The New York Times
talks about the recent news of a bot that solved a Rubik’s Cube without being told how to accomplish the goal.
Last week, on the third floor of a small building in San Francisco’s Mission District, a woman scrambled the tiles of a Rubik’s Cube and placed it in the palm of a robotic hand.
The hand began to move, gingerly spinning the tiles with its thumb and four long fingers. Each movement was small, slow and unsteady. But soon, the colors started to align. Four minutes later, with one more twist, it unscrambled the last few tiles, and a cheer went up from a long line of researchers watching nearby.
The researchers worked for a prominent artificial intelligence lab, OpenAI, and they had spent several months training their robotic hand for this task.
Though it could be dismissed as an attention-grabbing stunt, the feat was another step forward for robotics research. Many researchers believe it was an indication that they could train machines to perform far more complex tasks. That could lead to robots that can reliably sort through packages in a warehouse or to cars that can make decisions on their own.
“Solving a Rubik’s Cube is not very useful, but it shows how far we can push these techniques,” said Peter Welinder, one of the researchers who worked on the project. “We see this as a path to robots that can handle a wide variety of tasks.”
A robot that can solve a Rubik’s Cube is not new. Researchers previously designed machines specifically for the task — devices that look nothing like a hand — and they can solve the puzzle in less than a second. But building devices that work like a human hand is a painstaking process in which engineers spend months laying down rules that define each tiny movement.
The OpenAI project was an achievement of sorts because its researchers did not program each movement into their robotic hand. That might take decades, if not centuries, considering the complexity of a mechanical device with a thumb and four fingers. The lab’s researchers built a computer system that learned to solve the Rubik’s Cube largely on its own.
“What is exciting about this work is that the system learns,” said Jeff Clune, a robotics professor at the University of Wyoming. “It doesn’t memorize one way to solve the problem. It learns.”
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