🎯 Key Takeaways for quick navigation: 00:41 🧠 AlphaGo, the Go-playing AI, learns from human experts by analyzing prior games and then plays millions of games against itself using reinforcement learning to improve. 02:25 🤖 A policy neural network is trained to predict good moves based on the state of the Go board. 03:41 🌐 The value function estimates the likelihood of winning from a given state, helping the AI plan ahead and make strategic moves. 06:10 🔄 AlphaGo uses reinforcement learning to refine its move policy and value estimation through self-play, simulating millions of games. 07:51 🤯 AlphaZero, a newer approach, relies solely on reinforcement learning and is even more advanced, eliminating the need for learning from human experts. Made with HARPA AI
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🎯 Key Takeaways for quick navigation:
00:41 🧠 AlphaGo, the Go-playing AI, learns from human experts by analyzing prior games and then plays millions of games against itself using reinforcement learning to improve.
02:25 🤖 A policy neural network is trained to predict good moves based on the state of the Go board.
03:41 🌐 The value function estimates the likelihood of winning from a given state, helping the AI plan ahead and make strategic moves.
06:10 🔄 AlphaGo uses reinforcement learning to refine its move policy and value estimation through self-play, simulating millions of games.
07:51 🤯 AlphaZero, a newer approach, relies solely on reinforcement learning and is even more advanced, eliminating the need for learning from human experts.
Made with HARPA AI