The Four Waves Of A.I.

THE TERM “ARTIFICIAL INTELLIGENCE” was coined in 1956, at a historic conference at Dartmouth, but it has been only in the past 10 years, for the most part, that we’ve seen the first truly substantive glimpses of its power and application.

- Kai-fu Lee

A.I., as it’s now universally called, is the pursuit of performing tasks usually reserved for human cognition: recognizing patterns, predicting outcomes clouded by uncertainty, and making complex decisions. A.I. algorithms can perceive and interpret the world around us—and some even say they’ll soon be capable of emotion, compassion, and creativity—though the original dream of matching overall “human intelligence” is still very far away.

What changed everything a decade or so ago was an approach called “deep learning”—an architecture inspired by the human brain, with neurons and connections. As the name suggests, deep-learning networks can be thousands of layers deep and have up to billions of parameters. Unlike the human brain, however, such networks are “trained” on huge amounts of labeled data; then they use what they’ve “learned” to mathematically pick out and recognize incredibly subtle patterns within other mountains of data. A data input to the network can be anything digital—say, an image, or a sound segment, or a credit card purchase. The output, meanwhile, is a decision or prediction related to whatever question might be asked: Whose face is in the image? What words were spoken in the sound segment? Is the purchase fraudulent?