This is a linkpost for Epoch After Hours’ podcast episode Is it 3 Years, or 3 Decades Away? Disagreements on AGI Timelines by Ege Erdil and Matthew Barnett, which was released on 28 March 2025. The episode is on YouTube, Apple Podcasts, Spotify, Amazon Music, Pocket Casts, and Overcast. Ege is the 1st author of the paper about Epoch AI’s compute-centric model of AI automation, which was announced on 21 March 2025, and also discussed on the Future of Life Institute Podcast. I broadly agree with Ege on AI timelines, and like Ege’s and Matthew’s takes on AI risk. See AI 2027 for the case for short AI timelines, which was discussed on the Dwarkesh Podcast.
Blurb
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, two Epoch AI researchers with relatively long and short 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.
AI timelines
Ege
Yeah, I mean, I guess one way to try to quantify this is when you expect, I don’t know, we often talk about big acceleration, economic growth. One way to quantify is when do you expect, maybe US GDP growth, maybe global GDP growth to be faster than 5% per year for a couple of years in a row. Maybe that’s one way to think about it. And then you can think about what is your median timeline until that happens. I think if you think about like that, I would maybe say more than 30 years or something. Maybe a bit less than 40 years by this point. So 35. Yeah. And I’m not sure, but I think you might say like 15 or 20 years.
Matthew
Yeah, I’d say closer to 10 to 15 for the 5% threshold, I think especially so when you talk about things like 30%, which I think is a natural one that especially like Epoch has talked a lot about before for that one. I think that median is almost maybe misleading in a certain sense because I have uncertainty about. Even if we had like some sort of system that was just as good as humans at everything, and it just cost maybe 10e15 FLOP per second to run, then even if we had that, I’m still quite unsure whether that would lead to greater than 30% year on year economic growth.
Here is a long AI summary of the podcast.