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

Saks.

So I think, I think that's a great point.

I, I love how you, uh, differentiated in the Hugging Face, uh, episode between the mundane things they got wrong, like the misconfigured sandbox and the Hugging Face hack credentials just sitting in a public re- repository, and there's no monitoring, and then you have the genuinely novel behavior, the swarms of agents, the reward hacking.

That's the stuff that has everyone freaked out.

I agree that, you know, we have to now figure out how to fix the bugs or, you know, fix the deeper problem that's coming from that reward hacking.

What, what do you think that means for...

And, and, and, and, and I think to their credit, I think what the frontier labs are saying is we are now gonna slow down the pace of, let's say, raw power and shift towards reliability and predictability and, you know, what they call alignment, which I think is good business practice.

I guess, what do you think that means for what we see in terms of new products for the next year or two? Does it mean we just kind of improve what we already have, or do we see new capabilities? What do you think this is gonna mean for the future?

Yeah, it's a great question, David, because I, I do think there's already a massive model overhang, right?

Mm-hmm.

I mean, um, capability overhang in the sense of the models are very good, except the broad diffusion-

Mm-hmm

... uh, requires a lot of things, right? It even requires, uh, essentially, if you're compressing workflows and changing workflows to happen differently, uh, the amount of change management that needs to happen in order to even incorporate these systems is sort of what's taking time.

So to some degree, I would say the...

A- and also, uh, the, the ability to create these new form factors, right? I mean, if you think about coding agents, and coding agents became really usable, and you discovered that you could have an agent loop with a file system.

Uh, and that was the breakthrough that just made coding agents work.

Um, and I think now maybe with Kua, right? So which is with Astra, with Kua, uh, could be a way for us to even do computer use or just use, uh, long trajectory tasks that can get completely automated.

So I think these type of product innovations where the model plus the harness Allow us to do things that then lead to broad adoption, right? I, I even go back to the ChatGPT moment for me, right? Which was it was that RLHF at the very end that made a chat conversation possible.

Mm-hmm.

Uh, and so I think that, yes, so there's some science, there is some form factor that then leads to broad diffusion, and we now need to find the next level of these things that are doing real work in the real enterprise.

Um, and in that context, by the way, the other thing is it's going to be a multi-model world, right? So at this point, just out of resilience, right? I mean, think about, right, every enterprise now comes to me and says, "Hey, this model does refusals here.

This model I want weights here.

I don't..." And so the people are going to want multiple models.

So one of the other things that we have to get right is some standards of interop, right? Like even KV cache, like why the heck can't I use multiple model families and have-

Yeah