Anthropic AI-discovered Exponential Time Hypothesis refutation validation

Description Anthropic and OpenAI reports of AI-discovered Exponential Time Hypothesis refutations and related algorithms are awaiting independent validation. Overview An internal Claude research model reportedly found a core algorithm on Oct 16 that would disprove the Exponential Time Hypothesis. New reporting says Anthropic and OpenAI internal models separately announced ETH-disproving results, with Anthropic citing a subexponential 3-SAT algorithm. A further report says researchers applied the algorithm to integer factorization, but independent validation of the complexity-theory claims remains unresolved. Why it matters The claim matters to theoretical computer science, security assumptions and AI research because it tests whether frontier models can produce reliable advances in complexity theory. Key details • The Anthropic system was an internal Claude research model. • Anthropic reportedly used 14 million output tokens before researchers refined the presentation. • New reporting says OpenAI models separately reached a similar conclusion. • The work was described as not posing an immediate threat to current encryption standards.