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This breakthrough resolves a 31-year-old conjecture regarding high-dimensional geometry, directly advancing the theoretical foundations of randomized algorithms and optimization used in machine learning. The result establishes a universal geometric principle for log-concave distributions that is critical for understanding sampling efficiency and algorithmic complexity in AI systems. Notably, the discovery was achieved through a human-directed agentic research process where AI explored mathematical possibilities while researchers guided the search, highlighting a significant evolution in collaborative computational discovery.
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Solving a 31-year-old grand challenge in mathematics – the KLS conjecture

Microsoft Research7 min read

For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appeared first on Microsoft Research.

Fundamental scientific breakthrough: Researchers resolved the Kannan-Lovász-Simonovits (KLS) conjecture, a 31-year-old problem widely regarded as one of the central open questions in high-dimensional geometry, with implications for statistics, optimization, algorithms, and computer science. A universal geometric principle: The result establishes a universal geometric principle for log-concave distributions, showing that simple flat cuts can capture their narrowest bottlenecks within a fixed factor, regardless of dimension. Human-AI collaboration: The breakthrough emerged from a human-directed agentic research process in which AI systems explored mathematical possibilities while researchers evaluated, pruned, and redirected the search. Independent confirmation: Multiple independent researchers have validated this research, identifying its central criterion as the key breakthrough, followed by a machine-checked formal verification. For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted…

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