OpenAI 攻克千禧难题？深度拆解 1 万个 Agent 如何造出流体奇点
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TL;DR - OpenAI reportedly used roughly 10,000 parallel agents, 88 hours of search, and formal verification to construct a finite-time singularity for a forced 3D Navier–Stokes setting. The work illustrates an AI-assisted mathematics pipeline combining human-devised structures, large-scale constraint search, iterative correction, and machine-checked proofs, though its novelty and attribution are disputed.
- Human mathematicians supplied the core physical and geometric ideas, while agents searched a high-dimensional space of interacting profiles, scales, stress constraints, and corrections.
- The construction uses anisotropic self-similar scaling to make local velocity diverge while keeping total kinetic energy finite and managing viscous dissipation.
- High-frequency oscillations generate Reynolds stresses that absorb residual errors; local shear and low-frequency corrections keep stress-cone and integral constraints compatible.
- Lean checks the proof chain, while a separate Comparator reportedly verifies that formalization has not weakened or altered the original problem statement.
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OpenAI 攻克千禧难题？深度拆解 1 万个 Agent 如何造出流体奇点
TL;DR - OpenAI reportedly used roughly 10,000 parallel agents, 88 hours of search, and formal verification to construct a finite-time singularity for a forced 3D Navier–Stokes setting. The work illustrates an AI-assisted mathematics pipeline combining human-devised structures, large-scale constraint search, iterative correction, and machine-checked proofs, though its novelty and attribution are disputed.
- Human mathematicians supplied the core physical and geometric ideas, while agents searched a high-dimensional space of interacting profiles, scales, stress constraints, and corrections.
- The construction uses anisotropic self-similar scaling to make local velocity diverge while keeping total kinetic energy finite and managing viscous dissipation.
- High-frequency oscillations generate Reynolds stresses that absorb residual errors; local shear and low-frequency corrections keep stress-cone and integral constraints compatible.
- Lean checks the proof chain, while a separate Comparator reportedly verifies that formalization has not weakened or altered the original problem statement.