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I don't really understand your overall point. To whatever extent Phelps' success was said to be thanks to wheaties, it's obvious the same can't be said for Tao for the simple reason that wheaties are from 1924 (predating Phelps) and Tao won the fields medal in 2006 (predating ChatGPT). It's obviously a logical contradiction.
The other thing is that we are at the point where LLMs are solving open problems with minimal or no involvement from humans:
Automated theorem proving across open Erdos problems. Each solved problem cost a few hundred dollars, which is hardly an unbelievably large number.
A problem relating to sumset combinatorics. Gowers is also a Fields medalist and seems pretty impressed with ChatGPT here. Reading the post, it does not seem that it takes a Fields medalist to do the prompting here: "the era where you could enjoy the thrill of having your name forever associated with a particular theorem or definition may well be close to its end." This also doesn't seem to have cost an inordinate amount of money, although there isn't a figure given.
A disproof of a conjecture related to the planar unit distance problem. I'll grant that it's not explicitly clear what the human prompting looked like, but there's no mathematician whose name is attached to this so I can't imagine it was something that only a select few could have done.
This is not an exhaustive list.
In other words, you don't have to be Tao to find new results with these tools. I am sure your response will be that nobody cares about these results, but unless you were predicting beforehand that we would get to this stage but no farther, it's hard to take this seriously.
Sure but that still doesn’t eliminate the problem exactly. It’s somewhat reminiscent of when Fermat’s Last Theorem was proven by Andrew Wiles. The early stage formulated results he came up with he remained confident about, until it took other mathematicians joining in to show him where he was off track. You don’t have to be a Tao to “find” these results per se, but how do you validate them?
It's frequently the case that it's easier to check a result for correctness than it is to generate the result in the first place. This is especially the case if the problem can be formalized in Lean.
But it still requires complex understanding. Even if the models on hand compute the equations perfectly without error, each step requires input validation and verification of the end result. In some cases this can be a time save, in others, not no much.
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