AlphaGo & Machine Intuition
AI conquers a game with more moves than atoms in the universe.
Explore this event on the interactive timeline →DeepMind's AlphaGo defeated 18-time world champion Lee Sedol in the ancient game of Go. Unlike Chess, Go cannot be solved by brute-force calculation; AlphaGo proved that Deep Learning could successfully simulate human intuition and creativity.
Key Numbers
- AI Capability (1997 Chess)
- Brute-force calculation
- AI Capability (2016 Go)
- Deep-learning intuition
Verified Facts
- The search space in Go is roughly 10^170—vastly larger than the number of atoms in the observable universe. Traditional algorithms were paralyzed by this complexity.
- AlphaGo used a combination of neural networks (to "evaluate" the board visually) and Monte Carlo Tree Search. It was trained on millions of human games, and then played millions of games against itself to learn strategies humans had never conceived of.
- During Game 2, AlphaGo played "Move 37," a move so alien and counter-intuitive that experts thought it was a glitch. It turned out to be a brilliant winning strategy, marking the first time AI displayed undeniable, superhuman creativity.