980: AI Making Theoretical Physics Breakthroughs
About this episode
Jon Krohn discusses how AI models assisted physicists in solving a complex problem in particle physics.
A team of theoretical physicists from Harvard, Cambridge, the Institute for Advanced Study, and Vanderbilt used OpenAI’s models not just as a tool, but as a collaborator, cracking a problem in particle physics that had stymied them for months. In this Five-Minute Friday, Jon Krohn walks through how GPT-5.2 Pro simplified a 32-variable mathematical expression into a single line, proposed what it called the “obvious generalization” for any number of gluons, and how a more powerful internal model then produced a formal proof after 12 hours of autonomous reasoning. Find out why this may be a template for AI-assisted scientific discovery and what it means for the future of research. Additional materials: www.superdatascience.com/980 Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
More episodes of Super Data Science: ML & AI Podcast with Jon Krohn
- 986: Building Hardware is Hard but AI Agents Help, with Kishore Subramanian
- 985: The Four Types of Memory Every AI Agent Needs, with Richmond Alake
- 984: Building AI Agents Where 99.9% Accuracy Isn't Good Enough, with Raju Malhotra
- 983: AI in the Classroom: How a Top Elementary School Is Doing It Right, with Principal Traci Walker Griffith
- 982: In Case You Missed It in March 2026
- 981: How Data Engineers Are “10x’ing” Themselves With Agents, feat. Matt Glickman
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