Massimiliano “Max” Versace sits in a conference room at BU’s Neuromorphics Laboratory. The lab director is holding one of the lab’s frequent visitors—his infant son, who is looking intently at his father. “This is a great example of a general-purpose learning machine,” Versace says—and he is only half joking.
Versace has been discussing the lab’s primary goal: to build an artificial intelligence that is smarter than any robot yet created. As every parent knows, babies have astonishing brains; they take in a wealth of information from the senses and over time learn how to move around, communicate, and begin to make independent decisions. Compared to a baby—or even the simplest animal—computers are sorely lacking in learning ability. Even sophisticated robots and software programs can accomplish only tasks they’re specifically programmed to do, and their ability to learn is limited by their programming. A Roomba® may manage to clean your house with random movements, but it doesn’t learn which rooms collect the most dirt or what is the least distracting time of day to clean.