Terence Tao

I mean, Erdos posed the problem once or twice.

I think maybe some people tried it casually and they couldn't do it, but they never wrote up anything.

But it turned out that there was a solution and it was just maybe combining this one obscure technique that not many people know about with some other result in the literature.

And that's the median level of what AI can accomplish.

And that's really great.

It clears out 50 of these problems.

So I think you'll see some isolated successes.

But what we found, so people have done large-scale sweeps of these early problems.

If you only focus on the success stories, the ones that get broadcast on social media, it looks amazing.

All these problems that haven't been solved before for decades, now they're falling.

But whenever we do a systematic study, any given problem, an AI tool has a success rate of maybe 1% or 2%.

It's just that they can buy a scale.

And if you just pick the winners, it looks great.

So I think it'll be a similar thing happening with, you know, there are hundreds of really prestigious, difficult math problems out there.

A couple may make, you know, somebody may get lucky and solve them.

And there was there was some

some backdoor to solve the problem that everyone else missed.

And that will get a lot of publicity.

But then people will try these fancy tools on their own favorite problem, and they will again experience the 1% to 2% success rate.

So there will be a lot of noise amongst the signal of sort of when they're working, when they're not.