Grant Harvey

They've got deals with AMD.

Yeah, like there's all of this stuff going on.

And NVIDIA is, from my understanding, a partner with you as well.

Is that correct?

Because my understanding is that NVIDIA's CUDA is kind of like the reason, like, yes, their chips are the best right now, but also CUDA is really what keeps people locked in to work.

I wonder, though, if it's not like, you know, because eventually you'll have to scale whatever the current architecture is in theory.

Or sorry, well, you'll have to scale whatever the architecture is that works if you're following the better the better lesson, which for people who forget what that is, is basically like if you have, you know, basically reinforcement learning scaled properly is like just all you need, essentially.

That's a very.

So five years from now, if modular succeeds at its mission, what do you think the AI infrastructure landscape looks like?

You know, with the caveat that we know that there's going to be this big kind of like shift where it's like either scaling works or we have to come up with something different.

So we've established that that's a paradigm.

True.

It could be unanswered, I guess, by then.

But what does modular look like in the future?

Do you think that it's easier to build on modular now than it would be on PyTorch if you're a total noob?

Welcome, humans, to the latest episode of the Neuron Podcast.

I'm Corey Knowles, joined as always by Grant Harvey.

And today we have David Hsu, CEO of Retool, a platform trusted by more than 10,000 companies to build internal software kind of like Lego blocks.

David, welcome to the Neuron.

Thanks, Corey.