Unreleased Anthropic model cracks 18-year quantum puzzle

Short answer

On November 6, 2026, the AI research lab Physical Superintelligence (PSI) said its in-house research system, running a non-public Anthropic model, found a proof of the Aaronson-Ambainis conjecture, a quantum computing question that had been open since 2008. The proof was checked step by step in Lean, a proof assistant where a computer verifies every line. Human experts still need to confirm that the formal statement matches the original conjecture.

What happened

According to PSI, the system had a complete proof during the third day of a run on the lab's own infrastructure, and Lean accepted it. PSI then pointed the system at related open problems, and it improved the result twice before Lean accepted the final version. The paper and the Lean 4 formalization are public on GitHub under the Apache 2.0 license.

The conjecture, posed by Scott Aaronson and Andris Ambainis, is about when quantum computers can be exponentially faster than ordinary ones. In plain words, PSI says the result shows that on yes-or-no questions a quantum computer cannot save exponentially many "looks" at its input unless that input has a rare, special structure, like the one Shor's algorithm uses for factoring.

Some details, as reported by PSI and covered by Business Insider, Unite.AI and SiliconReport:

• Machine-checked: the repository's audit says the four final theorems have no placeholders and no added axioms, and they were re-checked by two independent implementations of the Lean kernel.
• Built on human work: PSI says the proof follows a plan by Shachar Lovett and Jiapeng Zhang and builds on David Reimer's Butterfly Lemma and other earlier results.
• Human responsibility: the repository states that the statements, first draft of the paper and the Lean code were produced by AI models, and that PSI researcher David Turturean reviewed the paper and is responsible for its correctness.

Why people are talking about it

The announcement reached Techmeme's front page and spread on X and Reddit (r/Physics, r/accelerate). Quantum researcher Henry Yuen called it "another beautiful question in quantum complexity theory solved". The hook is easy to share: an AI system settled a problem that experts had worked on for 18 years, and it did so in days.

What it means if you use AI

• AI as a research partner. This is a sign of where the strongest models are heading: not only chatting, but helping with real, checkable discoveries.
• Checkable beats impressive. What makes this result credible is that a computer verified every step. It is a good habit for everyday AI use too: ask for sources and double-check important answers.
• Not something you can try yet. The Anthropic model PSI used is non-public, so this is a research result, not a new app feature.

Quick checklist

1. Read PSI's plain-language explainer before the math-heavy paper.
2. Treat it as "PSI says, Lean checked": wait for wider expert review before calling it final.
3. When an AI helps you with numbers or facts, ask it to show its steps.
4. Follow the GitHub repository if you want to see the open issues and updates.

Sources

• PSI (Nov 6, 2026): A proof of the Aaronson-Ambainis conjecture (primary)
• GitHub: physical-superintelligence/aaronson-ambainis (paper and Lean 4 formalization)
• Business Insider (Nov 7, 2026): Unreleased Anthropic model helps solve major quantum-computing problem
• Unite.AI: PSI reports machine-checked proof of Aaronson-Ambainis conjecture
• SiliconReport: Physical Superintelligence says AI proved Aaronson-Ambainis conjecture
• Cover photo: IBM engineers installing IBM Quantum System One in Ehningen, Germany, by IBM Research, Wikimedia Commons, CC BY 2.0

Sources read on November 7, 2026.