Can Super Mario Save Artificial Intelligence?
Human brains are remarkably inefficient in some key ways: our memories are lousy; our grasp of logic is shallow, and our capacity to do arithmetic is dismal. Our collective cognitive shortcomings are so numerous I’ve written a book about them. And yet, in some ways, we continue to far outstrip the very silicon-based computers that so thoroughly kick our carbon-based behinds in arithmetic, logic, and memory.
Take, for example, our capacity to flexibly learn new things. Sure, I.B.M. has built monstrously fast computers to play chess and “Jeopardy!,” but Deep Blue and Watson were purpose-built, dedicated machines that excel only at the particular games for which they were built; Watson, built to conquer the game show “Jeopardy!,” would be hard-pressed to play chess. Your average ten-year-old, in contrast, can learn to play any number of games and well, if not quite at a world-class level.
How do human beings manage to be so flexible, and what would it take to make a machine equally supple in learning new things?