The AI Selloff Doesn't Match the Data | Top AI Investor Explains

Key Takeaway

GPU prices are defying expectations, rising 50-60% in 6-7 months instead of declining. Companies are paying nearly double ($4/hour vs $2.50/hour for identical clusters), signaling acute compute shortage despite market pessimism. The installed base of contracted compute is trading at massive discounts to spot rates, meaning as contracts reprice, hyperscaler operating cash flows will accelerate—potentially funding the entire buildout without additional debt. Action: Track GPU pricing trends and hyperscaler operating cash flow metrics quarterly to identify inflection points before markets react.

Episode Overview

A deep dive into July 2024's AI market turbulence, examining why stocks fell 40-60% despite accelerating fundamentals. The discussion explores GPU pricing dynamics, the impact of open-source models, credit market concerns, and why the market's interpretation of events (Meta renting compute, Kimi's release, China's DUV machine) missed the underlying strength in demand signals from private AI companies.

Full Transcript

Transcript of The AI Selloff Doesn't Match the Data | Top AI Investor Explains from Invest Like The Best. Auto-generated from episode audio; may contain minor errors.

I want to be scared, you know, I don't want to feel like a lunatic watching these stocks get more cheaper thinking the expected forward returns are growing up. I may be kind of missing out here this week. this week. this week. pressure test? pressure test? pressure test? Yeah. Yeah. Yeah. Find tell me something negative, but I haven't been able to find one that is like a quantitative metric. The underlying fundamentals are improving. Uh and stocks Nvidia's actually has we record this record this record this at its lowest forward PE of the last 10 years.

The market 100% thinks they're significantly overvalued. Gavin, it's only been 2 months like the model release cycles, the gap between our podcast episodes are shortening. shortening. shortening. We're basically you and I are basically on a model release cadence at this point. point. point. Well, I was I was sensitive to criticism that um that um that um that I think somebody pointed out that um our podcasts were coincident with like like like local market peaks. And nobody can say that after this. What's on your mind? It's been a crazy crazy month.

crazy month. crazy month. Yeah, I would describe um um um July as 2022 in a month. Yeah. Yeah. Yeah. There are some fundamental negatives which you 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. line. 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?

Yeah. Yeah. Yeah. A single instance of deceleration. Nothing. Nothing. Nothing. In fact, every metric is accelerating. And to your point, not just blind optimism from people excited about AI. Here's some data that they can show you and from their different vantage points. Absolutely. I mean, however you cut it, whether you cut GPU availability, whether you cut GPU retail pricing, retail pricing, retail pricing, I mean, whether you cut like the spot price of DRAM this month, token growth, token growth, token growth, everything is actually accelerated. And I do think a big part of the problem is is 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, Baseten, Model together.

[snorts] [snorts] [snorts] And the picture looks very different when you see that. Because open-source is accelerated massively because of GLM 5.2 KiB K3. And then, you know, Neurotron continues to kind of chug along. We had a great, you know, very small American open-source model release. OpenAI has accelerated. accelerated. accelerated. Anthropic continues to grow really strongly really strongly 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 cash free cash flow going like that, and is you're missing these private companies.

And then, I also think that that chart, that chart, that chart, um, um, 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 to price around a GPU would, you know, decline slowly. You know, if you're bearish, you thought it would decline precipitously. decline precipitously. decline precipitously. I I think anyone in 24 or 25 thought that the prices of old GPUs would still be would be going vertical in 2026.

in 2026. in 2026. Yeah, and so everybody thought hey, we're going to be smart. We're going to sign these long-term contracts. And to some degree like a lot of the deal clouds had to do that because they needed an off-take agreement to finance the GPUs. the GPUs. the GPUs. And so essentially you have the contracted base of installed compute trading at a massive discount to the current spot market. And And And has those has those has those contracts roll off and compute gets repriced higher. repriced higher.

repriced higher. It's spot could decline and compute will still get repriced higher. You know, I think you're going to see a lot of acceleration that's going to answer these ROI questions. You've started to see that this quarter if we look at operating cash flow, not free cash flow. Operating cash flow from Microsoft, Meta, and Amazon has reported accelerated from 28 to 32. There were some actually pretty big unusual items now like these hyperscalers they always seem to have like like like billions of dollars of legal expenses that are unusual.

Mostly fines to the EU. But there was an unusual amount of one-timers this one-timers this one-timers this this quarter. 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. scale. 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 challenging month that it's almost um you know, like is it helpful to kind of like walk through the month?

How we got here? You know, so first there's Meta is going to rent out compute. And this is seen as like very bearish. They have excess capacity. They're going to cut CapEx. CapEx. 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 compute compute and sell some big trading optimized clusters into the market at a truly massive premium to these contracted rates. rates.

rates. And And And you know, at least the at least at least analysts like that, they saw an opportunity. There's a lot of speculation they're going to raise capital. So, like you know, maybe what they're thinking is like, "Hey, we will show on a small chunk of capacity that we can generate really strong IRRs. Then we'll go raise equity capital and and we'll 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 nevertheless, the market sold off because it interpreted this very negatively.

And And And I was really sure it wasn't negative. You know, there's a lot of telemetry into Meta's CapEx plans. None of that telemetry had shifted at all. If anything, it was, you know, continuing to or continued to get more aggressive. And then shortly after that, they released their best model in a long time, use 1.1, which is 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 anything 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 silica data token index kind of dips and flattens. And the two are connected. What the silica 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, all of it took a while to layer in. in. 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 whether it's 80, 90, or 95.

95. 95. Yeah. Yeah. Yeah. 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. Takes the 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.

demand. 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 who charge the same 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 That was the catalyst. This this combination of things. Well, yeah, then it kept it it's it's like Jenson is the world's largest supporter of open source. Do we really And he's like a super idealistic guy.

He's a patriotic American. American. American. I think he always does what's right. But is it does it really stand to reason that Jenson would be the world's biggest supporter of open source if it was bad for his business? He'd still support if it was the right thing for the world. Yeah. Yeah. Yeah. But maybe it wouldn't be a signature issue. issue. issue. Yeah. Yeah. Yeah. And by the way, I think open source is really important to world where there's just one or two dominant for tier bottles that charge like 90% margins.

90% margins. 90% margins. It's not good for humans. It might not be good for society. And I think we want a lot of bottles as we've discussed before. before. before. So then it's like, okay, the market digests that comes through with it. Then China has a DUV machine and this causes, you know, everybody said these baskets has caused a huge sell off in semi-cap equipment. equipment. equipment. And then we get to what I think is in a lot of ways, um um um like the real concern, which is real yields have gone up, which makes sense, you know, 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 over what the 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 And the media CDS was was blowing All of these CD CDS for everybody is is blowing out. blowing out. blowing out. And, you know, very smart private capital people just like that, hey, this is just exactly what you would 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 are widened, real yield 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. Ramp is the only platform built to make your finance team leaner, faster, and better, saving businesses 5% annually on average, so you can stay focused on growth.

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Right. Right. Right. Which would be the classic like capital cycle, and then we start to overextend ourselves with debt, and that's where things get dicey. 100% to the, you know, debt-fueled buildouts, you know, they demand immediate repayment. Yeah. So, if supply and demand get a little bit out of whack, things can unwind very, very, very quickly. That's what happened to the internet. the internet. the internet. And so, And so, And so, if if if one believes as I do, rightly or wrongly, and I'm like, 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, buildout, buildout, this is like a significant negative. [snorts] [snorts] [snorts] And And And if you model it out, has has has if you look at the amount of gigawatts that are supposed to come out 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, Ampere, Ampere, which is two generations behind.

Not at Hopper, but Ampere. So, there's 1.3 trillion and 1.3 to 1.4 trillion in hyperscale operating cash flow. If you just assume that they they're not I I think it's very unlikely they monetize at the rate of Ampere and we can we can 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. Then it's more like 2 trillion of operating cash flow and that kind of takes 700 billion of credit demand out.

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. reprice. reprice. We're going to continue accelerating. Consensus is modeling in a deceleration, which I think is unlikely. Um then the credit metrics look better and then all of a sudden it gets easier to finance with credit. Now, Now, Now, whether they whether they they choose to do that or not, we'll see, but this this is all a little bit, um 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 where you're spending hundreds of billions of dollars on Blackwells. they're mostly being used for trading initially. Trading does not generate, you know, a return. And that this could be a risk. And we actually really saw that kind of it, you know, in the first quarter. And And And I think one reason, you know, like to the podcast two months ago, I I got comfortable with that risk was just that you were seeing such incredible things out of Anthropic.

And then it's like, "Okay, well, the market's kind of going to look past this." this." 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. past it. past it. Just as the operating cash flow started to really accelerate. And it's this is just a fact. It is accelerating at big scale. Um Um Um and you know, like Microsoft, they brought out 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 kind of quantitative demand signals seeing on the ground here in Silicon Valley from 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. Yeah, operating cash flows go up and you can fund this out of 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's so it's it's been a it has been a very un- very un- very un- usual episode in the market. And And And you know, in some ways, the fact that and we should talk about what the fundamentals are that are getting better that I'm talking about. You know, technicians would say it's actually in '22, okay, the market is worried about a recession, recession, recession, rates going up, you know, 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. Uh there's something very clear and it in a weird way that's that is comforting reassuring. 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 credit credit like are are just kind of ridiculous. Um it's to the fact that it is still going down. going down. going down. You know, a technician would say, "Hey, that's that's that's that's a little scary. You know, it's definitionally the bullet you don't see that gets you." You know, I think we've talked before about how like I think the three most important words in investing aren't margin of safety, but I don't know.

But just, you know, I've you've you've been out here for 2 months. I've been out here, you know, 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 block wells. 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.

Said, "No no differences." And they're hoping 7 months later to pay just under $4. Like you know, just you hear this today. And that's And that's 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. bullish. bullish. Instead, you know, we're up, you know, depending on the starting point 50 to 60% in 6 or 7 months. And it just there've been so many anecdotes like that. Like I think one of the inference clouds I think it was based in I'm not sure.

They went on a podcast and they essentially said essentially said essentially said we are planning to pay 100% more for Blackwell's when our contract expires. And that just means that essentially all the hyperscalers are under running. under running. under running. And I haven't like my main kind of mission out here this week It's like pressure test? Yeah. Yeah. Yeah. Find tell me something negative, you know? 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.

asking everyone. asking everyone. The main thing people are saying is the Anthropic like the third-party data suggests that the Anthropic like curve started to started to started to go off of its trajectory a little bit. That's like the only thing that I I think I think that's I think that may very well be true, but then you have OpenAI and open source massively accelerating. accelerating. accelerating. And if you look at the sub it is not accelerating. Maybe I don't know that it looks the same. I think it may have accelerated.

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 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 cuz you had this huge capability leap which you learn 5.2 and KBK3 KBK3 KBK3 which I think we're going to see continue.

I think you're going to see Nvidia bring Neobtron steadily closer to the frontier. It has been a very like it's been a hubbly challenging month and but just it's also like wow, I've kind of pressure tested every assumption. The underlying fundamentals are improving. improving. improving. Uh and stocks Nvidia's actually as we record this record this record this at its lowest forward PE of the last 10 years. years. years. Crazy. Crazy. Crazy. The only time the Sibbys have been cheaper were liberation day deep seek and that was those were kind of uh V bottoms.

Um Um Um And that means to you just that the market thinks they're significantly over earning? earning? earning? Yeah, the market 100% thinks they're significantly over earning. And you And you And you we need to be humble. Maybe they are. Um Um Um but like my kind of mission out here this week was to look for negative data points as hard as I could. I normally come to Silicon Valley and you know, there's a mixture of like okay, here's 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. Other like that that Anthropic third-party data, I would say that seems to be a hotly contested by the um by the Anthropic shareholders who are like like like who are bound or kind of like chopping at the bit to tell you what they know. They're 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 know, you can just see Anthropic shareholders like they want to be like, "It's not true." You know.

I mean, it's hard for me to believe that um um um open source and open AI have accelerated to the extent they did and but yeah, Anthropic is clearly, you know, kind of in the in the pole position. And oh, by the way, you know, Grok and Cursor have also, you can see from third-party data, like July was a pretty transformational month with um Grock 4.5 Grock builds coming out. So, it has been a tricky month and um and I have I have a friend um I have a friend at Fidelity who just says the way to have navigated like the last 3 years is just do the dumbest, most superficial thing as quickly as possible and just cycle between them.

What is that? What is that now? Well, that's just that has been to cut risk risk risk all month in response to these kind of narratives that just like factually except for credit are not true and the work we've done makes me think that credit just isn't going to matter has this reprice. Let's just say you do need credit to like build the flops we eat. Well, if credit's not there, it just means the flops that are there are going to be even more valuable cuz there is an interesting like essay that got sent sent to me.

You know, I think we've talked before about Mike Mauboussin's theory that like a breakdown of diversity is kind of what leads leads leads you know, to bubbles and crashes. And essentially everyone I know in the public 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, Claude it's probabilistic. There's probably not that much variation in the way it's interpreting this news. It's uh it's almost like we're back to um um 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 is kind of Walter Cronkite for the stock market and everybody just believes Whatever it says. And this is leading to like really and and by the way, it's really smart, smart, smart, but it's not always right. It's not um it's 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 this way. way. way. 90 a huge chunk of people trade on Claude's view. Um Um Um And so you've seen stuff. There's this guy uh TBU, TBU. He's like part of like the autonomous semiconductor mafia, but he posted this amazing chart of Japanese capacitor stocks. capacitor stocks. capacitor stocks. And he said we've had a capacitor an entire capacitor cycle in 6 weeks. And it's true, you know, the stocks like whether they double, triple, or quadruple, I don't know, but like vertical. vertical. vertical. And then whoosh, you know what I mean?

Like the actual fundamentals haven't even hit. And yet you've already had what probably would have normally been a 3-year cycle 3-year cycle 3-year cycle in like 6 weeks. 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?

curious? curious? Yeah, I am very curious. It was like all 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, it demand if it's that of, you know, having to like I think somebody told me that the uh like I was traded on effectively 20 billion tokens, and then it's like these models are traded on 300 trillion tokens.

And if, you know, you could trade something on 10 trillion tokens and then let it out into the world and learn sample efficiently, you know, that that doesn't sound good for trading demand, but like trading as a percentage of semiconductor demand and compute is going to 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 going to come out, you know, with their their model in in August.

You know, 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, yeah. This would be awesome for the world. world. world. Yeah, we all want we want this, right? 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 what what do we call it?

Scientific or technical takeaway. takeaway. takeaway. But it's just, you know, it's also We still don't know. Well, yeah, and also like Nvidia is heavily involved with all of these startups. So, what would like if I was forced to if If just forced to come up with the set of circumstances that would really switch you around and get you really scared. really scared. really scared. Is it 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?

cash flow does not continue to accelerate. That that would be negative. Um it that to some degree is going to be a function of how Anthropic, Open AI, Grok Cursor, we should call it Grok, and open source open source open source you know, if like if there was a pretty dramatic like dramatic like 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?

Like not not a single person. And it's not like it's the opposite. It sounds like a drug market or something. It really does. It's just wild. But yeah, I mean I think there's a long list of pretty obvious things. You know, if like Anthropic, Open AI, if the sum of these labs labs labs plateaus or you know, starts to decline, that's really negative unless it's just because open source tokens are not growing the pie and taking share. Uh and I do really think the future is like multi multi model.

Yeah, 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 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 outcomes 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 has you know, it's just a function of the margin on the tokens, and you're literally just shifting tokens from really expensive tokens with like 90% gross margins to tokens with maybe, let's call it a 30% gross margin. And that's where the savings are coming from, but the tokens cost the same amount of compute to produce.

to produce. to produce. And then also all these things are kind of happening of happening of happening at kind of um at 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 3 months." So, they set up a router, router, router, and that actually cuts their AI spend, but it doesn't really impact. It may actually increase the amount of tokens that they are generating just by shifting them to these cheaper open-source tokens, and that's just more compute.

compute. compute. So, you know, a company getting smarter about which model to use for which task, that you know, that may lead to a a 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 behind behind you know, these the these model layers of this router. The GPU compute hours probably are going up 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, companies, companies, and then you have this whole wave of AI natives, and natives, and natives, and like they're leading 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 on the coast who maybe aren't as cutting and then Europe who's like just trying to figure out how to regulate AI, before using it.

Yeah, so just like there's kind of these differential differential kind of waves of adoption all happening at the same time. time. time. But the thought I can't get out of my mind is like I think I said it maybe last time, but just Yoc's estimate like I don't know, 500,000 people in the world, 250,000 maybe are using a genetic AI. And we're in a cute compute shortage. That's That's That's Do you know there's seven or eight billion people on the planet? What happens when we go from 500,000 to 1% to 1% to 1% 100 billion, you know, to 500 billion?

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 in this compute re-prices. Are their operating cash flows going to accelerate and maybe we can fund this, but like but like but like who Where is that operating going to 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 going to start growing 10% or we're not. we're not. we're not. Or labor substitution. And for sure, I think in a lot of these AI natives, AI natives, 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 iconic, a bunch of companies that have done this work, you know, they're they're vertical they're vertical 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 of of your companies that their tokens bid relative to labor spend? Oh, yeah. I mean, it's always reported as a percent of percent tokens as a percent of like total comp spend or something like that. what are the ranges you've seen? I mean, like in the really pill companies, like it gets really high. 20%, 25%, something like that. Well, Well, Well, our our our our your our friend Dylan Patel at Jasper Jasper Jasper So, he's an ASI maxi, but he's at 30%.

Yeah. Yeah. Yeah. Uh Uh Uh He probably that's probably the highest one I've heard. Uh I've actually heard a 50. And there's 25 trillion dollars in knowledge work. And so, let's you know, let's say that that's you know, let's take your 20% number. That's 5 trillion and that either comes out of labor substitution or faster economic growth. economic growth. economic growth. And we really, really, really want to have, you know, humans it to come from faster economic growth. One interesting thing I heard this morning from one of the great like leading technology CEOs has founded several companies that if you look at the founder letting controlled companies and adjust for some of the like COVID era, you know, over hiring, like nobody's really laying people off.

Like these are the people that would probably be most quick to adopt AI to you know, become more efficient or whatever. Like they're not really doing jack aside like huge scale layoffs, which probably tells you something about where they think there will be lots of opportunity to still have people plus 100% 100% 100% well, the bull case So, growth not labor not labor growth. the bull case and you know, you've seen charts from Cognition, Ramp and Stripe that the companies that are spending the most on AI are growing growing meaningfully faster.

meaningfully faster. meaningfully faster. Yeah, I love that cognition index. Yeah, the cognition index is wild. Now, all the skeptics will point out rightfully, it's not really controlling for industry, but then if like you dig down into it, you know, I think one of them gave an example of I forget if it was a plumber or an HVAC contractor, but like, you know, and everybody who's a blue-collar workers doing great cuz of AI. By the way, something that I think we should touch on and we we could do it now or later is just everybody is citing these LTAs.

So, that we're everything is at a shortage. Everything is at a shortage right now. You know, if if there's weakness, it's just cuz we can't energize the gigawatts fast enough. The gigawatts are going to get energized like it, 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. ramping up. ramping up. You're you're 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. at this. at this. But I do think one of the most important questions in 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, anything else, anything else, from, you know, crushing numbers in in the short term to they are trading short-term upside for these, you know, what do they call them? Supply chain agreements, long-term agreements, LTAs, agreements, LTAs, agreements, LTAs, where they essentially, you know, agree there's there's many flavors, but the customer prepays customer prepays customer prepays and it's, you know, there's a floor and a ceiling.

a ceiling. a ceiling. And this comes back to the point about labor because, you know, a lot of people after um um um you know, after kind of like firing, you know, too many people, were, you know, you during during COVID, were really reluctant to lay people off. And that, you know, they talked about labor hoarding if you remember a few years ago. You remember this? I'm just I'm just 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 trade ups. There's Google with their TPUs. There's [snorts] AMD. And then there's Nvidia, who's like much bigger than everybody else combined. You know, let's just say it's 2027. 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 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 It's the axis that is dominating all others. Um And this is like at some level like a giant Game of Thrones or Imposters between these companies. And okay, it's 2027. You're like or 2028. 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. situation. situation. And but all 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 supply there's an over supply of making this up in 28, 29.

They break their LTAs. Well, if they're breaking their LTAs, it probably means, you know, you're over supply, prices are coming down. And then, you know, capacity that naturally contracts. Well, Well, Well, like what do you think's going to happen to Google's allocations? And then, you know, this is a cyclical industry and over supply is followed by under supply. What do you think they think is going to happen to their allocations next time? So, I just think given that this is like the access around which kind of everything is revolving, man, like you might blow up your entire business business 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. competitor. competitor. They're the over they're overwhelmingly the largest purchaser. They know they can do whatever this is, you know, going back three, four, five years. They know they can do whatever they want with no consequences cuz their volume is so big, you know, that even if they like super screw Hynix, Micron will of course take them. them. 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 And And if you break an LTA, and that they just say, "Okay, fine. You know what? Great. You broke the price agreement. agreement. agreement. We're going to break the volume agreement. And, you know, screw you. We're going to give the volume to your competitor." competitor." competitor." You just you just lost share, you know? That's so I think the the you know, it like I think, you know, Nvidia's dominance I think is uh like I think the current environment they state to which it favors Nvidia, like it is a 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, power, power, well, they're doing a very good job of playing that chess game and and matchmaking. matchmaking. 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 um with a revenue share if GPU prices are above a floor.

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. Yeah, and and like this isn't this isn't really vendor financing cuz 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 um It's um it's, you know, they're still making equity investments, but it's not it's not like you're just putting money into someone someone someone in return for them, you know, 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 you know, equity investments that um you know, the money can't be used to buy Nvidia chips, but obviously money is fungible.

fungible. fungible. And um And um And um Funny thing. Funny thing. Funny thing. What's that? What's that? What's that? like a funny little thing. Yes. Yes. Yes. Um Um Um Yeah. Yeah. Yeah. But, you know, I think at some level it probably makes everybody feel better. Um Um Um What would you do if you were the memory like if you were the CEO of Hynix? I'd do the exact same thing Nvidia's doing right now. Which is? Which is? Which is? I I would be going I say, all right, I'm going to say be going to the buyers of GPUs, Radeon, and whoever and whoever and whoever and say, I'll participate in the Nvidia credit wrapper.

Now, their business is just inherently less stable and predictable, predictable, 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. You know what I mean? I'm just making this up. But like, But like, But like, do something like you can because you have money now, and credit markets are revolting. There many, you know, like, you know, the 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 gone. It's, you know, surety uh that they, you know, makes the the the person who's extending the debt feel better, better, better, but we want a some sort of a cut of the ongoing revenues as well. Right. 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. Here, you know, you can effectively get a royalty on recurring revenues.

And that is that is what Nvidia is doing. And I do think that is very misunderstood. And I think it would serve Nvidia well to really to really to really explain this. One, they're really bullish on AI. Um Um Um Essentially, every time they haven't taken an equity stake in something, it's been a mistake. You know, I mean, they've taken equity stakes in everything essentially except the memory companies that for a long while Anthropic that they took an equity stake in Anthropic. But like, 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, you know, like all these continual learning labs, you know, safe superintelligence is now working with them. You know, he he sees everything and like what he sees makes him bullish. Um So, what have some equity upside and then two, have a revenue share and you're generating hundreds of billions of dollars of um um um of free cash flow um and a helping to kind of bridge, you know, what what is clearly kind of a gap at least, you know, given everybody's gone free cash flow negative flow negative flow negative until the operating cash flow accelerates enough that you can internally fund this.

It's almost like I mean it's um very opportunistic and it like significant and in a good way and it significantly increases their revenue per gigawatt. And then it also strengthens their competitive position. You know, that's you know, you and I, we both have startups, but okay, that's that's that's great. Use that startups chip. Um chip. Um chip. Um well, what prices are they paying big atomic to me? Higher than Nvidia and all these guys. What prices are they paying for um HBM D-Ram? Higher. Um Can you finance those chips easily at the same rate as Nvidia?

No. And so it's always like, you know, there's there's a real burden, particularly if you use HBM D-Ram, like you're just you're in the crosshairs of this. Um unless like actually you you know, maybe actually like they made really different architectural choices. Everything that's happening happening happening is actually pretty good for hip. Just are going back to game theory. Entropic Entropic Entropic if they had been as aggressive on compute as OpenAI had been, they would have run away with it. And so now OpenAI is back in the game.

I think Grok is in the game. Those are the companies on the Pareto frontier. And they have the compute. And do you think after watching that anyone is going to let off the gas? Cuz you just you know, it was I think 4 months ago that Dario was talking about how you know, it was a real it was a really thoughtful commentary, but he's like, it's really, really hard because, you know, if you buy too much compute, you could go bankrupt at the scale of these things.

things. things. But if you don't buy enough, you could lose. lose. lose. Well, Well, Well, We saw it happen. OpenAI just got back into the game, and now SpaceX is in the game in a big way of Grok 4.5 and Cursor. And like, 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? Vanta automates security and compliance for over 16,000 fast-moving companies like Ramp, Cursor, and Harvey, keeping them audit ready around the clock.

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I mean, essentially everyone out here is more bullish than me, man. I like I like I like You know, I read this thing that Dworkesh wrote, and I was like The 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 um you know, renting an H100 for a year would cost $250,000. You know, um the salary that's 15x the current spot or something. Yeah. something. Yeah. something.

Yeah. Exactly. Like, wow, you know, that was just like that in my book. That wasn't in my you know, forget my like Bayesian probability space of expected outcomes. That wasn't even in my considered but dismissed as totally unlikely outcomes. unlikely outcomes. unlikely outcomes. You know, and then that guy is, you know, he's very Dworkesh, he's a very smart guy, he's very plugged in. And um And um 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 So, everyone's more bullish Yeah, yeah, I like you know, I just I look at what's happening in the stock market and I feel like a foolish optimist. optimist. 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. essentially everyone. essentially everyone. Which is 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 like this is the equivalent of like what ASML had in 2001 or something.

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. cutting-edge compute. cutting-edge compute. 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 machine is like warp drive. Um you know, or what whatever it's going to be, you know, a DUV machine is like a propeller plane EUV is like a jet turbine.

Um Um Um but like they didn't have it before and and 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 should be dismissed, but I also also 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 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 um along the way.

Um so I do think that was probably an overreaction, but we shouldn't dismiss that either. that either. that either. And if you're China, like this is like really important to you. Um and they're you know, there are some reports that like an EV machine had been smuggled into China. into China. into China. Um Um Um and I mean, what a feat of espionage cuz those things are like giant machines. They're They're They're they're huge. Um 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 is super important for them as a country. Um Um Um but are they going to go from the year 2001 2001 2001 to 2026 to 2026 to 2026 or even 2000 and you know, 30? Are they going to it it cuz it really is it is it is it is It's a learning by doing. It's it's a learning by doing. And you kind of have to Yeah, if like like you can't you can't accelerate the doing.

You can't you can't teleport into the future. You actually have to go through those learning cycles. So, So, So, is it significant? Yes. Did the market overreact? Probably. But like I think a lot of lot of lot of like I think it's it's very hard as an American American American to really understand what is happening in China and like have like total conviction and clarity, you know, like for for better or worse, like we are decoupling. And decoupling. And decoupling. And um just that is a process that is been set in motion.

in motion. in motion. And at this point it almost feels like it's kind of self-reinforcing on each side. side. side. And you know, that's that's unfortunate. Um Um Um but but but we are where we are. And they're not they're not going to stop, neither are we. we. we. Any commentary on like every other company in America? Like I feel like right now it is 10 companies, couple private. private. private. Well, that that last month, I mean, everything but AI was vertical. And I do think open you know, open source getting closer to the frontier and companies like Fireworks making it really easy to customize a model such that you can get in some cases better than frontier for performance for meaningfully lower cost.

That is a godsend for the software industry. industry. industry. And it's also a godsend for all these like, you know, there's there's a lot of AI natives and like all these AI natives, you know, it's like our friend Vashria, I think he said 2 years ago, I've never seen more companies go from like 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 like back then, like it's like, hey, you know, these are a lot of people would dismiss them as chat GPT wrappers.

GPT wrappers. GPT wrappers. Well, now with open source, you've actually you you've generated some data that's unique to your your use case, whatever your vertical you're going after has a wrapper is. Fireworks, they did come out with a really cool product called Nexus. called Nexus. called Nexus. And if you're using cloud code, open AI codex, grok build, it is literally three lines of code, like 20 words. And um Fireworks adjust your data kind of, you know, they can RL a model and then there's a router that sends the query and they've had amazing results.

Um and this is kind of the solution for every AI native and that's why you saw, saw, saw, you know, Harvey uh before it was acquired, um Cursor leads so heavily into this. Harvey, Legora, all of them. Because if you can go from just using one, two, two three frontier models to use a Whatever's optimal. Whatever's optimal. Whatever's optimal. those frontier bottles for whatever it is, 30% is, 30% is, 30% 60% 60% 60% of your token consumption and then use your own RL bottle, all of a sudden you're not a rapper.

You're way more defensible. defensible. defensible. Um Um Um I was so interested by that cursor thing that came out. I think it was cursor where it's sort of like a AI speed running like 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. 100% 100% 100% And and it's 15 times more efficient or whatever the metric was. It it it may be that like if this is like super ironic, um um um but it may be that like lower margin open source tokens that are just a little bit behind the frontier and you know, we have a we have friends who believe that you know, frontier [clears throat] [clears throat] [clears throat] once a frontier model hits RSI it will actually have a dramatically lower cost lower cost lower cost to serve the local at at every at every level of intelligence by kind of distilling this and then there's no place for open source.

I would say that's like a you know, a um Anthropic Anthropic Anthropic OpenAI Grok maximalist view. And you know, we should we shouldn't dismiss anything. I don't know or really important. Anything is possible. Like you know, we we we would have like be be very humble. I particularly want to be humble after the month I've had. But that doesn't seem that likely to be and and and Why? Why? Why? Well, Well, Well, um um um one because there are so many of these AI natives that have actually generated a decent amount of domain specific proprietary data.

Yeah. Yeah. Yeah. And kind of before like open source had this moment to these inference clouds and these routers really developed like you kind of didn't have a choice. Like whatever the terms of service were, you accepted them. But if you can now kind of get off that treadmill, treadmill, treadmill, um that gives you a degree of independence, independence, independence, maybe durability, safety. But kind of going back to your point, it may be that these cheaper tokens just just just massively inflate the value of the most cutting-edge frontier tokens.

Because if like today if you have I you know I'm going to make this up, you know, 120 IQ open-source models, um and they're really cheap to run, well, doesn't that make a 160 IQ model that can orchestrate them more valuable? And so just we talked last time about how I've been really surprised that you know so much of the economic returns have accrued to the frontier. Now that that is changing with what we're seeing with these kind of inference clouds. Um together, Modal, um uh Base 10 in a very cash-efficient way.

What's shocking about those business models models models is they're growing almost as fast as the frontier labs in the early days, but burning very little cash. Like it's it's pretty extraordinary, you know, from like you know look 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. Absolutely. Yeah. Absolutely. Yeah. Something simple like we can Yeah, it may be that what we discussed last time where you know frontier tokens I think they may lose a like the pie is growing really really fast. They may continue to capture the overwhelming majority of economic value, but kind of not all of it the way they have been, and open source tokens might be the majority of token source tokens processed. processed. processed. It just again, going back, that's great for infrastructure demand because a token is a token and it takes the same amount of flops, watts, watts, watts, space, cooling to make.

What's the worst thing that could happen in AI? Is it regulatory? Is it some sort of like of like of like I think regulatory has to be the biggest risk. risk. risk. Um Um Um I mean, it's the most obvious risk. And so that was kind of one reason I was excited to be here this week was to just like I I I I want to be scared, you know? I like I don't I don't want to feel like a lunatic, 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 feels like the on the ground fundamentals have like pretty materially improved. improved. improved. Um Um Um in July relative to even June, but I still came 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. It just like we are we're living in this weird weird weird post-factual, post-logical political world. world. world. It It It you know, you know, you know, and I mean, I think the AI industry it has done a terrible job terrible job terrible job of PR, and I do think they're it at least realizes that now.

Yeah. Yeah. Yeah. Maybe if not fixed it, it realizes it. Yeah, but like kind of the narrative in Washington, you know, that that that the political narrative, you know, I think amongst a lot of ordinary Americans is like data centers, they're going to raise your electricity prices, they're going to take all your water, and they're going to take your job. job. job. 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 because of behind the meter deals.

deals. deals. This is that like data center pledge that kind of Trump asked people to to sign. Generally, the data center developer, you know, it 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 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, you know, HVAC contractors. And this is like data centers are like are in a lot of ways the best thing to happen happen happen for blue-collar wages in my lifetime. And yet, you have the Democrats who ostensibly ostensibly ostensibly represent the, you know, the blue, you know, these blue-collar workers taking their jobs away. Um Um Um And so, um it it also like it's it's just kind of wild how like, what is the phrase?

Like a lie can go around the world Faster than the truth gets out of bed, yeah. yeah. 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 10,000 X. Not a little bit. Like not one order of magnitude. Not two orders of magnitude. Not three, you know? Um Um Um and um and um and um she's admitted that mistake many times. I was completely wrong. It's like been super debugged.

uh Popeye effect. Did you Did you hear that example? that example? that example? No. No. No. The the, 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 through people still say it has more iron. I literally had I thought it had more iron. I mean that's wild. That's wild. I literally thought spinach had more iron.

That's amazing. That's amazing. That's amazing. Yeah, you learn something new every day. Same thing though. Uh yeah, it's the same thing and it's just just just So somebody just needs to tell the truth. Like like I I feel like the industry and I thought like jeez, maybe if nobody else is going to do it like I'll do it. Like there needs to be some sort of foundation. Maybe it's a pack that runs ads during the final four, during the NFL games, during college football games. football games.

football games. Here's the virtues. World Series. World Series. World Series. Here's what a data center does. Your power a data center that signed this pledge in your community. Yeah. Yeah. Yeah. Your power prices are going to go down. They're almost certainly going to um um um you know you know you know like contribute to the community in a material way. You're going to see a massive influx of super high paying blue collar jobs collar jobs 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 kind of you know, need for kind of RMA and then upgrades at these data centers and and technology is changing. So you're going to have more jobs, you're going to have cheaper power. cheaper power. cheaper power. You're going to have a wealthier community. Um there's going to be no impact on on water, no impact on the environment. You know, and it's easy to build the data center 10 miles out of town, you know.

And so like that story needs to be told along with, you know, like there are you know, we we we we we heard a we we heard a story I think we talked about it last time about how AI is increasingly really saving lives, curing rare diseases. Like we um you know, I think I can't remember if it was I I think it was at ASCO this year. You know, the kind of vibe, you know, the the vibe was like hey, we've this is the most scientific breakthroughs we've ever seen ever seen ever seen at a single conference.

And for sure some of that is due to AI. And so we need to like tell those stories. Like, you know, if you have a sick child, you know, a sick parent, uh a sick loved one, like AI meaningfully increases the odds of them recovering. Like if we just we we need it's everybody needs to tell this. And I think people out here it's all of this is so blindingly obvious to them that they they seems everyone else already knows. They they can't Yeah, they can't process that this is a true but wildly divergent view from most Americans.

And so like I think the industry really needs to tell its story better. Cuz this is like like like New York, it just feels like it's the first of many and even in some of these deep red states, they're super pro-growth. pro-growth. pro-growth. They're just like, "Hey, you guys are not doing a good job telling your story. Then we can't we can't tell your story. If you tell your story though, we can retell it, but like you're the experts." Um you know, if you like like something I've if you do not speak your own truth, no one else will.

[clears throat] [clears throat] [clears throat] Yeah. What have we missed with I 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 not constrained not constrained by HBM DRAM and are often made on older nodes that are not competing with like the latest and greatest GPUs. You can whether you there's when you disaggregate Fritz, there's people talk about prefill and decode, but decode has two parts, attention and feed forward network, and like the ultimate holy grail is if you could do pre-fill on one chip.

Um it probably doesn't have HBM DRAM. Do the attention on a super high-powered chip with HBM DRAM, and then do the feed forward network on one of these SRAM chips. chips. chips. But like But like But like the ROI on adding these SRAM accelerators, accelerators, accelerators, uh uh uh to the existing install base of compute and and new compute. But like what we're seeing is like you do better. You just can't beat SRAM in particular for that feed forward network. And And you just almost you can't, no matter how much you try to get the ratio of compute to HBM DRAM to SRAM on the chip correct.

Like the workloads are always changing, and there's different workloads. And like And like And like being able to disaggregate it to these three parts, three parts, three parts, uh uh uh like I think this is this is going to be really really positive for the ROI of 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 like the major Game of Thrones scale?

Like that could be like Micron all of a sudden, you know, it'd be like a sample answer to the question of someone that becomes as important as Anthropic, OpenAI, Microsoft, Amazon, you know, Nvidia, SpaceX. SpaceX. SpaceX. Yeah. Yeah. Yeah. So like a dark horse Game of Thrones player? player? player? that come to mind. Um Um Um like Li Bu is probably a dark horse. Um I do think um Lin at Fireworks, she is like a like a like a just an absolute killer. Um I think uh you know, our friend Scott Wool.

Mhm. Mhm. Mhm. You know, cognition is kind of like uh Here, here to that one. Yes. Yes. Yes. Uh uh Uh uh Uh uh I think those are uh the most obvious names. What about SpaceX? What's it been like watching that be digested by public markets at least initially? Uh uh Uh uh Uh uh 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 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 it IPO'd.

Like Rock 4.5, the Cursor acquisition. Cursor acquisition. Cursor acquisition. You know, Cursor uh has clearly accelerated meaningfully. And then they have showed that they could, you know, they've they've showed over the last 3 years they could bring out more compute faster than anyone at lower prices. And now we know that they could 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. Uh uh Uh uh Uh uh 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.

overnight. overnight. And it wasn't even really a blip. It was like the market just utterly absorbed it, you know? Like just the free trade didn't sold out at all. Uh uh Uh uh Uh uh But you know, a Substack But you know, a Substack writer Wolfund Fund AI, they think that SpaceX is going to try and bring out 8 gigawatts of compute. I will never bet against Elon. 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 50 billion a gig. And ConsenSys estimates for next year are 73 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 For For Forget all of that. Um you know, forget like the core base Starlink business. Starlink business. Starlink business. If they bring out anywhere near that, the ConsenSys 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. report. report. Um but but you it To this day, the only companies that have brought out more than 500 megawatts megawatts megawatts of power of power of power in a year are the hyperscalers, Coreweave, Crusoe, and SpaceX. And SpaceX has kind of brought out the most the fastest at the lowest cost. And then And then And then people do actually really like their clusters. clusters. clusters. Um 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. No, no. No, no. Um Um 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 going to go down 90% and, you know, you're going to bring out all this You're going to bring all this on all this compute. It's not going to generate, you know, nearly as much revenue as you think.

Maybe, but also want to be really clear like Like, I have seen those I have seen Yolt's companies, you know, do really impressive things over the year. Pretty the Funder AI report of 8 gigawatts at 18 months. 18 months. 18 months. I'm I'm just quoting that cuz it's public. It's available to everyone. Ooh, like that. yeah. yeah. yeah. That Yes. That Yes. That Yes. Um Um Um you know, I think one of Elon's phrases is we specialize in making the impossible late. impossible late. impossible late.

I've never heard that. That's great. Yeah. Um it you know, there's like kind of a lot of truth to that. Yeah, yeah. Um Um 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. eight. eight. Um and it's going to be really hard and energizing these GPUs is really hard. But they've been good at it and it doesn't feel like that's in estimates or really in people's thinking.

I'm thinking about that funny meme that says SpaceX, the data center company? You said yes, absolutely. absolutely. absolutely. Um and then I would also just say like from from from Yeah, I did spend a lot of time at Starbase and Starbase and Starbase and um um um orbital compute feels more real every day. day. day. Pretty cool to see that Starship landing the other day. Pretty cool to see the Starship landing and then it's you know, it is funny. There's our friends at Benchmark. They funded Star Cloud and I don't know last time Star Cloud is an orbital compute company that like SpaceX is kind of partnering with.

Um they're going to 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. And they're not coming from the Elon ecosystem at all. And they chose to fund an orbital compute company compute company compute company at like you know, a decent valuation without the internal launch that SpaceX gets. gets. gets. And that's just to me that's a good like, "Hey, am am I crazy?" crazy?" 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. But man, that just doesn't seem that probable to me. And I mean, we we should say should we say whose offices we're in? Yeah, we're sitting in the middle of the famous table. famous table. famous table. Yes, this is their famous table for their famous dinners. Um so thank you Benchmark. Thank you Benchmark for this episode. Yes, thanks Eric. Um and and she we should thank them all.

Um Eric Eric coordinated for me so he gets a special shout out. Thank you, Eric. Thank you all of the partners. Thank you, Eric. Well, you know, just you know, we will see where all of these stocks are in a year. And the great thing is, you know, time will tell. will tell. will tell. You know, people are going to be right or wrong. or wrong. or wrong. You know, the future's probabilistic, but we are at like it's an exciting moment. moment. moment. Well, if we keep doing this on the the model release cycle, I'll see you in a couple weeks.

couple weeks. couple weeks. Yeah, it's crazy. As always a blast to do with you. You know how small advantages compound over time? That's true in investing and just as true in how you run your company. Your spending system is your capital allocation strategy. Ramp makes it smarter by default. Better data, better decisions, better economics over time. See how at ramp.com/invest. ramp.com/invest. ramp.com/invest. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest.

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