AI labs claim their models refuted the Exponential Time Hypothesis
OpenAI and Anthropic say their algorithms solve hard puzzles faster than thought possible, and researchers are still checking the claims.
Research#02
3
math problems OpenAI released solutions to
Image: TechCrunch
3math problems OpenAI released solutions to
The short version
- OpenAI released solutions to three math problems that researchers had long struggled with, including one that rejects the Exponential Time Hypothesis (ETH).
- Anthropic mathematician Levent Alpöge suggested OpenAI based its solutions on pre-existing work, and hours later Anthropic released its own refutation of ETH.
- The lab split its releases by field: mathematicians got the work on GitHub, computer scientists formed a working group to discuss the proofs, and physicists formed a group to decide how their result will be released.
- MIT professor Ryan Williams is organizing the computer science response and is helping interpret the solution with UC San Diego researchers Russell Impagliazzo and Ramamohan Paturi, who first published the ETH in 1999.
Why it matters
The ETH supports the common assumption that P is not equal to NP, so a refutation would change how researchers think about hard problems. Williams said many papers that rely on ETH will need to be revisited if the claims hold up. He also said an improved algorithm could affect cryptographic systems that depend on certain key sizes, though OpenAI reportedly checked and found no breaks.
“I do think that it kind of calls into question a lot of the intuitions that we thought we had about … how tractable [hard NP problems] are.”