What do you feel is fundamentally different about the feedback loop in AlphaEvolve compared to, say, Einstein and Grossman repeatedly running calculations until they found the right tensor setup for General Relativity? Or Euler filling his notebooks with computations? Or Ramanujan? Or Newton working out infinite series? Or Kepler, etc etc.
They are all doing iterative search with feedback from a function that tells them whether they're getting closer or farther from their goal. They try different things, see what works, and keep the stuff that works.
The reward functions in the problems that they proposed alphaevolve are easy. The reward funtions of at least 50% of maths are not. You can say that validating if a proof is correct is a straightforward reward, but the size of interesting theorems over the space of all theorems is very small. And also what does "interesting" could even mean?
They are all doing iterative search with feedback from a function that tells them whether they're getting closer or farther from their goal. They try different things, see what works, and keep the stuff that works.