Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in …

Traditionally, cognitive and computer scientists have viewed intelligence solipsistically, as a
property of unitary agents devoid of social context. Given the success of contemporary …

In recent years, artificial intelligence (AI) has made incredible progress. Advanced
foundation models such as ChatGPT can offer powerful conversation, in-context learning …

We investigated whether deep reinforcement learning (deep RL) is able to synthesize
sophisticated and safe movement skills for a low-cost, miniature humanoid robot that can be …

Large language models (LLMs) have been transformative. They are pretrained foundational
models that are self-supervised and can be adapted with fine-tuning to a wide range of …

High-quality motion capture datasets are now publicly available, and researchers have used
them to create kinematics-based controllers that can generate plausible and diverse human …

Movement is how people interact with and affect their environment. For realistic character
animation, it is necessary to synthesize such interactions between virtual characters and …

We present a physics-based humanoid controller that achieves high-fidelity motion imitation
and fault-tolerant behavior in the presence of noisy input (eg pose estimates from video or …

Abstract Knowledge from animals and humans inspires robotic innovations. Numerous
efforts have been made to achieve agile locomotion in quadrupedal robots through classical …

DribbleBot (Dexterous Ball Manipulation with a Legged Robot) is a legged robotic system
that can dribble a soccer ball under the same real-world conditions as humans. We identify …