Key facts
- David Turturean, a recent MIT graduate and PSI technical staff member, solved the Aaronson-Ambainis conjecture using early access to Anthropic's Fable 5.2.
- Scott Aaronson wrote he does not fully understand the proof but believes it is correct because it was autoformalized in Lean and explained by top researchers.
- PSI CEO Matt Pines said the company's revenue comes from using its tools to optimize data centers.
- Jim Halverson, a Northeastern University professor who advises PSI, said best practices for AI-driven science are still emerging.
- PSI held its result until Anthropic's model was nearly ready for release, allowing it to share the solution with relevant researchers.
Physical Superintelligence (PSI), a startup lab, said on November 10, 2026, that its technical staff member David Turturean used early access to Anthropic's Fable 5.2 model to solve the Aaronson-Ambainis conjecture, an 18-year-old problem about whether quantum computers can solve certain problems faster than classical ones. Turturean, a recent MIT graduate who deferred a master's program to join PSI, told TechCrunch he is "totally accepting the idea that this might be the last paper I ever put out."
Scott Aaronson, one of the two researchers who posed the problem, wrote that he does not quite understand the proof but believes it is correct because it was autoformalized in Lean, a coding language for math, and explained by a team of top researchers with whom PSI shared the solution. He wrote that a proof of the conjecture was "one of the last remaining open problems in quantum query complexity that everyone seemed to agree was centrally important." The solution appears to close one avenue for quantum computers to solve certain difficult problems at high speed, but not all of them. Turturean said: "It's a negative result that allows people to know, okay, we're no longer looking there."
PSI CEO Matt Pines told TechCrunch that an effective research system should have "lots of things related to harnesses, lots related to tools, memory systems, simulation infrastructure." He said the company's revenue comes from using its tools to optimize data centers, simulating variables including heat, power, water and sound. Pines said the long-term goal is converting theoretical physics breakthroughs into technologies.
Jim Halverson, a Northeastern University professor who advises PSI, said the company held its result until Anthropic's model was nearly ready for release, allowing it to share the solution with relevant researchers. "As an academic, we wanted to play our role in doing things the right way," he said. Halverson said he will attend a summit at MIT the following week where leading physicists will try to hash out a response to the new pace of science.
PSI's approach contrasts with the difficulty of applying AI to less abstracted disciplines. Last week, the startup Discovered Materials released a $1 million grand challenge for researchers using AI to understand problems like superconductivity and heat dissipation. Pines said: "At the end of the day, physics is different than math because it's the real world … nature gets a vote in your models of reality."