Chris Lattner

It's a better experience that helps lift TensorFlow and PyTorch and make them even better.

I love Python.

I love TensorFlow.

I love PyTorch, right?

This is about making the world better because we need AI to go further.

Oh, so I mean, again, it depends.

So if you care about performance, then writing in Mojo is going to be way better than writing in Python.

But if you look at LLM companies, for example, if you look at OpenAI, rumored, and you look at many of the other folks that are working on many of these LLMs and other innovative machine learning models, on the one hand, they're innovating in the data collection and the model, billions of parameters and the model architecture and the...

RLEHF, and all the cool things that people are talking about.

But on the other hand, they're spending a lot of time writing cuda curls.

Right?

And so you say, wait a second, how much faster could all this progress go if they were not having to handwrite all these...

And so there are a few technologies that are out there, and people have been working on this problem for a while, and they're trying to solve subsets of the problem, again, kind of fragmenting the space.

And so what Mojo provides for these kinds of companies is the ability to say, cool, I can have a unifying theory.

Right, and again, the better together, the unifying theory, the two-world problem, or the three-world problem, or the n-world problem, this is the thing that is slowing people down.

And so as we help solve this problem, I think it'll be very helpful for making this whole cycle go faster.

You're saying this is an irrational set of life choices I make?

Yeah, well, so, okay.

I mean, I think there's a couple of different things.

So actually, I left Apple back in 2017, like January 2017.