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: 9781491974933
You might also like
Electronics All-in-One For Dummies, 3rd Edition
Open up a world of electronic possibilities with the easiest "how-to" guide available today If you're …
40 Algorithms Every Programmer Should Know
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools …
HBR Guide to Critical Thinking
Tackle complex situations with critical thinking. You're facing a problem at work. There are many ways …