MIT engineers have come up with a general code tool to optimise robot learning. They’re calling it an “automated recipe for success,” one that can be applied to “virtually any autonomous robotic system” to accelerate the development of walking robots, self-driving cars, and other important robotics projects. 

The standard process for robotics engineers is a monotonous one; there’s a great deal of trial and error involved in perfecting robot movement (opens in new tab), as we’ve seen in the past. It’s expected when engineers go into a robotics project that the AI will need to repeat the same movements over and over before it becomes even vaguely adept at completing a given task. 

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