It is.

What I think the parent post is missing is that breakthroughs in science don't immediately translate into breakthroughs in engineering and even less so into economically viable products.

The distinction for many people is that math and cs feel like very natural domains for LLMs (and importantly, domains that enable quick iteration and verification). Much less applicable with eg biology and other fields that require lots of physical experimentation.

(in)Conveniently those are also the fields where most ordinary people would experience the most effects from accelerated progress. Dario famously promises potential cures for cancer and dementia.

I think there's a pretty clear distinction between math and science. The former builds theoretical models of what certain axioms and assumptions imply. The latter builds actual models of what we see and measure in the real world.

Advances in math will probably result in advances in science, which in turn will result in advances in engineering (which is probably where the average person sees an actual benefit in their day to day life). But it's not automatic and a lot of the hand wringing by mathematicians about the AI math results include "is this (AI) method of finding proofs actually going to result in as many of those downstream advances as the old fashioned way?"

(I include theoretical CS as a subfield of math - and believe the S in it is a misnomer).

well they don't affect anyone's day-to-day lives, which is what the person you're replying to is talking about..

I have a feeling that many more fields are utilizing AI and having some success with it and we just don't know about it in our STEM bubble.

On the other hand, you could downplay the math findings a bit, since it didn't further our understanding of mathematics just yet, only provided proves to things we didn't have proves for.