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Like any proud father, Gary Marcus is only too happy to talk about the latest achievements of his two-year-old son. More unusually, he believes that the way his toddler learns and reasons may hold the key to making machines much more intelligent.

Sitting in the boardroom of a bustling Manhattan startup incubator, Marcus, a 45-year-old professor of psychology at New York University and the founder of a new company called Geometric Intelligence, describes an example of his boy’s ingenuity. From the backseat of the car, his son had seen a sign showing the number 11, and because he knew that other double-digit numbers had names like “thirty-three” and “seventy-seven,” he asked his father if the number on the sign was “onety-one.”

“He had inferred that there is a rule about how you put your numbers together,” Marcus explains with a smile. “Now, he had overgeneralized it, and he made a mistake, but it was a very sophisticated mistake.”

Marcus has a very different perspective from many of the computer scientists and mathematicians now at the forefront of artificial intelligence. He has spent decades studying the way the human mind works and how children learn new skills such as language and musicality. This has led him to believe that if researchers want to create truly sophisticated artificial intelligence—something that readily learns about the world—they must take cues from the way toddlers pick up new concepts and generalize. And that’s one of the big inspirations for his new company, which he’s running while on a year’s leave from NYU. With its radical approach to machine learning, Geometric Intelligence aims to create algorithms for use in an AI that can learn in new and better ways.

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