Kwasi Ankomah

And I'm sure there won't be a model that does exactly that.

But as we go on, you'll start to see these models narrowed down so that there'll be a day when you go onto Hugging Face and you'll be like, oh, I need this one.

Cool.

You know, and that is super, super powerful because that, again, will allow people to just be like, hey, I can use this model and it works for my use case as well as anything else.

There's a few things people should be looking out for.

I think they should be looking out for almost like the...

what we talked about, the kind of training inference, right?

So like people are like, we're now optimizing for inference.

And I think the companies who are largely going to be able to figure that out will be able to kind of own that next generation of AI applications.

Like we, of course, we think, you know, training is still going to have a big part, but we also see this new kind of resolved interest as AI grows and more and more people just run inference, right?

You know, you have companies that were not

that didn't deploy any AI applications in 2024, who have now started to deploy AI applications.

And if that keeps happening as it is, that market's going to grow even further.

Right.

And then the next is kind of like the agents as infrastructure, right?

Like, you know, this is something that I think about a lot.

Like how...

it's not just like AI systems, right?

AI systems are useful and they're going to be wrong, but I'm talking about something that's actually going to go, like, something that's as scalable as a database and a web server, you know, as an agent.

Like, and that is going to be, again, people who figure that out, that's a big one, so I spend a lot of my time thinking about that.