History of Technology 14
Brief History of A.I.'s
In the mid-20th century, some scientists have started to build calculating machines, based on recent discoveries in neurology, the new mathematical theory of information, on an understanding of control and stability as the cybernetics, and above all on the occurrence digital computer, a machine mathematical calculation based on abstract concepts.
IA's scope was founded at a conference in Darthmouth College campus in the summer of 1956. Those who attended later became leaders of research in this field for decades, especially John McCharty, Marvin Minsky, Allen Newell and Herbert Simon, they founded research centers in MIT's AI's, CMU and Stanford's site. They and their students wrote programs stunning, due to which the computer can solve an algebra problem, demonstrating logical theories and speak in English. By 1960, their research was sponsored by the US Department of Defense and were very optimistic about the future.
But they had to recognize the difficulties they faced. In 1974, responding to criticism of Sir James Lighthil and being pressured by Congress, which wanted the funds to be invested in productive projects, the US government and the British abandon the project's IA.
By the early 80s, he returned to life by the commercial success of expert systems, which simulated the knowledge and analytical skills of one or more human experts. Until 1985 IA's market was already worth over a billion dollars, and governments around the world invest in it. But a few years later, with the financial market crash calculation based on Lisp machines since 1987, the IA's been forgotten again. In the 90s and early 21st century, the successes recorded by IA are more behind the scenes. AI was adopted almost entirely by various technology industries, making "rough work" of logistics, medical diagnostics, data storage and searching and more. The success was due inter alia huge computing power of computers owned weather, the speed with which were resolved sub-specific problems of creating connections between IA and other branches of science that address similar issues.
The philosophy behind A.I.'s
AI in that it says can recreate the capabilities of the human mind, a challenge and an inspiration for philosophy. There are limits to intelligent machines? Is there any essential difference between human and machine intelligence? Can I have a soul and consciousness cars?
- Turing's polite convention: if a car behave as intelligent as a human being, then it is as intelligent as a human being. According to Turing, we can judge the intelligence of a car, relying solely on her behavior. The theory underlying the Turing test.
- Darthmouth proposal: each component of the learning process or any other aspect of intelligence can be so precisely described, a machine that can learn how to simulate it. This statement was made at the Conference of Darthmouth 1956 and is the official position of most researchers in the field.
- Physical symbol system hypothesis of Newell and Simon, a symbolic physical system offers sufficient and necessary means to act intelligently. This theory says that the essence of intelligence is the manipulation of symbols. Hubert Dreyfus says that on the contrary, human expertise depends more on instinct unconscious than conscious manipulation of symbols and that we "feel" a situation than to have an explicit understanding symbolic.
- Godels's theorem incomplete: a formal system (as it is a computer program) can not prove all true statements. Roger Penrose is among those who say that this theorem, limiting the ability of the car.
- IA's hypothesis "strong" by Searle: computer properly programmed and equipped with inputs and outputs suitable, would have a mind of its own, in the same manner in which people have their one. Searle argues his theory by Chinese room argument, which asks us to look inside a computer and indicate "location" mind.
- Artificial brain argument: the brain can be simulated. Hans Moravec, Ray Kurzweil and others have said that it is possible to copy a right brain in software and hardware, and that such a simulation would be identical to the original. This argument combines the idea that a machine powerful enough can simulate any process materialistic idea according to which the mind is the result of physical processes in the brain.