DeepMind's new robots learned how to teach themselves

The minute hand on the robot apocalypse clock just inched a little closer to midnight. DeepMind, the Google sister-company responsible for the smartest AI on the planet, just taught machines how to figure things out for themselves. AI that only exists to parse data, such as neural networks that decide whether something is a hotdog or not, have relatively little to concentrate on compared to the near-infinite number of things a physical robot has to figure out. To solve this problem DeepMind built a new learning paradigm for AI-powered robots called'Scheduled Auxiliary Control (SAC-X).' This new paradigm gives robots a simple goal like'clean up this playground' and rewards it for completion. The auxiliary tasks we define follow a general principle: they encourage the agent to explore its sensor space.