The Future of Go Summit: AlphaGo Pair Go & Team Go

Google DeepMind · Beginner ·🧠 Large Language Models ·8y ago
Watch AlphaGo team up with some of China's top pro players to explore the hidden mysteries of the game in two exciting match formats: Pair Go: where one Chinese pro will play against another with their own AlphaGo teammate, alternating moves, to take the concept of 'learning together' quite literally. Team Go: where AlphaGo and a five player team of China's top pro players work together to test AlphaGo's creativity and adaptability to their combined style. This is the livestream for Team & Pair Go to be played on Friday 26 May 08:30 CST (local), 01:30 BST and 12:30 CST (local), 05:30 BST.
Watch on YouTube ↗ (saves to browser)

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RL Course by David Silver - Lecture 9: Exploration and Exploitation
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10 RL Course by David Silver - Lecture 7: Policy Gradient Methods
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11 Google DeepMind: Ground-breaking AlphaGo masters the game of Go
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12 Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
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13 Match 2 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
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14 Match 1 15 min Summary - Google DeepMind Challenge Match
Match 1 15 min Summary - Google DeepMind Challenge Match
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15 Match 3 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
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16 Match 2 15 Minute Summary - Google DeepMind Challenge Match 2016
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17 Match 3 15 Minute Summary - Google DeepMind Challenge Match 2016
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18 Match 4 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
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19 Match 4 15 Minute Summary - Google DeepMind Challenge Match 2016
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20 Match 5 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
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21 Match 5 15 Minute Summary - Google DeepMind Challenge Match 2016
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22 DQN SPACE INVADERS
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23 DQN Breakout
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24 Asynchronous Methods for Deep Reinforcement Learning: Labyrinth
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25 Asynchronous Methods for Deep Reinforcement Learning: MuJoCo
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26 Asynchronous Methods for Deep Reinforcement Learning: TORCS
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27 DeepMind Health – Moorfields Eye Hospital London Collaboration
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28 Mustafa Suleyman – New Ways for Technology to Enhance Patient Care – King's Fund 5th July 2016
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29 DeepMind Health - Patient and Public Engagement Event
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30 Differentiable neural computer family tree inference task
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31 StarCraft II DeepMind feature layer API
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32 DeepMind Health – Partnership with the Royal Free London NHS Foundation Trust
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33 DeepMind Health – Michael Wise – a patient's journey
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34 Streams – a platform for a digital NHS
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35 DeepMind Lab - Nav Maze Level 1
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36 DeepMind Lab - Stairway to Melon Level
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37 DeepMind Lab - Laser Tag Space Bounce Level (Hard)
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38 Exploring the mysteries of Go with AlphaGo and China's top players
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39 Demis Hassabis on AlphaGo: its legacy and the 'Future of Go Summit' in Wuzhen, China
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40 The Future of Go Summit, Match One: Ke Jie & AlphaGo
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41 The Future of Go Summit: AlphaGo & Ke Jie match 1 moves analysis
The Future of Go Summit: AlphaGo & Ke Jie match 1 moves analysis
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42 The Future of Go Summit, Match Two: Ke Jie & AlphaGo
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43 The Future of Go Summit: AlphaGo & Ke Jie match 2 moves analysis
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The Future of Go Summit: AlphaGo Pair Go & Team Go
The Future of Go Summit: AlphaGo Pair Go & Team Go
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45 The Future of Go Summit, Match Three: Ke Jie & AlphaGo
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46 The Future of Go Summit: Pair Go moves analysis
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47 The Future of Go Summit: AlphaGo & Ke Jie match 3 moves analysis
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48 Emergence of Locomotion Behaviours in Rich Environments
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49 NIPS 2015 Symposium: Brains, Minds and Machines (Demis Hassabis)
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50 StarCraft II 'mini games' for AI research
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52 DeepMind open source PySC2 toolset for Starcraft II
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53 ICML 2017: Test of Time Award (Sylvain Gelly & David Silver)
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54 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 3rd AlphaGo vs Ke Jie game
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55 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 1st AlphaGo vs Ke Jie game
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56 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 2nd AlphaGo vs Ke Jie game
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58 AlphaGo Zero: Starting from scratch
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