yenchih/realai.org

title	permalink	mathjax
Welcome to Real AI	/	true

What's New

• 2017 August 9. DeepMind and Blizzard open StarCraft II as an AI research environment. (DeepMind; Starcraft II)
• 2017 July 26, Irina Higgins, Arka Pal, Andrei A. Rusu, Loic Matthey, Christopher P Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, and Alexander Lerchner. DARLA: Improving Zero-Shot Transfer in Reinforcement Learning. arXiv:1707.08475. video. (DeepMind; Transfer Learning)
• 2017 July 21, Marc G. Bellemare, Will Dabney, and Rémi Munos. A Distributional Perspective on Reinforcement Learning. arXiv:1707.06887. video. blog. (DeepMind; Model-Free Reinforcement Learning)
• 2017 July 19, Théophane Weber, Sébastien Racanière, David P. Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, David Silver, and Daan Wierstra. Imagination-Augmented Agents for Deep Reinforcement Learning. arXiv:1707.06203. (DeepMind; Reinforcement Learning Agents)
• 2017 July 19, Razvan Pascanu, Yujia Li, Oriol Vinyals, Nicolas Heess, Lars Buesing, Sebastien Racanière, David Reichert, Théophane Weber, Daan Wierstra, and Peter Battaglia. Learning model-based planning from scratch. arXiv:1707.06170. (DeepMind; Planning)
• 2017 July 11, Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P Burgess, Matthew Botvinick, Demis Hassabis, and Alexander Lerchner. SCAN: Learning Abstract Hierarchical Compositional Visual Concepts. arXiv:1707.03389. (DeepMind; Concept Learning)
• 2017 July 11, Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel. Meta-Learning with Temporal Convolutions. arXiv:1707.03141. (Meta-Learning)

Main Contents

1. AI and Society (Overview)

   1. Progress: Forecasts
   2. Timing
   3. Prosaic AI
   4. Roadmaps
   5. Impacts: Applications
   6. Industry
   7. Research Groups: Conferences
      1. DeepMind: Publications
      2. Google Brain: Publications
      3. FAIR: Publications
   8. Policies
   9. Safety
      1. Blog: Towards Safe and Beneficial Intelligence
      2. Effective Altruism
      3. Organizations

2. Understanding AI

   1. Philosophy of Intelligence

3. Course

   1. System: Google Compute Engine
   2. Programming in Python 3 with Jupyter Notebook
   3. Deep Learning in TensorFlow

4. Frontiers

   1. Outstanding Challenges
      1. Symbol Grounding
      2. World Model
      3. Planning
      4. Reasoning
   2. Learning Goals
      1. Concept Learning
      2. Continual Learning
      3. Few-Shot Learning
      4. Multi-Task Learning
      5. Predictive Learning
      6. Transfer Learning
      7. Unsupervised Learning
   3. Learning Techniques
      1. Attention
      2. Curriculum Learning
      3. Hierarchical Learning:
      4. Imitation Learning
      5. Meta-Learning
      6. Memory
   4. Reinforcement Learning
      1. Safe Reinforcement Learning
      2. Agents
      3. Model-Free Algorithms
      4. Intrinsic Motivation
         • Exploration
         • Empowerment
      5. Auxiliary Tasks
      6. Multi-Agent Learning
      7. General Reinforcement Learning
      8. Reinforcement Learning Implemtations
   5. Deep Learning
      1. Network Architecture
         • Architecture Search
         • Memory Augmented Neural Networks
         • Neural Interface
      2. Learning Rules
      3. Evolutionary Algorithms
      4. Adversarial Learning
      5. Generative Models
      6. Platforms
      7. Deep Learning Theory
      8. Deep Learning Implementations
   6. Experiments
      1. Vision
      2. Language: Program Induction
      3. Robotics: Autonomous Driving
      4. Games
      5. Automated Theorem Proving
   7. Neuroscience
   8. Alternative Theories

5. Research