Om denne podcast
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.
Episoder
- Are AI benchmarks doomed? · 1 t. 5 min. · Episode 7AI 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…
- AI math capabilities could be jagged for a long time – Daniel Litt · 2 t. 11 min. · Episode 6Daniel 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…
- The EU and the not-so-simple macroeconomics of AI - Luis Garicano · 1 t. 25 min. · Episode 5Professor Luis Garicano isn’t your usual academic economist. Academically, his theories have heavily influenced how modern economists understand the structure of firms and the…
- What does economics actually tell us about AGI? – Phil Trammell · 1 t. 49 min. · Episode 4Stanford 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…
- Forecasting AI progress until 2040 · 1 t. 39 min. · Episode 3What 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…
- Is it 3 Years, or 3 Decades Away? Disagreements on AGI Timelines · 4 t. 3 min. · Episode 2When 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…
- AI in 2030, Scaling Bottlenecks, and Explosive Growth · 2 t. 2 min. · Episode 1In 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…
