AlphaZero and MuZero

AlphaZero and MuZero are advanced AI systems that excel in various board and video games, contributing to real-world problem-solving.

AlphaZero: A key development towards general AI, AlphaZero taught itself chess, shogi, and Go, becoming the best player in history for each. Unlike AlphaGo, which analyzed numerous amateur games, AlphaZero learned by playing itself, using reinforcement learning to identify optimal moves.

MuZero: An advancement over AlphaZero, MuZero doesn't need predefined rules. It learns by modeling its environment, mastering games like Go, chess, shogi, and complex Atari games. This ability to plan represents significant progress for AI in tackling real-world challenges.

Proving AI’s Potential: AlphaZero and MuZero show that a single algorithm can adapt and discover new knowledge across diverse domains. They've contributed to faster algorithms for sorting, hashing, and matrix multiplication, and have enhanced YouTube video compression, demonstrating AI's broad potential in various fields.