A sense of curiosity is helpful for artificial intelligence

SOFTWARE that can learn is changing the world, but it needs supervision. Humans provide such oversight in two ways. The first is to show machine-learning algorithms large sets of data that describe the task at hand. Labelled pictures of cats and dogs, for instance, allow an algorithm to learn to discriminate between the two. The other form of supervision is to set a specific goal within a highly structured environment, such as achieving a high score in a video game, and then let the algorithm try out lots of possibilities until it finds one that achieves the objective.These two approaches to “supervised learning” have led to breakthroughs in artificial intelligence. In 2012 a group of researchers from the University of Toronto used the first method to build AlexNet, a piece of software that in a competition recognised one in ten more images than its closest competitors. In 2015 researchers at DeepMind, a British AI firm owned by Alphabet, used the second method to teach an algorithm to play Atari video games at superhuman levels, an advance that led to later triumphs at Go, a board game.