Gavin Baker - AI Market Jitters

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This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc Gavin, it's only been two months. Like the model release cycles that gap between our podcasts, I was so shortening. Basically, you and I are basically on a model release cadence at this point. I was sensitive to criticism that I think somebody pointed out that our podcasts were coincident with local market peaks. Nobody could say that after this. What's on your mind? It's been a crazy. I have July 2022 in a month. There are some fundamental negatives which we should talk. But on the whole, the ballots of fundamentals I think is improving significantly. Loads of AI-dames are down 50-60% from their highs. We'll call it 40-60% in a month and a straight line. I asked you before we started, you've been out here for the summer, have you heard a single negative quantitative metric about AI? A single instance of deceleration. Nothing. Nothing. In fact, every metric is accelerating. And to your point, not just blind optimism from people excited about AI. Yeah. Here's some data that they can show you from their different vantage points. Absolutely. However, you cut it. Whether you cut GPU availability, whether you cut GPU rental pricing, whether you cut the spot price of DRAM this month, token growth, everything is actually accelerated. And I do think a big part of the problem is one. The market does not have visibility into athropic open AI. And then I would say these open source inference clouds that monetize inference here in America, fireworks based to modal together. And the picture looks very different. Would you see that? Because open source is accelerated massively because GLM 5.2, KBK3. And Neemotron continues to kind of chug a log. We had a great, very small American open source model release. Open AI has accelerated. And athropic continues to grow really strongly and is almost certainly pumping out significant amounts of free cash flow. And I just think if you know there's this chart that everybody looks at of semiconductor cash flow going like this. And hyper scale free cash flow going like that. And you're missing these private companies. But I also think that that chart misses something very important, which is just that you have everyone in 24 and 25. Even if you were really bullish, you thought that GPU prices, if you're really bullish, you thought they would declines slowly. If you bear as you thought it would decline precipitously. I don't think anyone in 24 or 25 thought that the prices of old GPUs would be going vertical. Everybody thought, hey, we're going to be smart. We're going to sign these long term contracts. And to some degree, like a lot of the deal clouds had to do that because they needed an offtake agreement to finance the GPUs. And so essentially you have the contracted base of installed compute. Trading at a massive discount to the current spot market. And as those contracts roll off and compute gets reprised higher, it's spot can decline and compute will still get reprised higher. I think you're going to see a lot of acceleration that's going to answer these ROI questions. You've started to see that this quarter. If we look at operating cash flow, not free cash flow, operating cash flow from Microsoft, Meta and Amazon has reported accelerated from 28 to 32. There are some actually pretty big unusual items now like these hyper scalers. They always seem to have billions of dollars of legal expenses that are unusual, mostly fines to the EU. But there is an unusual amount of one time is this quarter. And if you just for that, we would from 28 to 35. That's a material acceleration at this scale. And that's really before they start to light up the rubids, which will come into being for premium before these contracts reprised. It's been a challenging month. Is it helpful to kind of like walk through the month that we got here? Yeah. So first, Meta is going to rent out compute. And this is seed as like very bearish. They have excess capacity. They're going to cut cat backs. This is a disaster. This is not at all what it was. They just supported. They didn't cut cat backs. What it was is they saw SpaceX have a big installed base of compute and sell some big trade. Optimize clusters into the market at a truly massive premium to these contracted rates. And at least analysts like that, they saw an opportunity. There's a lot of speculation. They're going to raise capital. So maybe what they're thinking is like, hey, we will show on a small chunk of capacity that we can generate really strong IRRs. Then we'll raise equity capital and we'll be off to the races and probably raise cat backs. It doesn't look like that's what they're doing. But nonetheless, the market sold off because it interpreted this very negatively. And I was really sure it wasn't negative. A lot of telemetry into Meta's cat backs plans. None of that telemetry had shifted at all. If anything, they're continuing to get more aggressive. And then shortly after that, they released their best model at a long time. Use 1.1, which is actually a very good model. It's overshadowed by Grock 4.5, but it was a good model way better than anything in two years. So just no chance they're taking their foot off the gas. Then Kimmy comes out. And then there's this huge freak out about open source. And at the same time, this Silicon data token index kind of dips and flattens. And the tour connected, what the Silicon data token index captures is mix. And they don't see all the tokens. Because of GLM 5.2 and then Kimmy, all that took a while to layer in. There's kind of a mix shift in this data from more expensive frontier tokens, which probably haven't inference margin. We can make whether it's 80, 90 or 95, but super high towards open source tokens. And for whatever reason, the market thought this was negative, but the reality is a token is a token. And you need the exact same amount of compute to make a token all else equal. It takes the same amount of flops, the same amount of memory, the same amount of watts. Token's are not equal, but broadly speaking, all open source taking share does is take margin dollars out of the frontier model layer. There is elasticity. There by driving token demand, you need more demand for compute. And the margins, you know, etharopic and open source, they all run on the same underlying cloud providers who charge the same amount of compute. So you're literally just taking margin from frontier models and essentially driving more margin dollars into the AI infrastructure layer. That was a catalyst. Well, yeah, Jensen is the world's largest supporter of open source. He's like a super idealistic guy. He's a patriotic American. I think he always does what's right. But does it really stand to reason that Jensen would be the world's biggest supporter of open source if it was bad for his business? He'd still support if it was the right thing for the world. And by the way, I think open source is really important to world where there's just one or two dominant frontier models that charge like 90% margins. It's not good for humans. It might not be good for society. And I think we want a lot of models. bottles. as we've discussed before. So then it's like, okay, the market digests that and comes to our worth it. Then China has a DUV machine. Everybody said these baskets has caused this huge selloff and semi-cap equipment. And then we get to what I think is, in a lot of ways, the real concern, which is real yields have gone up, which makes sense. We're investing a lot to fund this investment. And for sure, credit is an increasing part of it, even if the majority is still funded out of operating cash flows. So real yields go up. And spreads widened, metapriced, a bond last week. And it did not price where you would think a metapod would price. And this just shows that the credit market and VDS was blowing out. All of these CDS for everybody is blowing out. And you know, very smart, private capital people, just like, hey, this is just exactly what you'd expect. These are just bakes. Had you their commitments. But nonetheless, it doesn't look good. And these are undeniable facts. CDS is up. Spreads widened. Real yields are up. That would be really, really scary if we needed debt to finance this build out. And that's where I think it's this differential between spot and contract pricing for the installed base of compute is so important. It's so important to understand what the financing will be like for the next six months or something. The degree to which this build out is going to require credit, right? Which would be the classic capital cycle. Absolutely. Over extend ourselves with debt. And that's where things get 100% to the debt-fueled build outs. They demand immediate repayment. So if supply and demand get a little bit out of whack, things get on wide very quickly. That's what happened at the internet. If one believes as I do, rightly or wrongly, after the spot, I'm super open. You know, I'm looking like I've been pressured to testing all of these. And like I really went deep on credit because hey, this is real, it's undeniable. And if we need credit to fund this build out, this is a significant negative. And if you model it out, if you look at the amount of gigawatts that are supposed to come on and consent assessments for hyperscalers, they're effectively modeled. And these are gigawatts of Blackwell and Ruben. Ruben being in video's next chip, Blackwell being the current chip. They are essentially modeled to monetize roughly at the rate of ampere, which is two generations behind, not at Hopper, but ampere. So there's 1.3 to 1.4 trillion in hyperscale operating cash flow. If you just assume, I think it's very unlikely, they monetize the rate of ampere. We could go into why. Some of it comes from just seeing what is happening on the ground with demand here from real quantitative metrics. But like, let's just say they monetize in a discount to current Blackwells. Then it's more like 2 trillion of our pretty cash flow. And that kind of takes 700 billion of credit demand out, ironically, as that improves all the credit ratios, as these installed bases of compute, reprise, we're going to continue accelerating, consensus is modeling at a deceleration, which I think is unlikely. Then the credit metrics look better than all of a sudden. It gets easier in a finance with credit. Now, whether they choose to do that or not, we'll see. This is all a little bit, I think we spoke two months ago. No, but the time before that about the risks of a Blackwell air pocket, where you're spending hundreds of billions of dollars on Blackwells. They're mostly being used for trading initially. Trading does not generate a return. This could be a risk. But you actually really saw that in the first quarter. I think one reason to the podcast two months ago, I got comfortable with that risk was just that you were seeing such incredible things out of Anthropic. And then it's like, okay, well, the market's kind of going to look past this. And it did look past it in April and May in June. And then in July, because of this kind of confluence of things, stopped looking past it. Just has the operating cash flow started to really accelerate. And this is just a fact. It is accelerating at big scale. You know, like Microsoft, they brought on a huge chunk of capacity in the month of June that didn't even show up in the second quarter. So essentially, what this all comes down to is do you believe that the quantitative demand signals seeing all the ground here at Silicon Valley from private companies are going to continue such that the installed base of compute, reprises higher as contracts roll off. Operating cash flows go up and you could fund most of this out of operating cash flows. Maybe all of it. Like if it reprises at current rates, you could probably fund all of it for the next several years. It has been a very unusual episode in the market. We should talk about what the fundamentals are that are getting better than I'm talking about. Technicians would say it's actually in 22. Okay, the market is worried about a recession. Rates going up inflation. That's what the market was worried about in 22. You know exactly what it was. Okay, deep seek. You know what it's worried about. Liberation day. There's something very clear. And in a weird way, that's comforting. Sure. And here, you know, we talked about a lot of specific things, but it just feels all those specific things with the exception of credit are just kind of ridiculous. It's so the fact that it is still going down. A technician would say, hey, that's that's a little scary. But it's definitely the bullet you don't see that gets you. You know, I think we've talked before about how like I think the three most important words in investing aren't barge of safety, but I don't know. But just you've been out here for two months. I've been out here. I literally spoke to a company this morning who rented a cluster of several and this is one of the sexiest startups that people want to be in business with. And they had rented a cluster of several thousand black wells and we'll just call it somewhere in the mid two dollars for GPU hour. They're renting the exact same size cluster. Essentially identical in every way, B 200 said no differences. And they're hoping seven months later to pay just under four dollars today. Like that's pretty crazy because again, you would expect a really gentle decline in prices would be bullish. Instead, we're up depending on the starting point, 50 to 60%. It's six or seven months. There've been so many anecdotes like that. Like I think one of the inference clouds, I think it was based in I'm not sure they went on a podcast and they essentially said we're planning to pay 100% more for black wells with our contract expires. And that just means that essentially all the hyperscalers are underurding. My main kind of mission out here this week is like pressure test. Yeah, yeah. Tell me something negative. Like, you know, the question asked you, is there one negative quantitative metric you've heard? It has been what I've been asking everyone. The main thing people are saying is that third party data suggests that the anthropic curve started to go off of its trajectory a little bit. That's like the only thing that I think that may very well be true. But did you have open AI and open source massively accelerating? Yeah, the conferences. And if you look at the sub, it is net accelerating. Like I think open source is a little bit of a, you know, they talk about dark matter in the universe like open source is kind of dark matter to the public markets. It's hard for public markets to measure it. But like if you just track what these inference clouds are saying people saying things on podcasts or people saying things in meetings, they're not audited financials. Demand is clearly accelerating, which makes sense because you have this huge capability leap with GLM 5.2 and Kimi K3, which I think we're going to see continue. I think you're going to see Nvidia bring NeboTron steadily closer to the frontier. But man, it has been a humbling, challenging month. But just it's also like wow, I've kind of pressure tested every assumption. The underlying fundamentals are improving. Nvidia is actually as we record this at its lowest forward PE of the last 10 years. Crazy. The only time the Sibis have been cheaper where Liberation Day deep seek those were kind of V bottoms. And that means to you just that the market thinks they're significantly over earning? Yeah, the market 100% thinks they're significantly over earning. And you would need to be humble. Maybe they are. Maybe they are. But like my kind of mission out here this week was to look for negative data points as hard as I could. And normally come to Silicon Valley. And you know, there's a mixture of if you're something negative, you're something positive, done it on balance, it's positive, you know tech, it creates value over time. But I haven't been able to find one that is like a quantitative metric. That anthropic third party data, I would say that seems to be hotly contested by the, by the anthropic shareholders who are, who are chopping at the bit to tell you what they know. We're also very scared. They're not going to get an IPO allocation. And if it gets back to the company that they're the ones who said, actually things are great. You know, you can just see anthropic shareholders like they want to be like, it's not true. Yeah. It's hard for me to believe that open source and open AI have accelerated to the extent they did. But yeah, anthropic is clearly in the position to know, by the way, Grock and Kirstner have also, you can see from third party data. Like July was a pretty transformational but with GROC 4.5, GROC builds coming out. So it has been a tricky month and I have a friend, a friend of fidelity, who just says the way to have navigated the last three years. It's just do the dumbest, most superficial thing has quickly as possible and just cycle between them. What is that now? Well, that's just that has been to cut risk, all month in response to these narratives that factually accept for credit are not true. And the work we've done makes me think that credit just isn't going to matter, has this reprises. Let's just say you do need credit to like build the flops we need. Well, if credit's not there, it just means the flops that are there are going to be even more valuable. And then eventually that will improve the metrics. And then it's like credit is there. So as long as we're in a compute shortage, which I'm just like desperately trying to find a single side that we're not in one, and that it's not actually getting worse almost by the day. It's almost like the problem becomes the solution. And then this company Black Forest Labs, I think that's their name. I hope I got it right because there is an interesting essay that got sent to me. You know, I think we've talked before about Mike Bovis and Sterey that breakdown and diversity is kind of what leads bubbles and crashes. And essentially, everyone I know with the public equity investment business, whether retail or institutional, every piece of news gets fed into clot and clot, clot code, sometimes a clot agent. And it's probabilistic. There's probably not that much variation in the way it's interpreting this news. It's almost like we're back to it's stock market terms. There's never really been this way in the stock market before, but people talk about the fragmentation of media and how it used to be like Walter Crockite, old voice of truth. And now we don't have that anymore. It's like Claude, it's kind of Walter Crockite for the stock market. And everybody just believes whatever it says. By the way, it's really smart, but it's not always right. It's interpretation isn't always correct. And with the stock market, you are fundamentally dealing about a probabilistic, Bayesian interpretation of the future. It feels like in the market, here's this piece of news. It gets fed through clot, clot interpreted this way. A huge chunk of people trade on clot's view. And so you've seen stuff. There's this guy, TPU. He's like a part of the anonymous semiconductor mafia on X. Yeah. Actually, very smart guy. I know I'm in real life, but he posted this amazing chart of Japanese capacitor stocks. And he said we've had an entire capacitor cycle in six weeks. And it's true. You know, the stocks like whether they double, triple, quadruple, I don't know, but vertical, and then whoosh, like the actual fundamentals haven't even hit. And yet you've already had what probably would have normally been a three year cycle in like six weeks. 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Like, have you learned anything interesting about the long lead time innovation type stuff that has you especially excited or curious? Yeah, I have very curious. A lot of people seem to feel like they're very close to solving continual learning, it's simple, official learning, which we've talked about before. And it is possible that if those are solved, that could that be like a temporary discontinuity in demand, if instead of, I was trained on effectively 20 billion tokens, and that it's like these models are trained on 300 trillion tokens. And if you can train something on 10 trillion tokens that let it out into the world and learn sample efficiently, that does sound good for training demand, but like training has a percentage of semiconductor demand to compute is going to ask them to to something not approaching zero, but very small. But I would say that is the most interesting and who knows if it's long horizon or shorter horizon. SSI says that they're going to come out with their model in August. There's this whole generation of new labs that are focused on this. And this would be good for the world. This would be amazing. This would be awesome for the world. We all want this. We love this. It would be amazing for the world. And it's just it's hard for me to believe that that would actually be negative for AI infrastructure demand. But again, trying to be really, really open-minded, I would say that was probably like the biggest scientific or technical takeaway. You know, it's also. I just don't know. Yeah, and also like Nvidia is heavily involved with all of these startups. If you were just forced to come up with the set of circumstances that would really switch you around and get you really scared, it would just be that this operating cash flow thing doesn't play out. And therefore we just need to debt finance this. Yeah, the operating cash flow does not continue to accelerate. That would be negative. And that to some degree is going to be a function of how anthropic open AI, Grock cursor, and open source do. If there was a pretty dramatic contraction in GPU prices that was kind of sustained, the market would react to that instantly. That would be worrisome if it started to get to be really easy to get GPUs. I mean, have you heard anyone say they have too many GPUs? Like that, that's a single person. No, it's in fact it's the opposite. It sounds like a drug market or something. Yeah, it really does. It's just wild. But yeah, I mean, I think there's a long list of pretty obvious things. If the sum of these labs, Platoes are starts to decline. That's really negative. Unless it's just because open source tokens are net growing the pie and taking share. And I do really think the future is multi model, particularly for the AI natives. They're going to want to take an open source model. It's got all these inference clouds. We've got really good at supervised fine tuning and reinforcement learning. So you can take your data, customize an open source model, and then get something that you can put behind a router and the router routes it to often first your model and then quad frontier model, whatever quad rock checks it. And you can in a lot of cases get slightly better outcomes at half the cost. But again, that half the cost. I think a lot of people hear that. They're like, that's bad for AI demand. It's actually not at all because the cost the user pays is just a function of the margin on the tokens. And you're literally just shifting tokens from really expensive tokens with like 90% gross margins to tokens with maybe let's call it a 30% gross margin. And that's where the savings are coming from. But the tokens cost the same amount of compute to produce. And then also all these things are kind of happening on different cycle times. All these big public companies are like, oh my god, my AI spent 20x to burn my budget. In three months, so they set up a router and that actually cuts their AI spend. But it doesn't really impact. It may actually increase the amount of tokens that they are generating just by shifting them to these cheaper open source tokens. And that's just more compute. So a company getting smarter about which model to use for which task that may lead to a stabilization in their spend or even a decline. But it actually has nothing to do with the amount of GPU compute hours. They're effectively consuming behind these model layers of this router that GPU compute hours. Probably you're going up as you shift to these cheaper tokens. You can use more of that's happening to like a cutting edge of public companies. And then you have this whole wave of AI natives. They're leading it to this so hard and they're not hiring humans. They're just putting it mostly into tokens. They're not slowing down. And then you have companies on the east coast of America who have like barely adopted AI. Companies broadly speaking, you know, not in the coast who maybe are as cutting in Europe who's just trying to figure out how to regulate AI before using it. Yeah, so just like there's kind of these differential waves of adoption all happen and you get the same time. But the thought I can't get out of my mind is like I think I said it maybe last time, but just y'all access to like 500,000 people in the world, 250,000. Maybe you're using a Gentika AI and we're in a cute compute shortage. There's seven or eight billion people on the planet. What happens when we go from 500,000 to 100 million, you know, to 500 million. It is interesting. You know, a lot of people, I do think it's like helpful to post on X to see the pushback. I had a lot of people are saying we accept your argument that hyperscalers are a dirty and it's compute reprises. Are there operating cash flows going to accelerate and maybe we could fund this. But like, where's that operating cash flow going to come from? Where is the customer? And kind of, definitionally, it has to either come from faster economic growth through productivity, kind of such as comments like either we're going to start growing 10% or we're not. Or labor substitution. And for sure, I think at a lot of these AI natives, you're seeing labor substitution, but not because they're firing people. They're just not hiring nearly as many humans. The gross profit dollars per FTE and a 16z, Iconic, a bunch of companies have done this work. They're vertical, particularly relative to past generations of startups. And then it is interesting. Are you doing any surveys of your companies that their tokens bid relative to labor spend? Oh, yeah. I mean, it's tokens as a percent of total comp spend or something like this. What are the ranges you've seen? I mean, like in the really pilled companies, like it gets really high. 20%, 25%. Our Fred Dillard Patel at Hills and his companies. He's an ASI vaccine, but he's at 30%. That's probably the highest one I've heard. I've actually heard of 50. And there's $25 trillion in knowledge work. Let's take your 20% number. That's 5 trillion. And that either comes out of labor substitution or faster economic growth. And we really, really, really want his humans to come from faster economic growth. One interesting thing I heard this morning from one of the great bleeding technology CEOs has found at several companies. If you look at the founder, letting controlled companies and adjust for some of the like COVID era over hiring, nobody's really laying people off. These are the people that would probably be most quick to adopt AI to become more efficient or whatever. Like they're not really doing jackass eye like huge scale layoffs, which probably tells you something about where they think there will be lots of opportunity to still have people plus 100% well, the bulk case you've seen church from cognition, reapp, it's stripe, that the companies that are spending the most on AI are growing meaningfully faster. Yeah, love that cognition index. The cognition index as well. All the skeptics will point out rightfully. It's not really controlling for industry, but then if like you dig down into it, I think one of them gave an example of I forget if it was a plumber or an HVAC contractor, but like everybody who's a blue collar workers doing great because of AI. By the way, something that I think we should touch on and we can do it an hour later is just everybody is citing these LTAs. So everything's at a shortage. If there's weakness, it's just because we can't energize the gigawatts fast enough. The gigawatts are going to get energized like regulatory policies moving in a good way. The turbine manufacturers, the diesel chips manufacturers, you're ripping turbines off old airplanes and reconditioning them and then repurposing them. There's crazy things happening. Capitalism is very, very good at this. But I do think one of the most important questions in the market and like a transition of the market that I got wrong is we are shifting particularly for memory more than anything else from crushing numbers. In the short term, to their trading short term upside for these, what they call supply chain agreements, long term agreements, LTAs, there's many flavors with customer prepays, there's a floor at a ceiling. And this comes back to the point about labor because a lot of people after firing too many people during COVID were really reluctant to lay people off. They talked about labor hoarding if you remember a few years ago. You remember this? Yes. Let's just think about the game theory of breaking an LTA. So there's four companies that matter at scale. There's Amazon with their trademes, there's Google with their TPUs, there's AMD, and there's Nvidia who's like much bigger than everybody else combined. Let's just say it's 2027 and it's very important to realize, memory is the more memory you put with flop, for a given unit of compute, the more tokens you get out. It's the single most important thing you could do to increase token output per unit of compute, and then that obviously, definitely actually lowers costs, which is why the DMAID hasn't responded at all negatively. There's been no elasticity just because it's the access that is dominating all others. And this is at some level like a giant game of thrones or Ipers between these companies. Okay, it's 2027, you're vaguely tempted to break one of these LTAs and try and get a lower price. But to a large degree, market shares, I think for the next several years, are going to be determined by supply chain allocations and kind of what you have pre-purchased. So if you break the LTA, this is assuming we're not in a severe oversupply situation. The game theory even holds in a severe oversupply situation. If you break your LTA, and then in the next two or three years, for any reason, leverage shifts back to the memory guys, you're out of business. It's over. Let's just say Google breaks an LTA. There's an oversupply making this up at 2829. They break their LTAs. Well, after breaking their LTAs, it probably means your oversupply prices are coming down, and then capacity naturally contracts. Well, what do you think is going to happen to Google's allocations? Then this is a cyclical industry and oversupplies followed by undersupply. What do you think they think is going to happen to their allocations next time? So I just think given that this is the access around which kind of everything is revolving, you might blow up your entire business and your franchise by breaking it LTA. And that was never the case before. Apple, who cares? They don't have a competitor. They're overwhelmingly the largest purchaser. This is going back three, four, five years. They know they can do whatever they want with their consequences, because their volume is so big that even if they like super screw high-decks, microd will of course take them. This is just different. You have at least four players. Did you have all the startups? You're an investor and etched. If you break an LTA, they just say, okay, fine, great. You broke the price agreement. We're going to break the volume agreement and screw you. We're going to give the volume to your competitor. You just lost share, you know, Nvidia's dominance. The current environment, these stint to which it favors Nvidia, it is a little hard for me to understand why it's trading at such a low multiple. In other words, if you need to be able to finance the chips and you do, nothing's more financeable than an Nvidia GPU, nothing. If you need to get land and power, well, they're doing a very good job of playing that chess game and matchmaking. Then they've rolled out this really clever new business model, which I would describe as kind of like a credit wrapper with a revenue share if GPU prices are backstop. Yeah, yeah. This could lead to them having a really giant cloud business effectively through royalties really quickly. And it is another way of kind of alleviating this cash flow mismatch. Like, hey, we're making all the cash. This isn't really winter financing because they're not loading them the money. Somebody else is loading the GPU buyer of the money. They're still making equity investments, but it's not like you're just putting money into someone that some of that money was used by your chips. Even though Nvidia said that they write into all their equity investments, that the money can't be used to buy Nvidia chips, but obviously, money is fungible. And, uh, yeah, but you know, I think at some level, it probably makes everybody feel better. What would you do if you were the member? Like, if you were the CEO of Hynax, I'd do the exact same thing in videos doing right now, which is I would be going to the buyers of GPU's radios and whoever. It's saying I'll participate in the Nvidia credit wrapper. Now, their business is just inherently less stable and predictable, but in some way, and maybe they just put up some cash upfront. So it's like they're not on the hook. I'm just making this up. But like, do something like you can because you have money now and credit markets are revolting. I'm sure our friends at Blackstone and Apollo are suggesting some variant of this to the memory companies, but hey, we will put up some amount of money from our cash flow today. And then it's gone. It's surety that makes the person who's extending the debt feel better. But we want some sort of a cut of the ongoing revenues as well. That is 100% what I would do. And it's almost like a logical extension of the LTA is where they're trading upside for durability. Here it is. you can effectively get a royalty on recurring revenues. And that is what Nvidia is doing. And I do think that is very misunderstood. And I think it would serve in video well to really explain this. One, they're really bullish on AI. Essentially every time they haven't taken an equity stake and something, it's been a mistake. They've taken equity stake in everything, essentially, except the memory companies that for a long while, it's a Thropic that they took an equity stake and a Thropic. But why not if you have cash flow and you're bullish on AI in Jinssen because he sees every lab, he knows all the advances, like all these continual learning labs, safe super intelligence is not working with them. He sees everything and what he sees makes him bullish. So what have some equity upside? And then too, have a revenue share and you're generating hundreds of billions of dollars of free cash flow and helping to bridge what is clearly kind of a gap, at least you have everybody's got free cash flow negative until the operating cash flow accelerates enough that you can internally fund this. It's very opportunistic in a good way and it significantly increases their revenue per gig watt. And then it also strengthens their competitive position. You and I, we both have startups, but okay, that's great. Use that startups chip. What prices are they playing Pagatowen so we hire the Nvidia and all these guys? What prices are they paying for HBMD rim? Higher. Can you finance those chips easily at the same rate as Nvidia? No. And so it's always like there's a real burden, particularly if you use HBMD Ram, you're in the crosshairs of this, unless like they made really different architectural choices. Everything that's happening is actually pretty good for him. By the way, going back to game theory, anthropic, if they had been as aggressive on compute as OpenAI had been, they would have run away with it. Now OpenAI is back in the game. I think Grakis in the game. Those are the companies on the parade of frontier. And they have the computer. Do you think after watching that, anyone is going to let off the gas? Right. It was, I think four months ago that Dario was talking about how it was a really thoughtful commentary, but he's like, it's really, really hard because if you buy too much compute, you could go bankrupt at the scale of these things. But if you don't buy it off, you could lose. Well, OpenAI just got back into the game. And now SpaceX is in the game in a big way with Grakis 4.5 and Cursor. After watching that from a game theory perspective, is anybody going to back off any time soon, especially if it can be funded out of operating cash flow? Have you met anyone in your travels out here that you would say is like way more bullish than you? And if so, what do they believe that you don't? I mean, essentially, everyone out here was bullish. I shouldn't even. I read this thing that Door Kesh wrote, and I was like the three X-Cupute price thing or whatever. Yeah, well, I forget what it was. No, no, it was like 15 X or something. Yeah, but no, but just basically that Riching at H 100 for a year would cost $250,000. And that's 15 X the current spotter. Exactly. Like, wow, you know, that was just like, not-- That wasn't my book. That wasn't my, forget my like, Bayesian probability space of expected outcomes. That wasn't even in my considered, but dismissed his totally unlikely outcomes. For Cashy, very smart guy, he's very plugged in. Then he pointed out that margins on compute are going up. The amount of compute is going up. And inference margins going up. And if you multiply those three, that's how you're getting this crazy acceleration in the sum of the labs plus open source or though the margins on open source are not really going up. I look at what's happening in the stock market and I feel like a foolish optimist. And then when I talk to people, whether it's people at the labs, anyone in this ecosystem, I'm like bearish relative to essentially everyone just a strange state of affairs. What are you making the DV news out of China where I've seen reactions really along a spectrum of like, this is the equivalent of like what ASMR had in 2001 or something. Or like, no, this is actually the first bit of news in a new story for how we should think about the global supply of cutting edge compute. I think both can be true. Make an analogy. Like let's just say a DUV machine was a jet turbine. And now an EUV machine is like a warp drive. DV machines like a propeller played, EVs like a jet turbine. They didn't have it before. And now they allegedly do. And that is like a phase transition. You've got from like liquid to solid. Now, that's solid, that jettigent prop plane, whatever. It's 25 years behind, but still, it's important and I don't think it should be dismissed, but I also, it's kind of funny, you just see this in the stock market. The stock market massively overreacts. And then if this ever hits ASMR's orders, maybe it hits it at five years. And like the market has forgotten about it, got worried about it, got worried about it, forgotten about it multiple times along the way. So I do think that was probably an overreaction, but we shouldn't dismiss that either. And if you're China, like this is really important to you, there are some reports that like an EV machine had been smuggled into China. I mean, what a feat of espionage because those things are like, >> Shining concrete together. >> Yeah, they're huge. I don't know if that's true. There's some noise about it, but China, they're really, really good. They're really, really smart. They work brutally hard. And they see this as super important for them as a country. But are they going to go from the year 2001 to 2026 or even 2030? It's a learning by doing. And you can't accelerate the doing. You can't teleport into the future. You actually have to go through those learning cycles. Is it significant? Yes, did the market overreact? >> Probably, it's very hard as an American to really understand what is happening in China. And like have total conviction and clarity, you know, like for better or worse, we are decoupling. That is a process that has been set in motion. And at this point, it almost feels like it's self-reinforcing on each side. That's unfortunate. We are where we are. They're not going to stop. They're either are we? >> Any commentary on like every other company in America. I feel like right now it is 10 companies, couple, private. >> Not last month. Everything but AI was vertical. And I do think open source getting closer to the frontier and companies like fireworks making it really easy to customize a model such that you can get, in some cases, better the frontier performance for a meeting fully lower cost. That is a godsend for the software industry. And it's also a godsend for all these AI natives. It's like our friend Vishriya, I think he said two years ago, I've never seen more companies go from being founded to like $50 million a year in revenue, generating cash flow, and like whatever it is, nine months. And it's hard to know if any of them are durable because a lot of people would dismiss them as chat GPT rappers. Well now with open source, you've generated some data that's unique to your use case, whatever your vertical you're going after as a rapper is, fireworks did come out with a really cool product called Dexas. And if you're using Cloud Code, OpenAI Codex, GROC build, it is literally three lines of code, like 20 words, and fireworks ingest your data. They can RL model and there's a router that cids the query and they've had amazing results. And this is kind of the solution for every AI native. That's why you saw Harvey before it was acquired cursor leads so heavily into this Harvey LaGoura, all of them. Because if you can go from just using one, two or three frontier models to using those frontier models, for whatever it is, 30 to 60% of your token consumption and then use your own RL model. And you've got a rapper, you're way more defensible. I was so interested by that cursor thing that came out, I think it was cursor where it's sort of like AI speed running like what we've learned amongst humans, which is you could use the frontier model to plan and then format tasks to the drummer models. And it's 15 times more efficient or whatever the nemetric was. And it may be, and this is like super ironic, lower margin open source tokens that are just a little bit behind the frontier. We have friends who believe that once a frontier model hits RSI, it will actually have a dramatically lower cost to serve at every level of intelligence by kind of distilling this. And then there's no place for open source. I would say that's like a anthropic, open AI, GROC, maximalist view. We shouldn't just miss anything. Anything is possible. We want to be very helpful. I particularly want to be helpful after the bug that I've had. But that doesn't seem that likely to be one because there are so many of these AI natives that have actually generated a decent amount of domain specific proprietary data. And before open source had this moment and these inference clouds and these routers really developed, you kind of didn't have a choice like whatever the terms of service where you accepted them. But if you can now get off that treadmill, that gives you a degree of independence, maybe durability, safety, but going back to your point, it may be that these cheaper tokens massively inflate the value of the most cutting edge frontier tokens, because if today, if you have a, you're going to make this up. 120 IQ open source models, and they're really cheap to run, doesn't that make a 160 IQ model that could orchestrate them more valuable? If we talk last time about how I have been really surprised that so much of the economic returns of a crew to the frontier, that is changing with what we're seeing with these inference clouds together, modal, base-tid, they're all working. In a very cash-efficient way, what's shocking about those business models is they're growing almost as fast as the frontier labs in the early days, but burning very little cash. It's pretty extraordinary to go back to silly sass metrics, like the rule of 40 perspective, these are crazy numbers. Do you think there's a lot of instruction in just the distribution of pay inside of an organization? The CEO makes X times more than the median person at a company, and maybe that's frontier tokens versus, absolutely. Something simple. It may be that what we discussed last time, where frontier tokens, like the pies growing really, really fast, they may continue to capture the overwhelming majority of economic value, but not all of it the way they happen. An open source tokens might be the majority of tokens processed. Again, going back, that's great for infrastructure to be had, because a token is a token, and it takes the same amount of flops, watts, space, cooling, to make. What's the worst thing that could happen in AI as a regulatory? I think regulatory has to be the biggest risk. It's the most obvious risk. That was one reason I was excited to be here this week. I want to be scared. I don't want to feel like a lunatic watching these stocks get cheaper, thinking the expected foreign returns are going up, while it feels like the other ground fundamentals have pretty materially improved in July relative to even June. But I still come away thinking like regulation, it just has to be the biggest risk. You just can't ignore New York, making a data center moratorium. We're living in this weird post-factual, post-logical, political world. I think the AI industry has done a terrible job of PR, and I do think they're- I think he's realizes that now. Maybe if not fixed it, it's realizes it. Yeah, but like the political narrative, I think amongst a lot of ordinary Americans is like data centers, they're going to raise your electricity prices, they're going to take all your water, and then they're going to take your job. The reality is, given the deals that are being cut now, when a data center goes in, electricity prices actually generally go down for everyone around there because of behind the meter deals. This is that like data center pledge that Trump asked people to sign. Generally, the data center developer used to be, they just had to get the police department, the fire departments, like new trucks and new cars and new body armor, whatever. Now it's like, we're going to build you a hospital, a school, a new police station, and a fire station, and we're going to lower your power bills. How does that sound? And by the way, the jobs are ongoing because it turns out that you kind of need these plumber's, electricians, HVAC contractors, data centers, there are in a lot of ways the best thing to happen for blue collar wages in my lifetime. And yet you have the Democrats who is stintsably representative blue collar workers taking those jobs away. It's just kind of wild how what is the phrase like a lie could go around the world? Fashion that truth gets out of bed. Yeah. Fashion truth gets out of bed. But an author made a mistake in a book. It overestimated the amount of water usage and data centers by 10,000 decks. Not a little bit like not one order of magnitude, not two orders of magnitude, not three. She's admitted that mistake many times. I was completely wrong. It's like been super debunked. It's like the pop-I effect. You're here that example? No. You know, pop-I-ed spinach. The reason was same deal in a academic book. They placed the decimal two things wrong. So spinach does not have more iron than everything else. It was just this one source. And then that property that people still say it has more iron. I literally had I thought it had more iron. I mean, that's like eight years ago. That's wild. I literally thought spinach had more iron. That's amazing. It's crazy. Yeah, you learn something new. Everything. Yeah, same thing. Yeah, it's the same thing. And it's just so somebody just needs to tell the truth. I feel like the industry, geez, maybe if nobody else is going to do it, like I'll do it. There needs to be some sort of foundation. Maybe it's a pack that runs ads during the final four, during NFL games, during college football games. Here's the virtual world series. Here's what a data center does. Your power, a data center that's signed this pledge and your community, your power prices are going to go down. They're almost certainly going to contribute to the community in a material way. You're going to see a massive influx of super high-playing blue collar jobs that are going to persist. And I think a lot of people thought that they were one time and they're just not like there's for sure a spike that that moves to the next data center. But there is an ongoing need for RMA and then upgrades at these data centers and technology is changing. So you're going to have more jobs. You're going to have cheaper power. You're going to have a wealthier community. There's going to be no impact on water, no impact on the environment. But it's easy to build the data center 10 miles out of town. That story needs to be told, along with we heard a story I think we talked about it last time, about how AI is increasingly really saving lives, curing rare diseases. I think it was an asko this year. If I was like this is the most scientific breakthroughs we've ever seen at a single conference. And for sure some of that is due to AI. And so we need to tell those stories like if you have a sick child, sick parent, a sick loved one like AI, meaningfully increases the odds of them recovering. Everybody needs to tell this. And I think people out here, all of this is so blindingly obvious to them. They can't process that this is a true but wildly divergent view from most Americans. The industry really needs to tell its story better. New York, it just feels like it's the first of many and even in some of these deep red states, they're super pro growth. They're just like, hey, you guys are not doing a good job telling your story. We can't tell your story. If you tell your story though, we can retell it, but like you're the experts. If you do not speak your own truth, no one else will. What have we missed? I do think something that is missing from all of this conversation about compute is what is going to happen when you put these S-ray based accelerators that are not constrained by HBMD-RAM and are often made on older nodes that are not competing with like the latest GPUs. When you disaggregate inference, people talk about pre-fill and decode, but decode is two parts attention and feed-forward network. And like the ultimate holy grail is if you could do pre-fill on one chip, it probably doesn't have HBMD-RAM. Do the attention on a super high powered chip with the HBMD-RAM and then do the feed-forward network on one of these S-ray m chips. But like the ROI on adding these S-ray m accelerators to the existing install base of compute and new compute. But like what we're seeing is you do better. You just can't beat S-ray m in particular for that feed-forward network. And no matter how much you try and get the ratio of compute to HBMD-RAM to S-ray m on the chip correct, the workloads are always changing. There's different workloads being able to disaggregate it to these three parts. This is going to be really, really positive for the ROI at AI. For some reason, I just thought of a funny question which I love the framing of Game of Thrones versus all these people. Can you imagine a player that is not currently on everyone's mind becoming relevant at like the major Game of Thrones scale? Like that could be like Micron all of a sudden. Someone that becomes as important as Anthropic, OpenAI, Microsoft, Amazon. So like a Dark Horse. Like Leapoo is probably a Dark Horse, Lid at Fireworks. She is an absolute killer. I think our Fred Scott Wu, cognition is kind of here here to Alan. Yes. I think those are the most obvious names. What about SpaceX? What's it been like watching that be digested by public markets at least initially? Do you think the market understands it as a company? The most important new company to be public? It doesn't really feel like it does. The fundamentalists have gotten better since an IPO. Like Rock 4.5, the cursor acquisition, cursor has clearly accelerated meaningfully. They've showed over the last three years they could bring on more compute faster than anyone at lower prices. And now we know that they could even adjusting for the spot first contract gap. Their big advantage was they came into the market, hit those spot highs. And in a straight way, like one of the more bullish things for compute is they put a vast amount of compute into the market overnight. And it wasn't even really a blip. It was like the market just utterly absorbed it. The free trade didn't sewed out at all. A sub-stackwriter will fund AI. They think that SpaceX is going to try and bring on eight giggle lots of compute over the next 18 months. So eight kick of watts over the next 18 months. I will never bet against Elon, but I mean, that would be a truly incredible feat. Rates have caught up since they signed those last contracts, not down. And they're monetizing at something like 50 billion a gig and consists of estimates for next year or 73 billion. So forget Starlink V3, forget Starlink Direct to Cell, Grock 4.5 and Cursor. I think that the sum of that probably hits a $10 billion ARR pretty quickly. Forget all of that. You know, forget the core base Starlink business. If they bring out anywhere near that, the consensus estimate is 73 billion and that's eight gigs at 50 billion a gig and obviously that would not all be lit up at the beginning of 27. And it seems very implausible to be like, I almost don't believe the fund report. But to this day, the only companies that have brought on more than 500 megawatts of power in a year are the hyper scalers, CoreWeave, Crusoe, and SpaceX. It's SpaceX has kind of brought on the most the fastest at the lowest cost. And then people do actually really like their clusters. But again, it's kind of like the market is going to need to see that. That would not be the market's interpretation of SpaceX. No, no. And it does feel like, you know, there's this big New York hedge fund shortcase audit. And I think they think the spot price for compute is going to go down 90%. You're going to bring on all this compute that's not going to generate, you know, nearly as much revenue as you think. Maybe, but also what it would be really clear. Like, I've seen Elon's companies do really impressive things. The funder, AI report of eight kickawatts at 18 months, I mean, I'm just quoting that because it's public. It's available to everyone. I think one of Elon's phrases is we specialize in making the impossible late. I never heard that. That's great. Yeah. But, you know, there's kind of a lot of truth to that. Yeah. Yeah. But I just think very little is built in from my perspective to that stock for the amount of compute that they might be able to bring on. And again, I don't think it's anywhere near eight. And it's going to be really hard and energizing these GPUs is really hard. But they've been good at it. And it doesn't feel like that's an estimates or really in people's thinking. I think about that funny meme that says SpaceX, the data center company. Absolutely. And then I would also just say like, I did spend a lot of time at Starbase and orbital compute feels more real every day. Pretty cool. See that starship landing the other day. That's a starship landing. You know, it is funny. Our friends at Binchmark, they fund it star cloud. And I don't know. Last time star cloud is an orbital compute company that like SpaceX is kind of partnering with. They're going to, I think, let them use the Starlink laser technology, which is really important for orbital compute. But I do think that's like kind of a good sanity check. Last time I checked the Binchmark guys were pretty smart. And they're not coming from the E-Lonico system at all. And they chose to fund an orbital compute company, a decent valuation, without the internal launch cost that SpaceX gets. To me, that's a good like, hey, am I crazy? Am I crazy? And it's like, well, maybe I'm crazy and maybe E-Lon's crazy. And maybe Binchmark is also crazy. And maybe the SpaceX engineers are also crazy. That man, that just doesn't seem that probable to me. Should we say whose offices we're in? Yeah, we're sitting in the middle. We're sitting in the Binchmark office. Yes, this is their famous table for their famous dinners. So thank you, Binchmark. Thank you, Binchmark for this episode. Yes, thanks, Eric. I mean, it's you that we should think of all Eric coordinated for me. So he gets a special shout out. Thank you. Thank you all of the partners. Thank you, Eric. But I mean, we will see where all of these stocks are in a year. Hey, the great thing is, Tbiletel. People are going to be right or wrong. The future is probably a mistake, but it's an exciting moment. Well, if we keep doing this on the model release cycle, I'll see you in a couple weeks. Yeah, it's crazy. That's always a blast to do it, dude. If you enjoyed this episode, visit Colossus.com. You'll find every episode of this podcast complete with hand out of the transcripts. You can also subscribe to Colossus, our quarterly print digital and private audio publication featuring in-depth profiles of the founders, investors and companies that we admire most. Learn more at Colossus.com/subscribe. You know how small advantages compound over time that's true and investing and just as true in how you run your company. Your spending system is your capital allocation strategy. Ramp makes it smarter by default, better data, better decisions, better economics over time. 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