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How to Train Your Robot with Brain Oops Signals

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Thomas Miller
How to Train Your Robot with Brain Oops Signals

Baxter the robot can tell the difference between right and wrong actions without its human handlers ever consciously giving a command or even speaking a word. The robot’s learning success relies upon a system that interprets the human brain’s “oops” signals to let Baxter know if a mistake has been made.

The new twist on training robots comes from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Boston University. Researchers have long known that the human brain generates certain error-related signals when it notices a mistake. They created machine-learning software that can recognize and classify those brain oops signals from individual human volunteers within 10 to 30 milliseconds—a way of creating instant feedback for Baxter the robot when it sorted paint cans and wire spools into two different bins in front of the humans.

“Imagine being able to instantaneously tell a robot to do a certain action, without needing to type a command, push a button or even say a word,” said Daniela Rus, director of CSAIL at MIT, in a press release. “A streamlined approach like that would improve our abilities to supervise factory robots, driverless cars and other technologies we haven’t even invented yet.”

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