Technology News, Trends, And Future-Ready Signals

Learning sparse neural networks through L₀ regularization

Interpretable and pedagogical examples

Learning a hierarchy

We’ve developed a hierarchical reinforcement learning algorithm that learns high-level actions useful for solving a rang...

Generalizing from simulation

Our latest robotics techniques allow robot controllers, trained entirely in simulation and deployed on physical robots,...

Asymmetric actor critic for image-based robot learning

Sim-to-real transfer of robotic control with dynamics randomization

Domain randomization and generative models for robotic grasping

Meta-learning for wrestling

We show that for the task of simulated robot wrestling, a meta-learning agent can learn to quickly defeat a stronger non...

Competitive self-play

We’ve found that self-play allows simulated AIs to discover physical skills like tackling, ducking, faking, kicking, cat...

Nonlinear computation in deep linear networks

Learning to model other minds

We’re releasing an algorithm which accounts for the fact that other agents are learning too, and discovers self-interest...

Learning with opponent-learning awareness