Artificial Intelligence's "Holy Grail" Victory

In 1943, at the height of World War II, the U.S. military hired an audacious psychologist named B.F. Skinner to develop pigeon-guided missiles. These were the early days of munitions guidance technology, and the Allies were apparently quite desperate to find more reliable ways to get missiles to hit their targets. It went like this: Skinner trained pigeons to peck at an image of the military target projected onto a screen. Whenever their beaks hit the moving target dead center, he rewarded the birds with food pellets. Once the pigeons had learned how to peck at targets, they earned their wings: Skinner would strap three of his little pilots into a missile cockpit specially fitted with straps attached to gyroscopes that would steer the bomb. Now, when American jets released their pigeon-filled bombs, the birds would peck at an image of the bomb's target, their little straps twisting and bending, gyroscopes whirling, guiding the bomb and the birds to their final resting place. Used with permission of the artist. The military eventually pulled the plug on Project Pigeon, while Skinner continued to develop a discipline that came to be known as behavioral psychology. He just wanted to discover how to train animals (and his children) using scientific techniques of stimulus, reward, and punishment. Over the past three years, using techniques similar to those pioneered by Skinner, DeepMind has developed some of the most sophisticated machine-learning techniques in order to train a computer with artificial intelligence (AI) to master the ancient board game of Go. Weirdly enough, this millenia-old board game is the perfect demonstration of human complexity, machine limitations, and how powerful AI has become. For decades, researchers considered playing Go to be the holy grail of game-playing AI. No computer had ever come close to beating a professional in an even, full-board game. Intriguingly, AlphaGo plays Go with something akin to human-like intuition. Computers have always been good at doing the kinds of tasks that we can logically define, like multiplying large numbers, storing information, and playing recorded movies.