We humans take for granted our remarkable ability to predict things that happen around us. For example, consider Rube Goldberg machines: One of the reasons we enjoy them is because we can watch a chain-reaction of objects fall, roll, slide and collide, and anticipate what happens next.
But how do we do it? How do we effortlessly absorb enough information from the world to be able to react to our surroundings in real-time? And, as a computer scientist might then wonder, is this something that we can teach machines?
That last question has recently been partially answered by researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), who have developed a computational model that is just as accurate as humans at predicting how objects move.
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