AlphaGo
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AlphaGo is a computer program that plays the board game Go.[1][2] It was made by DeepMind Technologies (Google affiliate).[3] This program became famous due to the victories against professional players.[4][5]
Many new technologies were used to create AlphaGo, including deep learning,[6] optimization,[7] and the Monte Carlo algorithm.[8]
After the release of AlphaGo, DeepMind Technologies has made powered versions such as the AlphaGo Zero[9][10] and the AlphaZero:[11][12][13][14][15] AlphaZero is a self-taught program.[16] This means that it became powerful without human guidance.
The following table is the summary of AlphaGo achievements (including its variants).
Versions | Hardware | Elo rating | Date | Results |
---|---|---|---|---|
AlphaGo versus Fan Hui | 176 GPUs,[18]distributed | 3,144[19] | Oct 2015 | 5:0 against Fan Hui (professional player) |
AlphaGo versus Lee Sedol | 48 Tensor processing units (TPUs),[18] distributed | 3,739[19] | Mar 2016 | 4:1 against Lee Sedol (former Korean & world champion) |
AlphaGo Master | 4 TPUs,[18] single machine | 4,858[19] | May 2017 | 60:0 against professional players |
AlphaGo Zero (40 block) | 4 TPUs,[18] single machine | 5,185[19] | Oct 2017 | 100:0 against AlphaGo version that defeated Lee Sedol 89:11 against AlphaGo Master |
AlphaZero (20 block) | 4 TPUs, single machine | 5,018 | Dec 2017 | 60:40 against AlphaGo Zero (20 block) |
After the appearance of AlphaGo, several research groups have created computer Go programs with similar technical viewpoints.
This was made by Facebook.[21] The source codes are available on GitHub.[22]
This was made in Japan.[23][24] Nihon Ki-in was also involved in its research and development.