Epoch AI is a non-profit research institute investigating the future of artificial intelligence. We examine the driving forces behind AI and forecast its economic and societal impact. In this podcast, our team shares insights from our research and discusses the evolving landscape of AI.
AI benchmarks saturate quickly, struggle to capture what we care about, and cost more than ever to build. But are they doomed? Greg Burnham, who leads Epoch's benchmarking team, and Tom Adamczewski, who developed MirrorCode, push back on the pessimism and dig into what the next generation of AI benchmarks could look like.
29 Jan 2026TRANSCRIPT
AI math capabilities could be jagged for a long time – Daniel Litt
Daniel Litt is a professor of mathematics at the University of Toronto. He has been a careful observer of AI’s progress toward accelerating mathematical discovery, sometimes skeptical and sometimes enthusiastic.
Topics we cover: the hardest problems models can solve today, whether there is convincing evidence that AI is speeding up math research, and what’s missing before AI might have a shot at solving Millennium Prize problems.
We also discuss how to measure progress in math, including Epoch AI’s new FrontierMath: Open Problems (https://epoch.ai/frontiermath/open-problems) benchmark which evaluates models on meaningful unsolved math research problems.
18 Dec 2025TRANSCRIPT
The EU and the not-so-simple macroeconomics of AI - Luis Garicano
Professor Luis Garicano discusses the EU's response to AI developments, the potential disruption of entry-level worker training, and the issues with the EU AI Act in an interview with Andrei Potlogea and Anson Ho.
1 Oct 2025TRANSCRIPT
What does economics actually tell us about AGI? – Phil Trammell
Economist Phil Trammell and Epoch AI researcher Anson Ho discuss economic theory related to AGI development and impacts, including flaws in current models and the potential for explosive economic growth in this interview.
5 Sept 2025TRANSCRIPT
Forecasting AI progress until 2040
Epoch AI researchers Jaime Sevilla and Yafah Edelman forecast AI progress until 2040, exploring potential breakthroughs and the implications of advanced AI agents and self-improving robots in this interview.
28 Mar 2025TRANSCRIPT
Is it 3 Years, or 3 Decades Away? Disagreements on AGI Timelines
When might AI truly transform our world, and what will that transformation look like? Even within our own research team, timelines for AGI differ substantially. In this episode, the two Epoch AI researchers with the longest and the shortest AGI timelines candidly examine the roots of their disagreements. Ege and Matthew dissect each other’s views, and discuss the evidence, intuitions and assumptions that lead to their timelines diverging by factors of two or three for key transformative milestones.
The hosts discuss:
Their median timelines for specific milestones (like sustained 5%+ GDP growth) that highlight differences between optimistic and cautious AI forecasts.
Whether AI-driven transformation will primarily result from superhuman researchers (a "country of geniuses") or widespread automation of everyday cognitive and physical tasks.
Moravec's Paradox today: Why practical skills like agency and common sense remain challenging for AI despite advancements in reasoning, and how this affects economic impact.
The interplay of hardware scaling, algorithmic breakthroughs, data availability (especially for agentic tasks), and the persistent challenge of transfer learning.
Prediction pitfalls and why conventional academic AI forecasting might miss the mark.
A world with AGI: moving from totalizing "single AGI" or "utopia vs. doom" narratives to consider economic forces, decentralized agents, and the co-evolution of AI and society.
16 Jan 2025
AI in 2030, Scaling Bottlenecks, and Explosive Growth
In our first episode of Epoch After Hours, Ege, Tamay and Jaime dig into what they expect AI to look like by 2030; why economists are underestimating the likelihood of explosive growth; the startling regularity in technological trends like Moore's Law; Moravec’s paradox, and how we might overcome it; and much more!
Inside a recent episode
Are AI benchmarks doomed?
Published 1 May 2026 · Transcript excerpt
[…] And then there was also reasoning models that came out and suddenly some math benchmarks were saturated. I think if we feel a little shell shocked that like right now, that's understandable, but probably like, I think if you just look around at the world, there's plenty of things systems can't do. […]
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