Regarding the Navier Stokes theorem, one of the best posts I've seen about this (and the other OpenAI math proofs) recently is Nestor Guillen's post where he introduces "the convex hull of ideas". I love this because I've had some vague ideas about the limitations of LLMs that aligned with this, but Guillen really clarified the idea and explained it with a great analogy: https://terrytao.wordpress.com/2026/09/13/happy-those-able-t...
Basically Guillen is arguing that LLMs are great at finding results within the "convex hull" of existing literature (i.e. their training data). They can make connections across different parts of the literature where it would be impossible for a human to be an expert in all these areas. But when it comes to truly novel, original ideas, there is no proof yet that LLMs are able to go there. That's honestly a limitation I'm really rooting for because otherwise I think the future of humanity is generally fucked.
Basically Guillen is arguing that LLMs are great at finding results within the "convex hull" of existing literature (i.e. their training data). They can make connections across different parts of the literature where it would be impossible for a human to be an expert in all these areas. But when it comes to truly novel, original ideas, there is no proof yet that LLMs are able to go there. That's honestly a limitation I'm really rooting for because otherwise I think the future of humanity is generally fucked.