A researcher at UC Berkeley claims to have used OpenAI's GPT 5.6 Sol Pro model to solve a 30-year-old mathematical optimization problem. The model produced a proof for a complexity gap in convex optimization, which was then formally verified using Lean. This achievement follows OpenAI's recent announcement of using a similar methodology for a proof of the Cycle Double Cover Conjecture, suggesting a significant advancement in AI's capability for theoretical research. AI
IMPACT Demonstrates AI's growing capability in solving complex theoretical problems, potentially accelerating research across scientific disciplines.
RANK_REASON Research milestone achieved using an AI model, with formal verification. [lever_c_demoted from research: ic=1 ai=1.0]
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