Chris Lattner

Yeah.

Yeah.

So again, go back to like the simplest example of int, right?

And so what both Swift and Mojo and other things like this did is we said, okay, pull magic out of the compiler and put it in the standard library.

Right.

And so what modular is doing with the engine that we're providing and like this, this very deep technology stack, right.

Which goes into heterogeneous runtimes and like a whole bunch of really cool, really cool things.

This, this whole stack allows that stack to be extended and hacked and changed by researchers and by hardware innovators and by people who know things that we don't know.

Cause you know, modular has some smart people, but we don't have all the smart people.

It turns out.

Yeah, so what is heterogeneous, right?

So heterogeneous just means many different kinds of things together.

And so the simplest example you might come up with is a CPU and a GPU.

And so it's a simple heterogeneous computer to say, I will run my data loading and preprocessing and other algorithms on the CPU.

And then once I get it into the right shape, I shove it into the GPU.

I do a lot of matrix multiplications and convolutions and things like this.

And then I get it back out and I...

do some reductions and summaries, and they shove it across the network to another machine.

And so you've got now what are effectively two computers, a CPU and a GPU, talking to each other, working together in a heterogeneous system.

But that was 10 years ago.