Theme · 22 episode(s)

AI for Science

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Definition

AI for science is the application of machine-learning systems to accelerate scientific discovery: predicting protein structures, proposing experiments, scanning the literature, simulating systems. The interesting cases are where the AI changes what experiments are worth running, not just how fast existing ones get analyzed.

Episodes covering this

  1. 287
    Can You Measure Research Taste If The AI Isn't Allowed To Code?
    TasteVal: Measuring the Experimental Research Taste of AI Systems Against Human Experts
    Jaffe, Sherburn · P-Zero Research·14 min·Oct 06, 2026
  2. 276
    An AI Agent Rewrote Its Own Scaffolding For Eight Days. Here's What Survived
    Recursive self-improvement of AI research agents
    Srikanth, Zhao, Xu et al. · Weco AI·14 min·Sep 23, 2026
  3. 271
    The Proof Counter Hit Zero While a Third of It Was Missing
    Long-horizon autoformalization of a core theorem underlying MIP* = RE
    Lu, Deng, Zhu et al. · Max-Planck-Institut für Quantenoptik·17 min·Sep 19, 2026
  4. 240
    Frontier Models Designed Follow-Ups To Fraudulent Papers 93% Of The Time
    TRACES: A Benchmark for Epistemic Reliability in Scientific Reasoning by LLMs
    Rodionov, Assylbekov · Case Western Reserve University·24 min·Aug 13, 2026
  5. 188
    A Coding Agent Found a Hole in a Peer-Reviewed STOC Proof for Five Dollars
    Beyond the Library: An Agentic Framework for Autoformalizing Research Mathematics
    Moakhar, Gholami, Springer et al. · University of Maryland·20 min·Jul 02, 2026
  6. 187
    An 8-Billion Agent That Beats Models 80 Times Its Size By Looking Things Up
    An AI agent for treatment reasoning over a biomedical tool universe
    Gao, Noori, Zhu et al. · Department of Biomedical Informatics·19 min·Jun 30, 2026
  7. 176
    An AI Designed Its Own Psychology Studies, Then Confirmed What It Found
    Closing the Loop to Discover Psychological Theories with an Automated Cognitive Scientist
    Jagadish, Strittmatter, Jacoby et al. · Princeton University·31 min·Jun 26, 2026
  8. 159
    Can a Coding Agent Run Its Own Robot Experiments Overnight, With No Human Resetting the Scene?
    ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
    Xiao, Xie, Zhang et al. · NVIDIA·23 min·Jun 19, 2026
  9. 129
    How a Crowd of Anonymous AI Agents Broke a 40-Year Math Record
    Harnessing the Collective Intelligence of AI Agents in the Wild for New Discoveries
    Bianchi, Kwon, Pappu et al. · Together AI·29 min·Jun 11, 2026
  10. 117
    How an Open AI System Verified 672 Hard Math Proofs for Under $300
    Goedel-Architect: Streamlining Formal Theorem Proving with Blueprint Generation and Refinement
    Chung, Cai, Li et al. · Princeton University·26 min·Jun 05, 2026
  11. 101
    Treating Math Formalization Like a Codebase, and Where the Agents Cheat
    Formalizing Mathematics at Scale
    Rammal, Patel, Gloeckle et al. · FAIR at Meta / CERMICS·27 min·May 29, 2026
  12. 095
    Seven Wins to Zero: How Organizing AI Agents Like a Lab Changes the Search
    AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation
    Gao, Fang, Zitnik · Harvard University·24 min·May 28, 2026
  13. 076
    Same Model, Organized Differently: How an Agent Architecture Beat Frontier Systems at Research Math
    RMA: an Agentic System for Research-Level Mathematical Problems
    Zhao, Yuan, Choi et al. · Georgia Institute of Technology·22 min·May 25, 2026
  14. 075
    Growing Code and Proof Together: Verified Systems in Ten Hours Instead of a Year
    Inductive Deductive Synthesis: Enabling AI to Generate Formally Verified Systems
    Agarwal, Krentsel, Liu et al. · UC Berkeley·28 min·May 25, 2026
  15. 073
    When Three LLMs Talk to Each Other, Their Ideas Quietly Stop Moving
    Multi-LLM Systems Exhibit Robust Semantic Collapse
    Kong, Lai, Piao et al. · University of Toronto·28 min·May 23, 2026
  16. 072
    A Robot Made Graphene Without Help, And Caught Itself Hallucinating
    Qumus: Realization of An Embodied AI Quantum Material Experimentalist
    Shi, Zheng, Juan et al. · Princeton University·29 min·May 23, 2026
  17. 067
    An AI Just Solved a 1996 Erdős Problem—and the Simplest Agent Won
    Advancing Mathematics Research with AI-Driven Formal Proof Search
    Tsoukalas, Kovsharov, Shirobokov et al. · Google DeepMind·31 min·May 22, 2026
  18. 065
    One Loop to Optimize Them All: A Universal API for LLM-Driven Discovery
    optimize_anything: A Universal API for Optimizing any Text Parameter
    Agrawal, Lee, Tan et al. · UC Berkeley·27 min·May 22, 2026
  19. 048
    How a 30B Open Model Reached Olympiad Gold With the Right Recipe
    Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling
    Li, Zhan, Zhang et al. · Shanghai AI Laboratory / The Chinese University of Hong Kong·31 min·May 16, 2026
  20. 042
    An Agentic Scientific Computing System That Actually Remembers What It Learns
    GRAFT-ATHENA: Self-Improving Agentic Teams for Autonomous Discovery and Evolutionary Numerical Algorithms
    Toscano, Chai, Karniadakis · Division of Applied Mathematics·30 min·May 13, 2026
  21. 029
    Why Forty-Eight Percent on FrontierMath Isn't the Real Story in DeepMind's New Math Paper
    AI Co-Mathematician: Accelerating Mathematicians with Agentic AI
    Zheng, Glehn, Zwols et al. · Google DeepMind·20 min·May 08, 2026
  22. 002
    An AI Ran a Real Optics Lab for 21 Hours and Found a Transformer-Shaped Pattern in Light
    End-to-end autonomous scientific discovery on a real optical platform
    Yang, Chen, Zhao et al. · Zhejiang University·29 min·May 01, 2026

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