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Invest Like the BestInvest Like the Best

Why the Markets Are Pricing AI Wrong | Gavin Baker

In this episode of Invest Like the Best, Patrick O'Shaughnessy sits down with Gavin Baker to dissect the intense AI and semiconductor market sell-off of July 2026.

Gavin BakerguestPatrick O'Shaughnessyhost
Aug 4, 20261h 18mWatch on YouTube ↗

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Transcript

  1. 0:00 – 1:17

    Intro

    1. GB

      I wanna be scared, [laughs] you know? I don't wanna feel like a lunatic watching these stocks get more cheaper, thinking the expected forward returns are going up. My main kind of mission out here this week [laughs]

    2. PO

      Is like p- pressure test?

    3. GB

      Yeah.

    4. PO

      Yeah.

    5. GB

      Find... Tell me something negative.

    6. PO

      Yeah.

    7. GB

      But I haven't been able to find one that is, like, a quantitative metric. The underlying fundamentals are improving. Uh, and stocks, NVIDIA is actually, as we record this, at its lowest forward PE of the last 10 years. The market 100% thinks they are significantly overearning. [upbeat music]

    8. PO

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

    9. GB

      Well, I was, I was sensitive to criticism that, um, that I think somebody pointed out that, um, our podcasts were coincident with, like, local, uh, market peaks.

    10. PO

      [laughs]

    11. GB

      And nobody can say that after this. [laughs]

    12. PO

      [laughs] What's on your mind? It's been a crazy,

  2. 1:17 – 10:20

    AI Selloff vs. Fundamentals

    1. PO

      crazy month.

    2. GB

      Yeah, I would describe, um-

    3. PO

      [laughs]

    4. GB

      ... July as 2022 in a month.

    5. PO

      Yeah.

    6. GB

      There are some fundamental negatives which, which we should talk, but, like, on, 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, you've been out here for the summer. Have you heard a single negative quantitative metric about AI?

    7. PO

      Yeah.

    8. GB

      A single instance of deceleration.

    9. PO

      Nothing.

    10. GB

      Nothing.

    11. PO

      Nothing.

    12. GB

      In fact, every metric is accelerating.

    13. PO

      And to your point, not just blind optimism from people excited about AI.

    14. GB

      Yeah.

    15. PO

      But, like, here's some data that they can show you and from their different vantage points.

    16. GB

      Absolutely. 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, Base10, 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, you know, Nemotron continues to kind of chug along. We had a great, you know, a very small American open source model release. OpenAI has accelerated. 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 [laughs] and hyperscale cash, free cash flow going like that, and you're missing these private companies. But I also think that that chart, um, misses something very important, which is just that you have everyone in '24 and '25 thought, even if you were really bullish, you thought that GPU prices, if you were really bullish, you thought they would... Price to rent a GPU would d- you know, decline slowly. You know, 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 still be g- would be going vertical in 2026.

    17. PO

      In 200, yeah, yeah.

    18. GB

      Yeah. And so everybody thought, "Hey, we're gonna be smart. We're gonna 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, and spot could decline and compute will still get repriced higher, you know, 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 it accelerated from 28 to 32. There are some actually pretty big unusual items now, like these hyperscalers, they always seem to have, like, [laughs] billions of dollars of legal expenses that are unusual, mostly fines to the EU. But there is an unusual amount of one-timers this, this quarter, and if you adjust for that, we went from 28 to 35, and that's, that's a, that's a material acceleration at this scale, and that's really before, like, they start to light up the Rubins, which will come at a meaningful premium before these contracts reprice. It's been a, it's been a, it's been a challenging month, and it's almost, um, you know... Like, is it helpful to kind of, like, walk through the month?

    19. PO

      Yeah.

    20. GB

      How we got here?

    21. PO

      Yeah.

    22. GB

      You know, so first there's Meta's 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, you know, at least the-

    23. PO

      Saw an opportunity, yeah

    24. GB

      ... at least, at least the analysts like that, they saw an opportunity. There's a lot of speculation they're gonna raise capital, so, like, you know, maybe what they were thinking is like, "Hey, we will show on a small chunk of capacity that we can generate really strong IRRs, then we're gonna raise equity capital and, and we'll, and we'll be off to the, and we'll be off to the races and probably raise CapEx." It doesn't look like what, 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. You know, there's a lot of telemetry into Met- Meta's CapEx plans. None of that telemetry had shifted at all. If anything, it was, you know, continuing to, uh... or continued to get more aggressive. And then shortly after that, they released their best model in a long time, Muse 1.1, which was actually really a very good model. I mean, it was overshadowed by Grok 4.5, but it was a good model. Um, way better than, than you'd think in two years. So just no chance they're taking their foot off the gas. Then Kimi comes out, and then there's this huge freak-out about open source, and at the same time, this Silicon data, um, 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, and, and then Kimi, although it took a while to layer in, there's kind of a, a mix shift in this data from more expensive frontier tokens, which probably have an inference margin we can debate-

    25. PO

      Really high

    26. GB

      ... whether it's 80, 90 or 95.

    27. PO

      Yeah.

    28. GB

      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 sa- same amount of flops, the same amount of memory, the same amount of watts. Now, tokens are not equal, but broadly speaking, all open source taking share does is kind of take margin dollars out of the, uh, frontier model layer and effectively by, thereby, you know, there, there is elasticity, thereby driving token demand. You need more demand for compute. And the margins, you know, Anthropic and open source, they all run on the same underlying cloud providers-

    29. PO

      Yeah

    30. GB

      ... who charge the same [chuckles] amount of compute. You know, so you're literally just, um, taking margin from frontier models and essentially driving more margin dollars into the AI infrastructure layer. And, like, I think that's-

  3. 10:20 – 18:18

    Financing the AI Buildout

    1. GB

      an increasing part of it, even if the majority is still funded, overwhelming majority is still funded out of operating cash flows. And so real yields go up and spreads widen. Meta, Meta priced, um, a bond last week, and, you know, it, it, it did not price where you would think a Meta bond would price. And this just shows that the credit market-

    2. PO

      And maybe a CDS was, was blowing up

    3. GB

      ... all of these CD- uh, it's CDS for everybody is, is blowing out. Um, and, you know, very smart private capital people just like, "Hey, this is just exactly what you'd expect. These are just banks, you know, kind of hedging, hedging their commitments." But nonetheless, it doesn't look good, and these are undeniable facts. CDS is up, spreads have widened, real yield, y- real yields are up. And that is, 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.

    4. PO

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    5. GB

      The degree to which this build-out is going to require credit.

    6. PO

      Right. Which would be the cl- classic, like, capital cycle-

    7. GB

      Absolutely

    8. PO

      ... you know, we start to over- overextend ourselves with debt, and that's where things get tricky.

    9. GB

      100%. And then, you know, debt-fueled build-outs, you know, they demand immediate repayment.

    10. PO

      Yeah.

    11. GB

      So if supply and demand get a little bit o- out of whack, things can unwind-

    12. PO

      Right

    13. GB

      ... very, very f- very quickly. That's what happened to the internet. And so if one believes, as I do, rightly or wrongly, and I'm like, after this month, I'm super open.

    14. PO

      [laughs]

    15. GB

      You know, I'm, I'm looking, like I've been pressure testing-

    16. PO

      Checking your assumptions, yeah

    17. GB

      ... 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 f- fund this build-out, this is, like, a significant negative. And if you model it out, has... If you look at the amount of gigawatts that are supposed to come on in 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-

    18. PO

      Mm

    19. GB

      ... but Ampere. So there's 1.3 trillion in... 1.3 to 1.4 trillion in hyperscale operating cash flow. If you just assume that they d- they're not... I, I think it's very unlikely they monetize at the rate of Ampere, and we could, we could go into why. Some of it comes from just, you know, seeing what is happening on the ground with demand here for real quantitative metrics. But, like, let's just say they monetize at a discount to current Blackwells.

    20. PO

      Mm.

    21. GB

      Then it's more like 2 trillion-

    22. PO

      Of operating cash flow, yeah

    23. GB

      ... of operating cash flow. And that kind of takes 700 billion of credit demand out.

    24. PO

      Mm.

    25. GB

      Um, and, you know, and then obviously these, you know, ironically, has, you know, that improves all the credit ratios, has these installed bases of compute reprice. We're gonna continue accelerating. Consensus is modeling at a deceleration, which I think is unlikely. Um, then the credit metrics look better, and then all of a sudden-

    26. PO

      No problem

    27. GB

      ... it gets easier to [chuckles] finance with credit. Now, whether they, whether they, they choose to do that or not, we'll see. But this, this is all a little bit, uh... You know, I think we spoke-

    28. PO

      Two months ago

    29. GB

      ... No, but the time before that about kind of the risks of a Blackwell air pocket-

    30. PO

      Oh, yeah

  4. 18:18 – 24:23

    GPU Prices Keep Rising

    1. GB

      I literally spoke to a company this morning who rented a cluster of several... And this is one of, you know, kind of 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, you know, somewhere in the mid $2 per GPU hour. They're renting the exact same cluster, exact same size cluster, essentially identical in every way, B200s. No, no differences. And they're hoping seven months later to pay just under $4.

    2. PO

      Mm.

    3. GB

      Like, you know, just, you hear this today. And that's, like, that's pretty crazy because again, you would just, you would expect a really, like, a gentle decline in prices would be bullish. [laughs] Instead, you know, we're up, you know, depending on the starting point, 50 to 60%-

    4. PO

      Mm

    5. GB

      ... in six or seven months. And it just, there have been so many anecdotes like that. Like, I think, um, one of the inference clouds, um, I think it was Base10, I'm not sure. They went on a podcast, and they essentially said, "We are pl- pay- planning to pay 100% more for Blackwells when our contract expires." And that just means that essentially all the hyperscalers are under-earning. And I haven't, like, my main kind of mission out here this week-

    6. PO

      Is like p- pressure test?

    7. GB

      Yeah.

    8. PO

      Yeah.

    9. GB

      Find, tell me something negative. [laughs]

    10. PO

      Yeah, yeah.

    11. GB

      You know? [laughs] Like, you know, the question I asked you, "Have you, is there one negative quantitative metric you've, you've heard?" Has been what I've been asking everyone.

    12. PO

      Yeah. The main thing people are saying is the Anthropic, like, the third-party data suggests that the Anthropic, like, curve started to go off of its trajectory a little bit.

    13. GB

      Right.

    14. PO

      That's, like, the only thing that I-

    15. GB

      I think, I think that's, I think that may very well be true, but then you have OpenAI and-

    16. PO

      It's a different story altogether

    17. GB

      ... open source massively accelerating.

    18. PO

      Yeah. Yeah, the complexes.

    19. GB

      And if you look at the sub, it is net accelerating.

    20. PO

      Yeah.

    21. GB

      May- I don't know that it looks the same. I think it may have accelerated.

    22. PO

      Mm.

    23. GB

      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. You know, it's hard for public markets-

    24. PO

      Yeah

    25. GB

      ... to measure it. But, like, if you just track what these inference clouds are saying, and, you know, these are people saying things on podcasts or people saying things in meetings. They're not, you know, audited financials. But, like, demand is clearly accelerating, which makes sense 'cause you had this huge capability leap with GLM 5.2 and Kimbie K3, which I think we're gonna see continue. I think you're gonna see Nvidia bring Nebo Tron steadily closer to the frontier. It has been a very, like, it's 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. Uh, and stocks, Nvidia is actually, as we record this, at its lowest forward PE of the last 10 years.

    26. PO

      Crazy.

    27. GB

      The only time the Sibies have been cheaper were Liberation Day and DeepSeek, and that was, those were kind of, uh, V bottoms. Um-

    28. PO

      And that means to you just that the market thinks they're significantly over-earning?

    29. GB

      Yeah, the market 100% thinks they're significantly over-earning. And, you, we need to be humble.

    30. PO

      Maybe they are.

  5. 24:23 – 29:01

    Claude Moves Markets

    1. GB

      equity investment business, whether retail or institutional, everything immediately, every piece of news gets fed into Claude. And Claude, Claude code, sometimes, you know, a Claude agent and, you know, Cla- 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, you know, in stock market terms, like the, like 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 was the only voice of truth, and now we don't have that anymore. It's like Claude-

    2. PO

      [laughs]

    3. GB

      ... is kind of Walter Cronkite for the stock market, and everybody just believes-

    4. PO

      [laughs] Whatever it says

    5. GB

      ... whatever it says. [laughs] And this is leading to like-

    6. PO

      That's funny

    7. GB

      ... really... And, and by the way, it's really smart, but it's not always right. It's not, um, its interpretation isn't always correct. And with the stock market, you are fundamentally dealing about, you know, a probabilistic Bayesian interpretation of the future. And so it just, it feels like in the market there is this, here's this piece of news, it gets fed through Claude, Claude interpreted it this way. 90-

    8. PO

      So weird

    9. GB

      ... a huge chunk of people trade on Claude's view. Um, and so you've seen stuff, there's this guy, uh, TBU, TBU. He's like, uh, part of like the anonymous semiconductor mafia. But he posted this amazing chart of Japanese capacitor stocks, and he said, "We've had a capacitor, an entire capacitor cycle in six weeks." And it's true, you know, the stocks, like whether they double, triple, or quadruple, I don't know, but like vertical, and then whoosh. You know [laughs] what I mean? Like the actual fundamentals haven't even hit, and yet you've already had what probably would've normally been a three-year cycle in like six weeks.

    10. PO

      What's your sense of being out here especially, it makes me especially curious about this, the innovation that is going on here to improve the efficiency and every aspect of serving inference, of training models, et cetera, and how that will affect like public markets over time. Like, have you learned anything interesting about like the long lead time innovation type stuff that has you especially excited or, or curious?

    11. GB

      Yeah, I am very curious. It was... Like, uh, there seemed to be, like 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, you know, could that be like a temporary, like kind of like discontinuity, you know, in demand if instead of, you know, having to... Like I think somebody told me that the, um, like IO is trained on effectively twenty billion tokens, and then it's like these models are trained on three hundred trillion tokens. And if, you know, you could train something on ten trillion tokens and then let it out into the world and learn sample efficiently, you know, that, that doesn't sound good for training demand. But like training as a percentage of semiconductor demand to compute is gonna asymptote to something not approaching zero, but very small. But I would say that is the most kind of interesting, and, you know, who knows if it's long horizon or short horizon. You know, SSI says that they're gonna come out, you know, with their, their model at, in August. You know, there's this whole generation of new labs that are focused on this.

    12. PO

      And this would be good for the world.

    13. GB

      This would be amazing for the world.

    14. PO

      To be clear, yeah.

    15. GB

      This would be awesome for the world.

    16. PO

      Yeah. We all want, we want this for humanity.

    17. GB

      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, I would say that was probably like the biggest like, wh- whether we call it scientific or technical takeaway. But it's just, you know, it's also like-

    18. PO

      You just don't know.

    19. GB

      Well, yeah, and also like Nvidia is heavily involved with all of these startups. [laughs]

    20. PO

      Yeah. So what would s- like if I was forced to, if you were just forced to come up with, uh, the set of circumstances that would really switch you around and get you really scared, is it ju- would it just be, uh, that this operating cash flow thing doesn't play out, and therefore we just need to debt finance this whole thing?

    21. GB

      Yeah, if the operating cash flow does not continue to accelerate,

  6. 29:01 – 36:59

    What Could Break the Thesis

    1. GB

      that, that would be negative. Um, and, and that to some degree is gonna be a function of how Anthropic, OpenAI, Groq cursor, which is called Groq, and open source do. You know, if like all, if there was a pretty dramatic like contraction in GPU prices that was kind of sustained, I mean, 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? [laughs]

    2. PO

      No.

    3. GB

      Like not, not a single person.

    4. PO

      No.

    5. GB

      And it's not like-

    6. PO

      In fact, it's the opposite. It sounds like a drug market or something. [laughs]

    7. GB

      Yeah, it really does. It's just wild. But yeah, I mean, I think there's a l- long list of pretty obvious things. You know, if like Anthropic, OpenAI, if the sub of these labs plateaus or, you know, starts to decline, that's really negative, unless it's just because open source tokens are net growing the pie and taking share. Uh, and I do really think the future is like multi, multi-model. Y- I think particularly for the AI natives, they're going to want to take an open source model. It's got, you know, all these inference clouds have got really good at, um, you know, 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 may often first your model and then Claude, a frontier model, whatever Claude Grok, um, 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 and they're like, "That's bad for AI demand." It's actually not at all [laughs] because the cost the user pays has, you know, is just a function of the margin of 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.

    8. PO

      Right.

    9. GB

      And then also all these things are kind of happening at kind of, um, on different cycle times. You know, all these, you know, big public companies are like, "Oh my God, my AI spend is 20X. I've burned 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-

    10. PO

      Right

    11. GB

      ... that they are generating just by shifting them to these cheaper open source tokens, and that's just more compute. So, you know, a company getting smarter about which model to use for which task, that, you know, that may lead to a d- a dec- a stabilization of their spend or even a decline, but it actually has nothing to do with the amount of, you know, GPU compute hours they are effectively consuming behind, you know, these, the, these model layers of this router. The GPU compute hours probably are going up [laughs] as you, you know, shift to these cheaper tokens you can use more of. So and then, you know, that's happening to like a cutting edge of public companies, and then you have this whole wave of AI natives and like they're leaning into this so hard and they're not hiring humans. They're just really putting it mostly into tokens, and so they're not slowing down. And then you have companies on the East Coast of America who have like barely adopted AI, companies, you know, broadly speaking on other, you know, not in the coast who maybe are as cutting, and then Europe who's like just trying to figure out how to regulate AI, [laughs] you know.

    12. PO

      Before using it. [laughs]

    13. GB

      Yeah, so just like there's kind of these differential, differential kind of waves of adoption all happening at 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 your access to like, I don't know, 500,000 people in the world, 250,000 maybe are using agentic AI, and we're at a cu- compute shortage. That's... You know, there's 7 or 8 billion people on the planet. What happens-

    14. PO

      Mm

    15. GB

      ... when we go from 500,000-

    16. PO

      To 1% [laughs]

    17. GB

      ... to 100 million, you know, to 500 million? And then I do think it's, it, it, it is interesting. You know, a lot of people are just like, okay, well... You know, I, I do think it's like helpful to post on X to see the pushback, and a lot of people are saying, "Well, you know, where fundamentally is the... Okay, we accept your argument that hyperscalers are under earning and as compute reprices, their operating cash flows could accelerate and maybe we could fund this." But like who, where's that operating cash flow gonna come from? Where is the customer? And kind of definitionally it has to either come from, you know, faster economic growth through productivity, kind of Satya's comments like, "Either we're gonna 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. You know, the gross profit dollars per FTE and, you know, a16z, Ikona, like a bunch of companies that have done this work, you know, they're, you know, they're, they're vertical, uh, particularly relative to past generations of startups. And then it is interesting, you know. Like, are you kind of doing any surveys of your companies and their token spend relative to labor spend?

    18. PO

      Oh, yeah. I mean, it's th-

    19. GB

      What's-

    20. PO

      Always reported as a percent of, percent tokens as a percent of like total comp spend or something like this.

    21. GB

      And what, what are the ranges you've seen?

    22. PO

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

    23. GB

      Well, um, our-

    24. PO

      Sometimes higher

    25. GB

      ... our, your, our friend Dilip Patel at his-

    26. PO

      Okay, well he's [laughs] he's-

    27. GB

      At his company

    28. PO

      ... he's announced. [laughs]

    29. GB

      So he's an ASI maxi, but he's at 30%.

    30. PO

      Yeah.

  7. 36:59 – 42:08

    The Memory Supply War

    1. GB

      Everything's at a shortage right now. You know, if, if there's weakness, it's just 'cause we can't energize the gigawatts fast enough. Mm-hmm. The gigawatts are gonna get energized, like at, you know, regulatory policy is moving in a, in a good way. You-- the turbine manufacturers, the diesel gen set manufacturers, you know, they're ramping up. Suppliers responding, yeah. You're, 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 of the market, and like a transition of the market that, like, I got wrong, is we are shifting, particularly for, particularly for memory more than anything else, from, you know, crushing numbers in, in the short term to they are trading short-term upside for these, you know, whether they call them supply chain agreements, long-term agreements, LTAs, where they essentially, you know, agree there's, there's many flavors, but the customer prepays and it's, you know, there's a floor and a ceiling. And this comes back to the point about labor because, you know, a lot of people after, um, you know, after kind of like firing, you know, too many people were, you know, during, during COVID, were really reluctant to lay people off in that, you know, they talked about labor hoarding, if you remember a few years ago. You remember this? Yeah. I'm just-- Let's just think about the game theory of breaking an LTA. So there's four companies that, like, matter at scale. There's Amazon with their Trainiums, there's Google with their TPUs, there's AMD, and then there's Nvidia, who's, like, much bigger than everybody else combined. You know, let's just say it's 2027. Mm-hmm. 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. Yep. It's the single most important thing you could do to increase kind of 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, like, kind of the only a- it's the axis that is dominating all others. Um, and this is like at some level, like a giant Game of Thrones or IPers- Mm-hmm ... between these companies. And okay, it's 2027. You're like-- or '28. You're vaguely tempted to break one of these LTAs, try and get a lower price. But to a large degree, market shares are, I think for the next several years, are going to be determined by supply, by supply chain allocations and kind of what you have kind of pre-purchased. So if you break the LTA and you-- and this is, this is assuming we're not in a severe oversupply situation. It-- But, uh, the logic almost, 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. You know, like let's, let's just say Google breaks an LTA. You know, there's, there's an over, there's an oversupply. I'm making this up. In '28, '29, they break their LTAs. Well, if they're breaking their LTAs, it probably means, you know, your oversupply prices are coming down, and then, you know, capacity na- naturally contracts. Well, like what do you think's gonna 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 gonna happen to their allocations next time? So I just think given that this is like the axis around which kind of everything is revolving, man, like you might blow up your entire business and your franchise by breaking an LTA. And that was never the case before. You know, Apple, who cares? You know, they're buying-- They don't have a competitor. They're the over- they're overwhelmingly the largest purchaser. Yeah. They know they can do whatev-- This is, you know, going back three, four, five years. They know they can do whatever they want with no consequences 'cause their volume is so big, you know, that even if they like super screw Hynix, Micron will of course take them. This is, this is just different. You know, you have at least four players. Then you have all the startups. You're an investor in Etched. And if you break an LTA and that they just say, "Okay, fine. You know what? Great. You broke the price agreement, we're gonna break the volume agreement. And, you know, screw you, we're gonna give the volume to your competitor." You just, you just lost share, [chuckles] you know? The-- So I think the, the, you know, it, it, like I think, you know, Nvidia's dominance, I think is, um, l- like I think

  8. 42:08 – 50:14

    Nvidia’s New Playbook

    1. GB

      the current environment, the extent to which it favors Nvidia, like it is a little hard for me to understand why it's trading at such a low multiple. You know, in other words, like 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, you know, land and power, well, they're doing a very good job of playing that chess game and, and matchmaking. And then they've kind of rolled out this really clever, you know, new business model, which I would describe as kind of like a credit wrapper- Mm-hmm ... um, with a revenue share if GPU prices are above a floor. Yeah. Yeah. Um, and this could lead to them like having a really giant cloud business effectively through royalties really quickly. And it is another way of kind of alleviating this, um, you know, cash flow mismatch. Like, "Hey, we're making all the cash." [laughs]

    2. PO

      Oh, yeah, yeah.

    3. GB

      Yeah. And, and like this isn't, this isn't really vendor financing 'cause they're not loading them the money. Somebody else is loading the GPU buyer the money, so it's not quite vendor-- It's not vendor financing. It's, um, it's, you know, they're still making equity investments, but it not, it's not like you're just putting money into someone in return for the... You, you know, and then some of that money, you know, is used to buy your chips. Even though, you know, Nvidia said that they write into all their, [laughs] you know, equity investments that, um, you know, the money can't be used to buy Nvidia chips, but obviously money is fungible.

    4. PO

      [laughs]

    5. GB

      And, um-

    6. PO

      Funny thing. [laughs]

    7. GB

      What's that?

    8. PO

      It's just like a funny little thing. [laughs]

    9. GB

      Yes. Um-

    10. PO

      Makes no sense. [laughs]

    11. GB

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

    12. PO

      Sure.

    13. GB

      Um, it-

    14. PO

      What would you do if you were the mem- Like, if you were the CEO of Hynix?

    15. GB

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

    16. PO

      Which is?

    17. GB

      I, I would be going-

    18. PO

      I see. Oh, I, I finished that.

    19. GB

      I would be going to the buyers of GPUs, Tradiums, and whoever, and say, "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.

    20. PO

      Mm-hmm.

    21. GB

      They're not... I mean, I'm just making this up. But, like, do something. Like, you can-- Because you have money now, and credit markets are revolting.

    22. PO

      Mm-hmm.

    23. GB

      There are many, you know, like, you know, the, the people-- I'm sure the, you know, our friends at, you know, Blackstone and Apollo are suggesting some variant of this to the memory companies. "But hey, we will, like, put up some amount of money from our cash flow today, and then it's got, it's, you know, surety-

    24. PO

      Mm

    25. GB

      ... um, that, you know, makes the, the person who's extending the debt feel better. But we want a, some sort of a cut-

    26. PO

      Mm

    27. GB

      ... of the ongoing revenues as well."

    28. PO

      Right.

    29. GB

      Like, that is, like, 100% what I would do, and it's almost like a logical extension of, you know, the LTAs, where they're kind of trading upside for durability.

    30. PO

      Yeah.

  9. 50:14 – 1:01:51

    China and Open Source

    1. PO

      Ridgeline should be part of that conversation. You can request a demo at ridgeline.ai. 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?

    2. GB

      I mean, essentially everyone out here is more bullish than me, man.

    3. PO

      [laughs]

    4. GB

      I like... [laughs] I mean, you know, I read this thing that Dwarkesh wrote, and I was like-

    5. PO

      The 3x compute price thing or whatever?

    6. GB

      Yeah. Well, he was-

    7. PO

      [laughs]

    8. GB

      I forget what it was. He was-

    9. PO

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

    10. GB

      Yeah, but no, but just basically that, um, you know, renting an H100 for a year would cost $250,000. You know, um, the salary-

    11. PO

      And that's, and that's 15x the current spot or something.

    12. GB

      Exactly.

    13. PO

      Yeah, yeah.

    14. GB

      Like, wow. You know?

    15. PO

      [laughs]

    16. GB

      That was just like not-

    17. PO

      That wasn't in my book.

    18. GB

      That wasn't in my, you know, forget my, like, Bayesian probability space of expected outcomes. That wasn't even in my-

    19. PO

      [laughs]

    20. GB

      ... considered but dismissed his totally unlikely outcomes. You know, and then that guy is, you know, he's very... Dwarkesh, he's a very smart guy. He's very plugged in. And, um, and you know, and then he pointed out that, like, hey, the, you know, something like, I think he just said, "Margins on compute are going up. The amount of compute is going up, and inference margin's 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, obviously open source, the margins on open source are not really going up. But I mean-

    21. PO

      So everyone, everyone's more bullish. [laughs]

    22. GB

      Yeah, yeah. Like, you know, I just, 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, whether anyone in this ecosystem, like, I'm, like, bearish relative to essentially everyone [laughs] , which is just a strange state of affairs.

    23. PO

      What do you make of the DUV news out of China, where I've seen reactions really along a spectrum of, like, this is the equivalent of, like, what ASML had in 2001 or something [laughs] . Um, or like, no, this is actually the first bit of news in a, a new story for how we should think about the global supply of cutting-edge compute.

    24. GB

      I think both could be true. You know, it's just like, um, like let's just make an analogy. Like let's just say a DUV machine was a jet turbine, and now, like, an EUV sh- machine is like a warp drive. Um, you know, or what- whatever it's gonna be, you know. Um, a DUV machine's like a propeller plane. EUV is like a jet turbine. Um, but, like, they didn't have it before, and now they allegedly do. And that is, like, a phase transition. You know? You... It's like you've gone from, like, liquid to solid. Now, that solid, that, you know, jet engine, prop plane, whatever, is 25 years behind. But still, it's important, and I don't think sh- should be dismissed. But I also... You know, it's kind of funny. You just see this in the stock market. You know, it's like the stock market massively overreacts. And then, like, if this ever hits ASML's orders, maybe it hits it in five years, and, like, the market has forgotten about it, got worried about it, forgotten about it, gotten worried about it, forgotten about it multiple times, um, along the way. Um, so I do think that was probably an overreaction, but we shouldn't dismiss that either. And if you're China, like, this is, like, really important to you.

    25. PO

      Yeah.

    26. GB

      Um, and there, you know, there are some reports that, like, an EUV machine had been smuggled into China. Um, and I mean, what a feat of espionage 'cause those things are like-

    27. PO

      Some big [laughs] big hunk of a machine

    28. GB

      ... giant and delicate. Yeah, they're huge. I don't know if that's true. You know, there's some noise about it. But, um, you know, China, they're really, really good. They're really, really smart. They work brutally hard. And, you know, they see this as super important for them as a country. Um, but are they gonna go from the year 2001 to 2026 or even 2000 and, you know, 30? Are they gonna... It, it... 'Cause it really is. It is-

    29. PO

      It's a learning by doing.

    30. GB

      It's, it's a learning by doing. And you kind of have to... Yeah, like, like you can't-

  10. 1:01:51 – 1:11:11

    Data Centers and Regulation

    1. GB

      And so that was kind of one reason I was excited to be here this week, was to just, like... I, I wanna be scared [laughs] you know? I like-

    2. PO

      [laughs]

    3. GB

      I don't, I don't wanna feel like a lunatic-

    4. PO

      [laughs]

    5. GB

      ... you know, watching these stocks relative to, um, you know, get more cheaper, thinking the expected forward returns are going up, you know, while, you know, it, it feels like the on-the-ground fundamentals have, like, pretty materially improved, um, in July relative to even June. But I still ca- come away thinking like, you know, regulation, it just has to be the biggest risk. Like, you just can't ignore New York making a data center moratorium.

    6. PO

      Yeah.

    7. GB

      It just... Like, we are, we're living in this weird post-factual, post-logical political world. It, you know, it... I mean, I think the AI industry, it has done a terrible job of PR, and I do think there-

    8. PO

      I think it at least realizes that now. [laughs]

    9. GB

      Yeah.

    10. PO

      Maybe if not fixed it, it realizes it.

    11. GB

      Yeah, but, like, kind of the narrative in Washington, you know, the, the, the, the political narrative, you know, I think amongst a lot of ordinary Americans is, like, data centers, they're gonna raise your electricity prices-

    12. PO

      Take your job

    13. GB

      ... they're gonna take all your water-

    14. PO

      Take your job. [laughs]

    15. GB

      ... and then they're gonna take your job.

    16. PO

      [laughs]

    17. GB

      And the reality is, like, 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. Uh, this is that, like, data center pledge that kind of Trump asked people to, to sign. Generally, the data center developer, you know, used to be they just had to build a, like, you know, whatever. They had to get the police department or the fire departments, like, you know, new trucks and new cars and, you know, new body armor or whatever. Now it's like, "Well, we're gonna build you a hospital, a school, a new police station, and a fire station, and we're gonna lower your power bills. How does that sound?" [laughs] And by the way, the jobs are ongoing because it turns out that you kind of need these plumbers, electricians, you know, HVAC contractors, and this is like... Data centers are, like, are, 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-

    18. PO

      Represent

    19. GB

      ... represent the D- you know, the blue, you know, these blue collar workers, taking those jobs away. Um, and so, um, and, and also, like, it's, it's just kind of wild how, like, what is the phrase? Like, a lie could go around the world t-

    20. PO

      Fashion than truth gets out of bed. Yeah.

    21. GB

      Yeah, fashion 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, you know? Um, and, um, she's admitted that mistake many times. I was completely wrong. It's, like, been super debunked.

    22. PO

      It's like the, uh, Popeye effect. Do you-

    23. GB

      Yeah.

    24. PO

      Did you ever hear that example?

    25. GB

      No.

    26. PO

      The, the, you know, Popeye eats spinach. The reason was same deal in a academics, 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 [laughs] and people still say-

    27. GB

      I had a-

    28. PO

      ... it has more iron. [laughs]

    29. GB

      I literally had... I thought it had more iron.

    30. PO

      [laughs]

  11. 1:11:11 – 1:18:44

    SpaceX and Orbital Compute

    1. PO

      What about SpaceX? What's it been like watching that be digested by public markets, at least initially?

    2. GB

      Um-

    3. PO

      Do you think the market understands it as a company, the most important new company to be public?

    4. GB

      It, it doesn't really feel like it, it does because it's kind of like such a, it's such a... Like, everything to me is the fundamentals have gotten better since that IPO. Like Grok 4.5, the Cursor acquisition. You know, Cursor, um, has clearly accelerated meaningfully. And then they have shown that they can, you know, they've, they've shown over the last three years they can 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. Like, their big advantage was they came into the market, you know, and just hit those spot highs. Um, and in a strange way, like one of the more bullish things for compute is like, you know, 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 [laughs] you know? Like just the freight trade didn't slow down at all. Um, but you know, a, you know, a Substack writer, well, Funda, Funda AI, they think that SpaceX is gonna try and bring on eight gigawatts of compute. I will never bet against Elon.

    5. PO

      Hmm.

    6. GB

      But I mean, that would be a truly incredible feat. And they are, rates have gone up since they signed those last contracts, not down. And they're monetizing at something like fifty billion a gig. And consensus estimates for next year are seventy-three billion. So forget Starlink V3. Forget Starlink direct to cell. Grok 4.5 and Cursor, the sum of that probably hits a $10 billion ARR pretty quickly. For- forget all of that. Um, you know, forget like the core base Starlink business. If they bring on anywhere near that, the consensus estimate is seventy-three billion, and that's eight gigs at fifty billion a gig, and obviously that would not all be lit up-

    7. PO

      Yeah

    8. GB

      ... at the beginning of '27. And it seems very implausible to me. Like, I almost don't believe the Fundr report. Um, but pff, you know, and 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. And SpaceX has kind of brought on the most, the fastest, at the lowest cost, and then people do actually really like their clusters. Um, but again, it's kind of like the market is gonna need to see that.

    9. PO

      That would not be the market's interpretation of [laughs] SpaceX today.

    10. GB

      No, no. Um, and it does feel like, you know, there's this, there's, there's a big New York hedge fund short case on it, and I think they think, you know, oh, the spot price for compute's gonna go down 90% and, you know, you're gonna bring on all this... You're gonna bring all this, on all this compute, and it's not gonna generate, you know, nearly as much revenue as you think. Maybe, but I also want to be really clear, like, like I have seen those... I have seen Elon's companies, you know, do really impressive things over the year. Bringing the Fundr AI report of eight gigawatts in 18 months, um, and I'm just quoting that 'cause it's public, it's available to everyone. Oof. Like that-

    11. PO

      It's impossible, yeah.

    12. GB

      That... Yes.

    13. PO

      Mm.

    14. GB

      Um, you know, E- I think one of Elon's phrases is, "We specialize in making the impossible late." [laughs] You know?

    15. PO

      [laughs] I never heard that. That's great.

    16. GB

      Yeah. Um, it, you know, there's, like, kind of a lot of truth to that. [laughs]

    17. PO

      Yeah, yeah.

    18. GB

      Um, 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, um, and it's gonna 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 in estimates or really in people's thinking.

    19. PO

      I'm thinking about that funny meme that says, "SpaceX, the data center company?" [laughs]

    20. GB

      [laughs] Oh, 100%. Yes, absolutely. Um, and then I would also just say, like, f- from... Yeah, I did spend a lot of time at Starbase, and, um, orbital compute feels more real every day.

    21. PO

      Pretty cool to see that Starship landing the other day.

    22. GB

      Pretty cool to see the Starship landing, and then it's, you know, it is funny. There's our friends at Benchmark, they funded Starcloud, and I don't know the last time... Starcloud is an orbital compute company that, like, SpaceX is kind of partnering with. Uh, they're gonna, I think, let them use the Starlink laser technology, which is really important for orbital compute, and like... But I do think that's, like, kind of a good sanity check. Last time I checked, you know, the Benchmark guys were pretty smart.

    23. PO

      [laughs]

    24. GB

      And they're not coming from the Elon ecosystem at all, and they chose to fund an orbital compute company at like, you know, a, a decent valuation without the internal launch cost that SpaceX gets. And that's just, to me, that's a good like, "Hey, am, am I-

    25. PO

      Crazy

    26. GB

      ... 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, but man, that just doesn't seem that probable to me. Um, and I mean, we, we should s- shall we say whose offices we're in?

    27. PO

      Yeah, we're sitting in the, the fam- the famous Benchmark table.

    28. GB

      We're sitting in the Benchmark office.

    29. PO

      [laughs]

    30. GB

      Yes, this is their famous table for their famous dinners. Um, so thank you, Benchmark. Thank you, Benchmark, for this episode.

Episode duration: 1:18:44

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