Gavin Baker - AI Market Jitters - [Invest Like the Best, EP.485]

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Gavin, it's only been 2 months. Like the model release cycles, the gap between our podcast episodes are shortening. We're basically, uh, you and I are basically on a model release cadence at this point.

Well, I was, I was sensitive to criticism that I think somebody pointed out that our podcasts were coincident with local market peaks, and nobody can say that after this.

What's on your mind? It's been a crazy—

Yeah, I would describe July as 2022 in a month.

Yeah.

There are some fundamental negatives which we should talk, but on the whole, the balance of fundamentals I think is improving significantly. Loads of AI names are down 50, 60% from their highs. We'll call it 40 to 60% in a month in a straight line. And 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, but like here's some data that they can show you and from their different vantage points.

Absolutely. Yeah. I mean, however you cut it, whether you cut GPU availability, whether you cut GPU rental pricing, I mean, whether you cut like 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 Anthropic, OpenAI, and then I would say these open source inference clouds that monetize inference here in America, Fireworks, BaseTid, Modal together. And the picture looks very different when you see that because open source has accelerated massively because of GLM 5.2, Kibi K3, and then Nimrod continues to kind of chug along. We had a great very small American open source model release. OpenAI has accelerated, and Anthropic 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 hyperscale 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 were really bullish, you thought they would decline slowly. If you're bearish, 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 Neo 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 repriced higher, its spot can decline and compute will still get repriced higher. I think you're gonna see a lot of acceleration that's gonna 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 hyperscalers, they always seem to have billions of dollars of legal expenses that are unusual, mostly fines to the EU. But there was an unusual amount of one-timers this quarter. And if you adjust for that, we went from 28 to 35, and that's, that's a material acceleration at this scale. And that's really before they start to light up the rebids, which will come at a meaningful premium before these contracts reprice. It's been a challenging month. Is it helpful to kind of like walk through the month? Yeah. How we got here?

Yeah.

So first, Meta is gonna rent out compute and this is seen as like very bearish. They have excess capacity, they're gonna cut capex. This is a disaster. This is not at all what it was. They just reported they didn't cut capex. What it was is they saw SpaceX have a big installed base of compute. And sell some big trading optimized clusters into the market at a truly massive premium to these contracted rates. And at least the 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're going to raise equity capital and We'll be off to the races and probably raise capex. That 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 capex plans. None of that telemetry had shifted at all. If anything, they continued to get more aggressive. And then shortly after that, they released their best model in a long time, Muse 1.1, which is actually a very good model. I mean, it was overshadowed by Grok 4.5, but it was a good model, way better than you think in 2 years. So just no chance they're taking their foot off the gas. Then Kibbe comes out and then there's this huge freakout about open source. And at the same time, this Silicon Data Token Index kind of dips and flattens, and the two are connected. What the Silicon Data Token Index captures is mix., and they don't see all the tokens, but because of GLM 5.2 and, and then KIMI, although it took a while to layer in, there's kind of a mix shift in this data from more expensive frontier tokens, which probably have an inference margin. We can debate 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. Tokens 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, thereby driving token demand. You need more demand for compute. The margins, you know, Anthropic 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 the catalyst. Well, this combination of things.

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 it if it was the right thing for the world. And by the way, I think open source is really important to a 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 as we've discussed before. So then it's like, okay, the market digests that and comes to terms with it. Then China has a DUV machine. Everybody's in these baskets. This causes a huge sell-off in 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 widen. Meta priced a bond last week and it did not price where you would think a Meta bond would price. And this just shows that the credit market—

Nvidia CDS was blowing out.

All of these CDS for everybody is blowing out. And, you know, very smart private capital people just like that, hey, this is just exactly what you'd expect. These are just banks hedging their commitments, but nonetheless, it doesn't look good. And these are undeniable facts. CDS is up, spreads have widened, real yields are up. That would be really, really scary if we needed debt to finance this buildout. 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 6 months or something.

The degree to which this buildout is going to require credit, right?

Which would be the classic capital cycle.

Absolutely. Overextend ourselves with debt and that's where things get 100% and then debt-fueled buildouts, they demand immediate repayment. So if supply and demand get a little bit out of whack, things can unwind very, very quickly. That's what happened to the internet. If one believes, as I do, rightly or wrongly, after this month, I'm super open, you know, I'm, I'm looking like I've been pressure 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 buildout, 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 consensus estimates for hyperscalers, they're effectively modeled— and these are gigawatts of Blackwell and Rubin, Rubin being Nvidia'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 at 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 at a discount to current Blackwells, then it's more like $2 trillion of operating 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 reprice, we're going to continue accelerating. Consensus is modeling at a deceleration, which I think is unlikely. Then the credit metrics look better, and then all of a sudden it gets easier to finance with credit. Now, whether they choose to do that or not, we'll see. This is all a little bit, you know, I think we spoke 2 months ago. No, but the time before that about kind of the risks of a Blackwell air pocket.

Oh yes.

Where you're spitting hundreds of billions of dollars on Blackwells. They're mostly being used for training initially. Training does not generate a return. This could be a risk. 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 that it's like, okay, well the market's kind of gonna look past this. And it did look past it in April, in May, in June, and then in July, because of this kind of confluence of things, stopped looking past it just as the operating cash flow started to really accelerate. And this is just a fact, it is accelerating at big scale. Like Microsoft, they brought on a huge slug 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 on the ground here in Silicon Valley from private companies are going to continue such that the installed base of compute reprices 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 reprices 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 that 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 knew exactly what it was. Okay, deep seek, you know what it's worried about. Liberation Day, you know what it's worried about. There's something very clear. And in a weird way, that's comforting.

For 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. And so the fact that it is still going down, a technician would say, hey, that's a little scary. It's definitionally the bullet you don't see that gets you. I think we've talked before about how I think the 3 most important words in investing aren't margin of safety, but I don't know. But just, you've been out here for 2 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 Blackwells., and we'll just call it somewhere in the mid-$2 per GPU hour. They're renting the exact same size cluster, essentially identical in every way, B200s, no differences. And they're hoping 7 months later to pay just under $4 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% in 6 or 7 months. There've been so many anecdotes like that. Like I think one of the inference clouds, I think it was Base10, I'm not sure, they went on a podcast and they essentially said, we are planning to pay 100% more for Blackwells when our contract expires. And that just means that essentially all the hyperscalers are under-earning. My main kind of mission out here this week is like pressure test. Yeah, yeah. Tell me something negative. Like, you know, the question I asked you, is there one negative quantitative metric you've heard? Has been what I've been asking everyone.

The main thing people are saying is the 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—

I think that may very well be true, but then you have OpenAI and open source massively accelerating.

Yeah. The complex—

And if you look at the sum, it is net accelerating. I think open source is a little bit of a— they talk about dark matter in the universe. Open source is kind of dark matter to the public markets. It's hard for public markets to measure it. But 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 had this huge capability leap with Claude 3.5 and Kimi K2, which I think we're going to see continue. I think you're going to see Nvidia bring Nemotron steadily closer to the frontier. But man, it has been a humbling, challenging month. And 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 semis have been cheaper were Liberation Day and DeepSeek, and 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— we 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 you come to Silicon Valley and you know, there's a mixture of here's something negative, here's something positive, da da da. 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 Anthropic shareholders who are chomping at the bit to tell you what they know, but also very scared they're not going to get an IPO allocation if it gets back to the company that they're the ones who said, actually, things are great. You can just see Anthropic shareholders, they want to be like, it's not true. It's hard for me to believe that open source and OpenAI have accelerated to the extent they did. But yeah, Anthropic is clearly in the pole position. And oh, by the way, Grok and Cursor have also, you can see from third-party data, July was a pretty transformational month with Grok 4.5, Grok builds coming out. So it has been a tricky month. And I have a friend, I have a friend at Fidelity who just says the way to have navigated the last 3 years is just do the dumbest, most superficial thing as quickly as possible and just cycle between them.

What is that now?

Yeah. Well, that's just, that has been to cut risk all month in response to these narratives that factually, except for credit, are not true. And the work we've done makes me think that credit just isn't going to matter as this reprises. Let's just say you do need credit to 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. Yeah. 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 sign 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. I think we've talked before about Mike Mauboussin's theory that breakdown in diversity is kind of what leads bubbles and crashes. And essentially everyone I know in the public equity investment business, whether retail or institutional, every piece of news gets fed into Claude and Claude, Claude Code, sometimes a Claude agent. And it's probabilistic. There's probably not that much variation in the way it's interpreting this news. And so it's almost like we're back to, um, in 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 Cronkite, only voice of truth, and now we don't have that anymore. It's like Claude is kind of Walter Cronkite for the stock market and everybody just believes whatever it says, whatever it says. And by the way, it's really smart, but it's not always right. Its 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 Claude, Claude interpreted this way. It's a weird— a huge chunk of people trade on Claude's view. And so you've seen stuff, there's this guy, TBU, he's like, uh, part of the Anonymous Semiconductor Mafia on X. Yeah. Actually a very smart guy. I know him in real life, but he posted this amazing chart of Japanese capacitor stocks and he said, we've had an entire capacitor cycle in 6 weeks. And it's true. You know, the stock's like, whether they double, triple, or quadruple, I don't know, but like vertical and then whoosh. Like the actual fundamentals haven't even hit. And yet you've already had what probably would've normally been a 3-year cycle in like 6 weeks.

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Yeah, I am very curious. A lot of people seem to feel like they're very close to solving continual learning and sample efficient learning, which we've talked about before. And it is possible that if those are solved, that Could that be a temporary discontinuity in demand if instead of— I was trained on effectively 20 billion tokens and then it's like these models are trained on 300 trillion tokens. And if you can train something on 10 trillion tokens and then let it out into the world and learn sample efficiently, that doesn't sound good for training demand, but training has a percentage of semiconductor demand to compute is going to asymptote 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 short 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 for the world.

To be clear. Yeah.

This would be awesome for the world.

We all want this.

Yeah, we want 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—

we just don't know.

Well, 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? Would it just be that this operating cash flow thing doesn't play out and therefore we just need to debt finance this whole thing?

Yeah, if the operating cash flow does not continue to accelerate, that would be negative. That to some degree is going to be a function of how Anthropic, OpenAI, Groq, 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, not, not a single person.

No, it's not like 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 plateaus or 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 multimodal, particularly for the AI natives. They're going to want to take an open source model. It's got all these inference clouds have 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 Claude frontier model, whatever Claude, Groq 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. 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 spend is 20x, I've burned my budget in 3 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're 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 are effectively consuming behind these model layers of this router. The GPU compute hours probably are going up as you shift to these cheaper tokens you can use more of. That's happening to cutting edge of public companies. And then you have this whole wave of AI natives. They're leaning into 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 barely adopted AI companies, broadly speaking, not on the coast, who maybe are as cutting. And then Europe, who's just tried to figure out how to regulate AI before using it. Yeah. So just like there's kind of these differential waves of adoption all happening at the same time. But the thought I can't get out of my mind is, I think I said it maybe last time, but just, y'all, like 500,000 people in the world, 250,000 maybe are using Agentic AI, and we're in an acute compute shortage. There's 7 or 8 billion people on the planet. What happens when we go from $500,000 to $100 million, to $500 million? It is interesting. A lot of people, I do think it's helpful to post on X to see the pushback. And a lot of people are saying, we accept your argument that hyperscalers are under-earning, it is compute reprices, their operating cash flow is going to accelerate and maybe we could fund this. But 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 Satya's comments, like either we're going to start growing 10% or we're not, or labor substitution. And for sure, I think in 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 A16z, Ikota, a bunch of companies that 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 and their token spend relative to labor spend?

Oh yeah. I mean, it's tokens as a percent of total comp spend or something like this.

And what are the ranges you've seen?

I mean, in the really pilled companies, it gets really high, 20%, 25%.

Our friend Dylan Patel at his company, he's an ASI maxi, 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 as humans to come from faster economic growth.

One interesting thing I heard this morning from one of the great leading technology CEOs that's founded several companies, if you look at the founder-led and controlled companies and adjust for some of the COVID-era overhiring, 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. They're not really doing, jack aside, 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 bull case you've seen charts from Cognition, Ramp, and Stripe that the companies that are spending the most on AI are growing meaningfully faster.

Yeah, I love that Cognition Index.

Cognition Index is wild. All the skeptics will point out rightfully, it's not really controlling for industry. But then if 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 everybody who's a blue-collar worker is doing great because of AI. By the way, something that I think we should touch on, and we could do it now or 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 policy is moving in a good way. The turbine manufacturers, the diesel jet manufacturers, you know, you're ripping turbines off old airplanes and, you know, 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 a transition of the market that I got wrong is we are shifting particularly from memory more than anything else, from crushing numbers in the short term to they are trading short-term upside for these, what do they call them, supply chain agreements, long-term agreements, LTAs. There's many flavors, but customer prepays, there's a floor and 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 4 companies that matter at scale. There's Amazon with their Tradiums, there's Google with their TPUs, There's AMD, and then there's Nvidia, who's 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 definitionally actually lowers costs, which is why the demand hasn't responded at all negatively. There's been no elasticity just because it's the axis 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 or '28. You're vaguely tempted to break one of these LTAs and try to 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 2 or 3 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. I'm making this up at 28, 29, they break their LTAs. Well, if they're breaking their LTAs, it probably means, you know, you're oversupply, prices are coming down, and then, you know, capacity naturally contracts. Well, what do you think's going to happen to Google's allocations? And then, you know, this is a cyclical industry and oversupply is 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 axis around which kind of everything is revolving, you might blow up your entire business and your franchise by breaking an 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, you know, going back 3, 4, 5 years. They know they can do whatever they want with no consequences because their volume is so big. That even if they like super screw SK Hynix, Micron will of course take them. This is just different. You know, you have at least 4 players. Then you have all the startups. You're an investor in 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, the extent 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. And 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 above— Yeah, 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 vendor financing because they're not loaning them the money. Somebody else is loaning the GPU buyer the money. They're still making equity investments, but it's not like you're just putting money into someone, then some of that money was used to buy 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. Funny thing.

It makes no sense.

Yeah. But I think at some level it probably makes everybody feel better.

What would you do if you were the member, if you were the CEO of Hynix?

I'd do the exact same thing Nvidia's doing right now.

Which is?

I would be going to the buyers of GPUs, Tritiums, and whoever and 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 up front, 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 LTAs where they're trading upside for durability.

Yep.

Here 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 Nvidia well to really explain this. One, they're really bullish on AI. Essentially every time they haven't taken an equity stake in something, it's been a mistake. They've taken equity stake in everything essentially except the memory companies, then for a long while Anthropic, then they took an equity stake in Anthropic. But why not if you have cash flow and you're bullish on AI? And Jensen, because he sees every lab, he knows all the advances, all these continual learning labs, Safe Superintelligence is now working with them. He sees everything and what he sees makes him bullish. So one, have some equity upside, and then two, have a revenue share and you're generating hundreds of billions of dollars of free cash flow and helping to kind of bridge what is clearly kind of a gap, at least given everybody's gone 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 gigawatt, and then it also strengthens their competitive position. You and I, we both have startups, but okay, that's great. Use that startup's chip. What prices are they paying at TSMC? Higher than Nvidia and all these guys. What prices are they paying for HBM DRAM? Higher. Can you finance those chips easily at the same rate as Nvidia? No. It's so, it's always like there's a real burden particularly if you use HBM DRAM, you're in the crosshairs of this unless like Etched, they made really different architectural choices. 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've run away with it. Now OpenAI's back in the game. I think Groq is in the game. Those are the companies on the Pareto frontier.

And they have the compute.

Do you think after watching that anyone is going to let off the gas?

Right.

It was, I think, 4 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 enough, you could lose. Well, OpenAI just got back into the game and now xAI is in the game in a big way with Grok 4.5 and Cursor. After watching that, from a game theory perspective, is anybody going to back off anytime 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 way more bullish than you? And if so, what do they believe that you don't?

I mean, essentially everyone out here is more bullish than me, man. I read this thing that Dwarkesh wrote and I was like—

The three 3x compute price thing or whatever.

Yeah, well, he was— I forget what it was.

No, no, it was like 15x or something.

Yeah, but no, but just basically that renting an H100 for a year would cost $250,000, and that's 15x the current spot or something. Exactly. Like, wow, you know, that was just like—

that wasn't in my book.

That wasn't in my— forget my like Bayesian probability space of expected outcomes. That wasn't even in my considered but dismissed as totally unlikely outcomes Dwarkesh, he's a 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. Although 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 bearish relative to essentially everyone. Just a strange state of affairs.

What do you make of the DUV news out of China where I've seen reactions really along a spectrum of this is the equivalent of what ASML had in 2001 or something, or 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 could 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. DUV machine's like a propeller plane, EUV's like a jet turbine. They didn't have it before and now they allegedly do. And that is like a phase transition. You've gone from like liquid to solid. Now that's solid, that jet engine, prop plane, whatever, is 25 years behind. But still it's important and I don't think should be dismissed. But I also, you know, it's kind of funny, you just see this in the stock market. The stock market massively overreacts. And then if this ever hits ASML's orders, maybe it hits it in 5 years. And like the market has forgotten about it, got worried about it, forgotten 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. You know, there are some reports that like an EUV machine had been smuggled into China. And I mean, what a feat of espionage, because those things are like giant. Yeah, they're huge. I don't know if that's true. You know, there's some noise about it, but you know, 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. Neither are we.

Any commentary on like every other company in America? Like, 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 could get, in some cases, better than frontier performance for a meaningfully 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 Vishya, I think he said 2 years ago, I've never seen more companies go from being founded to like $50 million a year in revenue and generating cash flow in like, whatever it is, 9 months. And it's hard to know if any of them are durable because a lot of people would dismiss them as ChatGPT wrappers. 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 wrapper is. Fireworks did come out with a really cool product called Nexus. And if you're using Claude Code, OpenAI Codex, Groq Build, it is literally 3 lines of code, like 20 words, and Fireworks ingests your data. They could RL a model, and then there's a router that sends the query, and they've had amazing results. And this is kind of the solution for every AI native. And that's why you saw Harvey before it was acquired, Cursor leads so heavily into this, Harvey, Lagora, all of them. Because if you can go from just using 1, 2, or 3 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, all of a sudden you're not a wrapper, 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 is speedrunning what we've learned amongst humans, which is you could use the frontier model to plan and then farm out tasks to the dumber models and it's 15 times more efficient or whatever the metric was.

And it may be, and this is 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 an Anthropic, OpenAI, Grok maximalist view. We shouldn't dismiss anything. Anything is possible. We want to be very humble. I particularly want to be humble after the month 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 were, 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, I, you know, I'm gonna 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. We talked last time about how I've been really surprised that so much of the economic returns have accrued to the frontier. That is changing with what we're seeing with these inference clouds together. Modal, Base10, 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.

Right.

It's pretty extraordinary. To go back to silly SaaS metrics, like the, you know, the rule of 40 perspective, like these are crazy numbers.

Do you think there's a lot of instruction in just like the distribution of pay inside of an organization? Like the CEO makes X times more than the median person at a company, and maybe that's Frontier tokens versus, you know, open source tokens.

Absolutely. Yeah.

Something simple like that.

Yeah. It may be that what we discussed last time where, you know, Frontier tokens The pie's growing really, really fast. They may continue to capture the overwhelming majority of economic value, but not all of it the way they have been. And open-source tokens might be the majority of tokens processed. Again, going back, that's great for infrastructure demand 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? Is it regulatory?

I think regulatory has to be the biggest risk. It's the most obvious risk. And so that was kind of one reason I was excited to be here this week. I want to be scared, you know, I like, I don't want to feel like a lunatic watching these stocks get cheaper, thinking the expected forward returns are going up while it feels like the on-the-ground fundamentals have pretty materially improved. In July relative to even June. But I still come away thinking 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 mean, I think the AI industry, it has done a terrible job of PR. And I do think that—

I think it at least realizes that now. Yeah. Maybe if not fixed it, it realizes it.

Yeah. But the political narrative, I think amongst a lot of ordinary Americans is like data centers. They're gonna raise your electricity prices. They're gonna take all your water, and then they're gonna 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. 'Cause 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 or the fire department some new trucks and new cars and new body armor or 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 plumbers, electricians, HVAC contractors. Data centers 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 ostensibly represent the 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 faster than truth gets out of bed.

Yeah, yeah, faster than truth gets out of bed. But an author made a mistake in a book and overestimated the amount of water usage in data centers by 10,000x. 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 Popeye effect. You ever hear that example?

No.

You know, Popeye eats spinach. The reason was same deal. In an 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 propagated. People still say it has more iron.

I literally had— I thought it had more iron. I mean, that's what— 80 years ago. That's what— I literally thought spinach had more iron. That's amazing.

Crazy.

Yeah. You learn something new every day.

Yeah. Same thing though.

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 PAC that runs ads during the Final Four, during NFL games, during college football games.

Here's the virtues.

World Series. Here's what a data center does. Your power— a data center that signed this pledge in 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-paying 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 and then 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 at ASCO this year, the vibe 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, you know, 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, is the first of many. And even in some of these deep red states that are 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 could 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 SRAM-based accelerators that are not constrained by HBM DRAM and are often made on older nodes that are not competing with the latest greatest GPUs. When you disaggregate inference, people talk about prefill and decode, but decode is two parts, attention and feedforward network. And the ultimate holy grail is if you could do prefill on one chip that probably doesn't have HBM DRAM, do the attention on a super high-powered chip with HBM DRAM, and then do the feedforward network on one of these SRAM chips. But like the ROI on adding these SRAM accelerators to the existing installed base of compute and new compute, but like what we're seeing is you do better, you just can't beat SRAM in particular for that feedforward network. And no matter how much you try and get the ratio of compute to HBM DRAM to SRAM on the chip correct, the workloads are always changing and there's different workloads. Being able to disaggregate into these three parts, this is going to be really, really positive for the ROI on AI.

For some reason, I just thought of a funny question, which I love their 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 the major Game of Thrones scale? 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 Li Pu is probably a dark horse.

Lit at Fireworks. She is an absolute killer. I think Alfred Scott Wu, Cognition is kind of—

Hear, hear to that one.

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 fundamentals have gotten better since an IPO, like ROC 4.5, the Cursor acquisition. Cursor has clearly accelerated meaningfully. They've shown over the last 3 years they could bring on more compute faster than anyone at lower prices. And now we know that they can, even adjusting for the spot-first contract gap, Their big advantage was they came into the market, hit those spot highs, and in a strange 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 freight trade didn't slow down at all. A Substack writer, Wolf Funda AI, they think that SpaceX is gonna try and bring on 8 gigawatts of compute. Over the next 18 months. So 8 gigawatts over the next 18 months. I will never bet against Elon, but I mean, that would be a truly incredible feat. Rates have gone up since they signed those last contracts, not down, and they're monetizing at something like $50 billion a gig, and consensus estimates for next year are $73 billion. So forget Starlink V3, forget Starlink direct-to-cell, Grok 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 on anywhere near that, the consensus estimate is $73 billion, and that's 8 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 me like I almost don't believe the Funder Report, but to this day, the only companies that have brought on more than 500 megawatts of power in a year are the hyperscalers, CoreWeave, Crusoe, and SpaceX. 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 today.

No, no. And it does feel like there's this big New York hedge fund short case on it. And I think they think the spot price for compute's going to go down 90% and you're going to bring on all this compute. It's not going to generate nearly as much revenue as you think. Maybe. But I also want to be really clear, I've seen Elon's companies do really impressive things. The Funder AI report of 8 gigawatts in 18 months, But 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. There's kind of a lot of truth to that. 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 8, and it's going to be really hard and energizing these GPUs is really hard, but they've been good at it. It doesn't feel like that's in estimates or really in people's thinking.

I'm thinking about that funny meme that says SpaceX, the data center company.

Oh, no, 100%. Yes, absolutely. And then I would also just say, I did spend a lot of time at Starbase and orbital compute feels more real every day.

Pretty cool to see that Starship landing the other day.

Pretty cool to see the Starship landing. And then it is funny, our friends at Benchmark, they funded StarCloud, 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 Benchmark guys were pretty smart and they're not coming from the Elon ecosystem at all. And they chose to fund an orbital compute company. A decent valuation without the internal launch costs that SpaceX gets. To me, that's a good, like, hey, am, am I crazy? Am I crazy? And it's like, well, maybe I'm crazy and maybe Elon's crazy and maybe Benchmark 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, we're sitting in the Benchmark office table.

Yes. This is their famous table for their famous dinners. So thank you, Benchmark. Thank you, Benchmark, for this episode. Yes. Thanks, Eric. Um, and, and Sheila, we should thank them all.

Eric coordinated for me, so he gets a special shout out.

Thank you, Eric.

Thank you, all the partners.

Thank you, Eric. But I mean, we will see where all of these stocks are in a year. And the great thing is time will tell. People are going to be right or wrong. The future's probabilistic, 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.

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