AlphaGo Zero: Discovering new knowledge

Google DeepMind · Beginner ·📰 AI News & Updates ·8y ago

Key Takeaways

The video discusses AlphaGo Zero, a computer program that learned to play the game of Go from scratch without human data, and its ability to discover new knowledge and achieve a high level of performance. The program uses tabula rasa learning, starting from a blank slate and figuring out how to play the game through self-play.

Full Transcript

[Music] alphago has been through many generations now the first generation of alphago which we published in our original nature paper was able to beat a professional player for the first time now we have the final version of alphago alphago zero which has learned completely from scratch from first principles without using any human data and has achieved the highest level of performance overall the most important idea in alphago zero is that it learns completely tabula rasa that means it starts completely from a blank slate and figures out for itself only from self play and without any human knowledge without any human data without any human examples or features or intervention from humans it discovers how to play the game of Go completely from first principles so tabula rasa learning is extremely important to our goals and ambitions that deep mind and the reason is that if you can achieve tabula rasa learning you really have an agent that can be transplanted from the game of go to any other domain you untie yourself from the specifics of the domain you're in and you come up with an algorithm which is so general that it can be applied anywhere for us the idea of alphago is not to go out and defeat humans but actually to discover what it means to to do science and for a program to be able to learn for itself what knowledge is so what we starts to see was that alphago zero not only rediscovered the common patterns and openings that humans tend to play these joseki patterns that humans play in the corners it also learned them discovered them and ultimately discarded them in preference for its own variants which humans don't even know about or play at the moment and so we can say that really what's happened is that in a short space of time alphago zero has understood all of the go knowledge that has been accumulated by humans over thousands of years of playing and it's analyzed it and it started to look at it and discover much of this knowledge for itself and sometimes it's chosen to actually go beyond that and come up with something which the humans hadn't even discovered in this time period and developed new pieces of knowledge which were creative and and novel in many ways we're all really excited by how far alpha go zero has cotton but I think what we're most excited about is how far it can go in the real world that the fact that we've seen a program can achieve a very high level of performance in domain as complicated and challenging as go should mean that now we can start to tackle some of the most challenging and impactful problems for Humanity

Original Description

DeepMind's Professor David Silver describes AlphaGo Zero, the latest evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is arguably the strongest Go player in history. Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0. If similar techniques can be applied to other structured problems, such as protein folding, reducing energy consumption or searching for revolutionary new materials, the resulting breakthroughs have the potential to positively impact society. Find out more here: https://deepmind.com/blog/alphago-zero-learning-scratch
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Uploads from Google DeepMind · Google DeepMind · 48 of 60

1 RL Course by David Silver - Lecture 8: Integrating Learning and Planning
RL Course by David Silver - Lecture 8: Integrating Learning and Planning
Google DeepMind
2 RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning
RL Course by David Silver - Lecture 1: Introduction to Reinforcement Learning
Google DeepMind
3 RL Course by David Silver - Lecture 2: Markov Decision Process
RL Course by David Silver - Lecture 2: Markov Decision Process
Google DeepMind
4 RL Course by David Silver - Lecture 5: Model Free Control
RL Course by David Silver - Lecture 5: Model Free Control
Google DeepMind
5 RL Course by David Silver - Lecture 6: Value Function Approximation
RL Course by David Silver - Lecture 6: Value Function Approximation
Google DeepMind
6 RL Course by David Silver - Lecture 4: Model-Free Prediction
RL Course by David Silver - Lecture 4: Model-Free Prediction
Google DeepMind
7 RL Course by David Silver - Lecture 3: Planning by Dynamic Programming
RL Course by David Silver - Lecture 3: Planning by Dynamic Programming
Google DeepMind
8 RL Course by David Silver - Lecture 10: Classic Games
RL Course by David Silver - Lecture 10: Classic Games
Google DeepMind
9 RL Course by David Silver - Lecture 7: Policy Gradient Methods
RL Course by David Silver - Lecture 7: Policy Gradient Methods
Google DeepMind
10 Google DeepMind: Ground-breaking AlphaGo masters the game of Go
Google DeepMind: Ground-breaking AlphaGo masters the game of Go
Google DeepMind
11 Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Google DeepMind
12 Match 2 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 2 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Google DeepMind
13 Match 1 15 min Summary - Google DeepMind Challenge Match
Match 1 15 min Summary - Google DeepMind Challenge Match
Google DeepMind
14 Match 3 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 3 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Google DeepMind
15 Match 2 15 Minute Summary - Google DeepMind Challenge Match 2016
Match 2 15 Minute Summary - Google DeepMind Challenge Match 2016
Google DeepMind
16 Match 3 15 Minute Summary - Google DeepMind Challenge Match 2016
Match 3 15 Minute Summary - Google DeepMind Challenge Match 2016
Google DeepMind
17 Match 4 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 4 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Google DeepMind
18 Match 4 15 Minute Summary - Google DeepMind Challenge Match 2016
Match 4 15 Minute Summary - Google DeepMind Challenge Match 2016
Google DeepMind
19 Match 5 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 5 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Google DeepMind
20 Match 5 15 Minute Summary - Google DeepMind Challenge Match 2016
Match 5 15 Minute Summary - Google DeepMind Challenge Match 2016
Google DeepMind
21 DQN SPACE INVADERS
DQN SPACE INVADERS
Google DeepMind
22 DQN Breakout
DQN Breakout
Google DeepMind
23 Asynchronous Methods for Deep Reinforcement Learning: Labyrinth
Asynchronous Methods for Deep Reinforcement Learning: Labyrinth
Google DeepMind
24 Asynchronous Methods for Deep Reinforcement Learning: MuJoCo
Asynchronous Methods for Deep Reinforcement Learning: MuJoCo
Google DeepMind
25 Asynchronous Methods for Deep Reinforcement Learning: TORCS
Asynchronous Methods for Deep Reinforcement Learning: TORCS
Google DeepMind
26 Differentiable neural computer family tree inference task
Differentiable neural computer family tree inference task
Google DeepMind
27 StarCraft II DeepMind feature layer API
StarCraft II DeepMind feature layer API
Google DeepMind
28 DeepMind Health – Partnership with the Royal Free London NHS Foundation Trust
DeepMind Health – Partnership with the Royal Free London NHS Foundation Trust
Google DeepMind
29 DeepMind Health – Michael Wise – a patient's journey
DeepMind Health – Michael Wise – a patient's journey
Google DeepMind
30 Streams – a platform for a digital NHS
Streams – a platform for a digital NHS
Google DeepMind
31 DeepMind Lab - Nav Maze Level 1
DeepMind Lab - Nav Maze Level 1
Google DeepMind
32 DeepMind Lab - Stairway to Melon Level
DeepMind Lab - Stairway to Melon Level
Google DeepMind
33 DeepMind Lab - Laser Tag Space Bounce Level (Hard)
DeepMind Lab - Laser Tag Space Bounce Level (Hard)
Google DeepMind
34 Exploring the mysteries of Go with AlphaGo and China's top players
Exploring the mysteries of Go with AlphaGo and China's top players
Google DeepMind
35 Demis Hassabis on AlphaGo: its legacy and the 'Future of Go Summit' in Wuzhen, China
Demis Hassabis on AlphaGo: its legacy and the 'Future of Go Summit' in Wuzhen, China
Google DeepMind
36 The Future of Go Summit: AlphaGo & Ke Jie match 1 moves analysis
The Future of Go Summit: AlphaGo & Ke Jie match 1 moves analysis
Google DeepMind
37 The Future of Go Summit: AlphaGo & Ke Jie match 2 moves analysis
The Future of Go Summit: AlphaGo & Ke Jie match 2 moves analysis
Google DeepMind
38 The Future of Go Summit: Pair Go moves analysis
The Future of Go Summit: Pair Go moves analysis
Google DeepMind
39 The Future of Go Summit: AlphaGo & Ke Jie match 3 moves analysis
The Future of Go Summit: AlphaGo & Ke Jie match 3 moves analysis
Google DeepMind
40 Emergence of Locomotion Behaviours in Rich Environments
Emergence of Locomotion Behaviours in Rich Environments
Google DeepMind
41 StarCraft II 'mini games' for AI research
StarCraft II 'mini games' for AI research
Google DeepMind
42 Trained and untrained agents play StarCraft II full 1vs1 game
Trained and untrained agents play StarCraft II full 1vs1 game
Google DeepMind
43 DeepMind open source PySC2 toolset for Starcraft II
DeepMind open source PySC2 toolset for Starcraft II
Google DeepMind
44 ICML 2017: Test of Time Award (Sylvain Gelly & David Silver)
ICML 2017: Test of Time Award (Sylvain Gelly & David Silver)
Google DeepMind
45 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 3rd AlphaGo vs Ke Jie game
Ke Jie and DeepMind's Go Ambassador Fan Hui review the 3rd AlphaGo vs Ke Jie game
Google DeepMind
46 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 1st AlphaGo vs Ke Jie game
Ke Jie and DeepMind's Go Ambassador Fan Hui review the 1st AlphaGo vs Ke Jie game
Google DeepMind
47 Ke Jie and DeepMind's Go Ambassador Fan Hui review the 2nd AlphaGo vs Ke Jie game
Ke Jie and DeepMind's Go Ambassador Fan Hui review the 2nd AlphaGo vs Ke Jie game
Google DeepMind
AlphaGo Zero: Discovering new knowledge
AlphaGo Zero: Discovering new knowledge
Google DeepMind
49 AlphaGo Zero: Starting from scratch
AlphaGo Zero: Starting from scratch
Google DeepMind
50 Defining principles for tech companies in the NHS: DeepMind Health's Collaborative Listening Summit
Defining principles for tech companies in the NHS: DeepMind Health's Collaborative Listening Summit
Google DeepMind
51 A systems neuroscience approach to building AGI - Demis Hassabis, Singularity Summit 2010
A systems neuroscience approach to building AGI - Demis Hassabis, Singularity Summit 2010
Google DeepMind
52 Retour de Rémi Munos en France et ouverture de DeepMind Paris
Retour de Rémi Munos en France et ouverture de DeepMind Paris
Google DeepMind
53 Grid cells - Caswell Barry, UCL
Grid cells - Caswell Barry, UCL
Google DeepMind
54 DeepMind Health Research and Moorfields Eye Hospital NHS Foundation Trust: What our research shows
DeepMind Health Research and Moorfields Eye Hospital NHS Foundation Trust: What our research shows
Google DeepMind
55 DeepMind Health Research and Moorfields Eye Hospital NHS Foundation Trust: A Patient's Story
DeepMind Health Research and Moorfields Eye Hospital NHS Foundation Trust: A Patient's Story
Google DeepMind
56 Deep Learning 3: Neural Networks Foundations
Deep Learning 3: Neural Networks Foundations
Google DeepMind
57 Deep Learning 5: Optimization for Machine Learning
Deep Learning 5: Optimization for Machine Learning
Google DeepMind
58 Deep Learning 8: Unsupervised learning and generative models
Deep Learning 8: Unsupervised learning and generative models
Google DeepMind
59 Reinforcement Learning 1: Introduction to Reinforcement Learning
Reinforcement Learning 1: Introduction to Reinforcement Learning
Google DeepMind
60 Deep Learning 2: Introduction to TensorFlow
Deep Learning 2: Introduction to TensorFlow
Google DeepMind

AlphaGo Zero is a computer program that learned to play the game of Go from scratch without human data, achieving a high level of performance and discovering new knowledge. This technology has the potential to tackle some of the most challenging and impactful problems for humanity.

Key Takeaways
  1. Learn about the basics of AlphaGo Zero and its tabula rasa learning approach
  2. Understand how self-play is used to improve the program's performance
  3. Discover how AlphaGo Zero is able to discover new knowledge and achieve a high level of performance
  4. Explore the potential applications of this technology in other domains
💡 The ability of AlphaGo Zero to learn from scratch and discover new knowledge has significant implications for the development of artificial intelligence and its potential applications.

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