GoKawiilOpenAI and Anthropic AI models claim to disprove 27-year-old exponential time hypothesis
OpenAI and Anthropic both announced AI-generated proofs this week that refute the exponential time hypothesis, a foundational assumption in theoretical computer science used to explain why certain problems require exponentially more effort as they grow larger. The proofs, published on GitHub in natural language and machine-checkable Lean format, have not yet been independently verified by researchers. OpenAI has reached out to the hypothesis's original proponents and other academics to help review and validate the findings, including funding a dedicated conference.
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If verified, the result could invalidate large portions of published research that relied on the hypothesis as a given, with one professor estimating roughly 50 of his papers could become obsolete or need revision. The episode illustrates how AI systems might increasingly challenge long-held assumptions across scientific fields faster than the academic community can verify them, raising questions about how peer review and validation processes adapt to AI-generated proofs.
- OpenAI and Anthropic both claim AI helped disprove the exponential time hypothesis, a 27-year-old pillar of complexity theory.
- The AI-generated proofs remain unverified, and researchers are being recruited to check their validity, including via a Google form and a planned conference funded by OpenAI.
- Academics say dozens of published papers could become obsolete or require significant revision if the findings hold up.
Source: wired.com — Isabella Ward, 2026-10-29
Published there as: “An AI Breakthrough Has Made Decades of Computer Science Research ‘Irrelevant’”
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