Over a year ago, OpenAI, the San Francisco–based for-profit AI research lab, announced that it had trained a robotic hand to manipulate a cube with remarkable dexterity.
That might not sound earth-shattering. But in the AI world, it was impressive for two reasons. First, the hand had taught itself how to fidget with the cube using a reinforcement-learning algorithm, a technique modeled on the way animals learn. Second, all the training had been done in simulation, but it managed to successfully translate to the real world. In both ways, it was an important step toward more agile robots for industrial and consumer applications.
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