Even though AI is getting better at math and can solve harder problems, the question remains: is it truly useful? While it might eliminate bottlenecks in research, most new problems solved by AI are just byproducts with no incremental benefit.
The AI industry is monofocused on difficulty over utility. The NS problem is hard, but it is also useful if solved in a way that it illuminates a lot of areas of math, gives us new techniques etc.
Brute forcing a counter solve has not really changed the game as much.
Knowing whether something or true or isn't true is useful for other lines of inquiry, often practical. For example, a lot could be gained by determining whether P = NP.
Also an initial, cumbersome, complex proof is the first step to a more understandable, formalized proof. AI created a formal proof of Fermat's last theorem. I'm sure the initial proof was not comprehensible to all but a small subset of mathematicians anyway.
Even though AI is getting better at math and can solve harder problems, the question remains: is it truly useful? While it might eliminate bottlenecks in research, most new problems solved by AI are just byproducts with no incremental benefit.
The AI industry is monofocused on difficulty over utility. The NS problem is hard, but it is also useful if solved in a way that it illuminates a lot of areas of math, gives us new techniques etc.
Brute forcing a counter solve has not really changed the game as much.
Who would that be for? If AI comes up with problems that humans don’t understand and solves them, what does anyone gain?
Knowing whether something or true or isn't true is useful for other lines of inquiry, often practical. For example, a lot could be gained by determining whether P = NP.
Also an initial, cumbersome, complex proof is the first step to a more understandable, formalized proof. AI created a formal proof of Fermat's last theorem. I'm sure the initial proof was not comprehensible to all but a small subset of mathematicians anyway.