Chris Lattner

We took like 18 steps forward in terms of all this really cool technology across compilers and systems and runtimes and heterogeneous computing, like all this kind of stuff.

And like all this technology has been

you know, I wouldn't say beautifully designed, but it's been proven in different quadrants.

Like, you know, you look at Google with TPUs, massive, huge exaflops of compute strapped together into machines that researchers are programming in Python in a notebook.

That's huge.

That's amazing.

That's incredible.

Right?

It's incredible.

And so you look at the technology that goes into that, and the algorithms are actually quite general.

And so lots of other hardware out there and lots of other teams out there don't have the sophistication or maybe the years working on it or the budget or whatever that Google does, right?

And so they should be getting access to the same algorithms, but they just don't have that, right?

And so what modular is doing is we're saying,

cool, this is not research anymore.

We've built auto-tuning in many systems.

We've built programming languages, right?

And so have implemented C++, have implemented Swift, have implemented many of these things.

And so it's hard, but it's not research.

And you look at accelerators.

Well, we know there's a bunch of different weird kind of accelerators, but they actually cluster together.