Now that artificial intelligence researchers have used reinforcement learning and deep learning to achieve several notable successes in the areas of perception and action, some AI scientists are turning to the brain for inspiration about what to build next.
In this report, author Jack Clark interviews five prominent AI researchers to learn about the growing connections between AI and cognitive science, neuroscience, and developmental psychology.
Table of Contents
- Geoff Hinton: Adapting Ideas from Neuroscience for AI
- Dharmendra Modha: Brain-Inspired Chips for Better AI, What Comes After Von Neumann, and the Need for Fault Tolerance
- Adam Marblestone: What the Brain Tells Us About Building Unsupervised Learning Systems, and How AI Can Guide Neuroscience Research
- Leila Wehbe: What Harry Potter and Recurrent Neural Networks Tell Us About the Brain’s Inner Narrative
- Tom Griffiths: Why People Have Surprisingly Intelligent Intuitions, and What AI Researchers Can Learn from That
- Title: Artificial Intelligence: Teaching Machines to Think Like People
- Release date: April 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491990681