The Information's TITV
00:03:54 · Paul Kedrosky, Akash Pasricha
[00:03:54] S1: It's not a small number. You know what? And just to really quickly, not to interrupt, but to put it in another kind of context, it's not just that those data centers are in states where something like 40% of the queue is potentially delayed, It's also the global scale of Texas alone as a data center hub with respect to construction. The way I map it out globally that... It goes like this. The US ex Texas, China, and then Texas, if it were a sovereign nation, which I'm sure would be delightful for it, if it were a sovereign nation, would actually be the third largest hub with respect to global data center manufacturing. So this is consequential, not just in terms of The US or regionally, on a global scale. And so this goes back to this this this point you're making that, you know, the the maths matter because the Texas, in in effect, is a global player with respect to the size of its data center market with per per construction. [00:04:43] S0: Do you think NVIDIA has anywhere else to look for growth in this world where maybe Texas, the data centers in Texas are not buying as much as they would have once had?
00:04:43 · Akash Pasricha, Paul Kedrosky
[00:04:43] S0: Do you think NVIDIA has anywhere else to look for growth in this world where maybe Texas, the data centers in Texas are not buying as much as they would have once had? [00:04:56] S1: No. Because the the permitting the permitting and build up process is so slow. This just becomes this this game of saying, I now have a new project, and it's... We have a spec for, you know, Louisiana or somewhere else. And the problem, of course, is... And we've seen this in the recent construction data, that the the queue itself is very... How shall I say, slippery? The data center construction queue. So whenever utilities ask for deposits, and these can be modest deposits, not on the order of $20, I'll grant you, but, you know, in in the order of low millions, suddenly the data center construction queue begins to shrink dramatically. A Northeastern utility found that acquiring deposits shrank it by almost 70%. And so the queue itself, it's very difficult to understand what's actually in it because it's so far out in terms of when actually things will get built. So yes, the answer is yes, you can play that game, and no, it doesn't matter. [00:05:42] S0: And nothing overseas, you think?
00:05:42 · Akash Pasricha, Paul Kedrosky
[00:05:42] S0: And nothing overseas, you think? [00:05:45] S1: Well, no, because again, think back to the size of Texas as a sovereign nation. Texas is sovereign to replace that. There is no place where you can replace that size of queue if you grant that something on the order of, you know, 25 or 30% of the projects within this so called sovereign nation of Texas in the data center sense is gonna see delays. So, no, it's not straightforward to see how you do that. And I mean... Obviously, this has all kinds of other consequences, which I've written about many other times. The data center is a de facto stimulus program in The United States. It was on the order of 25 to 40% of US GDP growth for umpteen quarters in a row now, is which one of the reasons why the prior... While the current administration embraced it so strongly that it was a de facto stimulus program that was in part bankrolled by the private sector and then steamrolled a lot of local interests in terms of the permitting and build out. So this has consequences in terms of the health of the economy writ large, not just, you know, Jensen Huang's bankroll.
00:05:45 · Paul Kedrosky, Akash Pasricha
[00:05:45] S1: Well, no, because again, think back to the size of Texas as a sovereign nation. Texas is sovereign to replace that. There is no place where you can replace that size of queue if you grant that something on the order of, you know, 25 or 30% of the projects within this so called sovereign nation of Texas in the data center sense is gonna see delays. So, no, it's not straightforward to see how you do that. And I mean... Obviously, this has all kinds of other consequences, which I've written about many other times. The data center is a de facto stimulus program in The United States. It was on the order of 25 to 40% of US GDP growth for umpteen quarters in a row now, is which one of the reasons why the prior... While the current administration embraced it so strongly that it was a de facto stimulus program that was in part bankrolled by the private sector and then steamrolled a lot of local interests in terms of the permitting and build out. So this has consequences in terms of the health of the economy writ large, not just, you know, Jensen Huang's bankroll. [00:06:37] S0: So let me ask you this. You know, the data center build out is one half of the story. The other half is businesses trying to find efficiencies from the AI tools that we have as of now. So, even if the models don't continue to get better, I mean, we have these models and there's probably still some pressure from shareholders to use them, do you think that that pressure decreases at all? Because even if the tools aren't getting more cutting edge, you still have the story of Oh, AI absolutely.
00:07:09 · Paul Kedrosky
[00:07:09] S1: Oh, of course. Listen, and this is the thing that people get wrong all the time, this whole idea that you can hold two contradictory ideas in your head at the same time. That the data center build out is on this precarious point doesn't mean that large language models don't work. That would make all of this much easier. Right? Because the problem is they actually work remarkably well even in their current incarnation. So as you say, without having to go to building out even more advanced models, corporations under huge pressure to not only find efficiencies, but more specifically, and you saw this with Revolut the other day, was to say, wait a minute. This is costing me a fortune, and I grant you it works, but I need to find a way to make it less costly. So which the big pressure you're going to see going forward is increasing on premises use of large language models, in terms of sovereignty of data and cost reduction, which is bad for cloud based large language models, frontier model companies, but tremendous in terms of the likely productivity consequences. And you saw that yesterday or the day before, I'm losing track, in the BLS data with respect to the latest productivity gains. And the only caution I'd make about that was that most of the productivity gains came from capital, not labor. So the returns are accruing to capital, not to labor, which is very, very dangerous moment in terms of where the gains are coming from AI. It's coming, it's just not accruing to labor.
00:08:20 · Akash Pasricha, Dan Shipper, Paul Kedrosky
[00:08:20] S0: So you put out this other note talking about how S and P five hundred's earnings growth ex MAG seven, [00:08:28] S2: the first [00:08:29] S0: time since 2022 outpaced the MAG seven. This, of course, keeps in mind that NVIDIA hasn't yet reported. Why do you think that is? What's the story here? [00:08:43] S1: Well, it's this... It's the intense cyclicality of of what... Of the build out that in the early years was relatively relatively straightforward to fund it all from cash flow. And so funding it from cash flow was was tremendous because I didn't have this overhang of debt obligations, which in turn was eating incrementally to my cash flows alongside of this what I was spending on data centers. So now I have an extra... I'm feeding an extra hungry animal, and the extra hungry animal is the... Is external financing of... Which is now something like 50 plus percent, 55% of the funding of data centers. So that's the problem. So increasingly, we have a lot of mouths to feed with respect to cash flows that are flowing out of these large and heretofore very profitable hyperscalers. And so that's beginning to cut into... And we're seeing this with negative cash flows almost across the board in the hyperscalers. And so it's really remarkable to see for the first time since the build out really began, that not only do many of them have negative cash flows, but for the first time, the rest of the S and P is outperforming them in terms of earnings growth.