Satya Nadella

One is the hyperscalers do well, right?

Because the fundamental thing is, if you sort of go back to even how Sam and others describe it, I mean, like if, you know, intelligence is log of compute,

whoever can do lots of compute is a big winner.

And the other interesting thing is if you look at underneath even any AI workload, like take ChatGPT, it's not like everybody's excited about what's happening on the GPU side.

It's great, but it's like the ratio, like in fact, I think of my fleet even as a ratio of the AI accelerator storage to compute.

And at scale, you've got to grow it.

And so that infrastructure need for the world is just going to be

exponentially growing, right?

So in fact, it's mana from heaven to have these AI workloads because guess what?

They're more hungry for more compute, right?

Not just for training, but we now know for test time.

And as I said, test time, like here's an interesting thing.

When you think of an AI agent, it turns out the AI agents is going to exponentially increase compute usage because you now are not even bound by just one human invoking a program.

It's

But one human invoking programs that invoke lots more programs.

And so that's going to create massive, massive demand and scale for compute infrastructure.

So our hyperscale business, Azure business, I think that's like, and other hyperscalers, I think that's a big thing.

Then after that, it becomes a little fuzzy because you could sort of say, hey, there is a winner-take-all model.

I just don't see it, because this, by the way, is the other thing I've learned, is being very good at understanding what are winner-take-all markets and what are not winner-take-all markets is, in some sense, everything.

Like, I remember even in the early days when I was getting into Azure, I mean, Amazon had a very significant lead, and people would come to me, and investors would come to me and say, oh, it's game over, you'll never make it, Amazon's, it's winner-take-all.