Theoretical computer science

Okay.

This was started because people felt that the biggest conferences for theoretical computer science had become too much like technical weightlifting competitions.

Instead of the novelty of a simple, compelling new idea, people were more competing on who had the hardest proof.

Right.

They made a case to me that, yes, it's true that the progress in AI has been almost entirely empirical, but it is super-duper rapidly getting better, and we don't know how to reliably understand it, control it.

And maybe there are theoretical questions here, right? Maybe, like, if your goal is to align a superintelligence with human values, you can't just do that empirically.

You can't just do that by trial and error, right? For one thing, because, you know, you may have only one chance to get it right, right? And then, you know, if – right? So, like, you better understand what you're doing before you, you know – before you press the go button, right? And they mentioned all kinds of ideas that we have in theoretical computer science, such as interactive proofs, probabilistically checkable proofs, things that we do understand and that they thought might be relevant.

I think this was partly because of actually a former undergrad of mine from MIT named Paul Cristiano, who a decade ago actually left quantum computing where he was becoming a superstar in quantum computing, But he left in 2016 to join some obscure new outfit that was called OpenAI to work on AI alignment, whatever that was.

And somehow I told her my life story about how my math and how you know, I left my graduate program.

And then she immediately told me, you should go to theoretical computer science.

And then she goes, my husband is a professor in Weizmann Institute.

I actually hardly heard of the, I mean, I heard of it, but I had no idea what it is because it's not really a university.

I'm like,

okay.

And that's how I got into theoretical computer science.

And that I really enjoyed because it seemed like they asked relevant questions.

The raised eyebrow is now knitted.

An open AI paper and accompanying lean proofs from early August, entitled 10 Advances in Mathematics and Theoretical Computer Science, followed closely by a new result from Anthropic, have kicked up a much bigger stir, all of which is sure to be dwarfed by the announcement that a Millennium Prize has been nabbed.

Although these results have not been fully metabolized by the community, the reaction makes it clear to me that what is happening now hits much closer to what most mathematicians consider their core work.

Wild extrapolations of the future of math have abounded, as refuseniks preach rejectionism, and other more measured approaches are suggested.