Um, okay? Isn't that how most optimisation involving AI is supposed to go?

Perhaps some much needed context. Mathematicians are not stupid; we are very much aware of all the existing forms of genetic optimisation algorithms, cross entropy method, etc. Nothing works on these problems, or at least not well at scale. As I said, state of the art for many of these was SAT-related. The problem is that the heuristic used for exploring new solutions always required very careful consideration as the naive ones rarely worked well.

Here, the transformer is proving effective at searching for good heuristics, far more so than any other existing technique. In this sense, it is achieving far, far. far better performance in optimisation than previous approaches. That is a breakthrough, at least for us mathematicians. If this doesn't constitute improvements in optimisation, I don't know what does.

Saying it's "just meta heuristic relying on local search" is akin to saying these tasks are "just optimisation". If it's so procedural, why weren't we making ground on these things before?

Also, by the way, a :facepalm: is not exactly the pinnacle of academic rebuttal, no matter how wrong I could have been.