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

27:29If the sum of these labs plateaus or starts to decline, that's really negative, unless it's just because open source tokens are net growing the pie and taking share. And I do really think the future is multi-model, particularly for the AI natives. They're going to want to take an open source model. It's got all these inference clouds have gotten really good at supervised fine tuning and reinforcement learning. So you can take your data, customize an open source model, and then get something that you can put behind a router. and the router routes it to often first your model and then Claude, Frontier Model, whatever Claude, Grock checks it.

28:12And you can, in a lot of cases, get slightly better outcomes at half the cost. But again, that half the cost, I think a lot of people hear that. They're like, that's bad for AI demand. It's actually not at all because the cost the user pays is just a function of the margin on the tokens. and you're literally just shifting tokens from really expensive tokens with like 90 % gross margins to tokens with maybe, let's call it a 30 % gross margin. And that's where the savings are coming from, but the tokens cost the same amount of compute to produce. And then also all these things are kind of happening on different cycle times.

28:53All these big public companies are like, oh my God, my AI spend is 20X'd, I've burned my budget in three months. So they set up a router and that actually cuts their AI spend, but it doesn't really impact. It may actually increase the amount of tokens that they are generating just by shifting them to these cheaper open source tokens. And that's just more compute. So a company getting smarter about which model to use for which task, that may lead to a stabilization of their spend or even a decline, but it actually has nothing to do with the amount of GPU compute hours they are effectively consuming behind these model layers of this router.

29:36The GPU compute hours probably are going up as you shift to these cheaper tokens you can use more of. That's happening to like a cutting edge of public companies. And then you have this whole wave of AI natives. They're leading into this so hard and they're not hiring humans. They're just putting it mostly into tokens. They're not slowing down. And then you have companies on the East Coast of America who have like barely adopted AI. Companies, broadly speaking, you know, not on the coast who maybe are as cutting. And then Europe, who's just trying to figure out how to regulate AI. Before using it.

30:15Yeah. So just like there's kind of these differential waves of adoption all happening at the same time. But the thought I can't get out of my mind is like, I think I said it maybe last time, but just Yalak Sasato, like 500 ,000 people in the world, 250 ,000, maybe are using agentic AI and we're in an acute compute shortage. There's seven or eight billion people on the planet. What happens when we go from 500 ,000 to 100 million, you know, to 500 million? It is interesting. You know, a lot of people, I do think it's like helpful to post on X to see the pushback. And a lot of people are saying, we accept your argument that hyperscalers are under-earning, it is compute reprices, their operating cash flow is going to accelerate, and maybe we could fund this.

31:03But like, where's that operating cash flow going to come from? Where is the customer? And kind of definitionally, it has to either come from faster economic growth through productivity, kind of Satya's comments, like either we're going to start growing 10 % or we're not, or labor substitution. And for sure, I think in a lot of these AI natives, you're seeing labor substitution, but not because they're firing people. They're just not hiring nearly as many humans. The gross profit dollars per FTE and A16Z, Iconic, a bunch of companies that have done this work, they're vertical, particularly relative to past generations of startups.

31:42And then it is interesting. Are you doing any surveys of your companies and their token spend relative to labor spend? Oh, yeah. I mean, it's tokens as a percent of total comp spend or something like this. And what are the ranges you've seen? I mean, like in the really pilled companies, like it gets really high, 20%, 25%. Our friend Dylan Patel at his company, he's an ASI maxi, but he's at 30%. That's probably the highest one I've heard. I've actually heard of 50. And there's$25 trillion in knowledge work. Let's take your 20 % number. That's$5 trillion. And that either comes out of labor substitution or faster economic growth.

32:21And we really, really, really want as humans to come from faster economic growth. One interesting thing I heard this morning from one of the great leading technology CEOs that's founded several companies. If you look at the founder-led and controlled companies and adjust for some of the COVID-era overhiring, nobody's really laying people off. These are the people that would probably be most quick to adopt AI to become more efficient or whatever. They're not really doing, jack aside, huge-scale layoffs, which probably tells you something about where they think there will be lots of opportunity to still have people plus.

32:55A hundred percent. Well, the bull case, you've seen charts from Cognition, Ramp, and Stripe, that the companies that are spending the most on AI are growing meaningfully faster. Yeah, I love that Cognition Index. Yeah, the Cognition Index is wild. All the skeptics will point out rightfully, it's not really controlling for industry. But then if you dig down into it, I think one of them gave an example of, I forget if it was a plumber or an HVAC contractor, but everybody who's a blue-collar worker is doing great because of AI. By the way, something that I think we should touch on, and we can do it now or later, is just everybody is citing these LTAs.

33:29So everything's at a shortage. If there's weakness, it's just because we can't energize the gigawatts fast enough. The gigawatts are going to get energized, like regulatory policies moving in a good way. The turbine manufacturers, the diesel jet manufacturers, you're ripping turbines off old airplanes and reconditioning them and then repurposing them. There's crazy things happening. Capitalism is very, very good at this. But I do think one of the most important questions of the market and like a transition of the market that I got wrong is we are shifting, particularly for memory more than anything else, from crushing numbers in the short term to their trading short-term upside for these, what they call supply chain agreements, long-term agreements, LTAs.

34:17There's many flavors, but customer prepays, there's a floor and a ceiling. And this comes back to the point about labor, because a lot of people after firing too many people during COVID were really reluctant to lay people off. They talked about labor hoarding, if you remember a few years ago. You remember this? Let's just think about the game theory of breaking an LTA. So there's four companies that matter at scale. There's Amazon with their tradiums, there's Google with their TPUs, there's AMD, and then there's NVIDIA, who's much bigger than everybody else combined. Let's just say it's 2027.

34:56And it's very important to realize memory is the more memory you put with flop for a given unit of compute, the more tokens you get out. It's the single most important thing you could do to increase token output per unit of compute. And then that obviously, definitially, actually lowers costs, which is why the demand hasn't responded at all negatively. There's been no elasticity just because it's the axis that is dominating all others. And this is, at some level, like a giant Game of Thrones or IMPERS between these companies. Okay, it's 2027 or 28. You're vaguely tempted to break one of these LTAs and try and get a lower price.

35:39But to a large degree, market shares, I think for the next several years, are going to be determined by supply chain allocations and kind of what you have pre-purchased. So if you break the LTA, this is assuming we're not in a severe oversupply situation. The game theory even holds in a severe oversupply situation. If you break your LTA and then in the next two or three years, for any reason, leverage shifts back to the memory, guys, you're out of business. It's over. Let's just say Google breaks an LTA. There's an oversupply. I'm making this up at 28, 29. They break their LTAs. Well, if they're breaking their LTAs, it probably means, you know, your oversupply prices are coming down and then, you know, capacity naturally contracts.

36:26Well, what do you think is going to happen to Google's allocations? And then, you know, this is a cyclical industry and oversupply is followed by undersupply. What do you think they think is going to happen to their allocations next time? So I just think given that this is the axis around which kind of everything is revolving, you might blow up your entire business and your franchise by breaking an LTA. And that was never the case before. Apple, who cares? They don't have a competitor. They're overwhelmingly the largest purchaser. This is, you know, going back three, four, five years. They know they can do whatever they want with no consequences because their volume is so big that even if they like super screw Hydex, Micron will, of course, take them.

37:08This is just different. You know, you have at least four players. Did you have all the startups? You're an investor and etched. If you break an LTA, they just say, OK, fine, great. You broke the price agreement. We're going to break the volume agreement. and screw you, we're going to give the volume to your competitor. You just lost share, you know? NVIDIA's dominance, the current environment, the stint to which it favors NVIDIA, it is a little hard for me to understand why it's trading at such a low multiple. In other words, if you need to be able to finance the chips, and you do, nothing's more financeable than an NVIDIA GPU.

37:45Nothing. If you need to get land and power, well, they're doing a very good job of playing that chess game and matchmaking. And then they've rolled out this really clever new business model, which I would describe as kind of like a credit wrapper with a revenue share if GPU prices are bubble floor. Yeah, yeah. Yeah. And this could lead to them having a really giant cloud business effectively through royalties really quickly. And it is another way of kind of alleviating this cash flow mismatch. Like, hey, we're making all the cash. this isn't really vendor financing because they're not loading them the money somebody else is loading the gpu buyer the money they're still making equity investments but it's not like you're just putting money into someone that some of that money was used to buy your chips even though nvidia said that they write into all their equity investments that the money can't be used to buy nvidia chips but obviously money is fungible and um funny thing makes no sense yeah but you know i I think at some level, it probably makes everybody feel better.

38:50What would you do if you were the member, like if you were the CEO of Hynix? I'd do the exact same thing NVIDIA is doing right now. Which is? I would be going to the buyers of GPUs, Tradiums, and whoever and say, I'll participate in the NVIDIA credit wrapper. Now, their business is just inherently less stable and predictable, but in some way, and maybe they just put up some cash up front. So it's like they're not on the hook. I'm just making this up. But do something like you can, because you have money now, and credit markets are revolting. I'm sure our friends at Blackstone and Apollo are suggesting some variant of this to the memory companies.

39:33But hey, we will put up some amount of money from our cash flow today. And then it's gone. It's surety that makes the person who's extending the debt feel better, but we want some sort of a cut of the ongoing revenues as well. That is 100 % what I would do. And it's almost like a logical extension of the LTAs where they're trading upside for durability. Here, you can effectively get a royalty on recurring revenues. And that is what NVIDIA is doing. And I do think that is very misunderstood. And I think it would serve NVIDIA well to really explain this. One, they're really bullish on AI. Essentially, every time they haven't taken an equity stake in something, it's been a mistake.

40:20They've taken equity stake in everything, essentially, except the memory companies, then for a long while, Anthropic, then they took an equity stake in Anthropic. But why not if you have cash flow and you're bullish on AI and Jensen because he sees every lab. He knows all the advances, you know, like all these continual learning labs, you know, safe super intelligence is now working with them. He sees everything and like what he sees makes him bullish. So one, have some equity upside and then two, have a revenue share and you're generating hundreds of billions of dollars of free cashflow and helping to kind of bridge what is clearly kind of a gap, at least given everybody's got free cashflow negative until the operating cash flow accelerates enough that you can internally fund this.

41:05It's very opportunistic in a good way, and it significantly increases their revenue per gigawatt. And then it also strengthens their competitive position. You and I, we both have startups, but okay, that's great. Use that startup's chip. What prices are they paying at Taiwan Semi? Higher than NVIDIA and all these guys. What prices are they paying for HBMDRAM? Higher. Can you finance those chips easily at the same rate as NVIDIA? No. And so it's always like there's a real burden, particularly if you use HBMD RAM, you're in the crosshairs of this. Unless like actually they made really different architectural choices.

41:45Everything that's happening is actually pretty good for him. By the way, going back to game theory, Anthropic, if they had been as aggressive on compute as OpenAI had been, they would have run away with it. Now OpenAI is back in the game. I think Grok is in the game. Those are the companies on the Pareto frontier. And they have the compute. Do you think after watching that, anyone is going to let off the gas? Right. It was, I think, four months ago that Dario was talking about how it was a really thoughtful commentary, but it's like, it's really, really hard because if you buy too much compute, you could go bankrupt at the scale of these things.

42:25But if you don't buy enough, you could lose. Well, OpenAI just got back into the game and now SpaceX is in the game in a big way with GROC 4.5 and Cursor. After watching that, from a game theory perspective, is anybody going to back off anytime soon, especially if it can be funded out of operating cash flow? Have you met anyone in your travels out here that you would say is 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. I read this thing that Dorkesh wrote and I was like - The 3X compute price thing or whatever?

43:00Yeah. Well, he was, I forget what it was. No, no, it was like 15X or something. Yeah, but no, but just basically that renting an H100 for a year would cost$250 ,000. And that's 15X the current spot or something. Exactly. Like, wow. That was just like - That wasn't in my book. That wasn't in my, forget my like Bayesian probability space of expected outcomes. That wasn't even in my considered but dismissed his totally unlikely outcomes. Dworkash, he's a very smart guy. He's very plugged in. Then he pointed out that margins on compute are going up. The amount of compute is going up and inference margins going up.

43:39And if you multiply those three, that's how you're getting this crazy acceleration in the sum of the labs plus open source, although the margins on open source are not really going up. I look at what's happening in the stock market and I feel like a foolish optimist. And then when I talk to people, whether it's people at the labs, anyone in this ecosystem, I'm like bearish relative to essentially everyone. Just a strange state of affairs. What do you make of the DUV news out of China where I've seen reactions really along a spectrum of like, this is the equivalent of like what ASML had in 2001 or something.

44:17Or like, no, this is actually the first bit of news in a new story for how we should think about the global supply of cutting edge compute. I think both could be true. Make an analogy. Like, let's just say a DUV machine was a jet turbine. And now an EUV machine is like a warp drive. DUV machines like a propeller plane, EUV is like a jet turbine. they didn't have it before and now they allegedly do and that is like a phase transition you've gone from like liquid to solid now that's solid that jet engine prop plane whatever is 25 years behind but still it's important and i don't think should be dismissed but i also you know it's kind of funny you just see this in the stock market the stock market massively overreacts and then And if this ever hits ASML's orders, maybe it hits it in five years.

45:11And like the market has forgotten about it, got worried about it, forgotten about it, got worried about it, forgotten about it multiple times along the way. So I do think that was probably an overreaction, but we shouldn't dismiss that either. And if you're China, like this is really important to you. You know, there are some reports that like an EV machine had been smuggled into China. And I mean, what a feat of espionage because those things are like giant and delicate. Yeah, they're huge. I don't know if that's true. You know, there's some noise about it. But, you know, China, they're really, really good.

45:45They're really, really smart. They work brutally hard. They see this as super important for them as a country. But are they going to go from the year 2001 to 2026 or even 2030? It's a learning by doing. and you can't accelerate the doing. You can't teleport into the future. You actually have to go through those learning cycles. Is it significant? Yes. Did the market overreact? Probably. It's very hard as an American to really understand what is happening in China and like have total conviction and clarity, you know, like for better or worse, we are decoupling. That is a process that has been set in motion.

46:28And at this point, And it almost feels like self-reinforcing on each side. That's unfortunate. We are where we are. They're not going to stop. Neither are we. Any commentary on like every other company in America? Like I feel like right now it is 10 companies, couple private. Not last month. Everything but AI was vertical. And I do think open source getting closer to the frontier and companies like Fireworks making it really easy to customize a model such that you can get in some cases better than Frontier Performance for a meaningfully lower cost. That is a godsend for the software industry. And it's also a godsend for all these AI natives.

47:10You know, it's like our friend Vishria, I think he said two years ago, I've never seen more companies go from being founded to like$50 million a year in revenue and generating cash flow in like whatever it is, nine months. And it's hard to know if any of them are durable because a lot of people would dismiss them as chat GPT wrappers. Well, now with open source, you've generated some data that's unique to your use case, whatever your vertical you're going after as a wrapper is. Fireworks did come out with a really cool product called Nexus. And if you're using Cloud Code, OpenAI Codex, GrokBuild, it is literally three lines of code, like 20 words.

47:51And Fireworks ingests your data. They can RL a model. And then there's a router that sends the query and they've had amazing results. And this is kind of the solution for every AI native. And that's why you saw Harvey before it was acquired. Cursor leads so heavily into this Harvey, Lagora, all of them. Because if you can go from just using one, two or three frontier models to using those frontier models for whatever it is, 30 to 60 % of your token consumption and then use your own RL model, all of a sudden you're not a rapper. You're way more defensible. I was so interested by that cursor thing that came out.

48:36I think it was cursor where it's sort of like AI is 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 and it's 15 times more efficient or whatever the metric was. And it may be, and this is like super ironic, lower margin open source tokens that are just a little bit behind the frontier. We have friends who believe that once a frontier model hits RSI, it will actually have a dramatically lower cost to serve at every level of intelligence by kind of distilling this. And then there's no place for open source.

49:13I would say that's like a anthropic, open AI, Grok, maximalist view. We shouldn't dismiss anything. Anything is possible. We want to be very humble. I particularly want to be humble after the month I've had. But that doesn't seem that likely to me. One, because there are so many of these AI natives that have actually generated a decent amount of domain-specific proprietary data. And before open source had this moment and these inference clouds and these routers really developed, you kind of didn't have a choice. Like whatever the terms of service were, you accepted them. But if you can now get off that treadmill, that gives you a degree of independence, maybe durability, safety.

50:04But going back to your point, it may be that these cheaper tokens massively inflate the value of the most cutting edge frontier tokens. Because if today, if you have, I'm going to make this up, 120 IQ open source models, and they're really cheap to run, doesn't that make a 160 IQ model that can orchestrate them more valuable? We talked last time about how I've been really surprised that so much of the economic returns have accrued to the frontier. That is changing with what we're seeing with these inference clouds. Together, modal, base 10, they're all working in a very cash-efficient way. What's shocking about those business models is they're growing almost as fast as the frontier labs in the early days, but burning very little cash.

50:54It's pretty extraordinary To go back to silly SaaS metrics, like the, you know, the rule of 40 perspective, like these are crazy numbers. Do you think there's a lot of instruction in just like the distribution of pay inside of an organization? Like the CEO makes X times more than the median person at a company, and maybe that's frontier tokens versus, you know, open source tokens. Absolutely, yeah. Something simple. Yeah, it may be that what we discussed last time where, you know, frontier tokens, like the pie is growing really, really fast. They may continue to capture the overwhelming majority of economic value, but not all of it the way they have been.

51:29And open source tokens might be the majority of tokens processed. Again, going back, that's great for infrastructure demand because a token is a token. And it takes the same amount of flops, watts, space, cooling to make. What's the worst thing that could happen in AI? Is it regulatory? I think regulatory has to be the biggest risk. It's the most obvious risk. And so that was kind of one reason I was excited to be here this week. I want to be scared. You know, I like, I don't want to feel like a lunatic watching these stocks get cheaper, thinking the expected forward returns are going up while it feels like the on-the-ground fundamentals have pretty materially improved in July relative to even June.

52:15But I still come away thinking like regulation, it just has to be the biggest risk. Like you just can't ignore New York making a data center moratorium. We're living in this weird post-factual, post-logical political world. And I mean, I think the AI industry, it has done a terrible job of PR. And I do think - It at least realizes that now. Yeah. Maybe if not fixed it, it realizes it. Yeah, but like the political narrative, I think amongst a lot of ordinary Americans is like data centers, they're going to raise your electricity prices. They're going to take all your water and then they're going to take your job.

52:52The reality is, given the deals that are being cut now, when a data center goes in, electricity prices actually generally go down for everyone around there because of behind the meter deals. This is that like data center pledge that Trump asked people to sign. And generally, the data center developer used to be they just had to get the police department or the fire departments like new trucks and new cars and new body armor or whatever. Now it's like, we're going to build you a hospital, a school, a new police station and a fire station, and we're going to lower your power bills. How does that sound?

53:25And by the way, the jobs are ongoing because it turns out that you kind of need these plumbers, electricians, HVAC contractors. Data centers are in a lot of ways the best thing to happen for blue-collar wages in my lifetime. And yet you have the Democrats who ostensibly represent the blue-collar workers taking those jobs away. It's just kind of wild how, what is the phrase, like a lie could go around the world. Faster than truth gets out of bed, yeah. Yeah, faster than truth gets out of bed. But an author made a mistake in a book. and overestimated the amount of water usage in data centers by 10 ,000x.

54:04Not a little bit. Like not one order of magnitude. Not two orders of magnitude. Not three. She's admitted that mistake many times. I was completely wrong. It's like been super debunked. It's like the Popeye effect. You ever hear that example? No. You know, Popeye eats spinach. The reason was same deal. In an academic book, they placed the decimal two things wrong. So spinach does not have more iron than everything else. It was just this one source. and then that propagated. People still say it has more iron. I literally had, I thought it had more iron. I mean, that's wild. That's like 80 years ago.

54:36That's wild. I literally thought spinach had more iron. That's amazing. It'd be crazy. Yeah, you learn something new every day. Yeah, same thing though. Yeah, it's the same thing. And it's just, so somebody just needs to tell the truth. I feel like the industry, geez, maybe if nobody else is going to do it, like I'll do it. There needs to be some sort of foundation. Maybe it's a pack that runs ads during the final four, during NFL games, during college football games. Here's the virtues. World Series. Here's what a data center does. Your power, a data center that signed this pledge in your community, your power prices are going to go down.

55:09They're almost certainly going to contribute to the community in a material way. You're going to see a massive influx of super high playing blue collar jobs that are going to persist. And I think a lot of people thought that they were one time and they're just not. Like there's for sure a spike and then that moves to the next data center. But there is an ongoing need for RMA and then upgrades at these data centers and technology is changing. So you're going to have more jobs. You're going to have cheaper power. You're going to have a wealthier community. There's going to be no impact on water, no impact on the environment.

55:43But it's easy to build the data center 10 miles out of town. That story needs to be told along with, we heard a story, I think we talked about it last time, about how AI is increasingly really saving lives, curing rare diseases. I think it was at ASCO this year, the vibe was like, this is the most scientific breakthroughs we've ever seen at a single conference. And for sure, some of that is due to AI. And so we need to tell those stories. Like, you know, if you have a sick child, sick parent, a sick loved one, like AI meaningfully increases the odds of them recovering. Everybody needs to tell this.

56:22And I think people out here, all of this is so blindingly obvious to them. They can't process that this is a true but wildly divergent view from most Americans. The industry really needs to tell its story better. New York, it just feels like it's the first of many. And even in some of these deep red states, they're super pro-growth. They're just like, hey, you guys are not doing a good job telling your story. We can't tell your story. If you tell your story, though, we can retell it, but you're the experts. If you do not speak your own truth, no one else will. What have we missed? I do think something that is missing from all of this conversation about compute is what is going to happen when you put these SRAM-based accelerators that are not constrained by HBMDRAM and are often made on older nodes that are not competing with the latest and greatest GPUs.

57:21When you disaggregate inference, people talk about pre-fill and decode, but decode is two parts, attention and feedforward network. And like the ultimate holy grail is if you could do pre-fill on one chip that probably doesn't have HBM DRAM, do the attention on a super high powered chip with HBM DRAM, and then do the feedforward network on one of these SRAM chips. but like the ROI on adding these SRAM accelerators to the existing installed base of compute and new compute. But like what we're seeing is you do better. You just can't beat SRAM in particular for that feed forward network. And no matter how much you try and get the ratio of compute to HBM DRAM to SRAM on the chip correct, the workloads are always changing and there's different workloads.

58:12being able to disaggregate into these three parts, this is going to be really, really positive for the ROI on AI. For some reason, I just thought of a funny question, which I love the framing of Game of Thrones versus all these people. Can you imagine a player that is not currently on everyone's mind becoming relevant at like the major Game of Thrones scale? Like that could be like Micron all of a sudden, someone that becomes as important as Anthropic, OpenAI, Microsoft, Amazon. So like a dark horse. Like Leap Boo is probably a dark horse. Yeah. Lynn at fireworks. She is an absolute killer. I think our friend Scott Wu.

58:51Cognition is kind of... You're here to that one. Yes. I think those are the most obvious names. What about SpaceX? What's it been like watching that be digested by public markets, at least initially? Do you think the market understands it as a company, the most important new company to be public? It doesn't really feel like it does. The fundamentals have gotten better since an IPO, like ROC 4.5, the cursor acquisition. Cursor has clearly accelerated meaningfully. They've shown over the last 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, their big advantage was they came into the market, hit those spot highs.

59:38And in a strange way, like one of the more bullish things for compute is they put a vast amount of compute into the market overnight. And it wasn't even really a blip. It was like the market just utterly absorbed it. The freight train didn't slow down at all. A substack writer will fund AI. They think that SpaceX is going to try and bring on eight gigawatts of compute over the next 18 months. So eight gigawatts over the next 18 months. I will never bet against Elon, but I mean, that would be a truly incredible feat. Rates have gone up since they signed those last contracts, not down. And they're monetizing at something like$50 billion a gig.

1:00:21And consensus estimates for next year are$73 billion. So forget Starlink V3. Forget Starlink Direct to Sell. Grok 4.5 and Cursor. I think that the sum of that probably hits a$10 billion ARR pretty quickly. Forget all of that. Forget the core base Starlink business. If they bring on anywhere near that, the consensus estimate is$73 billion. And that's eight gigs at$50 billion a gig. And obviously, that would not all be lit up at the beginning of 27. And it seems very implausible to me. Like, I almost don't believe the funder report. But to this day, the only companies that have brought on more than 500 megawatts of power in a year are the hyperscalers, CoreWeave, Crusoe, and SpaceX.

1:01:10And SpaceX has kind of brought on the most, the fastest, at the lowest cost. And then people do actually really like their clusters. But again, it's kind of like the market is going to need to see that. That would not be the market's interpretation of SpaceX today. No, no. Oh, and it does feel like, you know, there's this big New York hedge fund short case on it. And I think they think the spot price for compute is going to go down 90%. You're going to bring on all this compute. It's not going to generate, you know, nearly as much revenue as you think. Maybe, but I also want to be really clear.

1:01:42Like I've seen Elon's companies do really impressive things. The funder AI report of 8 gigawatts in 18 months. I mean, I'm just quoting that because it's public. It's available to everyone. I think one of Elon's phrases is we specialize in making the impossible late. I've never heard that. That's great. You know, there's kind of a lot of truth to that. Yeah, yeah. But I just think very little is built in from my perspective to that stock for the amount of compute that they might be able to bring on. And again, I don't think it's anywhere near eight. And it's going to be really hard. And energizing these GPUs is really hard.

1:02:22But they've been good at it. It doesn't feel like that's in estimates or really in people's thinking. I'm thinking about that funny meme that says SpaceX, the data center company. Oh, 100%. Yes, absolutely. And then I would also just say, like, I did spend a lot of time at Starbase. And orbital compute feels more real every day. Pretty cool to see that Starship landing the other day. That seems so smooth. Pretty cool to see the Starship landing. And it's, you know, it is funny. Our friends at Binchmark, they funded StarCloud. And I don't know, last time StarCloud is an orbital compute company that like SpaceX is kind of partnering with.

1:02:56They're going to, I think, let them use the Starlink laser technology, which is really important for orbital compute. But I do think that's like kind of a good sanity check. Last time I checked, the benchmark guys were pretty smart. And they're not coming from the Elon ecosystem at all. and they chose to fund an orbital compute company, a decent valuation, without the internal launch costs that SpaceX gets. To me, that's a good like, hey, am 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.

1:03:39Should we say whose offices we're in? Yeah, we're sitting in the Benchmark offices. Yes, this is their famous table for their famous dinners. So thank you, Benchmark. Thank you, Benchmark, for this episode. Yes, thanks, Eric. And Sheila, we should thank them all. Eric coordinated for me, so he gets a special shout out. Thank you, Eric. Thank you, all of the partners. Thank you, Eric. But I mean, we will see where all of these stocks are in a year. The great thing is, time will tell. People are going to be right or wrong. The future's probabilistic, but it's an exciting moment. Well, if we keep doing this on the model release cycle, I'll see you in a couple of weeks.

1:04:14Yeah, it's crazy. Maybe you're going to benchmark. That's always a blast to do with you. If you enjoyed this episode, visit Colossus.com. You'll find every episode of this podcast complete with hand edited transcripts. You can also subscribe to Colossus, our quarterly print, digital, and private audio publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at Colossus.com slash subscribe. Thank you.

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