- OpenAI claims to have proven the 3D Kakeya conjecture and disproved the Exponential Time Hypothesis.
- Differentiated release strategies adopted: direct publication for math, external review for CS, and delayed release for physics.
- Researchers question the readability and verifiability of AI-generated proofs, as well as the ethics of excluding human contribution.
AI CURATED HOT STORY · 10/27/2026
OpenAI Claims AI Solves Major Scientific Problems, Tests Expert Verification
OpenAI announced three major breakthroughs in mathematics, computer science, and physics: proving the local smoothing conjecture (resolving the Kakeya conjecture), disproving the Exponential Time Hypothesis (ETH), and providing a strict existence proof for Yang-Mills theory. These achievements, if verified, would overturn foundational assumptions in computational complexity and touch upon Millennium Prize problems, marking a shift of AI from research assistant to original discoverer.
Cross-source verification reveals that Anthropic independently published its own disproof of ETH on the same day, claiming its Claude model generated the core algorithm without human input. OpenAI adopted a differentiated release strategy: mathematical and CS results were open-sourced with Lean formalization, while the physical proofs remain under review by an external expert panel including Nobel laureates. The scientific community has raised concerns regarding the readability of AI-generated proofs and ethical issues surrounding the exclusion of human contribution.
This event challenges hundreds of studies based on ETH and sparks intense debate over AI research paradigms, academic attribution, and verification transparency. While OpenAI's new human-AI collaboration mechanism may set a precedent for future scientific exploration, it highlights significant hurdles in reproducibility and peer-review acceptance for black-box AI reasoning.
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Total 13 reports · Latest first- IT之家 · IT业界T2·88 pts
- TechCrunch AIT2·85 pts
- OpenAI claims its models solved three long-standing math problems, including refuting the Exponential Time Hypothesis.
- Anthropic quickly released an independent proof refuting ETH, intensifying competition in AI-assisted research.
- AI labs are establishing new academic collaboration mechanisms (e.g., GitHub releases, funded workshops) to validate AI-generated scientific results.
- Rohan Paul (@rohanpaul_ai)T2·78 pts
- Advisory Group pressures OpenAI to disclose raw data (natural language + Lean code) for Yang-Mills and QCD proofs.
- OpenAI claimed these proofs were completed in September, but only partial results (e.g., Kakeya) are open-sourced; core physics proofs remain under internal review.
- The event highlights academia's strong demand for transparency and independent reproducibility of 'black-box' AI solutions to Millennium Prize problems.
- The DecoderT2·88 pts
- OpenAI claims substantive theoretical breakthroughs in math and CS, including progress on Millennium Prize Problems.
- The company employs a 'human-AI collaboration + formal verification' strategy, inviting experts to review and using Lean for machine checking.
- The event sparks broader debates on verifying AI scientific discoveries, access rights, and academic credit attribution.
- 宝玉 (@dotey)T2·95 pts
- Internal Claude research model found the core ETH algorithm generating 14M tokens with no human input
- OpenAI and Anthropic both announced AI disproving the Exponential Time Hypothesis on the same day
- Paper author listed solely as Claude, with researchers assisting only in presentation refinement
- 新智元 (微信公众号)T2·95 pts
- AI independently disproved the Exponential Time Hypothesis (ETH), undermining hundreds of CS papers built on this assumption.
- Resolved the century-old Kakeya conjecture by proving the full-dimensional local smoothing conjecture.
- Provided a rigorous mathematical existence proof for four-dimensional Quantum Chromodynamics (QCD), advancing theoretical physics.
- 宝玉 (@dotey)T2·92 pts
- OpenAI claims AI disproved the Exponential Time Hypothesis (ETH), a cornerstone of complexity theory, without proving P=NP.
- AI reportedly proved the existence of Yang-Mills theory (a Millennium Prize problem), but the mass gap part remains incomplete and details are not yet public.
- All core claims are under independent verification by external experts, bypassing traditional peer review and sparking debate on AI's role in scientific contribution.
- IT之家 · 智能时代T2·98 pts
- AI proved the local smoothing conjecture for all dimensions, thereby resolving the long-standing Kakeya and Stein restriction conjectures.
- Via Lean formal verification, AI refuted the widely accepted Exponential Time Hypothesis (ETH), suggesting potential for more efficient algorithms.
- AI proposed a rigorous mathematical existence proof for Quantum Chromodynamics and Yang-Mills theory, a Millennium Prize problem, currently under expert review.
- The Verge AIT2·68 pts
- OpenAI claims three 'major' scientific discoveries across math, CS, and physics.
- New workflow: external experts guide CS/physics results, while math outputs are left for researcher interpretation.
- Aims to mitigate controversy from previous mass releases by integrating academic oversight.
- Rohan Paul (@rohanpaul_ai)T2·95 pts
- AI claims to disprove the Exponential Time Hypothesis (ETH), affecting complexity theory research that relied on it for ~25 years.
- Solved the local smoothing conjecture (settling Kakeya) and provided rigorous proof for half of the Yang-Mills existence problem in QCD.
- Results span top-tier unsolved problems in math, CS, and physics, demonstrating AI's capability in extreme abstract reasoning.
- Hacker News AIT2·85 pts
- An internal OpenAI model generated manuscripts claiming to disprove the Exponential Time Hypothesis (ETH).
- The repository includes 721 manuscripts across 373 families, expanding evaluations on open research problems.
- Results are labeled as 'raw research data,' with some lacking Lean formalization and potential errors.
- Hacker News AIT2·68 pts
- AI generated new findings in harmonic analysis (math), complexity theory (CS), and quantum field theory (physics).
- Proposes treating AI outputs as 'raw research data' requiring specific mechanisms for conversion into scientific understanding.
- Tests three expert-guided release strategies: autonomous researcher interpretation, collaborative explanation with public output, and expert-led release.
- OpenAI 官方博客T1·68 pts
- AI produced three new discoveries in math, CS, and physics
- Testing three collaboration models: free organization, public collaboration, and full delegation
- Focuses on transforming raw AI output into community-accepted 'scientific understanding'