Steve Hsu

Easy to do so after you've raised $40 billion at a $300 billion valuation.

Why not?

But I actually don't think DeepSeek has much to do with the Chinese government.

You know, maybe now things will change because they've become such an icon.

They're so iconic for the Chinese AI effort.

But everything they did up till now really has almost nothing to do with the Chinese government.

I think that that is how things are going to evolve.

And our company is, in a sense, a bet on that kind of thing.

Now, the previous logic that someone like Sam would have given you, say, a year ago or a year and a half ago was

we're just going to crush you because the next version of our big model is going to be so awesome.

All the tweaking and stuff that you did will just be eclipsed by the increase in capability of our big model.

And I think that hasn't really turned out to be the case.

And I think there will be a broad diversity of models of different sizes applied to different tasks in the economy.

I would say we're at an early stage for that.

I don't know of too many people that are, you know, maybe you're one of the outliers in terms of how much productivity gain you're getting from, you know, using LLMs in the way you described.

As a company, we're still in the situation where we have to basically exquisitely architect and test the system for the customer because you don't you never want the AI saying the wrong thing.

to someone who's called in, who's a loyal customer of the company, right?

So we're very worried about tail risk and mistakes that the model makes.

And so one of the things that I think the general public doesn't understand is like, how much rigorous statistical testing is required to know

what are the tail risks associated with this deployment of autonomy?