Decoder with Nilay Patel
00:37:26 · Joey Brookhart, Nilay Patel
[00:37:26] S4: Yeah. Look, Elon is is... Obviously has some incentive to say Neo Clouds are going to be extinct. You know, there's a lot of... And cluster max, someone else just does amazing ratings of the Neo Clouds, there's a lot of like Neo Clouds that are like ex crypto miners that are not good businesses and are not good at operating. And to [00:37:43] S2: point out, CoreWeave is an ex crypto mining company, right? [00:37:46] S4: Yeah, and I don't mean CoreWeave, but there's others further down the list. I think CoreWeave, Nebius, anyone that has backing or backstops from one of the major labs, hyperscalers or Nvidia or Broadcom, is going to be okay. It's that longer tail. Think hyperscalers have been 65% of CapEx and net new compute brought online, so then there's 35% of the market that's non, doesn't have the balance sheets the hyperscalers have. Both Google and Meta have recently raised or announced they're going to raise. When we look at the big four hyperscalers, don't actually need to raise that money over the next two years, even though CapEx is growing from one point two to two trillion pretty quickly. But a lot of these other neo clouds, if you don't have that sort of backing, I think it gets it is very hard, even right now, and becoming extremely difficult if you don't have the backing or backstops from those players to keep building compute. It's a very, very tough financing market.
00:38:42 · Nilay Patel
[00:38:42] S2: One of the things I think is really interesting about Elon in particular talking about Neo Cloud's dying and obviously hyping up his own data center business is he's trying to put them in space and to get away from the backlash in United States around data centers in particular. We have a lot of coverage about data center backlash in United States, it is slowing down a lot of projects. But at the rate we're going, if you think the Neo Clouds are shaky, you might actually end up abandoning a bunch of GPUs and half built data centers or have them tied up in financing agreements where they can't be lit up. What do you make of that? Do you think we actually just need to go to space or do you think that market is going to rationalize and actually take advantage of all the compute that is currently allocated but not being used?
00:39:23 · Joey Brookhart, Nilay Patel
[00:39:23] S4: The market's very good at finding places to put ships. Mhmm. Here, you know, on on the ground, I should say. There will be, you know, politically, you know, we'll see what happens next week with midterms, and kind of the fallout from that. And and obviously, there's some very large sites, you know, still that have massive permitting problems. And then there's there's the entire power equation as we look towards next year. The data centers will will will... They'll be built. There will be a method to get these built. I think the biggest thing, and like the hyperscale CFOs have said this, from like an overbuilt perspective, know, it's on a relative basis, it's pretty cheap to build the data center shell. What they can do if they overbuild is they're going say, okay, we're just not going to take delivery, we're not going [00:40:03] S2: to buy chips, we're not going
00:40:03 · Nilay Patel, Joey Brookhart
[00:40:03] S2: to buy chips, we're not going [00:40:04] S4: to fill them up in these, you know, they'll just sit empty and chipless. But that's where a lot of the, you know, that's the majority of the spend is on the chip side. So if we do end up in a place where we're actually oversupply from a data center perspective, I know that's a little bit different, it's the exact opposite of what the question was, they kind of had said that from like an ROI perspective. I think this comes back to that larger question, are we still going to be super supply constrained? A lot of people now, especially in the last three weeks, are talking about are we in this massive glut of compute as we look towards 2028 actually? Because the same thing we talked about from Anthropic going from negative 94% margins to positive 85% in kind of compute efficiencies means as you bring on more inference megawatts that are making a lot more revenue per megawatt, all else equal, you need less compute. So it's a question of, you know, are we going to have enough revenue in 2028 to justify the ROI, you know, on 2,000,000,000,000 plus of CapEx?
00:40:57 · Nilay Patel, Joey Brookhart
[00:40:57] S2: This is why I spent so much time asking about capability overhang and how good the models are today because you can see some competitor that is less idealistic about AGI saying actually we're going to do a bunch of forward deployed engineers in all of these verticals where they haven't taken advantage of AI and sell them high margin inference because we'll automate big chunks of their business and they'll see the return. And right now a bunch of the Fortune 500 has not seen return on AI spending. So if you're actually just better at customer service and deployment and productizing the model, you might get way ahead of where Anthropic needs to be because they're still thinking about AGI every single minute of every single day. And I don't know man, I look at Dario standing next to Marc Benioff at Dreamforce and like that dude does not want to be there right now. Right, he wants to be thinking about like the machine God. There's something there where you can just see that competitors coming up with an open source model and be like we're actually going to productize this and we will actually take the revenue that everyone else is depending on. [00:41:58] S4: And too, like in the interim, that's why it is getting, you know, more verticalized because you need something to bridge, you know, an AGI where it just does fully does the job. You need something to bridge, you know, the actual model today. [00:42:09] S2: We'll just take that for granted. Yeah. Yeah.
00:42:12 · Joey Brookhart
[00:42:12] S4: To get there, you need some bridges of where it actually sits in with the actual end user at some point. And so I think everything is going to come down to this, is there going to be some timing or adoption mismatch where we just don't get the revenue at a certain point in time to justify that chase of training compute towards AGI? And I think that's a risk. The other risk I think we look at is do we get more models at the frontier, even at the open source, that are as competitive in coding, where token pricing across the frontier needs to be taken down because, you know, like I mentioned earlier, like, you know, lower switching costs. Even at SemiAnalysis, we went from, you know, 95%, 90% plus of our usage at the end of Q2 was on Anthropic models after release of 5.6 and Astra, that went down to 70%, and then with Opus 5.5 it's gone back to 90% plus, you know, roughly. So it does come back even like the base of revenue today, and they've said, know, that we have net revenue retention of 900% seeing this massive, massive growth. This isn't a traditional software business like ServiceNow or Workday where you have like just incredible like logo or gross, you know, retention of 95%, 98%. Customers sign these nice three year contracts, they never churn, they add some seats, maybe they adopt another product that is being upsold. This is purely consumption. Think the other portion was the 20% drop in the last two weeks of the year versus the prior two weeks you know, last year, in token or, you know, in token spend because the holiday season. You know, people aren't, you know, you're not going to do work code stuff. You're not going to be coding for work during the holidays. So this consumption business, mean, is extremely, extremely pure consumption business, different than how we think about like Snowflake or Datadog today in public markets.