Future of Life Institute Podcast How Close Are We to AGI? Inside Epoch's GATE Model (with Ege Erdil)
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Mar 28, 2025 
Ege Erdil, a senior researcher at Epoch AI, dives deep into the fascinating realm of AI development and the new GATE model. He explores how evolution and brain efficiency shape our understanding of AGI requirements. Ege discusses the economic impacts of AI on labor markets and wages, highlighting which jobs are most vulnerable to automation. The conversation also touches on Moravec’s Paradox and the challenges of training complex AI models with long-term planning capabilities, emphasizing the uncertainty surrounding AI timelines and future advancements.
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GATE Model
- GATE models AI development by simulating economic impacts of compute scaling and automation.
- It helps clarify thinking about AI by revealing inconsistencies in beliefs about software progress and compute scaling.
Key GATE Parameters
- R&D assumptions, economic complementarity, and adjustment costs significantly influence GATE's predictions.
- Doubling research efforts doesn't guarantee doubled progress due to parallelization challenges and limited researcher supply.
Default GATE Predictions
- Default GATE parameters predict substantial economic impacts from AI within 3-4 years and full automation in 10-15 years.
- These predictions hinge on the compute required for AGI, estimated around 10^36 FLOP, aligning with evolutionary and biological arguments.