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1980s: Artificial Intelligence (AI) - From Lab to Life |
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Following the commercial success of  expert systems, which started in the 1970s, also other AI technologies began to make their way into the marketplace. In 1986, U.S. sales of AI-related hardware and software rose to U.S.$ 425 million. Especially expert systems, because of their efficiency, were still in demand. Yet also other fields of AI turned out to be successful in the corporate world.
Machine vision systems for example were used for the cameras and computers on assembly lines to perform quality control. By 1985 over a hundred companies offered machine vision systems in the U.S., and sales totaled U.S.$ 80 million. Although there was a breakdown in the market for AI-systems in 1986 - 1987, which led to a cut back in funding, the industry slowly recovered.
New technologies were being invented in Japan. Fuzzy logic pioneered in the U.S. and also neural networks were being reconsidered for achieving artificial intelligence. The probably most important development of the 1980s was, that it showed that AI technology had real life uses. AI applications like voice and character recognition systems or steadying camcorders using fuzzy logic were not only made available to business and industry, but also to the average customer.
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Artificial intelligence approaches
Looking for ways to create intelligent machines, the field of artificial intelligence (AI) has split into several different approaches based on the opinions about the most promising methods and theories. The two basic AI approaches are: bottom-up and top-down. The bottom-up theory suggests that the best way to achieve artificial intelligence is to build electronic replicas of the human brain's complex network of neurons (through neural networks and parallel computing) while the top-down approach attempts to mimic the brain's behavior with computer programs (for example expert systems).
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