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That's what's gotta sting the most about this. Imagine you worked a problem for a long time… and then The Giant Pattern Matcher With Zero Fluid Intelligence actually finds something.
If it did find something, that implies the solution already existed in bits and pieces in the published literature. You would "just" have had to have read about it, and remember it, for successful application.
But suppose you had succeeded in that. You would have published a paper that enumerates a bunch of results some other people had reached, then plugs them together for a supposedly new theorem. Sort of like importing a dozen Python libraries, adding around fifty lines of glue code around them and then going, yeah, here's a "new" thing, Fields Medal plz!
How much remaining interestingness did your chosen problem really have if the new math you had to create for it fits on the placemat buttressing the campus cafeteria sandwich you had for lunch?
What I've seen appears to indicate some genuinely new approaches by the AI, rather than putting together existing information. That blog post, for example, quotes some running commentary from a mathematician studying the proof of the theorem that she had been working on for years:
Note that this particular proof is correct, according to that same mathematician.
The issue with longstanding problems such as these is that yes, they can be used to establish evidence of plagiarizing if your LLM is simply regurgitating stuff, but suppose you cannot come up with any… you don't really know if it's because this particular line of thought is new, or because you just hadn't read about it.
That's true even if you're an expert practitioner; LLMs have been trained on All Of The Text and have superhuman recall after all.