Evidence suggests that an ability to follow another person’s gaze emerges toward the end of a child’s first year. 1, Rao suspects, is getting a machine to look where an experimenter looks, just as a baby homes in on an adult’s visual perspective. Rao’s rationale: He wants to create a robot that sponges up knowledge baby-style. Not many cyberspecialists would forgo motherboards for mother love. Neural Networks Figuring out how to make robots, including the childlike iCub shown here, into social learners marks a new approach in artificial intelligence. Kids assume that robots engaged in such a game are social agents and know what they are doing. Bongard REAL TO KIDS In one study (depicted above), kids were more likely to follow a robot’s gaze toward a toy if they had watched the robot play an imitation game with an adult. Neural Networks A SMART COPYCAT A robot created by Josh Bongard (top) mimics the actions of another robot with the same body plan (middle), but it doesn’t try to replicate the movements of a third bot with body segments that are organized in a different way (bottom). Most children can follow a parent’s gaze by age 1. The Japanese-built robot is learning to track an instructor’s gaze to spot interesting objects. Time after time, tiny upturned heads tilt in whatever direction the caretakers look. Boldly going where most computer scientists fear to tread, Rajesh Rao watches intently as 1-year-olds lock eyes with their mothers in a developmental psychology lab at the University of Washington in Seattle.
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