articles

Deep dynamics models for dexterous manipulation

BAIR blog 03 Oct 2019

By Anusha Nagabandi Dexterous manipulation with multi-fingered hands is a grand challenge in robotics: the versatility of the human hand is as yet unrivaled by the capabilities of robotic systems...

Evaluating and testing unintended memorization in neural networks

BAIR blog 14 Aug 2019

By Nicholas Carlini It is important whenever designing new technologies to ask “how will this affect people’s privacy?” This topic is especially important with regard to machine learning, where...

Artificial intelligence agents begin to learn new skills from watching videos

Allie McFadden 29 Jun 2019

Whether it's tying a tie, making slime, fixing a leaky faucet, or some other daily task, millions of people watch how-to videos to learn new skills. Now, artificially intelligent (AI)&n...

Model-based reinforcement learning from pixels with structured latent variable models

BAIR blog 27 May 2019

By Marvin Zhang and Sharad Vikram Imagine a robot trying to learn how to stack blocks and push objects using visual inputs from a camera feed. In order to minimize cost and safety concerns, we want o...

Robots that learn to adapt

BAIR blog 15 May 2019

By Anusha Nagabandi and Ignasi Clavera Humans have the ability to seamlessly adapt to changes in their environments: adults can learn to walk on crutches in just a few seconds, people can adapt almos...

Robots that learn to use improvised tools

Sabine Hauert 22 Apr 2019

By Annie Xie In many animals, tool-use skills emerge from a combination of observational learning and experimentation. For example, by watching one another, chimpanzees can learn how to use twigs to...

Manipulation by feel

BAIR blog 12 Apr 2019

By Frederik Ebert and Stephen Tian Guiding our fingers while typing, enabling us to nimbly strike a matchstick, and inserting a key in a keyhole all rely on our sense of touch. It has been shown that...

Hot papers on Arxiv from the past month

Sabine Hauert 11 Apr 2019

What's hot on Arxiv? Here are the most tweeted papers from the past month....