Satya Nadella: prediction

Transcript context

…That's true. So, if you really think there's some potential here to 10x or 5x the growth rate of the world, and then you're like, "Well, what is the revenue from GPT-4?" If you really think that's the possibility from the next level up, shouldn't you just, "Let's go crazy, let's do the hundreds of billions of dollars of compute?" I mean, there's some chance, right? Here’s the interesting thing, right? That's why even that balanced approach to the fleet, at least, is very important to me. It's not about building compute. It's about building compute that can actually help me not only train the next big model but also serve the next big model. Until you do those two things, you're not going to be able to really be in a position to take advantage of even your investment. So, that's kind of where it's not a race to just building a model, it's a race to creating a commodity that is getting used in the world to drive… You have to have a complete thought, not just one thing that you’re thinking about. And by the way, one of the things is that there will be overbuild. To your point about what happened in the dotcom era, the memo has gone out that, hey, you know, you need more energy, and you need more compute. Thank God for it. So, everybody's going to race. In fact, it's not just companies deploying, countries are going to deploy capital, and there will be clearly... I'm so excited to be a leaser, because, by the way; I build a lot, I lease a lot. I am thrilled that I'm going to be leasing a lot of capacity in '27, '28 because I look at the builds, and I'm saying, "This is fantastic. " The only thing that's going to happen with all the compute builds is the prices are going to come down. Speaking of prices coming down, you recently tweeted after the DeepSeek model came out about Jevons’ Paradox. I'm curious if you can flesh that out. Jevons’ Paradox occurs when the demand for something is highly elastic. Is intelligence that bottlenecked on prices going down? Because when I think about, at least my use cases as a consumer, intelligence is already so cheap. It's like two cents per million tokens. Do I really need it to go down to 0.02 cents? I'm just really bottlenecked on it becoming smarter. If you need to charge me 100x, do a 100x bigger training run. I'm happy for companies to take that. But maybe you're seeing something different on the enterprise side or something. What is the key use case of intelligence that really requires it to get to 0.002 cents per million tokens?…

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