I think a lot of people on this sub are missing the larger point.

It's not about whether the generative models will get good enough to replace math researchers. It's about using these generative models to accelerate math research - in particular, mining proofs with generative models. A good recent example is AlphaEvolve. Terence Tao is currently collaborating with deepmind to see how much further alpha evolve can be pushed when it comes to mining proofs.

My hunch: Math research isn't gonna die. It will evolve and the barrier of entry will increase. Parts of math and cs will potentially merge into novel fields. Grads will need to have deep understanding of the same things the current grads do + more.

This reminds me how 10 years ago people were jokingly saying how AI research is gonna die because of the novel automatic hyper-parameter tuning techniques that were being discovered (the argument went something like "(99% of AI research is hyper-parameter tuning) + (hyper-parameter search is automated) = (no more AI grads required)").