Word: neural
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Dates: during 1980-1989
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Although barely off the production lines, the resulting computers, called neural networks, have already started altering the way people think about artificial intelligence. Researchers at Ford Motor, for example, are exploring the possibility of using neural-network computers to find and fix potential problems in new autos. The U.S. Government last year invested $40 million in neural-network research, according to market analysts. Eventually, proponents say, the new technology will lead to computers that can reprogram themselves to deal with any contingency, in situations ranging from directing combat to planning a sumptuous meal...
Last week 1,600 researchers and artificial-intelligence enthusiasts from around the world gathered in San Diego for the second international conference on neural networks. For five days, they studied the recent advances in this form of artificial intelligence and pondered its bright future. Before long, Tom Schwartz, an industry consultant in Mountain View, Calif., told the crowd, "these machines will be recognized as the steam engines of the 21st century...
Conventional computers function by following a chainlike sequence of detailed instructions. Although very fast, their processors can perform only one task at a time. This lockstep approach works best in solving problems that can be broken down into simpler logical pieces. The processors in a neural- network computer, by contrast, form a grid, much like the nerve cells in the brain. Since these artificial neurons are interconnected, they can share information and perform tasks simultaneously. This two-dimensional approach works best at recognizing patterns...
Instead of programming a neural-network computer to make decisions, its maker trains it to recognize the patterns in any solution to a problem by repeatedly feeding examples to the machine. The computer responds to each example by randomly activating its circuits in a particular configuration. The trainer electronically reinforces any connections that produce a correct answer and weakens those that produce an incorrect one. After as many as several thousand trials, the computer activates only those circuits that produce the right answer. "It works just like a kid," says Farrokh Khatibi, senior product manager at AI Ware...
...learned that some neural cells had a preference for being 'on' [processing hormones] during awake time, and some were always 'on' during sleep. But some of the 'awake' cells turn 'on' while in REM sleep," he says...