微软研究员用 AI 辅助证明 31 年数学猜想 KLS
AI 智能体跑了约 100 条数学路径，帮研究员关掉 1995 年悬置的 KLS 猜想，证明过程怎么分工的这篇讲得细。
微软研究员借助 AI 智能体探索了约 100 条研究路径，筛除薄弱方向，最终产出支撑 Song 与 Zhang 证明 Kannan-Lovász-Simonovits（KLS）猜想的关键判据。AI 参与候选方案探索、推导、稿件准备和内部证明检查，递归方法与误差界仍由两位研究者完成。最终形成 140 页证明，解决了自 1995 年悬置至今的难题。KLS 猜想描述随机游走者无法被高维凸形状中的狭窄通道困住。
A math problem older than Google has been solved, with AI doing much of the searching.
Microsoft researcher proved this 31-year-old Math conjecture (Kannan-Lovász-Simonovits conjecture) after AI agents explored over 100 approaches.
A 140-page proof, more than 100 AI-explored paths now have closed a question mathematicians had been working on since 1995.
A human-directed search, with AI agents exploring roughly 100 research trajectories while a researcher cut weak directions between rounds, produced the criterion underpinning Song and Zhang’s proof of the Kannan-Lovász-Simonovits (KLS) conjecture.
The AI explored candidate approaches, carried out derivations, helped prepare the manuscript and ran internal proof checks, while the recursive method and the error bound that finished the proof are credited to the 2 researchers.
About the Kannan-Lovász-Simonovits conjecture: Picture a random walker wandering inside a convex shape: the conjecture says no secret narrow passage can trap it, so it can explore the whole shape efficiently, even in huge dimensions.
