Advancing AI by teaching robots to learn


Robotics provides important opportunities for advancing artificial intelligence, because teaching machines to learn on their own in the physical world will help us develop more capable and flexible AI systems in other scenarios as well. Working with a variety of robots — including walking hexapods, articulated arms, and robotic hands fitted with tactile sensors — Facebook AI researchers are exploring new techniques to push the boundaries of what artificial intelligence can accomplish.

Doing this work means addressing the complexity inherent in using sophisticated physical mechanisms and conducting experiments in the real world, where the data is noisier, conditions are more variable and uncertain, and experiments have additional time constraints (because they cannot be accelerated when learning in a simulation). These are not simple issues to address, but they offer useful test cases for AI.

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These walking robots could help humans get back on their feet again


Bipedal robots could explore Mars one day. But first they’re teaching scientists at Caltech’s Amber Lab important lessons about helping humans here on Earth.

Watching a robot trip and fall makes my heart sink. The worst part about it? I’m the one responsible.

I’m standing in a Pasadena, California, lab filled with bipedal (or two legged) robots. A researcher challenges me to try and trip a 5-foot, semihumanoid robot called Amber that’s walking on a treadmill. It’s attached with a rope to a railing above as it walks in place, so it’s only going to fall forward or backward if I’m too heavy-handed.

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