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AI models have produced proofs challenging major theories in maths, computing, physics: OpenAI

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AI models have produced proofs challenging major theories in maths, computing, physics: OpenAI

Business News Tech AI AI models have produced proofs challenging major theories in maths, computing, physics: OpenAI

AI models have produced proofs challenging major theories in maths, computing, physics: OpenAI

OpenAI has claimed its AI models have disproved the Exponential Time Hypothesis, which impacts computer science research. The findings include proofs related to harmonic analysis and quantum field theory, influencing various scientific domains. Researchers will verify these claims, and OpenAI plans to share the results for independent examination. The company is also funding a conference to discuss the implications of these discoveries.

OpenAI said its AI models have produced mathematical proofs that refute a longstanding computer science hypothesis and establish results in mathematics and theoretical physics, as the company brings together independent academic experts to verify the findings and assess their implications. The company announced three results covering harmonic analysis, computational complexity and quantum field theory , including a proof that refutes the Exponential Time Hypothesis (ETH), a widely used conjecture about the computational effort required to solve certain problems. "Surprisingly, our system has recently proved that the ETH is false, a result that was subsequently verified in Lean," OpenAI said.

The ETH has been used in hundreds of research papers to establish limits on how efficiently computational problems can be solved across fields such as graph theory, computational biology, databases and computational geometry. OpenAI said the finding "reopens questions about how much faster these tasks could become, and may help guide the search for better algorithms". However, it cautioned that "finding such algorithms, and turning theoretical advances into practical improvements, will require significant further research".


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