Mark Zuckerberg

It's also how we've done a lot of our infrastructure.

We took our whole data center design and our server design and we built this open compute project where we just made that public.

Part of the theory was like, all right, if we make it so that more people can use the server design, then that'll enable more innovation.

It'll also make the server design more efficient and that'll make our business more efficient too.

So that's worked and we've just done this with a lot of our infrastructure.

We shared it with researchers.

No, I think it's been really neat to see.

I mean, there's been folks who are getting it to run on local devices, right?

So if you're an individual who just wants to experiment with this at home,

you probably don't have a large budget to get access to like a large amount of cloud compute.

So getting it to run on your local laptop, um, you know, is, is, uh, is pretty good, right.

And pretty relevant.

Um, and then there were things like, yeah, Lama CPP, um, re-implemented it more efficiently.

So, you know, now even when we run our own versions of it, um, we can do it on way less compute and it just way more efficient, save a lot of money, um, for everyone who uses this.

So that, that is, is, is good.

Um,

I do think it's worth calling out that because this was a relatively early release, Lama isn't quite as on the frontier as, for example, the biggest OpenAI models or the biggest Google models, right?

I mean, you mentioned that the largest Lama model that we released had 65 billion parameters.

And no one knows...

I guess outside of open AI, exactly what the specs are for GPT-4.