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: Never underestimate a computer. Never overestimate one either. For many years Garry Kasparov, a world chess champion, said that a computer would never beat him (or, indeed, any other human in his position). In May 1997 he had to eat his words. Deep Blue, an invention of IBM, did just that.

This was impressive, but it demonstrated processing power rather than intelligence. Computers are generally good at solving specific problems, not specifically good at solving general ones. Deep Blue did not learn to play chess from experience. It was painstakingly programmed with thousands of “tactical weighting errors” devised by human experts. So whenever it selected a move, it used these to work through multitudes of possible options and their possible responses. No one is quite sure how Mr Kasparov’s processor operates but it certainly does not do that. One theory goes that the human brain recognises strategic positions in a general way, and that this helps to reduce the problem to a manageable size.

Thomas Serre and his colleagues at the Massachusetts Institute of Technology have built a computer processing system that tries to work in this general way. Among the tasks that computers are bad at is recognising broad categories of images. Tell one to search for something specific, such as a rectangle or even a human face, and it can make a reasonable fist of the task. Ask it to find “animals” among photographs of dragonflies, trees, sharks, cars and monkeys, and it falls over. Indeed a monkey—or even a human baby—would leave it in the dust. That was how it used to be. But as Dr Serre describes in last week’s Proceedings of the National Academy of Sciences, his computer handles this problem rather well. In a recent test it even did a little better than humans.

Picture perfect

Given the briefest of glances at a picture, most people believe they have not had time to recognise anything in it at all. Ask them whether they saw an animal and they consider themselves to be making a futile guess. Yet those guesses are right much more often than they are wrong. That is because the brain can carry out immediate visual processing even when it does not have time for any cognitive back-chatter. A neuroscientist trying to understand how people recognise objects would thus start with this simplest of systems.