#mathematical-proofs5 articles

5 articles

AIBullisharXiv – CS AI · 15h ago7/10

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Accelerating Scientific Research with Gemini: Case Studies and Common Techniques

Google's Gemini-based AI models, particularly Gemini Deep Think, have demonstrated the ability to collaborate with researchers to solve open problems and generate new proofs across theoretical computer science, economics, optimization, and physics. The research identifies effective techniques for human-AI collaboration including iterative refinement, problem decomposition, and deploying AI as adversarial reviewers to detect flaws in existing proofs.

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AIBullishImport AI (Jack Clark) · Feb 167/106

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Import AI 445: Timing superintelligence; AIs solve frontier math proofs; a new ML research benchmark

Import AI newsletter issue 445 covers significant AI developments including timing predictions for superintelligence, breakthrough AI capabilities in solving advanced mathematical proofs, and the introduction of a new machine learning research benchmark. The article appears to focus on frontier AI research developments and their implications.

AIBullishOpenAI News · Dec 117/108

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Advancing science and math with GPT-5.2

OpenAI has released GPT-5.2, their most advanced model for mathematics and science applications, achieving state-of-the-art performance on benchmarks like GPQA Diamond and FrontierMath. The model demonstrates significant research capabilities, including solving open theoretical problems and generating reliable mathematical proofs.

AIBullishOpenAI News · Nov 207/106

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Early experiments in accelerating science with GPT-5

OpenAI has released the first research cases demonstrating how GPT-5 accelerates scientific discovery across mathematics, physics, biology, and computer science. The AI system is shown collaborating with researchers to generate mathematical proofs, uncover new insights, and significantly increase the pace of scientific progress.

AIBullishHugging Face Blog · Jul 106/108

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Kimina-Prover: Applying Test-time RL Search on Large Formal Reasoning Models

Kimina-Prover represents a breakthrough in formal reasoning by applying test-time reinforcement learning search to large language models. This approach enhances mathematical proof generation and formal verification capabilities, potentially advancing AI's ability to handle complex logical reasoning tasks.