat specialist and so forth. And, yeah, think that will continue. And they will all be using AI, for sure, right? But, yeah, they're going to get more specialized and the tasks which physicians do will differ, will change. But, so far, you know, I'm not terribly worried about the job market per se.
Speaker 5:Yeah. You know, look, this is a problem of, know, people are worried people are worried about the, oh, the AI is going do all the jobs. Right? Like, this means we're going to be fabulously wealthy and, you know, even without any jobs, just being fabulously wealthy, we'll figure things out.
Speaker 2:You know?
Speaker 5:This is the sort of problem you want to have. Right? Yeah. Again, this is not like a tornado or hurricane, the tsunami Sure. Which destroys wealth.
Speaker 5:Yeah. This is a tsunami which creates wealth. And, yes, it could be a tsunami in the sense that it's going to be very dramatic. Okay? But it's going to be very dramatic like, you know, Santa Claus coming and leaving us goods, you know, under the Christmas tree.
Speaker 5:So that's drama that we can handle. It won't be without problem. Yeah. Okay? But problems where the pie gets bigger are problems that we can solve.
Speaker 5:You know, it's problems when the pie gets smaller when we are forced into a zero sum society of one person versus another. Mhmm. That's when society breaks down, not when the pie is getting bigger. Like we'll figure out ways to make sure everyone gets a decent slice. If the pie is getting so much bigger, we can solve the problem of dividing it up with everybody being happy.
Speaker 5:I'm not I'm much less worried about that.
Speaker 1:Mhmm. How do you how do you think about value capture with this technology wave versus historical technologies? You know, if you get really good at inventing engines, you can sell a lot of those engines and hopefully have a nice margin and maybe other people copy the engine and also make similar engines and and benefit from that. But we're at a moment right now where frontier intelligence is is like very widely available. Right?
Speaker 1:There's certain internal models that aren't with the public yet and if you have one of those Erdos, you know, moments in medicine, it could just be an off the shelf model that helps make a breakthrough and you pay for the tokens or you pay your subscription, but then right now the labs are not really set up well to capture that value at all. It could be, you know, some it could be a big company that that captures the value. It could be another startup. There's small businesses. And so how are you thinking about value capture versus like public benefit of this technology cycle and how it would differ to prior technologies, let's say like the Internet and telecom and all the way back to railroads and the steam engine, etcetera?
Speaker 5:Yeah. It's a very interesting technology because this will sound odd, but it doesn't seem that hard. But, you know, the fundamentals is, you know, it's linear algebra. It's very surprising.
Speaker 2:Yeah.
Speaker 5:I don't think anyone predicted this. But, and it's true, of course, that the frontier models are ahead, you know, OpenAI and Anthropic, you know, have the best models. But they're like six months ahead, you know, of open source And for most of what you want the models to do, you don't even need the frontier models. And, you know, what today is a frontier model? Like tomorrow, you know, it'll be much cheaper second rate model, right?
Speaker 5:Like, people are worried, oh, some people have access to 5.5 and other people are still working with 5.4. But, the big point is that even 5.4, the free model, is a 100 times better than three point zero, right? Right. Which was also incredible. The models seem to be getting more powerful and cheaper at a faster rate than any other technology that I have ever seen.
Speaker 5:Mhmm. So I think the gains will be fairly widespread, if not at first, you know, then soon afterwards. I mean, you know, some people are obviously OpenAI and Anthropic. You know, the people who got in early and the programmers there, you know, they're going to be fabulously wealthy. No question about that.
Speaker 5:But, the technology itself, so much of it is open source, so much of it is really quite accessible. There's no magic there as far as I can see. Like, it was just you had a few good ideas and then those ideas just turned out to be incredibly powerful. So, I'm expecting to see really the technology being quite widespread.
Speaker 1:Yeah. Nolan? I know we're out of time, but one last question. How do you think about the part of the reason I think we feel this insane acceleration with this technology shift, maybe, you know, more more so than certainly mobile, but, you know, looking back to the Internet and everyone in this moment wants to figure out, okay, we in '98? Are we in '99?
Speaker 1:Are we in early two thousand? Trying to figure out the moment that we're in. And it feels like because we have the internet today, like there's this like compression in the technology cycle because ideas get distributed faster, products get distributed faster. If there's a breakthrough, it's instantly everywhere. There's instantly hundreds or thousands of companies working on improving it, furthering it.
Speaker 1:And so I find it hard to try to think about where we are because it felt like in q four of last year we actually did have a correction. Like we were joking we were joking like, great, the bubble popped because like there was over like maybe too much excitement around chatbots and there was somewhat of a correction and then we got agents that really worked. And then it feels like in some ways we're in a new a new cycle now and and so I'm I'm curious if you have any sort of frameworks or thinking around that like compression in progress that we're getting because we're building on top of all these other technology cycles for this new one.
Speaker 5:Absolutely. And of course, the AIs themselves are starting to improve the AIs.
Speaker 2:Mhmm.
Speaker 5:Right? Some people worry that precisely because of that we'll get a sort of a fume scenario under which one day everything is fine and the next day you have a god in the laboratory. Right? I'm not too worried about that but it's not insane. It's not insane.
Speaker 5:Yeah. So far, my view is that I trust the technologists when they say that the technology is going to keep getting better quite rapidly. Where I think the technologists are not quite right is that it's gonna take much longer than they think for this to start affecting, jobs and the economy writ large and things of that nature. That'll be slower. So the economists generally are on the slow side in terms of it's going to take time to adapt to this technology.
Speaker 5:I mean, we saw like with electricity, for example. You know, electricity was another, you know, incredible technology. But it took time. You know, it took time to adapt to that even when the frontier, you know, was very far ahead. But for that to work its way in the economy and for people to figure out how they're going to change their production structures, that took time.
Speaker 5:And I think it will take time here as well. But as far as I can see, the technology is going to keep getting better, which it does give one pause. And I will say, never in my life have I felt that the window of what is possible is as large as it is today, both on the possibilities for superintelligence huge gains, the boomers, and also on the doomer side. I I don't discount those entirely. My view is more in the middle, but those two sides, they're not they're not insane.
Speaker 5:So we do have to do a lot of thinking.
Speaker 2:Yeah. Well, thank you so much for taking the time to come chat with us. We'd love to have you back on the show soon. It was long overdue. But Yeah.
Speaker 1:Thanks the time, Alex.
Speaker 2:Rest of your week. Have a great weekend. And hopefully, we'll talk to you soon. Talk
Speaker 5:soon. Goodbye. Alright.
Speaker 2:GMU economist, always so much fun to talk to. Well, our next guest is Bill from Convective Capital here with a new fund. Get that gong ready. Let's bring Will from Convective Capital into the TBPN. To the show.
Speaker 2:How are doing?
Speaker 9:Doing great. Thanks for having me, guys.
Speaker 2:Kick us off with the news. What happened today?
Speaker 9:Yeah. So we raised the new fund to 85,000,000 Woo. There it is. Congratulations. It's thank you so much.
Speaker 9:It's up two x from our from our last fund, and we're focused on disaster resilience. The thesis of the fund
Speaker 2:Yeah.
Speaker 9:Is that the world's getting warmer, our infrastructure's getting older, and that's literally a recipe for disaster. And so as as disasters rise and volatility rises in the world, there's got to be private markets that can respond and that can build solutions and services and technology to to stop that. And so we back founders that are building those things.
Speaker 1:Give us an overview of the fire give us a fire market map. What's exciting in fire? It's top of mind right now. There's a fire burning in LA slash I think Ventura County. And so my house has been very has been very smoky Smokey.
Speaker 1:Around my house. And yeah, I wanna know. This this feels like a a particularly brutal industry because there's these, like, insane spikes of interest and then people just kind of forget about
Speaker 2:Are thinking Watch Duty for profit conversion?
Speaker 1:Yes. It's gotta happen. Yes. Lead a series a in Watch Duty, please. Lever it up.
Speaker 9:Yeah. John, Watch Duty is a good friend, and we started you know, I started my company around the same time he started that. And he will never take that for profit.
Speaker 8:He's a
Speaker 9:to hide in the wall.
Speaker 2:It's such a good
Speaker 4:app. So important.
Speaker 2:But yes.
Speaker 9:And it's actually become the standard not just for people that care about their homes, also people in the fire service use it.
Speaker 2:Oh, yeah.
Speaker 9:It's an amazing example of how technology can address this problem.
Speaker 4:So I
Speaker 9:guess to get to your question around market map, we think about a lot of like who's the end buyer because that's actually what's kept people out of this space historically. VCs typically don't get excited about companies that sell to utilities or insurance companies or government agencies. Our thesis is that that is in the middle of a really big change that if you see PG and E went bankrupt a couple of years ago, the insurance companies have had to leave California in some of these really large markets, and that's changing behavior. You lose $70,000,000,000 of market capitalization and you respond and you do something about it, you act differently. And so we think a lot about the market in terms of who's going to buy these technologies.
Speaker 9:We've had a lot of success investing in startups that sell to utilities like Overstory, which uses satellite imagery to help utilities trim trees around power lines. We just invested in fund too in a company called Volt Air, which does autonomous drone power line inspections. So, you know, utilities cost about 11% of fire ignitions, but about 60% of the acres burned. So if you can actually just help reduce utility ignitions, that's like a huge leverage point.
Speaker 2:Interesting. Interesting. Interesting. What what what's going on on disaster prevention in, like, more of the consumer, prosumer space? I saw a house for sale over in Malibu and the it was by some actor and he had installed like fire shutters and like all this different equipment.
Speaker 2:He was like living off grid and this was like his getaway. And it feels like I I saw after the LA fires, like, the autonomous water sprinkler that would be bolted to the top of the house. I think a lot of homeowners in Los Angeles at least were, oh, I want one of those. And they would have clicked the button to buy it if they'd seen an ad that day, but then a year goes by and nothing happens in the next fire season. And they think, oh, maybe not.
Speaker 2:But it does feel like there's some fertile ground in the consumer space. But is that more challenging than people might think it is in reality?
Speaker 9:I think you're totally right. Like, consumer demand goes in spite. It's a very seasonal, volatile business. You know, I just saw today Watch Duty is the number two downloaded app on the App Store today, and, you know, that probably was not the case Yeah. A couple weeks ago.
Speaker 9:So, you know, it's certainly that's the nature of the beast here. In terms of home hardening and things you can do to protect your home, I think that also kind of goes in waves to your point. But to me, the real unlock is going to be when insurance companies create incentives for people to actually install these things around their their home. So we're investors in a company called Stand. They help model homes.
Speaker 9:They use computational fluid dynamics to simulate wildfires moving through the property. They come up with a list of recommendations for the homeowner of what they should do with shutters and windows and remove certain vegetation. They remodel it and then they can actually provide discounts on insurance. I think that's going to be the real unlock that drives, you know, at scale consumer behavior.
Speaker 1:Yeah. It has to be a real time, like, you're renewing your home insurance and they're like, if you do spend, you know, in California, it could be like, spend $10,000 on this new system. And if you do that, we'll give you a $10,000 reduction this year and, you know, further discounts in the future so that you end up, you know, effectively, you know, saving real money.
Speaker 9:Mhmm. Yeah. Exactly. I think historically, insurance companies have not done that, but that's the that's the key to protecting, you know, homes in this kind of new era. And and it's it's gotta happen.
Speaker 9:You know, the the California Fair Plan, which is like the state backed insurer of last resort, just announced they're gonna raise rates 30% this year after the LA fires. And so, you know, if we don't actually reduce the probability of homes burning, housing and insurance is just gonna become unaffordable.
Speaker 2:How are you thinking about selling to the government maybe in California or elsewhere? Anderol has this interesting story where they built a firefighting tank. They were trying to sell it to California firefighters, there was pushback around job displacement even though it was ideally a new capability that would actually have support staff and not really take anyone's job because no firefighter can sit in the middle of a blaze like this particular firefighting tank could, but it was still became a political issue and ultimately did not become a real product. Is there movement there? How are companies positioning themselves as additive?
Speaker 2:When I think about drone review of of of power lines, there's probably someone that went up there earlier. Cost savings is good. Doing more with less is great, but also there's always that pushback around job displacement.
Speaker 9:Yeah. I think there's kind of two issues at play here. First is, like, is there actually job displacement? I think the reality is no. I mean, it's just
Speaker 2:Yeah.
Speaker 9:We are so under resourced relative to the scale of these disasters. They're happening three times more frequently with huge severity. You know, CAL FIRE is the largest and best resourced firefighting agency in the world, bar none. Like, that's not gonna change. And I think we're it's really about how do we get leverage out of those investments.
Speaker 9:I do think, though, you're pointing out a cultural issue, though, and that's something that we've really worked at trying to bridge. You know, I think it can be really harmful if, like, a bunch of guys in Palo Alto sipping lattes, like, walk out to the fire line and try to tell people how to do their jobs. Sure. You know, there's just this huge disconnect. And so one of the things that we built is this conference called the Red Sky Summit where we actually get 600 fire chiefs and other emergency managers together every year in San Francisco.
Speaker 9:And we kind of create, like, an off the record venue for them to talk to people that are building stuff and technology. And it kind of creates this great sharing back and forth where, you can show the value of this technology. You can have these two way conversations. It sort of changes the tenor and that's been a real unlock. We've seen a lot of buying behavior come out of that event.
Speaker 9:I think things like watch duty that show how impactful technology can be. The firefighters see that. And, you know, I think the tide and the cultural tide is really changing. And so it's it's an exciting time to be building in this space.
Speaker 2:Yeah. Is there any relevance? Like, we talked to some other sector specific funds or thematic funds. And the classic example is like in CPG, they can be a harder business sometimes, but there's a number of like clear acquirers for midscale companies like Unilever or Coca Cola will take out a lot of these companies at a unicorn valuation. And so it sort of changes the underwriting.
Speaker 2:It's worked for a lot of funds in that category. Is there a 800 pound gorilla in this category that's maybe not being disrupted but maybe can be a partner at some point in time? Or or is the thinking like everything is IPO, it needs to be a stand alone business or bust? Or is anything different financially about these these businesses that you see?
Speaker 9:Yeah. It's a good question. I I don't look at wildfire as like a market in and of itself. It's this sort of dynamic that touches these huge markets like energy
Speaker 3:Yeah.
Speaker 9:Insurance
Speaker 2:Yep.
Speaker 9:Housing Yeah. Real estate, forestry, government emergency response. And in each one of those categories, there are really large companies.
Speaker 2:There
Speaker 9:are contractors in the utility space or providers in all of those markets. I think there's certainly exit paths, but the economics here are just, like, immense. You know, the Bloomberg just published a report. Disasters cost The US economy a trillion dollars a year. That's, like, on par with what we pay for interest on the national debt or defense.
Speaker 5:And
Speaker 9:so it's like, you know, you there are really big public companies that will be built, you know, solving that because the that cost falls on these really large deep pocketed institutions. You know, we think that there's just just very big businesses to be built.
Speaker 1:Yeah. Corey? Is there opportunities for wearables for firefighters? I was once the the the Sandy fire started here in LA, I was I was showing my son some videos on, like, wild, just like wildland firefighters and I was shocked that a lot of them just like weren't wearing gear. They were wearing wear something like a piece of fabric over their face.
Speaker 1:Seems like there's probably opportunities there and potentially a decent sized market.
Speaker 9:Yeah. I mean, it's it's a travesty what we equip our firefighters with and send them out there. I mean, it's like, you know, the the health impacts of wildfire smoke are just terrible. I mean and so and there's really not a practical way currently to help filter that air for these wildland firefighters. So they're out there, you know, really with no masks, sleeping in smoke days at a time, carrying packs.
Speaker 9:It's a 110, 120 degrees. You know, they're working hard with chainsaws and axes. It's a really dangerous, really grueling job. I think part of the original thesis for Convective was I was actually volunteering with my local fire department up in Mendocino County. I just was watching this and I'm like, I can't believe we're doing this with trucks from the 1970s axes and that's the state of the art.
Speaker 9:There's a huge opportunity there. You can look at wildfire as a market and it's a certain size, but it's also a path into all types of field service jobs and all types of worker safety. And so we've looked at a lot of companies there. We haven't made any investments yet, but that's that's category we're really interested in.
Speaker 2:We we jumped straight into the discussion of the fund, the strategy. Can you take us back a little bit to what you were doing before? Why start this fund when you started it? Sort of the the prehistory of the fund.
Speaker 9:Yeah. So I was a founder. I started a company called WePay back in 2008. It was an early fintech company and we built that up over about twelve years and sold it to JP
Speaker 4:headquartered? Overnight success. Yeah. I wish. It was
Speaker 9:yeah. It was it was recorded in in Palo Alto.
Speaker 2:Palo Alto. Okay. Yeah. I I just remember running into it in Boston, I think in like 2012 or something. That was around Yeah.
Speaker 2:We the time. It was probably Seattle
Speaker 9:She started in Boston.
Speaker 2:Okay. That's
Speaker 9:in Boston.
Speaker 2:That's right. That's right. Yeah. Okay. Got it.
Speaker 2:Cool.
Speaker 9:We started in Boston.
Speaker 2:We were
Speaker 9:funded by Y Combinator, moved to West Coast.
Speaker 2:Oh, that's right. Built that
Speaker 9:up for about twelve years, and then we sold to JP Morgan.
Speaker 2:Yeah.
Speaker 9:I left JP Morgan, and I one of the things that really suited us well at WePay was we were early to the financial technology market. People called it banking technology at the And a lot of the same skepticism that I hear around utilities and government, we heard, we're trying to raise money from Boston VCs in 2008. Sure. They were wrong. Mean the fintech market was like the most exciting sector of technology over the next ten years.
Speaker 9:And so as I was leaving JPMorgan, I wanted to work on something that was a market that was early and that we could be sort of one of a kind, that we could be a market leader in, and that also had an important mission where we're helping people doing good for the world. This sort of lined up all of those things. My wife and I own a ranch up in Mendocino County, couple hours north of San Francisco, and a fire almost burned onto the property. Wow. And, you know, all the dots started to connect and and here I am.
Speaker 2:Yeah. That's amazing. It's it's sort of like the VC version of like build something you use yourself like the YC ethos, make something people want. Well, thank you so much for coming on the show and breaking it down for us. Congratulations.
Speaker 2:Yeah. I'm really glad
Speaker 1:you're doing this. Yeah. Thank you.
Speaker 2:We need more.
Speaker 9:Thanks, guys. Love you, Have
Speaker 2:good rest of your day. Great to Cheers, Bill. Goodbye. Up next, we have the co CEO of Spotify joining, Alex Norstrom
Speaker 1:On a huge day.
Speaker 2:Calling in from Spotify Investor Day. Welcome to the show. How are you doing? What's going on?
Speaker 3:Thank you. Hey, John and Jordy. It's good to be here.
Speaker 2:Great to have you.
Speaker 1:Fantastic.
Speaker 2:First time on the show, why don't you kick us off with the news today, what's new in Spotify's world?
Speaker 3:Yes. We just had a fantastic Investor Day twenty twenty six. We talked about what we've delivered in the past four years, which put us in a really great position in terms of user growth and financial metrics. We also laid out our four big ideas for the future. And then we also talked a little bit about how we can further monetize Spotify and all the sort of financial metrics and goals of the company.
Speaker 3:I want to send my greetings from Gustav Sarrosson, who was also on your show
Speaker 2:Yes. A while Yeah. Yeah. We talked to him in South by Southwest. Was a great conversation.
Speaker 2:We're very excited to have you here. Where should we start? I'm I'm I'm I want to jump into
Speaker 1:I love big ideas.
Speaker 2:Yeah. I mean
Speaker 1:Let's start there.
Speaker 2:There's so many different things. Maybe we should start with the reserve ticket access because I saw that organically promoted to me And it seems so logical. And I'm fascinated by the rollout, the strategy, and also, like, sort of why did it take so long? Has this been in the chamber for a long time? What has been the plan?
Speaker 2:What has been the go to market with this particular product?
Speaker 3:Great question. So I've been with Spotify for, I think it's now almost sixteen years. This is In
Speaker 2:great success.
Speaker 10:Of the most
Speaker 3:lovely improvements to Spotify Premium that we've done, I guess, since the founding, really. So you're right. It's long overdue. It's a great one. And the reason why it's so great, it's really that it solves a couple of different problems.
Speaker 3:One is who hasn't been sitting there in front of a website trying to get tickets for a concert. Mhmm. Like, it's very hard. Yeah. And if you get it, it's gonna cost you a lot.
Speaker 3:Right? And the second second thing is even if you get tickets, it may not be to the artist that you actually listen to and love. Yeah. Right? So this solves that.
Speaker 3:So what we're launching is basically we're giving you we're holding tickets for you for a certain time window for you to just go and pay and collect with our partners. So it really solves the problem in a unique way because we're matching the tickets and the concerts and the participating artists and tours with the users on our platform that are actually the true fans of this. And we look at it from many standpoints, like not just the number of streams that you're doing, so you can't just grind yourself there. It's also the catalog engagement and so on. Yes.
Speaker 3:So it's terrific. This is a fantastic improvement in Spotify Premium.
Speaker 1:Yeah. Yeah. I have a new problem which was which will be ticket scalpers setting up, you know, infinite Paying the
Speaker 2:monthly subscription fee for years.
Speaker 1:Just to try to run out of this. No. But I I think it's absolutely brilliant. Solves a problem, you know, even even from the artists like being in this position where you're trying to make your ticket prices affordable for your fans but due to market dynamics, no matter where you price it, they'll they'll go they'll go way up. And then the only beneficiary in that transaction is the is the person that's just buying the tickets to resell, and and everyone else loses.
Speaker 1:So Yeah. I think You're
Speaker 3:totally right. I mean, this, like many things that we, do at Spotify, we look at what organically happens on the platform and and what we do. And then when we see that there is some sort of signal or trend that actually just come by way of organic behavior on the platform, then we double down on it. So we've done many events with artists and groups and bands and so on over the years. On a yearly basis, we probably do 150 to 200 events.
Speaker 3:And the magic really happens when we look at who to invite to those events. And if we can really strike the balance of getting enough people there that are really sort of on a very, very high engagement level with that artist, not only again, not only just listening to the artist, but doing it maybe on a daily basis, listening having listened to the whole catalog and do it for at least an hour per day or something like that, it really gives the artist also, like, a magical experience of facing, you know, your truest fans. And this is something that uniquely we can do for for for artists.
Speaker 2:Yeah. AI is obviously at the top of everyone's mind. The large taste model is the latest technology from Spotify in the AI world. But I feel like you have to have been embedding every song into some sort of machine learning learning model for probably over a decade. Can you take me through a little bit of the history of machine learning or AI at Spotify?
Speaker 2:And then what has actually changed? Like, where are you seeing a break in the graph? Like, where where are you okay. Seeing We're we're we're experiencing some sort of discontinuity in the progress we were making.
Speaker 3:Yeah. So you're right. It was actually just about a decade ago Mhmm. When when Daniel and Gustav and I started investing into into AI then. Was called machine learning.
Speaker 9:Yeah.
Speaker 3:Right? And it was very basic the algos then. Like, it was almost like, okay, similar to what you do on Amazon, you know, John listened to this. He's similar to Jordi. He also listened to this other thing.
Speaker 3:Therefore, he should listen to that too. Yeah. So lookalike algorithm, if you will.
Speaker 2:Yeah. Collaborative filtering probably based on text, not actually looking at the waveform even.
Speaker 3:Exactly like that. Yeah. Yep. And so now many many years later, having continued to invest in that and just the the the the data, not just the data, but the learnings we have Mhmm. And the feedback loops we've had over the years, it's been compounding.
Speaker 3:So and now, you know, you're asking me what changed lately. Well, obviously, what changed is that, you know, we've got access to, you know, large language models like general intelligence that we can use to reason over the data that we have. Yeah. But what what it comes down to really is the unique data at scale here. Right?
Speaker 3:So, you know, we we log probably, you know, between I think it's three and four trillion events that happen per day on Spotify. So we really get billions of signals that are relevant to feed it to feed algorithm with. And then the the second thing that happened is is only obviously, because we started to sort of, you know, understand English. Algorithms started to understand English. So when we we sort of started importing a lot of knowledge from outside, from the outside world onto Spotify.
Speaker 3:Yeah. And and Yeah. I've noticed that the the search
Speaker 2:bar has gotten so much better at detecting lyrics. Like, I used to have to go in Google or search a lyric and then go to Spotify, and now I can just type it right in. I get it. I'm like, this is an amazing experience. I'm interested in your build versus buy versus fine tune and open source model.
Speaker 2:What's working? What's interesting? Music is you know, obviously, you're benefiting from transformer architectures from all the all the open source work. But I imagine that a lot of the tasks that you're doing aren't exactly okay, just fine tune the like a text based open source model. You might need to go a layer deeper.
Speaker 2:You might need to partner with someone. How have you been thinking about the way to deploy AI?
Speaker 3:Yeah. We we certainly believe in general intelligence and, you know, we've been riding that cost curve that that's that's gonna come down to
Speaker 2:Yeah.
Speaker 3:Collapse by a thousand x over the last four or five years or so. So we believe in in this industry commoditizing more and more. So we are going to buy, you know, the best reasoning capabilities that are out there, and then we're going to use that on top of what we call our large taste model, which we are uniquely able to using proprietary data to actually build out, much thanks to the stuff that I was talking to. The other side of the equation here that is important, I think, is also that we get a lot of feedback and data from artists as well via our Spotify for Artists application, which feeds us with data that's also proprietary and unique, which is great. So you asked about build and buy and so on.
Speaker 3:I think it's a great question. If we see opportunities to actually build something to help bootstrap or add capability, a we will do it. And I'll I'll draw two examples that are quite good. I think three years ago, we bought Symantec, which really helped us create AI DJ.
Speaker 2:Okay.
Speaker 3:Yeah. And yeah. It really accelerated the build out of AI DJ, and now AI DJ is all over the world, and we have it in different languages, and people are using it at scale. Mhmm. So that was a that was a that was a great, I think, transaction that we made.
Speaker 3:Another one that is also it's more recent actually. It was just before the end of last year, we bought WhoSampled, which provided us not with so much capability, but a unique set of data. So I don't know if you've used SongDNA lately. It's it's been killing it. I think 50 to 60,000,000 people are using it already.
Speaker 3:You know, you can listen to a song and then you can check, like, which were the samples in that song.
Speaker 2:Oh, interesting.
Speaker 3:And then you can also, like, follow the Go
Speaker 2:back to the lineage.
Speaker 3:The original yeah. You can listen to the original track and then hear how they sort of flip that into the new one. That's the see what was in there, the studio technicians, the artists, the composers, and so on. Yeah. And a lot of this, we couldn't have done, or it would have taken us much longer time without who sampled.
Speaker 2:Yeah. Structurally, how how is AI changing the work that Spotify employees are doing? Matthew Prince from Cloudflare was talking about this concept of you have builders and sellers, but just the raw measurement, that's less important as a discipline. And so he's pushing more of his staff to build new things and then go and sell it. Do you have a framework for thinking about how your employees should be using AI in the future?
Speaker 3:Yeah. I mean, we you know, a couple of years ago, I think we all you went through that, the chat GBT moment. Yeah. And just before the holidays of last year
Speaker 2:Yep.
Speaker 3:We had a similar moment around coding tools.
Speaker 2:Yep.
Speaker 3:And we also got enamored with it and started adopting it. But at Spotify, the engineering and development teams have just done a crazy good job adopting it. Yeah. So we now have, I think, to 99% adoption across Spotify. Yeah.
Speaker 3:And and this goes, you know, beyond the engineering team, but also into the marketing team that are using it not just for design, but also for for better gaining insight into what type of compelling stories to to to to tell on top of the story. So we do have very many different use cases. And, you know, people are crazy about just creating prototypes now all around Spotify, just testings in a way faster way. So what you get basically is a lot of, like, productivity gains. And I I know for a fact, one of my dear colleagues, the Chief Co Architect of Spotify NGN, he was just at Anthropic, and he was doing a presentation for their staff.
Speaker 3:And I hear from Anthropic that we are actually one of the leading developers out there in adopting AI and using it to gain productivity improvements.
Speaker 2:Yes. Have you thought about the I don't know if there is a trade off. You might be doing both. But there's a world where you have some sort of engineering pod and there's an opportunity to have more members of that team pushing code, shifting to individual contributor roles, but of course, they're managing agents, so it's also a managerial role versus embedding more technically minded folks across different organizations. You have more cross functional teams.
Speaker 2:A marketing team gets an engineer who can oversee How are you
Speaker 3:thinking
Speaker 2:about just spreading different AI tool use across different organizations that might not previously have been in a position to build a piece of software? Maybe they're in the market to buy a couple SaaS products for whatever whatever their their vertical is, but now they have the opportunity to actually build.
Speaker 3:Yeah. What you're seeing actually happening organically at Spotify is that, you know, as, you know, adoption goes up, it's typically, you know, you're by your own and you're, you know, looking at what's out there, which MCPs to connect to and how that can help your work. And then you're basically sort of copying some of the people's skills around at the company. And you're just sort of experiencing how it is to use AI to do your work, your particular field. But what now is more happening is that we all of our Slack groups and in our communities, we see people sharing use cases with each other.
Speaker 3:And the next step really is that, for instance, someone a product developer and an engineer sits down with a marketer, starts to understand, hey, okay, we the three of us can actually build something of a holistic experience of not just new product and feature, but also tell a compelling story about it, you know, in a in a much much more sort of amplified and leveraged way, which I think is fantastic when that happens.
Speaker 1:Love it. We gotta talk about fan made covers and remixes, the new deal with UMG. Yeah. Super super excited about this personally. And of course, it's been
Speaker 2:You got a song you wanna cover? Gonna do Gunna cover you were planning on.
Speaker 3:What you listening? What's your favorite track right now?
Speaker 2:Is it a Drake I've been
Speaker 1:No. I think I I think I was expecting Drake to kind of grow up by this point in his career and maybe a bit more. I feel like I grew up maybe faster than Drake. He's still obviously, you know, an incredible incredible superstar. But yeah, John was talking about Gunna.
Speaker 1:I'm a big Gunna Gunna fan. Oh, yeah. Yeah. It's great. So I'll be making some Gunna covers and remixes.
Speaker 1:But yeah, to talk about this deal, certainly controversial but this feels like one of those things that people will have one reaction and then Yes. They'll have the experience which I'm assuming will be
Speaker 2:Yeah.
Speaker 1:You know, incredibly magical and and you know, we've had Mikey from from Suno on the show. He's a friend friend of ours. And, you know, people people fundamentally, they they they say one thing on the Internet, but when they use the products, they love them. And so I think it's I think it's super exciting. So, yeah, talk about this deal.
Speaker 1:What what were the factors that were most important in getting this right so that, you know, fans win, artists win, and everyone involved wins?
Speaker 3:Yeah. Yeah. Certainly. I am certainly very, very pleased with it. I mean, it's a landmark deal and it's a landmark deal from the vantage point of we're enabling something that is, for the first time, a legal product for users and fans to actually create these remixes and covers.
Speaker 3:Mhmm. And what's more is that it's really the first time, you know, in a controlled and licensed medium that artists get to partake in in in the AI economy, really. So that that is like the the core of it. And then if you think a little bit about what is it that we're doing here, well, people love, to your point, like people love remixes and covers, and they've always done that. But there hasn't been any scaled way to really sort of tap into this opportunity.
Speaker 3:And what we're doing right now with our product is that we're unlocking this market. So where where we think actually in the end, it's going to be very additive to both the music industry and ourselves, including artists and songwriters. Totally. So it's very cool. We're launching it as a paid add on, which means that, you know, if you have Spotify Premium, you're eligible to actually buy into this add on.
Speaker 3:And when you have the add on, you can actually go ahead and create remixes it covers. And what's cool with Spotify is that we've been very experienced when it comes to free and premium and how to convert people and lead people up the ladder. And so what we're going to do is obviously to give you a certain limited usage on premium so you can actually try it out, play with it, create habits around it and then commit to buying add on. But the important point here is that you can think about it as you know, creation is paid for and consumption is included. So basically, you know, the output that you create around the Ghana, the the Ghana remix that you're gonna create, you know, I'll be able to listen and everyone will able to listen.
Speaker 3:Sure.
Speaker 1:Yeah. Is there so so I can imagine I can imagine a world, you know, maybe six months from now where the number one track globally on Spotify is a fan made remix. Like, you know, may may take more time but it doesn't feel doesn't feel doesn't feel impossible. Is there is do you think this could potentially create a new category of actual artists on Spotify? Would the person that creates a remix ever be able to get, you know, some elements of of rev share?
Speaker 1:Mhmm. Or is this like entirely gonna be more like, you know, more like a live DJ where, you know Mhmm. You're putting you're mixing and mashing and putting things together and and maybe you can build up your brand, but you're not monetize you're getting royalties for any any revenue share. Yeah.
Speaker 3:Yeah. I can't speak to the specifics of it, but but I can tell you how I think about it. You know, when I started at Spotify, together with Gustav, like sixteen years ago, we had roughly, I think it was 2,000,000 tracks in the catalog. And I've lost count, but I think it's in the order of 200,000,000 tracks now, fifteen, sixteen years later. So the catalog being big and growing is a good thing.
Speaker 3:And the problem you're talking about, a real opportunity is for us to to to do recommendations well. And that's always been at the heart of Spotify. If you ask them what why why do you love Spotify? Well, most people say, hey, it's because they seem to know me. So we're able to sort of help you discover by way of personalization, help you kind of find your tracks again that you like and so on.
Speaker 3:So really this is what you're talking to is really a personalization problem. Right? So when this product creates more catalog, our job is to make sure that the best song gets gets to the best place.
Speaker 2:Last question. Talk about the app icon redesign. I thought it really cool. Loved it.
Speaker 1:We loved it.
Speaker 2:But I'm interested in the actual I mean, I I I wanna
Speaker 4:know how did Did
Speaker 2:process it internally.
Speaker 1:That a disco ball could get people
Speaker 2:People are really talking about it. Talking about it? But but Yeah. My assumption was that, you know, it was the Spotify icon is on my home screen, and I click it when I wanna listen to music. But it jumped out to me.
Speaker 2:And I feel like that would show up in the metrics of jarring people awake. But I'm interested to know like what actually happened. Did these are you going to be changing the icon randomly every five years? Is it got to be every twenty years? Like what's the what what is the learning from doing something sort of bold?
Speaker 3:Right. So about ten days ago, we decided to change our the Spotify app icon or Spotify logo to one that is more of like a glittery disco bar version of the Spotify logo. And and, you know, to to your point, this just sparked a massive conversation around the Internet
Speaker 2:Yeah.
Speaker 3:On on basically every major social platform.
Speaker 2:Yep.
Speaker 3:And and and, you know, what a lovely and wonderful piece of culture to have a conversation around the change of our our our logo icon. Right? So not only users, you know, have been sounding off, but also other big brands. Yeah. Chuck and I made their version.
Speaker 2:The meme
Speaker 3:and suggested the that they would make a version like that. Kit Kat Kit Kat joining on the funk. That's great. So, yeah. So when you have, you know, hundreds of millions of people that passionate about culture and art and and and Spotify, this is what happens.
Speaker 3:Right? So this is sports like a massive conversation that I think is is is lively and fun. And and to be honest with you, the reason why this is happening, you know, having reflected on it a few days later now, it's pretty intense when it happens because there are two sides to it. And and then there's also all of this, like, byproduct, you know, the Internet coined a new design term around this called discomorphism. Disco morphism.
Speaker 2:Yeah. Oh, yeah.
Speaker 3:It's kinda funny. I love it. Yeah.
Speaker 2:And people have been asking for an answer to flat design. Lots of people have been lamenting how boring things have gotten. You spice it up and then people, oh, I didn't mean that, which is a very funny way to process it but Yeah. Sorry. Continue.
Speaker 3:I mean I mean, I just the the reason why this is happening after having sort of thought about it for a few days and discussed it internally, it really is because we are truly at the intersection of the humanities and technology.
Speaker 2:Sure.
Speaker 3:And I think we're we're in a good place when it comes to that. We're at scale. Yeah. You know, when when when hundreds of millions of people or potentially even billions are talking about you Yeah. Then you did something interesting.
Speaker 2:I love it. I love it. Love it. Yeah. A really, really well executed stunt and yeah, just got everyone talking and and reminding.
Speaker 2:And it's hard to break through with with something like a twenty year anniversary with a milestone like but it's important to do something like that. So congratulations. Yeah.
Speaker 3:Did the most yeah. Thank you. We did the most for ourselves Yeah. In the beginning, but now it turns out that, you know, everyone else
Speaker 2:Building a company around music should be Like, of this, like, it it's I I know people have their think pieces and their deep dives on contrast ratios and all sorts of things. But, like, at the end of the day, it's fun for a company like Spotify to do something fun with an app icon for few days.
Speaker 3:It is.
Speaker 1:I love it. Also, I put back on those people. I thought I looked exactly like a disco ball would look if you were in a dark room
Speaker 2:That's right.
Speaker 1:Listening to music wake Yeah. So I thought it was I thought it was
Speaker 3:Yeah.
Speaker 1:Pure to the to the disco ball brand.
Speaker 2:I agree.
Speaker 3:I agree. That's good. Thank you. Keep it on that.
Speaker 2:Anyway, thank you so much for coming on
Speaker 1:the show. Great to hang.
Speaker 2:Congratulations on the progress. Yeah.
Speaker 1:Congrats to the team on all the new milestones.
Speaker 2:We will talk to you soon. Have a great rest your day. Goodbye. And if you haven't been following, the stock is up 13% today. Spotify is a $103,000,000,000 company.
Speaker 2:Not too shabby. Our next guest, Jordan Schneider from China Talk. You know him. You love him. He's back on the show for the third, fourth, fifth, sixth time.
Speaker 2:Who knows how many times it's been. We lost count. But it's been too long, and we're happy to have you here. How are doing?
Speaker 4:I'm good. I gotta be honest. Was also pretty confused by the Spotify. You were confused by it. I thought,
Speaker 1:why being a $100,000,000,000 company can't have fun in this country. Yeah. What's wrong?
Speaker 4:Just saying it took me longer than click it. I thought I had like some weird iOS update. I just think Tahoe, whatever.
Speaker 2:Oh, yeah. Sure. Sure. Sure. I just think that like the fact that you processed it, even if it slowed you down, it put you in, you know, a fast thinking, slow thinking.
Speaker 2:You're in slow thinking mode.
Speaker 1:Not addicted to phone enough.
Speaker 2:Are they still are they still rocking the are they still rocking? It's still the disco ball. I like it. I think they should just keep this thing. It stands out so much from every other app on my phone right now.
Speaker 2:I love it. Anyway, how are doing? Give us maybe let's start with the postmortem on last week. How is the China summit? And then we can just go into everything else.
Speaker 4:So boring,
Speaker 2:man. Right. I knew I knew you were gonna say that. Was like, we're gonna talk about everything but China because it was so boring. But
Speaker 5:And they let
Speaker 4:me down. I mean, look. I think there is a clear period of stalemate which we've gotten into where The US has some leverage over China Mhmm. Which has been something that really since like 2017, Trump won Obama Trump won Biden and then start of Trump Truth thought that they could kind of keep turning the temperature up and squeezing on tariffs and export controls and investment restrictions. And then all of a sudden, China, April 2025, punches back with rare earths.
Speaker 4:And all of a sudden, they realize, you know, they run they run the experiment and it works, that actually the PRC has real leverage over The US and is able to kind of constr like, meaningfully constrain what American presidents want to do when it comes to more course of actions on China's, you know, technological and economic expansion. So both sides have kind of realized that and what we got is a, you know was my headline? Prestige on the cheap. Prestige on on Where The US decide where, you know, you have the whole cabinet flying over, you have every fancy CEO flying flying over, just being awed and wowed by, you know, their thirty six hour vacation to Beijing.
Speaker 1:Yeah. It felt like tourism.
Speaker 4:Yeah. And look, there's an interesting debate to be had about whether the like, giving them the face and giving them the atmospherics of that is actually like, kinda, in some level, costless, and maybe this, like, makes them feel less aggrieved, less likely to start World War three. I mean, this is the argument with Putin. Right? Disrespecting him Mhmm.
Speaker 4:And then he decided, no. Like, I'm gonna show you just how tough I am. So I'm not kind of on face opposed to it, but, you know, it was it was kind of just more or nothing.
Speaker 2:Yeah. I mean, you mentioned every fancy American CEO was there. But were you surprised or were you expecting or did it break your expectations that no Sam, no Dario, no Demis, no Sundar, a sort of lack of AI representation. Yes. You have Elon, and, yes, you have Jensen.
Speaker 2:Very important figures in the AI American AI build out, but no true lab leaders from my, you know, rough estimate if I define it a certain way. And it felt like, okay. Maybe this discussion should be about AI and it's and it's they're they're they're not even bringing the people to let them get a word in edgewise. Not even a single line of of conversation will happen. Was that as expected or how how do you process that?
Speaker 4:Yeah. I mean, it's interesting because like this is phrased this is framed as like a trade delegation.
Speaker 2:Sure.
Speaker 4:Right? And so almost all of those companies like Meta excluded. I mean, I guess they
Speaker 2:have a person there. But Zuck wasn't there. Yeah.
Speaker 4:Yeah. But but that person's like a Trump one person. Yeah. It's kind of just like keeping with the vibes. And I guess Meta builds glasses builds glasses in China.
Speaker 2:Yeah. And they and they acquire a AI agent companies, Manus. They they they are a buyer of Chinese companies or formerly Chinese companies that have moved to Singapore.
Speaker 4:Which they're now not allowed to do. So, they had some lobbying to But, do, I like, the you know, the asks, I think, are really inchoate. Look, the US government, we just had news today that Trump eighty sixth a executive order because he doesn't know what he wants to do about this Yeah. Sort of thing about AI safety. And if like, you can't even figure out what you want from a domestic regulatory perspective, like, are you really ready to like, put all the cards on the table have this big, you know, grand summit with the Chinese to make sure that bioweapons don't kill us all in 2029?
Speaker 4:I don't think so. I mean, it'll happen at some point, but it's it's just a little premature, I think. Maybe not from a technological perspective, but from a sort of policy perspective that you don't expect much of a serious discussion between Yeah.
Speaker 2:Are are you Sebastian Malabai had an op ed where he was sort of gesturing towards, like, the possibility of more collaboration on AI between America and China. You're you have your hands in your face or your face in your hands, so I assume you are skeptical that that will take place anytime soon. But I mean, also the AI 2027 folks, very good at forecasting, have predicted a lot of what's happened. Say China wakes up in 2026.
Speaker 4:Yeah. I mean, it's not impossible. Yeah. I think the sort of look. If the American political system has not yet woken up to an understanding that you need a different regulatory strategy in order to keep humanity safe.
Speaker 4:Mhmm. I think it is unrealistic to expect a strategic adversary who does who is, you know, six, twelve, eighteen months behind where you are on the sort of technology development trajectory to come to the same realization. Now, you know, it'll happen at some point. I think this stuff is really powerful and the the sort of logic that America doesn't want, you know, bioweapons to be developed by Al Qaeda or ISIS or Hezbollah just in the same way that China wouldn't want it to be done by, you know, the Falun Gong or Tibetan separatists or, you know, any any group that see they see as like a non state actor that would that would want to kind of take down the party, applies. Right?
Speaker 4:But, China, I think, is deeply the Chinese leadership is deeply hardware built. I think they're deeply skeptical of these sorts of arguments on face because they're kind of sci fi and the the sort of jour the analogy or the journey that The US and Soviet Union went on over the course of the Cold War to start to have real kind of discussions about strategic stability and arms control happened after you had the Berlin crisis and after you had the Cuban Missile Crisis. So like, look, Anthropic putting out a paper saying Claude Mythos is really scary is one thing, but it is different at a fundamental level than like completely shaking a society and like having the entire world realize that you are on the verge of apocalypse.
Speaker 2:So Yeah.
Speaker 4:I hope we don't need that, but I am I am Haven't had the time to talk about that much will come of this and the What do you Before it really accelerates.
Speaker 1:Yeah. How much have you read into the theories that maybe China would would fund data center pushback in The United States? I don't know that they they would need to. But if they were, if they felt that was important enough, they would signal something about how they think about the technology.
Speaker 4:I think this is Cope by the laps. Look. Like Yeah. And the Okay.
Speaker 2:And then
Speaker 4:I mean, you know, it it is I think Ben Thompson had the right take on this a few days ago. This can be solved with money. Like, if if you really put it you know, put put the choice to a town saying, okay, we will pay everyone within a 20 mile radius $10,000 a year. People will start this ugly thing.
Speaker 1:People will start frantically trying
Speaker 3:to buy
Speaker 4:a to live next door. Or like, look, make the data centers beautiful. Build a park on top of them. Like, give me some playgrounds.
Speaker 2:That is the one that I'm the most skeptical of in the American society. I feel like they will be companies will be paying dividends and mailing checks far beyond far like, long before anything looks beautiful in this country. Like, build massive, like, monolithic structures all the time. It's a lot of cement over here. I don't know.
Speaker 1:Turn the turn the GPU racks into free slots.
Speaker 2:Every time I see one of these like beautiful industrial structures, it's always in The Nordics. It's never in America. Sometimes it's in China. They build a
Speaker 1:train Yeah. You have the the the data center. You got all the all the different racks of GPUs. Yeah. Then you just put a slot machine attached to each one them.
Speaker 2:Maybe that's through and Yeah.
Speaker 1:And you get, like, three or
Speaker 2:four. Wonder we we I wonder what's the you know those cell phone towers that look like trees? And I don't think they look any better, really, but I guess they do sort of blend in. I wonder what the, like, economic mechanism was for going that direction. Because when I'm driving here to LA, I see normal cell phone towers, and I see tree like, fake trees cell phone towers.
Speaker 2:And there had to be a reason. Like, it has extra cost to make it look like a tree. Like, is that just a choice? Is this like a nonprofit that's funding this? Like, who's who's lobbying for this?
Speaker 2:Is there a law? I don't know.
Speaker 1:We gotta Every time I drive
Speaker 4:Can we please get the TBPN segment?
Speaker 2:Yeah. We need to dig into this.
Speaker 4:The tree phone poll.
Speaker 2:Come for the questions, not the answers. I'm just riffing about things I don't know and would like to know.
Speaker 5:If I
Speaker 1:drive by and and and they get me, I just start slapping me and I'm like, you got me big telly. Trick. You got me.
Speaker 4:I thought it was a tree. From a distance. Yeah. Every time. Well, bad ones are like when they're five times as tall as all the other trees around.
Speaker 2:Yeah.
Speaker 4:And just like and like the branches only start like four fifths of the way
Speaker 2:up. Yeah. It's just Yeah. Yeah. Yeah.
Speaker 2:Yeah. It's very it's very half hearted in its attempt at disguising itself. Ridiculous. On on other China issues, did you see there are two sort of, dueling predictions? Maybe maybe I'm making them dueling predictions.
Speaker 2:Chamath Paliapitiya says Taiwan not gonna be a factor geopolitically in eighteen months. Dan Wang, has talked about how, technologists overrepresent the chip story in the Taiwan story. And in fact, the discussion over Taiwan goes back much further and is grounded in more of like capitalist versus communist decision making and alliances. Where do you stand on the on Taiwan today versus in two years?
Speaker 4:I have to acknowledge Chamath's existence. I refuse to do that. I think that Taiwan is a place that has mattered for a while
Speaker 3:Mhmm.
Speaker 4:And will continue to matter Mhmm. For a very long time to come. I mean, first, only on the chips thing, the idea, like, I
Speaker 6:know. Ask any analysis, like the
Speaker 4:percentage of chips that are going to be manufactured in Taiwan Yeah. Eighteen months from now is still gonna
Speaker 6:be like 85%.
Speaker 4:Or 90%. So yeah, it used to, you know, it was a 100% Yeah. For a window. I am glad Intel isn't a a flaming pile of crap anymore and it's like nice to see Samsung also starting to get their act together. But if if really that's the only thing you care about
Speaker 2:Yeah.
Speaker 4:No. You will still have a, you know, global economic catastrophe if the lights go off in Taiwan in 2028. Now why should you care about Taiwan besides the chips? I mean, it's a it's a democracy. People have, you know, deserve to have self determination.
Speaker 4:We can set principles aside if we really have to do that. But look, I think from a from a sort of geo strategic perspective, there's also this kind of concept of the first island chain. I think it makes it it it makes the the, you know, broader Pacific architecture that America has has has built over the course of the past seventy five years in Asia a lot more tenuous if all of a sudden, you know, the the kind of anchor to both Southeast Asia as well as North Asia becomes, you know, a PL and base. So Yeah. Yeah.
Speaker 4:They're wrong.
Speaker 2:Yeah. So so so many reasons that Taiwan will remain important into the distant future regardless of what happens with Intel and TSMC, Arizona, etcetera. Agree with you on that. What do you think the next catalyst might be in the rare earth story? Because we're starting to see rumblings about funding for American indigenous supply chains there.
Speaker 2:Eventually, that becomes at least a stocking horse, if not a poker chip on the table, on the bargaining table. But where are we on the rare earth stalemate that became an important bargaining chip somewhat recently as you put it in the intro?
Speaker 4:I mean, it's a really interesting question. I've I've read reports saying that even five years from now, the leverage is going to still exist. And I think there's a sort of broader question of like, this is the second largest country in the world and largest economy in the world and it's gonna stay that way for a really long time.
Speaker 2:Yeah.
Speaker 4:And the sort of ambition to fully decouple such that China does not have leverage over The US economy and can kind of squeeze it coercively seems to me to be a very tricky thing. Now you can spend lots of money to sort of make that less acute or sort of turn it down over time or or, you know, protect the particular things if you're worried about, you know, individual like specialized inputs into fighter jets or, you know, something that would be really catastrophic like insulin getting cut off or something. But it is you know, this is like a this is like a generational challenge of shoring this up and b, there's also an offensive side, right, of, you know, escalation dominance in deterring an adversary from from squeezing on stuff like this also requires you to be able to sort of credibly send signals that you can take pain and cause pain in a way that would require the, you know, the the other party to to back down and not necessarily use these tools. So we're, you know, we're we're we're at this like awkward equilibrium. I think there's a lot of like hard thinking that still needs to be done to like like really conceptualize, like what's the right way to spend money and the right way to think about this relationship.
Speaker 4:We actually just ran an essay contest on China Talk about economic security. We're gonna be I have at 4PM, we're doing a mega pod with three of the winners. Amazing. So maybe I'll have a better answer for you after that.
Speaker 2:Love it.
Speaker 4:But it's a hard one.
Speaker 1:Does g day trade
Speaker 2:prolifically? Who's the best day trader in the global In power
Speaker 4:in Here's the thing. I got a piece coming out about comparing American and Chinese corruption.
Speaker 7:The
Speaker 4:difference is that in China, they still feel like they have to hide it.
Speaker 2:Okay. Will be an interesting Shifting gears shifting gears both literally and figuratively. Cars. Have you driven any Chinese vehicles? Have you been outside in the BYD?
Speaker 2:Are you planning
Speaker 6:I'm doing car reviews on China talk.
Speaker 2:I would love to see one. Have you been in a Zeeker? I keep seeing these. They look amazing.
Speaker 4:Zeekers? I watch a lot of YouTube I watch a lot of YouTube and Bilibili reviews.
Speaker 5:Okay.
Speaker 4:I have been in a BYD in Norway. In Norway. Of all places. They had like in the main Yeah. Like like park, they had a giant setup.
Speaker 4:You know, it's really impressive. Yeah. I you should get some you should get some American car manufacturers on Yelleth, though. It's pretty embarrassing. You know, one of the more interesting developments, I don't know if you guys have been tracking this.
Speaker 4:No. The Waymo using a Zeeker That's body?
Speaker 2:Yeah. Yeah. Crazy. Import restrictions because if Zeeker's not here, BYD's not here, you would think that like the supply chain would be restricted but they must have found a way around.
Speaker 4:So the trick is that it's their it's the chassis and the battery and literally nothing else.
Speaker 2:Yeah.
Speaker 4:So they are saving money Sure. On that. But like the the rules right now are just on all of the sort of electronics and connected anything. So Yeah. Waymo is filling up the entire car with stuff that Interesting.
Speaker 4:Is not
Speaker 2:Okay. Yeah. Well, that's probably like more reassuring that Xi Jinping won't be tele operating. You'll have a a Waymo employee beaming in if you see a traffic cone out of What
Speaker 1:what do you how much attention do you pay to their like humanoid antics? Like I feel like they're just leaking out videos of just this like all this silly stuff to kinda just get us a little bit comfortable with it. But if you actually go there on the ground, it's like droid army, you know. They've got like Sure. A 100,000 humanoids marching in in in unison and then they just put out the video of it like dancing to Michael Jackson like collapsing collapsing and and getting getting dragged dragged off off stage.
Speaker 1:Stage.
Speaker 4:You know, it's interesting because there isn't a market yet. Right? Like these are not these are toys and these are like things you sell to universities for research. But at some point, there will be. Yeah.
Speaker 4:And then there's gonna be a really interesting challenge of like whether or not I I think there's like some level of consensus now that the western makers have like smarter software. But if you can like, you know, it's it's one thing to fast follow the models themselves, but like if you can only if you can apply them like at a 100 x scale, right, then yeah, it could be really dramatic. I mean, you know, I don't I'm not doing like the the episode, you know, Star Wars episode one by Droid Army. Like, well well, that might take a that might take a few more cycles. But just from
Speaker 3:a Can you
Speaker 2:imagine can you imagine a Chinese humanoid company trying to distill Tesla Optimus after they have a fantastic data breakthrough and they're just having all the Optimus work in cubes like trying to farm the data out of it? Like they I just feel like
Speaker 5:it's such a flea of my
Speaker 2:god. Yeah.
Speaker 5:It's brilliant.
Speaker 2:You have to physically distill the data for so you buy you buy a million Tesla Optimus robots and lock them in a warehouse so that they can move boxes for you so that you can distill it into your own robots or something.
Speaker 5:Is a company.
Speaker 4:This is a RL environment. Yes. I I love it.
Speaker 2:I should start this. In China? Think I
Speaker 4:Oh, no. I mean, they're just like Resell. In The US.
Speaker 2:Yeah. Yeah. You need a hair dryer to remove the Optimus sticker and slap on some other stickers. That's where the money is being made these days. But you gotta hide that corruption.
Speaker 1:And it's really great that we have a software advantage and they have a hardware advantage on this. Right?
Speaker 2:Think that's
Speaker 1:really bullish for us.
Speaker 2:Yeah. Because software because like they
Speaker 1:would never be able to copy like software off of a hard drive, put it on their hardware.
Speaker 4:Well, and that's the thing is like this is the difference with AI, right? Yeah. Is at least America has way more chips and way more compute
Speaker 2:Yeah.
Speaker 4:As long as Taiwan still exists. Yeah. Hardware advantage. But that will not be the case for the like, you know, humanoid embodied AI Yeah. Takeoff.
Speaker 4:It's like the thing you need to actually use the fancy model
Speaker 2:Yep.
Speaker 4:Is almost certainly going to be manufactured in China and manufactured at the scale that could be like, you know, multiple orders of magnitude bigger than in the West. Now, this may change like once this becomes economic. Yeah.
Speaker 2:Right? So America can I mean, like you look at you look at space like like we have multiple companies that land rockets, very capital intensive, it's an industrial process? You would assume that China would win that but they are but we have a lead in in master orbit still and so it's not impossible but we do tend to let our leads languish like we have in the car industry seemingly.
Speaker 4:And it'll be interesting because there'll be this lag where China like because they already have all these humanoid companies that like have the ability to scale, will scale faster once the kind of like economic utility of these things turns on.
Speaker 2:Yeah. Definitely.
Speaker 1:If you if you believe in AI progress, do you have to believe in a Taiwan invasion? Because assuming assuming, you know, we keep making progress or we have accelerating progress, doesn't that just increase the prize for
Speaker 2:Yeah. But it might increase the defensive capabilities.
Speaker 5:Sure.
Speaker 4:Yeah. And I think there's there's like plenty of other things you can do to be obnoxious. Mhmm. And there's so much there's look, this is this is why Chamath is wrong about everything is because it's not all about technology. Like there are other risks and incentives at Sure.
Speaker 4:And like institutional dynamics and historical dynamics at play. And there are a whole lot of downsides to starting something that you don't know how, like, you don't know how it's gonna end, is a lesson that she has now got to relearn from Putin over the past five years.
Speaker 2:So Makes sense.
Speaker 1:Last thing, we touched on it briefly and then I know we're over time. What happens with Manus? What's your prediction? Are they gonna are they gonna buy the company back from from Meta and just head home? Is there any precedent for something like this?
Speaker 4:I don't really understand. I mean, like, all of the employee like, do they have to give the tech back? They weren't really buying the tech. They were buying the was like an apple hire. Everyone's in Singapore except for the two founders.
Speaker 4:So like, maybe the founders just get screwed out of all this money and, you know, the employees continue on their merry way in Singapore. I think it's a it's a messy one and I don't know, like, Mehdi eats a loss. Yeah. Something. I hope Bill Gurley
Speaker 2:is Before you go, we have an answer to the question of telephone pole camouflage. Tyler, do you wanna do you wanna give us a little update on this? Can we can we do yeah. Let's cut
Speaker 7:to Yeah. Telephone pole camouflage basically began after the 1996 telecommunications act.
Speaker 2:Mhmm.
Speaker 7:So it basically, like, restricted the ability of local communities to regulate, like, the actual placement of the telephone pole.
Speaker 2:So a city can't say, you can't put a telephone pole there. You can't put a cell phone tower there, but they responded.
Speaker 8:But but but they basically made it so oh, wait. They they they made it so
Speaker 4:Stop. The
Speaker 8:local governments would say, you have to can't flush it. Right? So so now we see that all different
Speaker 7:forms of these. There's there's trees, there's cacti, there's like church steeples.
Speaker 2:Yeah. Bigger than these.
Speaker 5:A lot
Speaker 4:of chipmunks run up and down those poles too. Right?
Speaker 6:And camouflaged an ad over a 100,000 to tower construction prices, which is still cheaper than losing the site. Three towers can cost up to double.
Speaker 4:Hey. You can play this game. You can play this game.
Speaker 2:You have a soundboard too?
Speaker 4:I got my buttons.
Speaker 2:We have a guest with buttons. Uh-oh. Let's see. Can you get it to work? Uh-oh.
Speaker 2:Oh, no. Oh, no.
Speaker 5:Another one.
Speaker 6:That's a narrative violation. Will it work? Let's find out.
Speaker 1:Your buttons aren't working. Anyway But bring bring them next time.
Speaker 2:Bring them next We'll
Speaker 1:it again today.
Speaker 2:It's too long. We'll talk to you soon Jordan. Have a great day. Hey. We're good.
Speaker 2:There we go.
Speaker 5:Hey. Very
Speaker 2:well done. Thank you so much for taking the time. Have a great rest of your day. We'll talk to you soon. We went overtime, so we will bring in our next guest immediately.
Speaker 2:We have Christina Lee Storm from secret level. Welcome to the show. Sorry for delay.
Speaker 1:What's happening?
Speaker 8:Hey. How's it going?
Speaker 1:It's going good. Little too much fun with our having soundboard. Fun
Speaker 2:with the regular I love it.
Speaker 3:It's great.
Speaker 2:Sound cues, all sorts of stuff. But since it is your first time on the show, please introduce yourself a little bit.
Speaker 8:Hi. I'm Christina Lee Storm. I am head of studio over at Secret Level, which is an AI native studio. Yeah. And I also am co founder over at Playbook PLBK.
Speaker 8:Yeah. I identify myself as a producer. Okay. Like an independent film producer.
Speaker 2:Yeah. How are you thinking about the the blurry line of how AI works its way into productions these days? Yeah. You have Toy Story with CGI. You also have a little set extension and maybe even a little CGI creeps into a Nolan movie every once in a while.
Speaker 2:But AI is very different. People are thinking maybe it'll generate the whole movie. Maybe it'll just sort of make a green screen a little bit sharper. How are you thinking about the opportunities and and the trends?
Speaker 8:I mean, it's interesting because we've had technology in the entertainment industry for a while. I was a consulting producer on a film called Jurassic Punk, which was at the about the birth of computer graphics. Yeah. It was about a gentleman who was from Canada. His name was Spaz, Steve Williams, and he actually created the first walk cycle
Speaker 2:Okay.
Speaker 8:T Rex
Speaker 3:Yeah.
Speaker 8:For Jurassic Park, and he was a total rebel. And in the in the documentary, we talk about how he just felt like, you know, we could do this with computer graphics. At the time, Jurassic Park was like, hey, we're gonna do an animatronics. We're gonna do it old school. We'll do
Speaker 2:it
Speaker 8:onset. And there was an an ability to actually now, like, wait. Hold on a second. We could create this. And so when Spielberg and Kathleen Kennedy saw the first walk cycle as he was playing it on his computer screen.
Speaker 8:Yeah. You know, just sort of he knew when they were gonna walk by. It it changed everything, and that was the birth of computer graphics. So we know that technology has always been a part of that story, And so I think, you know, it is quite it a lot of people like to use the headlines like disruptive, but I think it's just an ongoing process Mhmm. Of how things should sort of evolve.
Speaker 8:And me being my background's traditional production producer. I've been an independent producer for a while. I think it's just it's part of the process. And I think before, I think a lot of producers would just offline, you know, any kind of technology or any specialty to different departments or groups. Mhmm.
Speaker 8:And today, I think anyone who's gonna really survive and thrive into the new world order of this, you know, everything's sort of shifting and changing, we have to actually lean in. And there's this interesting, like, technology storytelling, you know, convergence
Speaker 2:Yeah.
Speaker 8:Entertainment that is exciting. And I think, you know, that's yeah.
Speaker 2:On the topic of Jurassic Park, grade this grade this prediction. Jurassic Park, massive success. The franchise has grossed I think billions, maybe over a billion dollars. It's it's it's a fantastic financial success. But interestingly, Jurassic Park, of course, is owned by Universal and but dinosaurs are not particular intellectual property.
Speaker 2:It's not like Superman. The T Rex is not something that a studio can Oddly, no other studio has created like the Superman to Spider Man. There's not the Marvel Universe to the DC Universe. I would have expected a reaction series to Jurassic Park in that IP library at some point. Never really developed.
Speaker 2:But in the age of AI where it's increasingly easy to generate imagery of dinosaurs and you don't have any intellectual property concerns because you're not recreating a particular actor, I predict that there will be a massive surge in dinosaur themed movies. What do
Speaker 1:you You create the Dino Prize. The Dino Prize.
Speaker 8:The Dino Prize. You know?
Speaker 2:Is there anything here? Am I thinking about it correctly?
Speaker 8:I think that you're on the right track in terms of like dinosaurs are not, you know, there's not a particular IP. But here's the thing, and and this is sort of where it does fall back to traditional Mhmm. Methods. It's like the storytelling is everything. Like Yeah.
Speaker 8:You could have there's a lot there's a lot of different ways, you know, that you can tell and share stories, but it's really what is the you know, what are the specific things with the character? What's happening? What's the world? And so, yeah, someone could come up with a dinosaur type movie, but what is it? Why why is that special?
Speaker 8:Why is that undeniable for someone to say, yes, I want to watch that, and I want to and I want to engage in that? So I think the concept of that is is good. Think, you know, at the end of the day
Speaker 2:Potentially half baked, but we'll get Well,
Speaker 8:that's the difference between really great like Yes. No matter what the technology is, you have to still be a really good storyteller.
Speaker 1:Yeah. Please. Article in the Wall Street Journal this morning about a new film called Hellgrind that's I guess premiering at Cannes. They're saying that it cost half $1,000,000 to make and around 400,000 of that was yeah. I'm sure there were, you know, there with all these things, there ends up being costs that aren't kind of captured Sure.
Speaker 1:On on maybe a napkin.
Speaker 3:Sort of a
Speaker 2:deep sea moment.
Speaker 1:Yes. But but is this the beginning of of like, do you expect hundreds of these over the next year? I I imagine you're you're hearing and seeing a lot that are in the works and and working on some yourself, but
Speaker 8:Yeah. Yeah. So I mean, I think there are, you know, can I I actually didn't go this year? I usually go every year. I knew that there was gonna be a lot of announcements about different projects and things, and at secret level, you know, we actually will have an announcement next week.
Speaker 8:I was like, should I come on the show Because next week, there's gonna be, you know Oh, that's
Speaker 2:a good event.
Speaker 8:At the I'm happy to come back. But at the end of the day, I think, you know, it's it's let's just be real. Let me just be real. There's a lot of things that are being pioneered. Like, what are the costs?
Speaker 8:What what's happening here? How do we align with even, like, guild related things that are issues? You know, how how can we it's not just like, let me just get this out. You know, I think there's something even bigger to to that degree. You know, I think people a lot of people could say, yeah.
Speaker 8:I can make a movie. But I think it's really again, I'm gonna go full fall back on story. I'm gonna fall back on what is the process in which that's gonna happen. Like, at secret level, we do we have our own proprietary workflow pipeline that really really allows us to scale, and I think those costs, when those get flagged, it's like, yeah. What what's the total cost in it?
Speaker 8:There's a there are a lot of costs, and so I don't think I think it's really I I think when people talk about, like, the the budget and they're just focused on the budget, think they've missed the mark on Yeah. Doing the bigger thing.
Speaker 1:So what what is your maybe it's too early to say, but what do you think is going to be the winning formula? Obviously, you're it's still an experimental time, but you said story matters a lot. Obviously, technology matters a lot, the what models you're using. But where are you thinking of taking, you know, traditional filmmaking approaches versus, like, reinventing your approach?
Speaker 8:Yeah. I think there's okay. There's a couple things here. Great question, Jordy. I think that there will you know, we there was a time where like independent film was like on the rise.
Speaker 8:It it was awesome. We saw really great filmmakers come out of that, like, know, going to Sundance and whatnot. And I think that that's really important to feed and and bring about, like, creativity, really great stories. So I I do believe that with the tools, we have more of an opportunity for independence to sort of bring that to the forefront. But, again, I you know, story it's about the story.
Speaker 8:Like, is it gonna be a really great story? I think the other piece is is will we see this you know, I I I kinda share with this because I've been a former studio exec surviving studio executive and also a producer, and I think that what's needed is, you know, is the chasm gonna widen? Like, how do we sort of bring that? Do we wanna bring the chasm closer together so it's not just traditional, you know, studio affair? Or do we wanna, like, really see these independent voices come out and we're we we can see those play out?
Speaker 8:And I think as time tells in how people will refine their storytelling abilities, I think that's really important. I think there's also, to be honest, there's a way in which filmmakers who use AI tools are using it at their the best abilities is is it almost a slight variation than maybe a traditional approach from, let let's just say, like, a studio, you know, pipeline type film. I think and that reminds me of, like, you know, when our you know, when Lou George Lucas came out, like, you know, he was breaking new ground in technology. He was like, this doesn't exist, so how do we create something that doesn't exist? And I think we have to allow for that creativity to to to be to birth.
Speaker 1:Totally. Wanna take a
Speaker 2:question from the chat. What is your favorite movie? Oh,
Speaker 8:gosh. I have a
Speaker 2:Or maybe something just with a great story that you think is
Speaker 8:I love Subtitles. Subtitles.
Speaker 5:That's a great movie.
Speaker 2:Have you seen that?
Speaker 1:I have. Yeah. There we go.
Speaker 8:I like to say, and I I'm gonna embarrass him, our founder Jason Zada from secret level. I call him like the he's like the like the blossoming Chris Nolan.
Speaker 1:Oh. Woah.
Speaker 8:And he's just really creative. He the way he approaches story.
Speaker 2:Does he use a phone? Nolan famously, no phone.
Speaker 1:So no phone guy.
Speaker 8:No phone.
Speaker 2:Did an interview with with he doesn't know email either. Printed out emails if somebody needs to email them. No phone. Also doesn't like maps because they reorient you. They don't always face north, he doesn't consider that a map.
Speaker 2:Very interesting lifestyle. Yeah. Anyway
Speaker 8:I would say Inception, I would say, like, let's go really old school. It's a Wonderful Life.
Speaker 2:Oh, yeah.
Speaker 8:And then if I get my, like like, just real old school I I love, like, great character based
Speaker 2:Yeah.
Speaker 8:When Harrods met Sally. I'm all over the place. Yeah. I'm all over the place. I I like being that way, people can't
Speaker 2:Yeah.
Speaker 8:Say, oh, like sci fi or she,
Speaker 5:you know.
Speaker 2:Sure. Sure.
Speaker 8:Godfather. Godfather.
Speaker 2:I saw When Harry Met Sally at an outdoor movie theater at one of the screenings you buy tickets to seeing an old movie outside with a bunch of people. Tons of fun.
Speaker 1:Last question from the chat. Yeah. What is your single favorite piece of fully AI generated content? It could be like thirty seconds long, a minute long. I I can't really expect it anything else.
Speaker 1:Think for us it's like Harry Harry Potter Balenciaga, which funny enough was like Pokemon a the year coat. A year and a half ago maybe at this point. So
Speaker 8:if you haven't seen it, yes, you know, there's a secret level the heist.
Speaker 2:Okay.
Speaker 8:Watch the heist. When Jason shared his first thirty seconds, I was like, okay.
Speaker 2:Okay. We got something.
Speaker 1:We're cooking.
Speaker 8:We're we're we're approaching some really interesting things.
Speaker 2:That's So great.
Speaker 8:You can see a lot of things at secret level.
Speaker 2:Yeah. Yeah. I love it.
Speaker 8:At c o.
Speaker 2:Amazing. Well, thank you so much for taking the time.
Speaker 10:Really great
Speaker 9:to meet you.
Speaker 2:It's great to meet you.
Speaker 1:Make sure to share Yeah. Your announcement next week with us.
Speaker 8:Yeah. I will.
Speaker 2:Cover it
Speaker 5:in the show.
Speaker 2:Can't wait. Have a great rest of your day. Cheers. Talk to you soon. Bye.
Speaker 2:Goodbye. Bye. Up next, our last guest, Eric from Modal Labs with some big It's been a minute.
Speaker 10:It's been a minute.
Speaker 2:I'm excited to catch up. How you been? Good. You've been busy? What'd you do?
Speaker 2:Turking. What happened?
Speaker 10:We just announced a c round today, which is very exciting.
Speaker 1:How much? How much?
Speaker 10:How much? 4.65 post value.
Speaker 5:Woah. Wow.
Speaker 10:I'm racing 355,000,000. So general catalyst Yeah. Led it together with Redpoint.
Speaker 1:Fantastic. What was the specific catalyst that led to this round?
Speaker 10:There there's been a lot of stuff that's been going on. I I I think one particular exciting moment in the last twelve months or really the last six months has been we've we now have a a a product called sandboxes that's just growing insanely fast, almost two x every month for the last six months. So sandboxes, if you don't know, basically, the idea is, like, you can take typically LM generated code and execute it in a safe environment. So it powers a lot of reinforcement learning, powers a lot of vibe coding apps, a lot of background agents. But, yeah, I mean, in general, we've seen tremendous growth also with inference.
Speaker 10:Moto has always been kind of we started a company five years ago with the idea of building pretty general purpose infrastructure. We felt that a lot of infrastructure wasn't really built for AI. And so when you look at all these companies out there building sort of AI applications, they all need different things. Some some of them need sandboxes, inference, training, batch jobs, like all kinds of stuff. And and our goal is to provide all of that and and really kind of build a new sort of almost like a new cloud in a way that that supports all these types of very cool applications.
Speaker 1:Very cool. I feel like it's been almost a year since you were on, which feel which is like, you know, fifteen years fifteen years. It's back in October. October. Well, there there we go.
Speaker 1:Like feels like feels like a year ago even though it's maybe maybe less. What yeah. What have been the key kind of inflection points since then? Sandboxes sounds like sounds like one, but I imagine a lot of this is the space is moving so quickly if you get a signal from two or three customers, hey, we have this problem. Can you build a solution?
Speaker 1:And then you can just see tremendous growth in like a a very short period of time. And so in some ways, like you have an existing portfolio of products that are all growing, but are you trying to constantly be making new bets based on customer needs, or is it is that maybe not even the the approach?
Speaker 10:I I I think one of the benefits of building infrastructure is, like, you can sort of, you know, look at customers, of course, and and see what they're doing. But you but I think with infrastructure, you can also sort of argue a little bit more from, like, first principles. Like, what are the building blocks that people are gonna need in terms of compute? So sandboxes was actually something we launched three years ago, and it really started taking off, like, nuts in in in, in the summer last year. And and and similarly, I I think with with, you know, inference is sort of similar.
Speaker 10:We launched it almost, four years ago. We're working on some other really cool stuff, around training and some other products. And and I think one of the benefits of infrastructure is you can have a little bit more sort of a first principle, like, you know, let's build the right building blocks and then let our customers sort of figure out what to use them for.
Speaker 1:How how do you think about planning? Like planning planning demand?
Speaker 2:Add a zero to
Speaker 1:last year. Add two zeros. Yeah. It's everything. Yeah.
Speaker 1:Yeah, it just feels like the, you know, the best this is the hardest like demand planning challenge that really any biz set of businesses have ever faced in history.
Speaker 10:Yeah. It's rough. It it like, I mean, for us, it's like, we basically look at, like, the last couple of months, figure out, you know, we're growing 40% every month. We just, you know, take, you know, take the power of three. That's how much you're gonna need in three months.
Speaker 10:That's how many GPUs. You go out and get those GPUs. You can typically get GPUs with, like, about three years of sorry, three months in advance. Sure. But, yeah, that's a big part of how we think about the business today.
Speaker 10:It's like we need to get the GPUs now that we're gonna need in three to six months, which is a lot.
Speaker 1:Yeah. Yeah. In some ways, it's like, you know, not not too dissimilar to the challenges that, you know, consumer consumer packaged goods founder is facing. You're growing super quickly, but if you wanna stay on that growth curve, it means you need to be committing to things, you know, now and and committing capital. Got it.
Speaker 1:But
Speaker 2:What what's exciting to you
Speaker 10:across We have capital now.
Speaker 2:Yeah. Yeah. Well, what what's exciting to you across the, like, semiconductor ecosystem? There's a whole bunch of ASIC startups that have been on the show, Cerebras IPO ed. Every hyperscaler is working on different chips at this point.
Speaker 2:What's most interesting? What's under discussed? What's on your road map? Or or or what have you already sort of sunk your teeth into?
Speaker 10:Yeah. I mean, there's some, like, really cool alternative accelerators. I'm quite bullish on on TPUs, AMD, Tranium, like all of these things.
Speaker 2:Yeah.
Speaker 10:We see zero demand from our customers for for any of those things, to be clear.
Speaker 2:Because only the really big labs, Anthropic, can actually go and and figure out how to run it. Is that the issue?
Speaker 10:Yeah. I I think the cost today of rewriting a software to run on those stacks is just like very high. Sure. So while I remain like very bullish on this sort of, you know, two, three year horizon Yeah. You know, I do also wanna like
Speaker 2:Yeah.
Speaker 10:Temper the expectation a little bit. Like, this is
Speaker 5:It sort of
Speaker 2:has a fixed cost to rewriting for that chip stack. And if you're not doing billions a month in revenue, it's
Speaker 3:hard to Yeah.
Speaker 2:Amortize that cost.
Speaker 10:That's exactly right. Yeah. It's just not worth it unless you're, you know, operating at a very large scale. So but
Speaker 3:but I think
Speaker 10:that that cost is gonna go down over time. We're gonna have software that that basically lets you take existing CUDA compatible stuff and run it on other alternative accelerators.
Speaker 2:So Yeah.
Speaker 10:I I think it would be good for everyone to have a little bit more competition in this space, but we also love NVIDIA, and and that's what our customers want today.
Speaker 2:That's great. Do you have a view or any opinions or predictions about the compute futures market that's been talked about? Any I've seen like these price charts of like b 2 hundreds going up and down. Everyone is trying to read the tea leaves, understand, you know, where we are in the various AI cycles based on it. But is that something that's relevant or or important at all?
Speaker 2:Do you do you look at that data? Do do you have your own internal dataset that's more relevant to you?
Speaker 10:We we we look at it a lot. I mean, also, like, I feel like we're very plugged into the market. We talk to Neoclass all the time. We get capacity all over the place. So we're we have, like, a very good, like, pulse of the market.
Speaker 10:I I think the market's gonna remain quite tight. Yeah. I I think fundamentally, like, also, like, that's a big part of what we do is, like, we offer, you know, that as a product. Like, don't think about capacity. Come to us instead.
Speaker 10:Yeah. And so that becomes now our problem is, like, managing that capacity for thousands of companies at the same time. Like, we built a multi tenant product that sort of aggregates all that demand. So if you need a thousand GPUs, you can come to us, and we'll give you to that give you those GPUs, like, often within minutes, because we have, like, a very big pool we can sort of tap from. Yeah.
Speaker 10:But but, yeah, like, I I I, you know, I think GPUs are gonna be tight. We look at the prices. They keep going up. At some point, obviously, I think it's gonna normalize like most markets do, but it might remain tight for the next year or two.
Speaker 2:When I think about the big applications of a big pool of compute, think training and inference of LLMs, coding models, agentic workflows, I think image, video, audio generation. What's next? What do you think the next big driver demand is? Is it world models? Do those fit in?
Speaker 2:Are those structurally different? Is there something else that you're tracking where you're seeing customers come to you with sort of like a different product, but it it it fits in the same shape so you can work with them as a business partner.
Speaker 1:Yeah. We have a very wide
Speaker 10:range of customers. So we have everything from Suno, which generates music using AI. Cognition is training, coding models using reinforcement reinforcement learning. Ramp uses us for background agents. We have a lot of vibe coding platforms like Lovable.
Speaker 10:We also have, you know, drug discovery companies like CHI using us to simulate, you know, molecular dynamics and That's huge. Weather forecasting companies
Speaker 3:k.
Speaker 10:Robotics. So so so we we we have, you know, very general you know, we look at across, like, a lot of different verticals. Obviously, like, the the the big application in the last couple years has been LM inference, and that keeps growing a lot. But we've also seen some really cool applications with the future models. In terms of what I look forward to, like, I I think that probably, personally, the coolest thing I kind of expect to happen in the next couple of years is speech to speech.
Speaker 10:Like, imagine just, like, talking to a computer. In order to to figure that out, we need to get the latency down, you know, for for for all the three components of speech to speech. Yeah. You know, doing the LM and the, you know, text to speech and stuff like that. So that's something very cool.
Speaker 10:But I'm also really cool about I I think it's incredibly cool if we can, I don't know, cure cancer or something like that?
Speaker 2:Yeah. Yeah. It's interesting because I'm with you on that timeline speech to speech being, know, somewhat impressive but you're often not actually hitting a real reasoning model. There's so much speed up. You know, we could be we probably need to be a 100 x faster, a thousand x faster on the response time to really have a breakout moment.
Speaker 2:And then you watch Google IO this week and you see with Omni a glimpse of, okay, it's more like a FaceTime call with the AI and it's generating a video in real time. And you know how long it takes to crank on video models to get an eight second clip. It's minutes and minutes. And and and they're still have errors and stuff. And we're still not even at the super the superhuman element.
Speaker 2:So lots to do, lots of servers to rack, lots of GPUs to set on fire, I'm
Speaker 1:sure. And CPUs. Yeah. Any plans to actually, you know, go full stack, get your own, you know, LAN, power, powered shells, etcetera? Is that, like, not the highest and best use of your guys', you know, talents?
Speaker 10:We we think of our values like adding a big software layer on top of the underlying computer Yeah. On the underlying compute layer. So we think of ourselves as almost like a cloud, like, one layer up from the existing clouds. The existing clouds are very good at running computers, you know, in the cloud and and offering that through an API. We we would love to keep tapping that as much as we can.
Speaker 10:If we can't get the capacity we need, we might have to build it ourselves. Yeah. Ultimately, it's like, you know, it's a kind of a economics question or, you know, or practical question. I I wouldn't rule out any sort of move. The idea of, you know, racking computers and plugging in cables and dealing with, you know, fires in data centers and whatnot, like, to to me, that's not super appealing.
Speaker 3:But but at the end of
Speaker 10:the day, we'll do it if we have to. Absolutely.
Speaker 1:Yeah. Makes sense. Well, congratulations. Yeah. Congrats to whole team on on an awesome milestone and and incredible progress.
Speaker 1:It felt like a year. It's It only been since October.
Speaker 2:Only a couple months.
Speaker 10:Yeah. It's like ten AI years.
Speaker 2:I love it. Congratulations. We'll talk to
Speaker 10:you soon.
Speaker 3:You so much. Cheers.
Speaker 2:Have a great rest of your day. Let's click through the timeline, see if there's anything that we missed before we jump off. DJ Cows has an idea here. Found a $10 bill. It took five seconds to pull to pick it up.
Speaker 2:That's $63,000,000 in annualized ARR. This is the thinking you need to be deploying if you're gonna be raising money potentially. No. Don't do that.
Speaker 1:It's the funny numbers. Messi, the football player Oh, and a prime copycat called Moss.
Speaker 2:Moss.
Speaker 1:And it's shutting down. That's a huge three months in business.
Speaker 2:I wonder if that has
Speaker 3:I would think
Speaker 1:the this was
Speaker 2:logistics of shipping internationally because he is an international icon. But setting up distribution and retail presence across many countries very quickly, it's not quite as easy as dropping it on Amazon and and flying off the shelves. A lot of those are sort of one country by country, and I wonder if that has a piece of what happened. So this is shutting down fully, Moss Plus. Interesting.
Speaker 2:Well, Mitchell Baldridge recommends setting up a Vanguard account. Not Fidelity, not Schwab, Vanguard. Smart advice, you might think. They do have the lowest fees. If you want to get up to speed on Vanguard, listen to the latest episode of the Acquired FM podcast.
Speaker 2:But he says, wrong. It's not because they have the lowest fees. It's because their interface is so awful you will never trade. It's his May it has made his clients millions.
Speaker 1:Let's close it out with this
Speaker 2:What you got?
Speaker 1:Playing Catan with a billionaire. Yes. I think I think you'll like
Speaker 2:What is this face? Is this a face filter or a background replacement or both? Something funny is going on here.
Speaker 1:Face filter. Okay. Face filter.
Speaker 7:My turn. I'm gonna put down a
Speaker 9:data center.
Speaker 10:That's against
Speaker 3:the rules.
Speaker 4:How else am I supposed to AI generate my Christmas card?
Speaker 2:Not popular.
Speaker 4:I'm not joking. Do you
Speaker 10:like it? No. It's blocking all the land.
Speaker 4:Wait a minute.
Speaker 2:Are you one of those paid protesters?
Speaker 4:Next turn, I'm gonna use seven water on my data center. That's not how that works. That's not a resource in the
Speaker 2:water. How
Speaker 4:else am I supposed to power it?
Speaker 8:The way
Speaker 2:it does The water stuff is really it's so interesting that no one has moved to energy. Like natural gas. There are natural gas turbines that I really wanna do that. Would be opposed, and yet people are focused
Speaker 7:Stop giving them ideas.
Speaker 2:On know. I'm I'm doing their job for them I suppose. But it's like I I I don't know how I don't know why the water I think it's just because like water's delicious and electricity is is vague and abstract and you don't think about it. Like you can visualize a glass of water. It's hard to visualize a battery in the same way.
Speaker 2:But yeah. The what is it? It's like dozens of LLM queries every day for a full year is equivalent to eating a single almond or something like that. But Matthew Ball is back at Xbox. Congratulations on the move.
Speaker 2:He announced it yesterday. We're going try and get him on the show because he's one of my favorite people, favorite authors. If you haven't read his book or his his blog, he has a fantastic mind for future of technology, and he I could not be more optimistic about the the future of Xbox with him on the team. Taek Kim says this hire is a literal game changer. Matthew Ball knows gaming and what needs to be done.
Speaker 2:This news makes me the most bullish I've been on Xbox in seven years and I completely And
Speaker 1:to close it out, the White House is awarding 2,000,000,000 in grants.
Speaker 2:Oh, yeah.
Speaker 1:1,000,000,000 of Quantum computing. IBM to nine quantum computing companies and taking an equity stake of They're their grants? Yeah. We're taking an equity stake?
Speaker 2:It's an investment.
Speaker 1:It's an investment.
Speaker 2:It's an investment. And you, American taxpayer, will now own a basket of quantum computing companies.
Speaker 1:Spaghetti computing is up.
Speaker 2:That's not spaghetti Spaghetti computing. It's Ragheti computing. Shout out
Speaker 1:computing is up 30%.
Speaker 7:Who
Speaker 2:came up with that? That seems like a Trump like something he would say.
Speaker 1:I created that.
Speaker 2:You created that. Okay.
Speaker 1:Just now.
Speaker 2:I like study.
Speaker 1:I'm sure I'm not the first person to think of it but anyways folks.
Speaker 2:Thanks for watching. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com And we will see you tomorrow, Friday. Goodbye. We'll smoke you.
Speaker 3:We love flashback.
Speaker 1:Have a wonderful evening.