Terence Tao

This is a great question.

We don't have the data to fully answer it yet.

Certainly, a lot of work that human mathematicians do, when you take a new problem, one of the first things we do is we look at all the standard things that have worked on similar problems in the past and we try them one by one.

And sometimes that works.

And that's still worth publishing sometimes because the question was important.

Sometimes they almost work and you have to add one more wrinkle to it.

And that's also interesting.

But then, you know, the papers that go into the top journals are usually ones where you, you know, the existing methods can kind of solve, you know, 80% of the problem, but then this is 20%, which is resistant.

And a new technique has to be invented to fill in the gaps.

It's very, very rare now that a problem gets solved with sort of no reliance on past literature, where all the ideas come out of nowhere.

That was more common in the past, but math is so mature now that it's just so much of a handicap to not use the literature first.

So AI tools are really good at...

are getting really good at the first part of that, just trying all the standard techniques on a problem, often now actually making fewer mistakes in implementing them than humans.

They still make mistakes, but I've tested these tools on little tasks that I can do, and sometimes they pick up errors that I make, sometimes I pick up errors that they make.

It's about a tie right now.

But

yeah i i haven't yet seen them take the next step you know so so when there are holes in in in the argument where none of the things are working to to how then what do you do um and then they can kind of suggest random things and it but it it um often i find that trying to chase them down and make them work and finally they don't work it wastes more time than it saves yeah so um

Now, so I think some fraction of problems that we currently think are hard will fall from this method.

I mean, especially the ones that haven't received enough attention.

So like with the Erdos problems, almost all of the 50 problems that were solved by AIs were ones for which basically there was no literature.