Why the Markets Are Pricing AI Wrong | Gavin Baker

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 going up. My main kind of mission out here

up. My main kind of mission out here this week is like pressure test.

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 and stocks. Nvidia is actually, as we

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 overrated.

Gavin, [music] it's only been two months. Like the model release cycles,

months. Like the model release cycles, the gap between our podcast episodes are shortening.

[laughter] We're basically uh you and I are basically on a model release cadence at this point.

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

[laughter] and nobody can say that after this.

What's on your mind? It's been a crazy crazy month.

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

Yeah. 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

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

line. And I asked you before we started you've you've been out here for the summer. Have you heard a single negative

summer. Have you heard a single negative quantitative metric about AI?

Yeah.

A single instance of deceleration?

Nothing.

Nothing.

In fact, every metric is accelerating.

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

Like 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 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 open AI. And

then I would say these open source inference clouds that monetize inference here in America, fireworks, base 10, modal together. [snorts] And the picture

modal together. [snorts] And the picture looks very different when you see that because open source has accelerated massively because of GLM 5.2, Kimmy K3

and then you know Neatron continues to kind of chug along. We had a great you know very small American open source model release. OpenAI has accelerated

model release. OpenAI has accelerated and Anthropic continues to grow really strongly and is almost certainly pumping out significant amounts of free cash

flow. And I just think if you know

flow. And I just think if you know there's this chart that everybody looks at of semiconductor cash flow going like this and hypers scale 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're really bullish you thought they would to price to rate a GPU would 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 would be going vertical 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 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 has those contracts roll off and compute gets repriced higher and spot can decline and compute will still get

repriced higher. You know I think you're

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

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 billions of dollars of legal

expenses that are unusual mostly fides to the EU but there was an unusual amount of one-times this this quarter and if you from 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 Reubins which will come at a

meaningful premium before these contracts repric. It's been a it's been

contracts repric. 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 how we got here?

Yeah. 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. This is a disaster. This is not

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 at least at least the analysts like that. They saw an opportunity.

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 were 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 and we'll be off to the races and

probably raise capex. That 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 metaccapex plans. None of that telemetry had shifted at all. If

anything, it was, you know, continuing to u continuing to get more aggressive.

And then shortly after that, they released their best model in a long time, Muse 1.1, which is actually really a very good model. I It was overshadowed by Croc 4.5, but it was a good model.

Um, way better than you think in two years. So just no chance they're taking

years. So just no chance they're taking their foot off the gas. Then Kimmy comes out and then there's this huge freak out about open source and at the same time

this Silicon data um token index kind of dips and flattens and the two are connected. What the silicon data token

connected. What the silicon data token index captures is mix and they don't see all the tokens but because of GLM 5.2 too. And and and then Kimmy, although it

too. And and and then Kimmy, 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 whether it's 80, 90, or 95, but super high towards open source tokens.

And for whatever reason, the market thought this was negative. But the

reality is a token is a token, and you need the exact same amount of compute to make a token. and all else equal. It

takes the same amount of flops, the same amount of memory, the same amount of watts. Now, tokens are not equal, but

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

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 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 a catalyst.

Well, this combination of things. Well,

yeah. Then it kept it's it's like Jensen is the world's largest supporter of open source.

Do we really and he's like a super idealistic guy. He's a patriotic

idealistic guy. He's a patriotic American. I think he always does what's

American. I think he always does what's right.

But is it does it really stand to reason that Jensen would be the world's biggest supporter of open source if it was bad for his business? [laughter]

he'd still support if it was the right thing for the world, but maybe it wouldn't be his signature issue.

Yeah.

And by the way, I think open source is really important to world where there's just one or two dominant frontier models that charge like 90% margins.

It's not good for humans. It might not be good for society. And I think we want a lot of models as we've discussed before.

So then it's like okay, the market digests that and comes term with it.

Then China has a DUV machine and this causes, you know, everybody's in these baskets. This causes a huge sell off in

baskets. This causes a huge sell off in semicap equipment. And then we get to

semicap equipment. And then we get to what I think is in a lot of ways 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 overwhelming majority is still funded

out of operating cash flows and so real yields go up and spreads widen. Meta

Metapiced 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 maybe a CDS was was blowing out all of these CD CDS for everybody is is blowing out. Um

blowing out. Um and you know very smart private capital people just like that 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 widened, real yield real yields are up. And that is that would be really

are up. And that is that would be really really scary if we needed debt to finance this buildout.

And that's where I think it's this differential between spot and contract pricing for the installed base of compute is so important.

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[music] It's so important to understand what the financing will be like for the next six months or something.

The degree to which this buildout is going to require credit, right? Which would be the classic like

right? Which would be the classic like capital cycle. We start to overextend

capital cycle. We start to overextend ourselves with debt and that's where things get 100% and then you know debt fueled buildouts you know they demand immediate repayment.

So if supply and demand get a little bit out of whack, things can unwind very very quickly. That's what happened in

very quickly. That's what happened in the internet.

And so 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, this is like a significant negative.

[snorts] And if you model it out, has if you look at the amount of gigawatts that are supposed to come on and

consensus estimates for hyperscalers, they're effectively modeled and these are gigawatts of Blackwell and Reuben.

Ruben being Nvidia's next chip.

Blackwell being the current chip. They

are essentially modeled to monetize roughly at the rate of AER which is two generations behind. Not at Hopper but

generations behind. Not at Hopper but Aier. So there's 1.3 trillion and 1.3 to

Aier. So there's 1.3 trillion and 1.3 to 1.4 trillion in hypers scale operating cash flow. If you just assume that they

cash flow. If you just assume that they they're not I I think it's very unlikely they monetize at the rate of amp here 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 from real quantitative metrics but like let's just say they monetize in a discount to current blackwells

then it's more like two 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 repric we're going to continue accelerating consensus is modeling 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 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 two 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 black wells.

They're mostly being used for trading initially. trading does not generate,

initially. trading does not generate, you know, a return and that this could be a risk. And

we actually really saw that kind of in, you know, in the first quarter. 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. And it

did look past it in April, in May, in June. And then in July, because of this

June. And then in July, because of this kind of confluence of things, stopped looking past it just as the operating cash flow started to really accelerate.

And and it's this is just a fact. It is

accelerating at big scale. Um

and you know like Microsoft, they brought on a huge slug of capacity in the month of June that didn't even show up in the second quarter.

So essentially what this all comes down to is do you believe that the 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. operating

cash flows go up and you could 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. And so it's it's been a

several years. And so it's it's been a it has been a very unusual episode in the market.

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 rates going up you know inflation that's what the market was worried about in 22 you knew exactly

what it was okay deepseek you know what it's worried about liberation day you know what it's worried about uh there's something very clear in a 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 like are are just kind of ridiculous.

Um, and so the fact that it is still going down, you know, a technician would say, "Hey, 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 you've been

out here for two 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 black 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, no no differences, and they're hoping

seven months later to pay just under $4.

Like, you know, just you hear this today. And that's like that's pretty

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.

Instead you know we're up you know depending on the starting point 50 to 60%. in six or seven months

60%. 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 based in I'm not sure they went on a podcast and they essentially said we are planning to pay 100% more for blackwells

when our contract expires and that just means that essentially all the hyperscalers are under earning and I haven't like my main kind of mission out here this week like pressure test.

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 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. That's like the only thing

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 open AAI and open source massively

accelerating the comp and if you look at the sub it is net accelerating may 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 because you had this huge capability leap with GLM 5.2 2 and Kimmy K3 which I think we're going to see continue. I think

you're going to see Nvidia bring Neotron 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 and stocks Nvidia is actually as we record this at its lowest forward PE of the last 10 years.

Crazy.

The only time the civies have been cheaper were liberation day and deepseek and that was those were kind of uh Vbottoms. Um and that means to you just that the

market thinks they're significantly over earning. Yeah, the market 100% thinks

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

Maybe they are.

Maybe they are. Um

but like my kind of mission out here this week was to look for negative data points as hard as I could. And normally

you come to Silicon Valley and you know there's a mixture of like okay here's here's something negative here's something positive d 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 hotly contested by the um by the anthropic shareholders who are like [laughter] who are bound or kind of like chopping at the bit to tell you what they know.

We're also very scared they're not going to get an IPO allocation [laughter] if it gets back to the company that they're the ones who said actually things are great. You know, you can just see

great. You know, you can just see anthropic shareholders like they want to BE LIKE IT'S NOT TRUE. YOU KNOW,

[laughter] I mean it's hard for me to believe that um open source and OpenAI have accelerated to the extent they did and but yeah, Enthropic is clearly, you

know, kind of in the in the pole position. And oh by the way you know

position. And oh by the way you know Grock 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 I have a friend um I have a friend in Fidelity who just says the way to

have navigated like the last three 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. Yeah.

risk. Yeah.

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 repric. Let's just say you do need credit to like build the flops we need.

Well, if credit's not there, it just means the flops that are there are going to be even more valuable. Because there

was an interesting like essay that got sent said sent said sent said sent said sent said sent said sent said sent said sent said sent said sent to me you know I think we've talked before about Mike Mikeson's theory that like a d breakdown in diversity is kind of what 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, claw, it's probabilistic,

but there's probably not that much variation in the way it's interpreting this news. And so, it's almost like

this news. And so, it's almost like we're back to um, you know, in stock market terms, 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 Krogite was the only voice of truth and now we don't have that anymore. It's like Claude

that anymore. It's like Claude is kind of Walter Kronite for the stock market and everybody just believes whatever it whatever it [laughter] says and this is leading to like

funny 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

correct. And with the stock market, you are fundamentally dealing about, you know, a probabilistic basian 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.

90 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 u part of like the

TBU TBU. He's like u part of like the anonymous semiconductor mafia, but he posted this amazing chart of Japanese capacitor stocks. And he said, "We've

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 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 threeyear cycle in

like 6 weeks. What's your sense of being out here especially 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 etc 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?

Yeah, I am very curious.

like a there seemed to be like a lot of people seem to feel like they are 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 I was trained on effectively 20 billion tokens and then it's like these models are trained

on 300 trillion tokens and if you know you can 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 has a percentage of semiconductor demand to compute is going to asmtote to something not approaching zero but very small but

I would 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

August you know there's this whole generation of new labs that are focused on this and this would be good for the world to be clear this would be awesome for the world yeah we all want we want this for

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 whether we call it scientific or technical takeaway, but it's just you know it's also like you just don't know.

Well, yeah. And also like Nvidia is heavily involved with all of these startups. So what would like if I was

startups. So what would like if I was forced to if you were just forced to come up with the 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 operating cash flow does not continue to accelerate that that would be negative

um and and that to some degree is going to be a function of how anthropic openai gro cursor which Cook Rock and open

source do you know if like 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 [laughter]

like not not a single person in fact it's the opposite sounds like a drug market or something yeah it really does. It's just wild. But

yeah, I mean I think there's a long list of pretty obvious things. You know, if like entropic open AI, if the sum 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

share. Uh, and I do really think the future is like multi multimodel.

Yeah, I think particularly for the AI natives, they're going to want to take an open source model. It's gotten, you know, all these inference clouds have

gotten really good at um, you know, supervised fine-tuning and reinforcement learning. So, you can take your data,

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 Grock

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 they're like that's bad for AI demand. It's actually

not at all because the cost the user pays has, you know, is just a function of the margin on the tokens. And you're

literally just shifting tokens from really expensive tokens with like 90% gross margins to tokens with maybe let's call it a 30% gross margin.

And that's where the savings are coming from. But the tokens cost the same

from. But the tokens cost the same amount of compute to produce. 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 20xed. I've burned my budget in 3

is 20xed. I've burned my budget in 3 months. So they set up a router and that

months. So they set up a router and that actually cuts their AI spend but it doesn't really impact it may actually increase the amount of tokens that they

are generating just by shifting them to these cheaper open source tokens and that's just more compute. So, you know, a company getting smarter about which

model to use for which task that, you know, that may lead to a a stabilization in 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 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 are 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

adopted AI. Companies, you know, broadly speaking on other, you know, not in the coast who maybe are has cutting and then Europe who's like just trying to figure out how to regulate AI, you know, [laughter]

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. But the thought I can't get out of

time. But the thought I can't get out of my mind is like I think I said it maybe last time but just Yak as like I don't know 500,000 people in the world 250,000

maybe are using agentic AI and we're in an acute compute shortage that's you know there's seven or eight billion people on the planet what

happens when we go from 500,000 to 1% 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 push back 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 flow is going to accelerate and maybe we could fund this

but like who where's that operating cash flow 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 Satcha's comments

productivity. Kind of Satcha's comments like either we're going to start growing 10% or we're not 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

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, you know, they're they're vertical u 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?

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 this. What what are the rages you've seen? I

mean like in the really pled companies like it gets really high 20% 25% something like that.

Well um our your our Fred Dylan Patel at the company [laughter] so he's an ASI back seat but he's at 30%.

Yeah.

Um he probably that's probably the highest one I've heard.

Um I've actually heard of 50 and there's $25 trillion 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 five trillion and that either comes out of labor substitution or faster economic

growth and we really really really want as 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 that's founded several companies that if you look at the founder and controlled companies and adjust for some of the like COVID era you know overhiring 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 100k token spend 100%. Well, in the bull case,

100%. Well, in the bull case, so growth, not labor, labor growth in 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.

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 bluecollar worker is doing great because 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, the we're everything's

these LTAs. So, the we're everything's in a shortage. Everything's in a shortage right now. you know, if if there's weakness, it's just because 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 manufacturers, you know, they're ramping up. You're you know, you're ripping

up. You're you know, you're ripping turbines off old airplanes and, you know, reconditioning them and then repurposing them. There's crazy things

repurposing them. There's crazy things happening. Capitalism is very, very good

happening. Capitalism is very, very good at this. But I do think one of the most

at this. But I do think one of the most important questions of the market and like a transition in 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 what they call supply chain agreements long-term agreements LTA 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 and that, you know, they talked about labor hoarding. If you remember a few years

hoarding. If you remember a few years ago, you remember this?

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 tradeiums, 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.

Mhm.

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 IPERS 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 overupp situation and but the logic almost the game theory even holds in a severe overupp

situation. If you break your LTA

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 overupp. I'm

making this up. And 28 29 they break their LTAs. Well, if they're breaking

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 naturally contracts.

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 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

an LTA. And that was never the case before. You know Apple who cares you

before. You know Apple who cares you know they're buying they don't have a competitor. They're the over they're

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

years. They know they can do whatever they want with no consequences because their volume is so big, you know, that even if they like super screw, highex, Micron will of course take them.

This is this is just different. you

know, you have at least four players and you have all the startups, you're an investor and 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 going to break the volume agreement and you know, screw you. We're

going to give the volume to your competitor. You just you just lost

competitor. You just you just lost share, you know." So I think the the you know like I think you know Nvidia's

dominance I think is um like I think 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 financable 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 in in 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

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.

Yeah. And and like this isn't this isn't really vendor financing because they're not loaning them the money. Somebody

else is loaning 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

financing. It's um it's you know they're still making equity investments but not it's not like you're just putting money into someone in return for them you you know and then some of that money you know is used to buy 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 fungeible and um funny thing what's that just like a funny little thing

yes [laughter] um makes the sense yeah but you know I think at some level it probably makes everybody feel better.

Um, what would you do if you were the member? Like if you were the CEO of

member? Like if you were the CEO of Highix, I'd do the exact same thing Nvidia is doing right now, which is I I would be going I say I would be going to the buyers of GPUs,

tradeiums, and whoever, and saying I'll participate in the Nvidia credit wrapper. Now, their business is just

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. 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 revoling.

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 gone. it's, you know, shity u that, you

gone. it's, you know, shity u that, you know, makes the the person who's extending the debt feel 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, you know, you

here. you know, you can, you know, you can effectively get a royalty on recurring revenues. And that is that is

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 explain this one. They're really bullish on AI. Um,

on AI. 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, then they took an equity stake getting 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 super intelligence is now working with them. You know, he he sees everything and like what he sees

makes him bullish. Um so one have some equity upside and then two have a revenue share and you're generating

hundreds of billions of dollars of um of free cash flow um and 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 until the operating cash flow accelerates enough that you can internally fund this. It's almost like I mean it's um it's very opportunistic and

it like significant 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 startup's chip um well what prices are they play paying at Taiwan semi higher than Nvidia

and all these guys what prices are they paying for um HBMD 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 HBMD RAM like you're you're in the crosshairs of this. Um, unless like at you, you know,

this. Um, unless like at you, you know, maybe at like they made really different architectural architectural choices. Everything that's

architectural choices. Everything that's happening is actually pretty good for him. Just going back to game theory,

him. Just going back to game theory, anthropic, if they had been as aggressive on compute as open had been, they would have run away with it.

Yeah.

And so now OpenAI is back in the game. I

think Grock is in the game. Those are

the companies on the paro frontier and they have the compute and do you think after watching that anyone is going to let off the gas right

cuz you just you know it was I think four months ago that Dario was talking about how you know it was a real and 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 but if you don't buy enough you could lose.

Well, we saw what happened.

Open just got back into the game and now SpaceX is in the game in a big way with Gro 45 and Curser and like after watching that from a game

theory perspective, is anybody going to back off anytime soon, especially if it could be funded out of operating cash flow?

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Have you met anyone in your travels out here that you would say is like way more bullish than you? And if so, what do they believe that you don't?

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

[laughter] I like, you know, I read this thing that Doresh 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

you know. Um and that's 15x the current spot or something.

Exactly.

Like wow, you know, that was just like that was in my book. That wasn't in my, you know, forget my like basian probability space of expected outcomes.

That wasn't even in my [laughter] considered but dismissed his totally unlikely outcomes, you know. And then

that guy is, you know, he's very dork.

He's very smart guy. He's very plugged in. And um and you know, and then he

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 margins going up. And if you multiply those three, that's how you're getting this crazy acceleration in the sum of the labs plus open source.

Although obviously open source, the margins on open source are not really going up. But I mean,

going up. But I mean, so everyone's [laughter] Yeah. Yeah. I like, you know, I just I

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 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, [laughter] which is just a strange state of

affairs. What do you make of the DUV

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. I think both could be true. You

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 a warp

drive. Um you know or what whatever it's

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

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

phase transition. You know, you it's like you've gone from like liquid to solid. Now that solid that, you know,

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, you know, it's kind of funny. You just see this in the stock

funny. You just see this in the stock market. You know, it's like 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, gotten

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. Um, and there, you know, there are some reports that like an EV machine had been smuggled

into China. Um,

into China. Um, and I mean, what a feat of espionage cuz those things are like giant [laughter] 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

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 200 you know 30? Are

they going to it it because it really is it is it's a learning by doing.

It's it's a learning by doing and you kind of have to Yeah. 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

future. You actually have to go through those learning cycles.

So, is it significant? Yes. Did the market overreact? Probably. But like I think a

overreact? Probably. But like I think a lot of like I think it's it's very hard as an 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 um just that is a process that has been set in motion and at this point it almost feels like it's kind of self-reinforcing

on each side and you know that's that's unfortunate.

Um but we are where we are and they're not they're not going to stop. Neither are

we.

Any commentary on like every other company in America like I feel like right now it is 10 companies couple private well not not 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 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 Vishria I think he said two 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 were durable because

like back then like it's like hey you know these are a lot of people would dismiss them as chat GPT rappers. Well,

now with open source, you've actually you you've generated some data that's unique to you your use case, whatever your vertical you're going after has a wrapper is. Fireworks, they did come out

wrapper is. Fireworks, they did come out with a really cool product called Nexus.

And if you're using cloud code, openAI codeex, grock build, it is literally three lines of code like 20 words

and um fireworks ingests 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, you know, Harvey, uh, before it was acquired, um, Curser

lean so heavily into this, Harvey, Lora, all of them, because if you can go from just using one, two, or three frontier models to using whatever's optimal,

those frontier models for whatever it is, 30 to 60% of your token consumption, and then use your own RL model. All of a sudden, you're not a rapper. You're way more

defensible. Um,

defensible. 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 is speedrunning 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 and and it's 15 times more efficient or whatever the metric was. And it and it

may be that like and this is like super ironic 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 uh we have friends who believe that you know [clears throat] Frontier once a Frontier model hits RSI it will actually have a dramatically lower cost to serve the low cut

to serve at at every or whatever at every level of intelligence by kind of distilling this and then there's no place for open source and I would say that's like a

you know a u anthropic open AI Grock maximalist view and you know we we shouldn't just miss anything.

I don't know. Really important. Anything

is possible. Like, you know, we we we want to like be be very humble. I

particularly want to be humble after the month I've had. Um but that doesn't seem that likely to be. And

why?

Well, um one because there are so many of these AI natives that have actually generated a decent amount of domain

specific proprietary data.

Yeah. And kind of before like open source had this moment and 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 um that gives you a degree of independence

maybe durability safety but kind of going back to your point it may be that these cheaper tokens just

massively inflate the value of the most cutting edge frontier tokens because if like today if you have 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 have been really surprised that you know so much of the economic returns recruited to the frontier. Now that that is changing with what we're seeing with

these kind of inference clouds um together modal um uh based tip in a very cashefficient way. What's shocking about

cashefficient way. What's shocking about those business models is they're growing almost as fast as the frontier labs in the early days

but burning very little cash, right? Like it's it's pretty

right? Like it's it's pretty extraordinary, you know, from like, you know, to go back to silly SAS metrics like the, you know, the rule of 40 perspective. Like these are crazy

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

organization? Like the CEO makes X times more than the median person at a company. And maybe that's Frontier

company. And maybe that's Frontier tokens versus, you know, open source.

Absolutely.

something simple like we 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 tokens tokens

processed and just again going back that's great for infrastructure demand because a token is a token and it takes the same amount amount of flops, watts,

space, cooling to make.

What's the worst thing that could happen in AI? Is it regulatory? Is it some sort

in AI? Is it regulatory? Is it some sort of like I think regulatory has to be the biggest risk. Um I mean it's the most obvious

risk. Um I mean it's the most obvious risk. And so that was kind of one reason

risk. And so that was kind of one reason I was excited to be here this week was to just like 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 um

in July relative to even June. But I

still come 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 moratorum and just like we are we're living in this weird postf factual postlogical political

world and you know and I mean I think the AI industry it has done a terrible job of PR are and I do think

I think it at least realizes that now maybe if not fixed it it realizes it.

Yeah. But like kind of the narrative in Washington, you know, the the 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 then they're going to take your job.

[laughter] 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 and this is that like data center pledge that kind of Trump asked people to to sign. Generally the data center developer, you used to be they just had to build a like, you know, whatever they had to get the police department and 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 gonna 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

HVAC contractors. And this is like data centers are like are in a lot of ways the best thing to happen for bluecollar wages in my lifetime. And yet you have

the Democrats who ostensibly represent the you know the blue you know these blueco 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 faster than truth gets out of bed.

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 necks.

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

times. I was completely wrong. It's like

been super debunked like the Popeye effect. Did you ever hear that example?

No. the the you know papaya ate spinach.

The reason was same deal in an academic in an academic book they place the decimal two things wrong. So spinach

does not have more iron than everything else. It was just this one source and

else. It was just this one source and then that propagated and people still say it has more iron.

I literally had I thought it had more iron. [laughter] I mean that's wild 80

iron. [laughter] I mean that's wild 80 years ago.

That's wild. I literally thought spinach had more iron. [laughter]

That's amazing.

Crazy.

Yeah. You learn something new every day.

Same thing though.

Um yeah it's the same thing. And it's

just so somebody just needs to tell the truth like like I I feel like the industry and I thought like gez maybe if nobody else is going to do it like I'll do it. Like there needs to be some sort

do it. Like there needs to be some sort of foundation. Maybe it's a pack that

of foundation. Maybe it's a pack that runs ads during the final four during NFL games during college football games.

Here's the virt world series.

Here's what a data center does. Your

power a data center that signed this pledge in your community.

Yeah. your power prices are going to go down. They're almost certainly going to

down. They're almost certainly going to um you know like contribute to the community in a material way. You're

going to see a massive influx of super highpaying bluecollar 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.

You're going to have a wealthier community. um there's going to be no

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 us 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 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 and 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 assume 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. Um,

and so like I think the industry really needs to tell its story better. because

this is like New York it just feels like is the first of many and even in some of these deep red states that are super progrowth

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 u you know if you like like something I've do not speak your own truth no What else will? [clears throat]

else will? [clears throat] Yeah.

What have we missed through and I do think something that is missing from all of this conversation about compute is what is going to happen when you put these SRAM based accelerators

that are not constrained by HBMD RAM and are often made on older nodes that are not competing with like the latest greatest GPUs.

You can whether you there's when you disagregate inference there's people talk about pre-fill and decode but decode is two parts attention and feed forward network and like the ultimate

holy grail is if you could do prefill on one chip um that probably doesn't have HBMD RAM do the attention on a super high-owered

chip with HBMD RAM and then do the feed forward network on one of these SRAM chips but like the ROI

on adding these SRAM accelerators um to the existing installed base of compute and and new compute.

But like what we're seeing is like you do better. You just can't beat SRAAM in

do better. You just can't beat SRAAM in particular for that feed forward network and and you just almost you can't no matter how much you try and get the

ratio of compute to HBM DRAM to SRAMM on the chip correct like the workloads are always changing and there's different workloads and like being able to

disagregate into these three parts um like I think this is this is going to be really really positive for the ROI on AI. For some reason, I just thought of a

AI. For some reason, I just thought of a funny question, which I love the framing of Game of Thrones versus all these people. Can you imagine a player that is

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, would be like a sample answer to the

question of someone that becomes as important as Anthropic, OpenAI, Microsoft, Amazon, you know, Nvidia.

Um, so like a dark horse game of thrones names that come to mind. Um

like Lee Buu is probably a dark horse.

Um I do think um Lynn at Fireworks, she is like a

just an absolute killer. Um I think uh you know our friend Scott Woo, you know, cognition is kind of like um you're here to that one.

Yes. Um,

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,

markets? At least initially, 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 like Rock 4.5 the Cursor acquisition you know Cursor um has clearly accelerated meaningfully and then they

have shown that they could 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, you know, like just the freight train didn't slow down at all. Um, but

you know, a you know, a Substack writer will fund a fund AI. They think that SpaceX is going to try and bring on 8 gawatts of compute.

I will never bet against Elon, but I mean that would be a truly incredible feat. And they are

incredible feat. And they are rates have gone up since they signed those loss contracts, not down. And

they're monetizing at something like 50 billion a gig. And consensus estimates for next year are 73 billion. So forget

Starlink V3, forget Starlink Direct to sell Gro 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 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 fun report.

Um but you and to this day the only companies that have brought on more than 500 megawatts of power

in a year are the hyperscalers Cororeweave, Crusoe and SpaceX. And

SpaceX has kind of brought on the both 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 going to need to see that.

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

No. No. Um, and it does feel like, you know, there's this there's there's a big New York hedge fund shortc 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 on 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 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 fun AI report of 8 gigawatts at 18 months and I'm just quoting that because it's public. It's

available to everyone like that.

Yeah, that yes um you know I think one of Elon's phrases is we specialize in making the impossible late, you know.

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

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

Yeah.

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 going to be really hard. and

energizing these GPUs is really hard, but they've been good at it. It It

doesn't feel like that's in estimates or really in people's thinking.

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

Oh, [laughter] no. 100%. Yes,

absolutely. Um and then I would also just say like from I did spend a lot of time at

Starbase and um orbital compute feels more real every day. Pretty cool to see that Starship landing the other day.

Pretty cool to see the Starship landing and then it's, you know, it is funny.

There's our friends at Benchmark, they funded StarCloud and I don't know last time StarCloud is an orbital compute company that like SpaceX is kind of partnering with. Uh they're going to I

partnering with. Uh 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 at like, you know, a decent valuation without the internal launch cost that

SpaceX gets. And that's just to me

SpaceX gets. And that's just to me that's a good like, hey, am I crazy?

Am I crazy? And it's like, well, maybe I'm crazy and maybe Elon's crazy and maybe Benchmark is also crazy and maybe the SpaceX engineers are also crazy.

That man, that just doesn't seem that probable to me. Um,

and I mean, we should we say whose offices we're in?

Yeah, we're sitting in the We're sitting in the benchmark office.

[laughter] 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 we wish we thank them all. Um,

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

Thank you all the partners.

Thank you, Eric. Well, you know, and 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.

You know, people are going to be right or wrong. You know, the future's

or wrong. You know, the future's probabilistic, but we are at like it's an exciting moment.

Well, if we keep doing this on the the model release cycle, I'll see you in a couple weeks.

Yes. [laughter]

Yeah. Maybe here again at Benchmark.

That's always a blast to do with you.

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