That was a really nice talk. Most of it would be understandable to an undergraduate math major. Some interesting quotes:
> [shows a slide with 3 sentences on it] If somebody tweeted this to me from the future, I would know what to do with this... Every step is very natural, and you just know how to continue.
> Everything was basically known, it's just that nobody tried this combination. Everybody believed that this is a combination that has a very realistic combination of working soon... [lists a sequence of technical but standard steps that were used in the proof] Exploiting the Gauss sum that resonates with Mobius, that's a genuinely clever step, but which Iwaniec [sp] observed, but which he actually intended to exploit for this purpose. So this was clever but was actually known by some people... And then there's the final hope that you can take all of this and obtain quasi-RH, and I think this is probably where more people were checking out, because it seemed a bit like a stretch.
> It turned out that [quasi-RH] came from tools we already had, but we somehow lost the confidence. So I think this is one of the big advantages of AI - it is not subject to psychology. It tries a lot of hopeless things, and it tries them with enthusiasm.
> This method caps out at 3/4 [meaning that it cannot suffice to prove the full Riemann hypothesis].
That was a really nice talk. Most of it would be understandable to an undergraduate math major. Some interesting quotes:
> [shows a slide with 3 sentences on it] If somebody tweeted this to me from the future, I would know what to do with this... Every step is very natural, and you just know how to continue.
> Everything was basically known, it's just that nobody tried this combination. Everybody believed that this is a combination that has a very realistic combination of working soon... [lists a sequence of technical but standard steps that were used in the proof] Exploiting the Gauss sum that resonates with Mobius, that's a genuinely clever step, but which Iwaniec [sp] observed, but which he actually intended to exploit for this purpose. So this was clever but was actually known by some people... And then there's the final hope that you can take all of this and obtain quasi-RH, and I think this is probably where more people were checking out, because it seemed a bit like a stretch.
> It turned out that [quasi-RH] came from tools we already had, but we somehow lost the confidence. So I think this is one of the big advantages of AI - it is not subject to psychology. It tries a lot of hopeless things, and it tries them with enthusiasm.
> This method caps out at 3/4 [meaning that it cannot suffice to prove the full Riemann hypothesis].
Presentation given at NYU Courant Institute on Oct. 28, 2026.