Watch a Robot AI Beat World-Class Curling Competitors

Artificial intelligence still needs to bridge the “sim-to-real” gap. Deep-learning techniques that are all the rage in AI log superlative performances in mastering cerebral games, including chess and Go, both of which can be played on a computer. But translating simulations to the physical world remains a bigger challenge.

A robot named Curly that uses “deep reinforcement learning”—making improvements as it corrects its own errors—came out on top in three of four games against top-ranked human opponents from South Korean teams thatincluded a women’s team and a reserve squad for the national wheelchair team. (No brooms were used).

One crucial finding was that the AI system demonstrated its ability to adapt to changing ice conditions. “These results indicate that the gap between physics-based simulators and the real world can be narrowed,” the joint South Korean-German research team wrote in Science Robotics on September 23. 

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Gary Stix is the former senior editor of mind and brain topics at Scientific American.

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Jeffery DelViscio is currently chief multimedia editor/executive producer at Scientific American. He is former director of multimedia at STAT, where he oversaw all visual, audio and interactive journalism. Before that he spent more than eight years at the New York Times, where he worked on five different desks across the paper. He holds dual master's degrees in journalism and in Earth and environmental sciences from Columbia University. He has worked onboard oceanographic research vessels and tracked money and politics in science from Washington, D.C. He was a Knight Science Journalism Fellow at the Massachusetts Institute of Technology in 2018. His work has won numerous awards, including two News and Documentary Emmy Awards.

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