Terence Tao

I hope next one.

It won't happen this IMO.

The performance is not good enough in the time period.

But there are smaller competitions.

There are competitions where the answer is a number rather than a long-form proof.

And AI is actually a lot better at problems where there's a specific numerical answer.

Because it's easy to reinforce learning on it.

Yeah, you got the right answer, you got the wrong answer.

It's a very clear signal.

But a long-form proof either has to be formal, and then the lean can give it thumbs up, thumbs down.

or it's informal, but then you need a human to grade it.

And if you're trying to do billions of reinforcement learning runs, you can't hire enough humans to grade those.

I mean, it's already hard enough for the last language learners to do reinforcement learning on just the regular text that people get.

But now if you hire people and not just give thumbs up, thumbs down, but actually check the output mathematically, yeah, that's too expensive.

That's a good question.

I think the nature of what mathematicians do over time has changed a lot.

You know, so a thousand years ago, mathematicians had to compute the date of Easter, and those really complicated calculations, you know, but it's all automated, been automated for centuries.

We don't need that anymore.

They used to do spherical trigonometry to navigate how to get from the old world to the new.

Very complicated calculations.