Subvolts take AI helped solve an 80-year-old math problem, showing AI's power in scientific discovery. Jun 4, 2026 - Developers
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This episode details a significant AI achievement in pure mathematics, demonstrating AI's potential for scientific breakthroughs.
How a reasoning model cracked an 80-year-old math problem - Episode 20
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The OpenAI Podcast episode 20 features reasoning researchers Alexander Wei, Hongxun Wu, and Lijie Chen discussing how a general-purpose AI model disproved the 80-year-old Erdős unit distance conjecture. They detail the verification process, the implications for AI in mathematical discovery, and how mathematicians can collaborate with AI tools. The conversation also touches on future research directions in math and AI.
Smart AI helped mathematicians solve a puzzle that stumped experts for 80 years. This shows how AI can be a powerful partner in scientific discovery, helping us understand complex ideas and find new answers.
This episode offers insight into how advanced AI models can contribute to fundamental mathematical breakthroughs, moving beyond pattern recognition to actual reasoning. It's for mathematicians, AI researchers, and anyone interested in the evolving capabilities of AI in scientific discovery. This aligns with frontier labs' current focus on developing more capable and general AI systems that can assist in complex problem-solving across various domains, pushing the boundaries of what AI can achieve.
- HostAndrew Mayne
- GuestAlexander Weireasoning researcher, OpenAI
- GuestHongxun Wureasoning researcher, OpenAI
- GuestLijie Chenreasoning researcher, OpenAI
- Episode Title: How a reasoning model cracked an 80-year-old math problem - Episode 20
- Show: The OpenAI Podcast
- Length: 41 minutes
- Conjecture Disproved: Erdős unit distance conjecture
- Conjecture Age: 80 years old
- Guests: Alexander Wei, Hongxun Wu, Lijie Chen
Last month AI found something mathematicians had missed for decades. Reasoning researchers Alexander Wei, Hongxun Wu, and Lijie Chen join the podcast to discuss how a general-purpose model helped disprove an 80-year-old conjecture from famed mathematician Paul Erdős. They walk through the moment the result started looking real, what it took to verify the proof, and what’s happened since sharing the discovery with the world. They also explore what this means for the future of math and for researchers learning to work with AI.
Chapters
0:44 AI and the International Math Olympiad and International Olympiad of Informatics
6:35 An OpenAI model disproves the Erdős unit distance conjecture
8:33 Running the model and checking the proof
11:04 Why general models matter for discovery
15:55 Creativity, tools, and how the proof worked
18:25 Why AI should feel empowering for mathematicians
22:31 Advice for researchers using AI
27:24 What comes next for math and AI research
37:30 Cryptography, quantum computing, and the future
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- Erdős unit distance conjecture
- Paul Erdős
- A mathematical problem about the minimum number of distinct distances between points in a set.
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Questions people ask
- What math problem did AI help solve?
- An AI model helped disprove the 80-year-old Erdős unit distance conjecture, a problem that had stumped mathematicians for decades.
- Who worked on this AI-assisted proof?
- OpenAI reasoning researchers Alexander Wei, Hongxun Wu, and Lijie Chen discussed how a general-purpose AI model was used to find and verify the proof.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to OpenAI.