Sam Altman

It's a system that we'll look back at and say was a very early AI.

And it's slow, it's buggy, it doesn't do a lot of things very well, but neither did the very earliest computers.

And they still pointed a path to something that was going to be really important in our lives, even though it took a few decades to evolve.

That is a good question.

I sort of think of progress as this continual exponential thing.

It's not like we could say here was the moment where AI went from not happening to happening.

And I'd have a very hard time pinpointing a single thing.

I think it's this very continual curve.

Will the history books write about GPT-1 or 2 or 3 or 4 or 7?

That's for them to decide.

I don't really know.

I think...

If I had to pick some moment from what we've seen so far, I'd sort of pick ChatGPT.

You know, it wasn't the underlying model that mattered.

It was the usability of it, both the RLHF and the interface to it.

So we train these models on a lot of text data.

And in that process, they learn the underlying something about the underlying representations of what's in here.

are in there and they can do amazing things but when you first play with that base model that we call it after you finish training it can do very well on evals it can pass tests it can do a lot of you know there's knowledge in there but it's not very useful

or at least it's not easy to use, let's say.

And RLHF is how we take some human feedback.