Compute commitments must price in a one-year demand miss

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 46:52

   if you really believe that we're going to have a country of geniuses, you want as big a data center as you can get. There's no reason to slow down. The TAM of a Nobel Prize winner that is actually can do everything a Nobel Prize winner can do is like trillions of dollars. And so I'm trying to square this conservatism, which seems rational if you have more moderate timelines, with your stated views about AI progress. Yeah. So it actually all fits together.

2. 47:17

   And we go back to this fast, but not infinitely fast diffusion. So like, let's say that we're making progress at this rate. You know, the technology is making progress this fast. Again, I have, you know, very high conviction that like it's going, you know, we're going to get there within a few years. I have a hunch that we're going to get there within a year or two. So a little uncertainty on the technical side, but like, you know, pretty strong confidence that it won't be off by much.

3. 47:48

   What I'm less certain about is, again, the economic diffusion side. Like, I really do believe that we could have models that are a country of geniuses, a country of geniuses in a data center in one to two years. One question is, how many years after that do the trillions in revenue start rolling in? I don't think it's guaranteed that it's going to be immediate. You know, I think it could be one year.

4. 48:22

   It could be two years. I could even stretch it to five years, although I'm like, I'm skeptical of that. And so we have this uncertainty, which is even if the technology goes as fast as I suspect that it will, we don't know exactly how fast it's going to drive revenue. We know it's coming, but with the way you buy these data centers, If you're off by a couple of years, that can be ruinous. It is just like how I wrote, you know, in Machines of Loving Grace, I said, look, I think we might get this powerful AI, this country of geniuses in the data center.

5. 48:56

   That description you gave comes from the Machines of Loving Grace. I said, we'll get that 2026, maybe 2027. Again, that is my hunch. Wouldn't be surprised if I'm off by a year or two, but like that is my hunch. Let's say that happens. That's the starting gun. How long does it take to cure all the diseases, right? That's one of the ways that drives a huge amount of economic value, right? You cure every disease.

6. 49:20

   There's a question of how much of that goes to the pharmaceutical company, to the AI company, but there's an enormous consumer surplus because everyone – assuming we can get access for everyone, which I care about greatly. We cure all of these diseases. How long does it take? You have to do the biological discovery. You have to manufacture the new drug. You have to, you know, go through the regulatory process.

7. 49:42

   I mean, we saw this with like vaccines and COVID, right? Like there's just this, we got the vaccine out to everyone, but it took a year and a half, right? And so my question is, how long does it take to get the cure for everything, which AI is the genius that can in theory invent out to everyone? How long from when that AI first exists in the lab to when diseases have actually been cured for everyone, right?

8. 50:08

   And, you know, we've had a polio vaccine for 50 years. We're still trying to eradicate it in the most remote corners of Africa. And, you know, the Gates Foundation is trying as hard as they can. Others are trying as hard as they can. But, you know, that's difficult. Again, you know, I don't expect most of the economic diffusion to be as difficult as that, right? That's like the most difficult case.

9. 50:28

   But there's a real dilemma here. And where I've settled on it is it will be faster than anything we've seen in the world, but it still has its limits. And so then when we go to buying data centers, you know, again, the curve I'm looking at is, okay, we've had a 10x a year increase every year. So beginning of this year, we're looking at $10 billion in rate of annualized revenue at the beginning of the year.

10. 51:02

    We have to decide how much compute to buy. And, you know, it takes a year or two to actually build out the data centers, to reserve the data centers. So basically I'm saying like in 2027, how much compute do I get? Well, I could assume that the revenue will continue growing 10x a year. So it will be $100 billion at the end of 2026. and one trillion at the end of 2027. And so I could buy a trillion dollars.

11. 51:37

    Actually, it would be like $5 trillion of compute because it would be a trillion dollar a year for five years, right? I could buy a trillion dollars of compute that starts at the end of 2027. And if my revenue is not a trillion dollars, if it's even 800 billion, there's no force on earth. There's no hedge on earth that could stop me from going bankrupt if I buy that much compute. And so even though a part of my brain wonders if it's going to keep growing 10x, I can't buy a trillion dollars a year of compute in 2027.

12. 52:13

    If I'm just off by a year in that rate of growth or if the growth rate is 5x a year instead of 10x a year, then you go bankrupt. And so you end up in a world where, you know, you're supporting hundreds of billions, not trillions. And you accept some risk that there's so much demand that you can't support the revenue. And you accept still some risk that, you know, you got it wrong and it's still slow.

13. 52:43

    And so when I talked about behaving responsibly, what I meant actually was not the absolute amount. that that actually was not um you know i think it is true we're spending somewhat less than some of the other players it's actually the other things like have we been thoughtful about it or are we yoloing and saying oh we're going to do 100 billion dollars here 100 billion dollars there i kind of get the impression that you know some of the other companies have not written down the spreadsheet that they don't really understand the risks they're taking they're just kind of doing stuff because it sounds cool. And we've thought carefully about it, right? We're an enterprise business. Therefore, we can rely more on revenue. It's less fickle than consumer. We have better margins, which is the buffer between buying too much and buying too little. And so I think we

14. 53:31

    bought an amount that allows us to capture pretty strong upside worlds. It won't capture the full 10x a year. And things would have to go pretty badly for us to be in financial trouble. So I think we've thought carefully and we've made that balance. And that's what I mean when I say that we're being responsible. Okay. So it seems like it's possible that we actually just have different definitions of the country of a genius in a data center. Because when I think of actual human