Physical Superintelligence technical staff member David Turturean solved the Aaronson-Ambainis problem using Anthropic's Fable 5.2 model. Co-originator Scott Aaronson accepted the validity of the proof after it was autoformalized in the Lean mathematical coding language and vetted by leading researchers. To advance its discoveries toward commercial viability, the firm relies on proprietary simulation infrastructure, specialized harnesses, and memory systems. The broader community is now responding to these machine-led discoveries, with top physicists planning to meet at MIT to assess their impact on academic research.
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The laboratory supports its long-term research ambitions by generating near-term revenue…: The laboratory supports its long-term research ambitions by generating near-term revenue from data center physics optimization.
Adapting artificial intelligence to physical sciences introduces difficult hurdles becaus…: Adapting artificial intelligence to physical sciences introduces difficult hurdles because theoretical concepts require verification through real-world experiments.
Machine-led breakthroughs are compelling academic institutions to rethink established sta…: Machine-led breakthroughs are compelling academic institutions to rethink established standards for reviewing and validating scientific research.
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David Turturean, a recent MIT graduate and a member of the technical staff at the startup lab Physical Superintelligence (PSI), used early access to Anthropic’s Fable 5.2 model to solve an eighteen-year-old problem about quantum computing.
“I’m totally accepting the idea that this might be the last paper I ever put out,” Turturean, who deferred plans to pursue a master’s at MIT’s prestigious computer science and AI lab to join PSI, told TechCrunch. “In a few months, like, why would you even put out a paper?”
The problem in question, the Aaronson-Ambainis conjecture, concerns the ability of quantum computers to solve problems faster than classical ones. Scott Aaronson, one of the two researchers who posed the problem, writes that he doesn’t quite understand the proof, but that he believes it’s 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.
The solution appears to close the door on one avenue quantum computers could follow to solve certain difficult problems at high speed, but not…
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