OpenAI says it started training a new internal model on August 28 . That was just 24 days ago. Since then, the model has reportedly solved 100+ long-standing open problems in mathematics across multiple fields on top of its recently announced work on the Navier–Stokes Millennium Prize Problem . And apparently, even OpenAI’s own mathematicians are surprised by the pace. But here’s the part that really caught my attention: The problem may no longer be “Can AI solve difficult mathematics?” It may be: “What do we do when AI starts producing too much new mathematics for humans to evaluate?” An independent advisory group involving mathematicians such as Edward Witten, Timothy Gowers, and Martin Hairer has reportedly been formed to help assess the significance of these results and coordinate their release to the mathematical community. The group’s immediate challenge? The “large number of significant results” reportedly being generated by the model. Of course, these claims still need rigorous, independent verification. Mathematics doesn’t accept impressive demos proofs have to survive expert scrutiny. But if even a substantial fraction of these results hold up… submitted by /u/BilelKort
Originally posted by u/BilelKort on r/ArtificialInteligence
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