#144 – Michael Littman: Reinforcement Learning and the Future of AI
Lex Fridman Podcast
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Reinforcement Learning Evolution: From AlphaGo to AlphaZero
This chapter examines the significant advancements in reinforcement learning through the examples of AlphaGo and AlphaZero, focusing on their differing training methods. It discusses the implications of self-play versus human-generated data in AI development and explores how these innovations challenge our understanding of intelligence. Additionally, the chapter raises important questions about the future potential of AI systems, their limitations across various domains, and the evolving relationship between human intelligence and algorithmic learning.
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