Episode notes
Eric Jang walks through how to build AlphaGo from scratch, but with modern AI tools. Sometimes you understand the future better by stepping backward. AlphaGo is still the cleanest worked example of the primitives of intelligence: search, learning from experience, and self-play. You have to go back to 2017 to get insight into how the more general AIs of the future might learn. Once he explained how AlphaGo works, it gave us the context to have a discussion about how RL works in LLMs and how it could work better – naive policy gradient RL has to figure out which of the 100k+ tokens in your…
Dwarkesh Podcast
by Dwarkesh Patel · English · Tech & Science
Deeply researched interviews www.dwarkesh.com
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22 May 2026 · 1 hr 21 min
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David Reich – Why the Bronze Age was an inflection point in human evolution
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Reiner Pope – The math behind how LLMs are trained and served
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AI researchers debate how close we are to recursive self-improvement
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