AlphaGo: How AI Mastered Go
For decades, Go was considered the hardest classic board game for computers to play. That changed in 2016, when DeepMind's AlphaGo beat one of the world's best players — and then a later version taught itself the game from scratch, reshaping how people think about both Go and AI.
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Why Go was so hard for computers
The 19×19 board has more legal positions than there are atoms in the observable universe, so the brute-force search that cracked chess simply does not work for Go. Good moves often come down to judgment about shape and influence that resisted hand-written rules. Progress needed a different approach: machine learning.
The Lee Sedol match
In March 2016, AlphaGo played a five-game match in Seoul against Lee Sedol, one of the strongest players of his generation, and won 4–1. One of its moves — the famous "move 37" in game two — was so unusual that commentators first thought it was a mistake, before it proved to be brilliant. Lee Sedol's single win, in game four, is still celebrated.
AlphaGo Zero and what changed
A later version, AlphaGo Zero, learned Go with no human games at all — only the rules and millions of games against itself — and became even stronger. It changed professional opening theory almost overnight, and its self-play method influenced AI research far beyond board games.
Frequently asked questions
- When did AlphaGo beat a human champion?
- AlphaGo beat European champion Fan Hui in late 2015, then defeated top professional Lee Sedol 4–1 in March 2016, and later beat world number one Ke Jie in 2017.
- How was AlphaGo different from chess computers?
- Chess engines rely heavily on brute-force search. Go has far too many positions for that, so AlphaGo combined neural networks that evaluate positions and moves with a guided search — learning judgment rather than only calculating.
- Can I play against an engine as strong as AlphaGo here?
- No. GoingBoard's computer opponent is a relaxed practice partner, not a top engine. It is a friendly way to learn and play, not a match for a system like AlphaGo.
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