![]() ![]() In 1988, students at Carnegie Mellon University developed a sophisticated chess computer called Deep Thought. Then it became 16, then 210, and so on to chips and supercomputers,” says Schaeffer. When I started in the game, we were using a single computer. Programs could thus analyze more and more moves per second, increasing their chances of finding the best move possible.Īccordingly, computer chess “became about getting the fastest technology. That decade, pioneering American computer scientist Ken Thompson released a paper proving something that now seems intuitive: If your computer was faster, your chess program would perform better. If you are not interested in philosophical debates (and prefer to ignore the fact that the dominant materialist paradigm affects-through government policies, for example-many aspects of your life), at least read Tom Simonite excellent Wired article “ AI Beat Humans at Reading! Maybe not” in which he shows how exaggerated are recent various claims for AI “breakthroughs.”īeware of fake AI news and be less afraid.“Computer chess changed in the ’80s.” says Jonathan Schaeffer, president of the International Computer Games Association and professor of computer science at the University of Alberta. Read here and (especially) here for a different take. You build a device with enough number-crunching algorithmic power and speed-and, lo, quantity becomes quality, tactics becomes strategy, calculation becomes intuition… After all, how do humans get intuition and thought and feel? Unless you believe in some metaphysical homunculus hovering over (in?) the brain directing its bits and pieces, you must attribute our strategic, holistic mental abilities to the incredibly complex firing of neurons in the brain. You build a machine that does nothing but calculation and it crosses over and creates poetry. But that explanation escaped observers, then and now, preferring to believe that humans can create intelligent machines (“giant brains” as they were called in the early days of very fast calculators) because the only difference between humans and machines is the degree of complexity, the sheer number of human or artificial neurons firing. ![]() ![]() So the earth-shattering moves may have been just a bug in the software. It is a project in - we play chess through sheer speed of calculation and we just shift through the possibilities and we just pick one line." It is not an artificial intelligence project in any way. Krauthammer quotes Joe Hoane, one of Deep Blue's programmers, answering the question "How much of your work was devoted specifically to artificial intelligence in emulating human thought?" Hoane’s answer: "No effort was devoted to. IBM’s programmers, in contrast, were more modest. Still, Google’s programmers have not dissuaded anyone from believing they are creating human-like machines and often promoted the idea (the only Google exception I know of is Peter Norvig, but he is neither a member of the Google Brain nor of the Google DeepMind teams, Google’s AI avant-garde). From where Lee sat, AlphaGo displayed what Go players might describe as intuition, the ability to play a beautiful game not just like a person but in a way no person could.ĪlphaGo used 1,920 Central Processing Units (CPU) and 280 Graphics Processing Units (GPU), according to The Economist, and possibly additional proprietary google Tensor Processing Units, for a lot of hardware power, plus brute force statistical analysis software (processing and analyzing lots and lots of data) known as Deep Neural Networks, or more popularly as Deep Learning. It was the moment AlphaGo proved it understands, or at least appears to mimic understanding in a way that is indistinguishable from the real thing. ![]() Move 37 showed that AlphaGo wasn’t just regurgitating years of programming or cranking through a brute-force predictive algorithm. In “ The AI Behind AlphaGo Can Teach Us About Being Human,” Metz reported on yet another earth-shattering artificial-intelligence-becoming-human-intelligence move: It played with - forgive me - nuance and subtlety.įast forward to March 2016, to Cade Metz writing in Wired on Go champion Lee Sedol’s loss to AlphaGo at the Google DeepMind Challenge Match. Machines are not supposed to play this way… To the amazement of all, not least Kasparov, in this game drained of tactics, Deep Blue won. Grandmaster observers said that had they not known who was playing they would have imagined that Kasparov was playing one of the great human players, maybe even himself. What was new about Game Two… was that the machine played like a human. ![]()
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