AlphaGo Zero and AlphaZero master games through pure self-play
Confirmed
Importance: historic (5 of 5)The takeaway
AlphaGo Zero (Nature, October 2017) learned Go from scratch with no human games and beat the version that defeated Lee Sedol 100–0; AlphaZero (December 2017) generalized the method to chess and shogi.
Status
- Claim
Confirmed
- Our reporting
- High confidence
- Importance
- Historic (5 of 5)
- Last verified
- 29 September 2026
Your AI and this story
- GPT-6 AstraIn its training data
- Claude Opus 5.5In its training data
- Gemini 4 HydrogenIn its training data
- Grok 4.7In its training data
It happened before the cutoffs of all four assistants, so it can be in their training data.
Key facts
- AlphaGo Zero Nature paper published 18 October 2017
- AlphaGo Zero beat AlphaGo Lee 100–0
- AlphaZero preprint arXiv 1712.01815 (5 December 2017); Science paper December 2018
- AlphaZero defeated Stockfish (chess) and Elmo (shogi) after hours of self-play training
What happened
DeepMind showed that a single algorithm combining a neural network with tree search, trained only by playing against itself, reached superhuman strength in three classic board games.
Why it matters
Proved that learning from self-generated experience can exceed human knowledge — an idea that resurfaced in RL-trained reasoning models (o1, R1) in 2024–2025.
Sources
3 sources from 2 sites. Numbers match the chips in the text.
3 sources: 3 primary
Primary
Changes
- Filed