Chris Lattner

Why can't I deploy it?

And if you dig into this,

Every layer is problematic.

So if you look at the language piece, I mean, this is tip of the iceberg.

It's a very exciting tip of the iceberg for folks, but you've got Python on one side and C++ on the other side.

Python doesn't really deploy.

I mean, it can theoretically, technically in some cases, but often a lot of production teams will want to get things out of Python because they get better performance and control and whatever else.

So Mojo can help with that.

If you look at serving, so you talk about gigantic models.

Well, a gigantic model won't fit on one machine, right?

And so now you have this model, it's written in Python, it has to be rerun in C++.

Now it also has to be carved up so that half of it runs on one machine, half of it runs on another machine.

or maybe it runs on 10 machines.

Well, so now suddenly the complexity is exploding, right?

And the reason for this is that if you look into TensorFlow, PyTorch, these systems, they weren't really designed for this world, right?

They were designed for, you know, back in the day when we were

starting and doing things where it was a different, much simpler world.

Like you want to run resonant 50 or some ancient model architecture like this.

It was just a, it was a completely different world than train on one GPU.

Exactly.