Yeah

...

I think we're gonna see more and more of that, uh, of that happening.

And, um, yeah, so, so we're, um, bringing up quite a bit of, uh, GPU capacity, and it's been important both for research and also to power the API.

So as more people are starting to tune their own models, it's ve- becoming very, very popular now.

A lot of companies are reaching out about, um, wanting to build their own custom models that they own and trying to train on their own data, uh, using their own evals.

Um, so demand is gonna keep going up, we expect.

Mm-hmm

Uh, and so maybe to start, I'm, I'm curious, what inspired you to, to write these?

Yeah.

I, I, I think there's, um, you know, something pretty big that happened to all of us software engineers, AI researchers around November, December of last year, which is that the coding agents suddenly became, uh, so powerful that you can't ignore them.

You know, pre-previously you could...

You know, some people used them, some people, uh, uh, didn't use them, um, but from that point onwards, uh, you know, that, that latest iteration of, um, Claude Opus models, uh, suddenly everybody agreed that, yes, these models are very powerful.

Yes, they, they make our jobs much, much easier, and also while they're doing so much of the software engineering, um, now that we used to do, that we used to, used to enjoy.

So it was a real transformation for all of us, and like, like many, like many folks, um, I spent, uh, a large part of December, uh, rewriting all of the coding projects that I've ever, you know, um, uh, wanted to do [laughs] in, in my life or, or have done, um, us-using the coding agents.

Well, maybe an interesting, uh, time to just talk about your vision for, like, the River AI as a company, the product, um, and you know what-- how you hope to kind of achieve that.