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MIT robotics engineers are accelerating robot learning across the board

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fatima khan
fatima khan
A brand new writer in the fields, Fatima has been taken under my electric spark's RGB- rich and ensures she doesn't engage in excessive snark on the website. It's unclear what command and Conquer are; however, she can talk for hours about the odd rhythm games, hardware, product reviews, and MMOs that were popular in the 2000s. Fatima has been creating various announcements, previews, and other content while here, but particularly enjoys writing regarding Products' latest news in the market she's currently addicted to. She is likely talking to an additional blogger with her current obsession right now.

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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