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Автор Arseniy, ноября 10, 2013, 23:57

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Arseniy

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Artificial intelligence
  Almost from the moment digital computers made their appearance in the business world, computer scientists have been lured by the dream of a different kind computer, one that would emulate the way human beings think rather merely crunch numbers.

  A personal computer that thinks, or dies a reasonable imitation thereof, looms as a revolution in productivity. it would radically change the way people do their work in several respects. the most obvious is the computer's user interface, the way people interact with it. not only does john-the-manager not have to touch a keyboard, he has no concerns about the syntax of the instructions he gives the machine. it can interpret a vague reference, a grunt and can even anticipate his wishes.
Of even greater significance, however, are the types of tasks a thinking computer could take on. while today's productivity programs usually speed up the job you used to do on paper, tomorrow's promise to let you do things you can't do now. for instance, instead of passively storing data for you to retrieve, an intelligent personal computer could extract the information it thought relevant to a situation - much as a human advisor or consultant would marshall his expertise, even when you don't know enough to ask the right questions. the thinking computer would also have the ability to learn about you and your work, giving it the ability, like any good assistant, to do things for you way you would do them yourself.
  Computers that are faster, easier to use and more responsive to particular needs of their users have long been the promise of the field of artificial intelligence, which is a research area that is now decades old.
  In that time it has inspired a number of new programming languages, complex and powerful computer architectures, radical innovations in program development tools, and any number of exciting pilot projects. for all of its promise, though, artificial intelligence  - universally known by the acronym AI - has yielded precious little in the way of practical applications.
  There are some good reasons to think that situation may be changing. while John-the-manager's ideal desktop machine is still a long way off, new genres of software are beginning to appear that attempt to give the user tools which help him think and let him communicate thoughts to the computer more naturally. two fields of particular importance in AI research, expert systems and natural language, are providing the inspiration for this movement in software development.
  An expert system is a program that takes the place of a human expert by codifying the knowledge and rules he uses to reach his conclusions. the feasibility of expert systems has been  demonstrated in a geophysical company to interpret data for oil exploration or several medical systems that analyze symptoms and test results in order to diagnose diseases. Even in the specialized areas where they appear to have demonstrated their practicality, however, expert systems have yet to catch on as reliable or cost-effective alternatives to a human expert.
  Natural language has, for the most part, been seen as a technology that's even further away from practicality than expert systems. a computer that would employ natural language would understand English or another human language - not just in the strict rules of grammar and syntax but in the ambiguous shorthand form we use everyday . hopes were raised as early as the 1960s by the demonstration program called Eliza, originally developed at MIT, which could carry on a seemingly natural dialogue while taking the role of a clinical psychologist helping the human user work out his or her problems. in the point of fact, Eliza was based on some clever but unsubstantial routines responding to a keyword in the user's statement. Until just the last few years, very little else of practical significance had been done with natural language.
  Many individual in the data processing world, where the imminent arrival of true expert systems and natural language interfaces have long been prophesied, have come to conclusion the AI will never be more than pie-in-the-sky promises. The personal computer arena, rather than corporate data proccesing environment is where software developers are now turning to AI concepts to help explore ways of making computer more productive. The results are not always products that the AI scientists in universities and research labs would deem to represent true artificial intelligence, but they are real tools that address real need of computer users

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