Sam Altman

And there's, you know, different ways to accomplish that.

You can bump up the clock speed.

Sometimes that causes other problems.

Sometimes it's not the best way to get gains.

Um,

But I think what matters is getting the best performance.

And, you know, we, I think one thing that works well about OpenAI is we're pretty truth-seeking in just doing whatever is going to make the best performance, whether or not it's the most elegant solution.

So I think like,

LLMs are a sort of hated result in parts of the field.

Everybody wanted to come up with a more elegant way to get to generalized intelligence.

And we have been willing to just keep doing what works and looks like it'll keep working.

I think it's part of the way.

I think we need other super important things.

But I wouldn't say any of this stuff with certainty, like we're deep into the unknown here.

For me, a system that cannot go significantly add to the sum total of scientific knowledge we have access to, kind of discover, invent, whatever you want to call it, new fundamental science, is not a superintelligence.

And

To do that really well, I think we will need to expand on the GPT paradigm in pretty important ways that we're still missing ideas for.

Look, if an oracle told me far from the future that GPT-10 turned out to be a true AGI somehow, maybe just some very small new ideas, I would be like, okay, I can believe that.

Not what I would have expected sitting here and would have said a new big idea, but I can believe that.

The thing that I am so excited about with this is not that it's a system that kind of goes off and does its own thing, but that it's this tool that humans are using in this feedback loop.