Epoch After Hours

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.

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...

Professor Luis Garicano isn’t your usual academic economist. Academically, his theories have heavily influenced how modern economists understand the structure of firms and the labor market. But his influence hasn’t been confined to the ivory towers of academia — Luis spent three years in the EU parliament, seeing first-hand how EU policy gets made. This has given him an unusually grounded view of...

Stanford economist Phil Trammell has been rigorously thinking about the intersection of economic theory and AI (incl. AGI) for over five years, long before the recent surge of interest in large language models. In this episode of Epoch After Hours, Phil Trammell and Epoch AI researcher Anson Ho discuss what economic theory really has to say about the development and impacts of AGI: what current ec...

What will AI progress look like over the next 15 years? Informed by current trends, Epoch AI researchers Jaime Sevilla and Yafah Edelman argue that the default expectation should be wild. They discuss whether AI will solve the Riemann Hypothesis in 5 years, what AI agents will be able to do in 2030, and what happens if we have 100,000 self-improving robots. They also explore what might make progre...

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 assumptio...

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!