Chris Lattner

But now I figure out, okay, well, there's a lot of activation functions.

What about leaky value?

What about like a million things that are out there, right?

And so as I start fusing these in, now I get permutations of all these algorithms, right?

And so what the compiler people said is they said, hey, cool, well, I will go enumerate all the algorithms and I will enumerate all the pairs and I will actually generate a kernel for you, right?

And I think that this has been very, very useful for the industry.

This is one of the things that powers Google TPUs, PyTorch 2s, like rolling out really cool compiler stuff with Triton, other technology and things like this.

And so the compiler people are kind of coming into their fore and saying like, awesome, this is a compiler problem, we'll compiler it.

Here's the problem.

Not everybody's a compiler person.

I love compiler people, trust me, right?

But not everybody can or should be a compiler person.

Turns out that they're people that know analog computers really well, or they know some GPU internal architecture thing really well, or they know some crazy, sparse, numeric, interesting algorithm that is the cusp of research, but they're not compiler people.

And so one of the challenges with this new wave of technology trying to turn everything into a compiler

Because again, it has excluded a ton of people.

And so you look at what does Mojo do?

What does the modular stack do?

It brings programmability back into this world.

It enables, I wouldn't say normal people, but a different kind of delightful nerd that cares about numerics or cares about hardware or cares about things like this to be able to express that in the stack and extend the stack without having to

actually go hack the compiler itself.