Satya Nadella on the AI Doomer Slowdown, Microsoft's Master Plan & Who Wins AI

SPEAKER_1 (0:01)

He has generated $250 billion with a B in market value from Microsoft.

David Sacks (0:05)

Satya Nadella, Chairman and CEO of Microsoft.

SPEAKER_3 (0:07)

Since you've been the CEO three and a half years, the stock is up about, I guess it's about 120 percent.

Satya Nadella (0:14)

I'm good for my 80 billion. I'm going to spend $80 billion building out Azure. Maybe after the Industrial Revolution, this is the biggest thing. That's our goal with our front-year model. Our model should be the best model that they can use as a base. We create technology so that others can create more technology. That's who we are. We are tool maker.

Chamath Palihapitiya (0:35)

Please welcome Satya Nadella. All right.

My guy.

Satya Nadella (0:43)

Good to see you. Thank you for coming out. Good morning, guys.

Jason Calacanis (0:52)

How are you?

Satya Nadella (0:53)

Good.

Jason Calacanis (0:54)

Thanks for joining us.

Satya Nadella (0:55)

Crazy weekend, but here we are.

Jason Calacanis (0:57)

Do we need to pace the frontier?

Satya Nadella (1:03)

So let's start with the common sense part first, which is we should do what it takes to build stuff that serves humanity first, and is in human control. It's kind of crazy that we have to start with that level of common sense but I think it's a good place.

Then when I think about pacing whatever, the first thing that at least I believe is the broad diffusion of this technology is the most critical thing, because the benefits of this tech showing up everywhere is really what's all about. So at the end of the day, if you say serving humanity, let it actually reach humanity in ways that it serves humanity, and that means you got to have choice, you have to have competition, you have to have all kinds of business models, whether they're open-weights, close-weights, what have you.

Then the other aspect I think that is not talked about when we talk about control, is actually the control that, for example, customers have, enterprises or businesses have around this technology, because sometimes this is so opaque, right? I want my privacy. I want to be able to embed my knowledge in a set of weights I control. I want to see all of the COT that's being generated. I want to use it to do fine-tuning of my own models. My IP shouldn't leak. So there's an entire body of things that nobody's talking about as much, which is, I really want to make sure that this tech is in my control. Then we get to, what is, I think, a real issue of safety and we should take it seriously, which is we should take all the time we want to test things. In fact, I love this idea of having third-party testers. Oh, wow. I grew up in a company that's always done testing. So it's novel that we should say, wow, they're having embedded third-party testers. Why not? It's a great idea. In fact, the only thing I would say is, we should avoid these cozy arrangements of who's testing what, who has access to what, and it should be broad.

David Sacks (3:17)

Were you surprised though then when both the essay landed, and then it seemed like there was a circling of the wagons amongst the frontier companies?

Satya Nadella (3:27)

I think that it comes, my suspicion is it comes genuinely from this place where, when you start seeing, in fact, it's fascinating. We are, when you start saying reward hacking, and what's happening in these environments, with these agents swarms, there is the mundane, there is some DevOps error where somebody misconfigured a container.

David Sacks (3:51)

Right. Or these API keys.

Satya Nadella (3:52)

Or an API keys, or yeah, exactly. There's no monitoring, there's Internet access, there's sort of classic, I'll call it basic DevOps. And then there is real novel new stuff, right? Which is what is this reward hacking, with these persistent agents and so on. And that's a place where I'll admit that the science is not there. It's, I thought, Jakob's post, which is a good one, which he said he called it, we're growing intelligence, not building intelligence. So it's an experimental science.

And so the more experimental a science is, then you really need to make sure you're doing those experiments in controlled environments. If anything, the place where I would love is taking even the hugging face incident in other places, more transparency on what would it take. In fact, one of the fascinating things right now is the insider risk. I mean, think about it, right? If you're sitting in an enterprise, this is all test time compute, by the way, right? So it's not like, oh, it's going to only happen when in some training run. It can happen for a very mundane task that I give one of these frontier models inside an enterprise, where I say, I was telling David this. Suppose I say, hey, go optimize my working capital. It may fake my books, because this is like a new type of insider risk.