“We have moved from an era of proof scarcity to proof abundance. … I think going forward, the idea of focusing on individual problems is that currency has basically been hyper-inflated. So we now have machines that can just brute force basically solve massive numbers of the old problems that we used to use as landmarks. … We are not used to mass production of mathematics. We are still in many ways in a pre-industrial economy, math academia. We are forced almost at gunpoint right now to switch to an industrial or post-industrial economy.”
sputnikintelligence.com
Tyler Cowen asked how long before AIs create the equivalent of new Millennium Prize problems. Tao says the question is the wrong frame: open problems used to be rare, hard-won landmarks, and AI is now mass-producing proofs.
…We close to Hollywood. We had a lot of ties with computer graphics industries and the movie industry. There are many, many areas, many sectors of the economy now, which are becoming more and more mathetized. They need people with good math skills, and we should engage with all of them, I think.
How long do you think it will be before AIs create the equivalent of new millennium problems for mathematics? Is that two years away, 20 years away, or interesting ones?
…towards these goals very slowly and deliberately. But we'd pick up all these insights and techniques and learn all these things along the way. And so, yeah, so we have these millennium price problems and we have these targets that guided us, but they're relatively few in number, like there's only seven millennium price problems. And that was kind of the way things worked in a proof scarcity era. I think going forward, the idea of focusing on individual problems is that currency has basically been hyper-inflated. So we now have machines that can just brute force basically solve massive numbers of the old problems that we used to use as landmarks. And we have to really switch to some sort of math 2.0. I think instead of dealing with individual problems, we may start creating huge data sets of thousands or millions of problems. Trying to sweep them out. With this AI, I can handle 30% of these problems using this idea that this human contributed, I can solve this 10%, but not pick out individual problems per se anymore as the goals, but…
on that, you're happy, unhappy?
That's not the right word. It's very complicated. I mean, I'm excited by the possibility of completely new types of mathematics that didn't exist before. But I'm also actually quite horrified by the disruption, which I think was much more than necessary. I mean, you know, of course, every…
But it would have been better overall, right? Like our standard of living people might have had in the 1950s.