This episode is presented by Invest Puerto Rico.

If you believe your business can go anywhere, Puerto Rico is the place. Hello and welcome back to Equity, TechCrunch's flagship podcast about the business of startups.

I'm Max Zeph, and today we're zeroing in on Deepseek, the Chinese AI lab that's been going absolutely

viral this week. To talk about it all, I'm joined by Jan Stoica, a professor of computer science at

UC Berkeley, and also the co-founder and executive chairman of Databricks, as well as any scale. He's very active in the AI policy world, and he's perfect

to break all this down for us. Jan, welcome to the show. Thanks for having me, Max. Of course. So I think

right off the bat, I'd love to kind of just quickly separate, you know, facts from hype here.

And could you kind of break down for us? What to you are the real breakthroughs that Deep Seek has

achieved with its recent models? And what is overhyped and has gotten too much play?

Yeah. So I think I will start with three things, which are pretty factual.

So first, obviously, is performing very well on the benchmarks.

Not only that, but also on our own chatbot arena, which, as you probably know,

it's a very popular in the wild, large language model evaluation platform.

And where it's now in number three,

at least the last time I checked.

So clearly, it's matches or provide roughly similar performance

as the top live language models, proprietary models.

The number two, what we know, because the model is released,

we know that serving queries on deep sync R1 and V3 is very efficient.

And obviously the number three is open source.

So I think that's what definitely in my mind, behind the hype, it's changing a little bit the trajectory of evolution of these models in the sense that it's accelerated.

Now, in terms of fundamentally, deep seek is not a new architecture.

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