Playing against a top Go player, Google DeepMind's AlphaGo artificial-intelligence program has puzzled commentators with moves that are often described as "beautiful," but do not fit into the usual human style of play. Artificial-intelligence experts think these moves reflect a key AI strength of AlphaGo, its ability to learn from its experience. Such moves cannot be produced by just incorporating human knowledge, said Doina Precup, associate professor in the School of Computer Science at McGill University in Quebec, in an email interview. "AlphaGo represents not only a machine that thinks, but one that can learn and strategize," agreed Howard Yu, professor of strategic management and innovation at IMD business school. AlphaGo won three games consecutively against Lee Se-dol last week in Seoul, securing the tournament and US$1 million in prize money that Google plans to give to charities.
"Learning", "thinking", "intelligence", even "cognition"… Such words were once reserved for humans (and to a lesser extent, other highly complex animals), but have now seemingly been extended to a "species" of machines, machines infused with artificial intelligence or "AI". In October 2015, a computer program developed by Google DeepMind, named AlphaGo, defeated the incumbent European champion at the complex ancient Chinese board game of Go. In March 2016, AlphaGo went on to defeat the world champion, Lee Sedol. This seminal moment caught the world's attention, the media have since been incessantly covering every AI-related story, and companies from all walks of life have since been on a mission to add "artificial intelligence" to their business description. At Platinum we have been closely following the major technological trends for many years.
Today, inside the towering glass and steel Four Seasons Hotel in downtown Seoul, South Korea, Google will put the future of artificial intelligence to the test. At one o'clock in the afternoon local time, a digital Google creation will challenge one of the world's top players at the game of Go, the ancient Eastern pastime that's often compared to chess--though it's exponentially more complex. This Google machine is called AlphaGo, and to win, it must mimic not just the analytical skills of a human, but at least a bit of human intuition. Over the years, machines have topped the best humans at checkers, chess, Othello, Scrabble, Jeopardy!, and so many other contests of human intellect. But they haven't beat the very best at Go.
Sitting on a stage in Wuzhen, China, a historic city up the river from Shanghai, Google chairman Eric Schmidt described what he called "the age of intelligence." He trumpeted the rise of deep neural networks and other techniques that allow machines to learn tasks largely on their own, either by finding patterns in vast amounts of data or through their own trial and error. At Google, using a sweeping software tool called TensorFlow, engineers have built deep learning systems that can identify faces and objects in photos, recognize commands spoken into smartphones, and translate one language into another. Schmidt called this the biggest technological change of his lifetime. Then he mentioned China's three largest internet companies: Baidu, Tencent, and Alibaba.
About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent. On move 37, AlphaGo chose to put a black stone in what seemed, at first, like a ridiculous position. It looked certain to give up substantial territory--a rookie mistake in a game that is all about controlling the space on the board. Two television commentators wondered if they had misread the move or if the machine had malfunctioned somehow. In fact, contrary to any conventional wisdom, move 37 would enable AlphaGo to build a formidable foundation in the center of the board. The Google program had effectively won the game using a move that no human would've come up with. One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words. In the images that accompany this story, several artists demonstrate the use of a variety of visual clues to convey meanings far beyond the actual letters.