Artificial intelligence
From Wikipedia
From Wikipedia
"AI" redirects here. For other uses of "AI" and "Artificial intelligence", see AI (disambiguation).
The modern definition of artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.[1] John McCarthy, who coined the term in 1956,[2] defines it as "the science and engineering of making intelligent machines."[3] Other names for the field have been proposed, such as computational intelligence,[4] synthetic intelligence[4][5] or computational rationality.[6] The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates.
AI research uses tools and insights from many fields, including computer science, psychology, philosophy, neuroscience, cognitive science, linguistics, operations research, economics, control theory, probability, optimization and logic.[7] AI research also overlaps with tasks such as robotics, control systems, scheduling, data mining, logistics, speech recognition, facial recognition and many others.[8]
History
The field was born at a conference on the campus of Dartmouth College in the summer of 1956.[9] Those who attended would become the leaders of AI research for many decades, especially John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, who founded AI laboratories at MIT, CMU and Stanford. They and their students wrote programs that were, to most people, simply astonishing:[10] computers were solving word problems in algebra, proving logical theorems and speaking English.[11] By the middle 60s their research was heavily funded by DARPA,[12] and they were optimistic about the future of the new field:
1965, H. A. Simon: "machines will be capable, within twenty years, of doing any work a man can do"[13]
1967, Marvin Minsky: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."[14]
These predictions, and many like them, would not come true. They had failed to anticipate the difficulty of some of the problems they faced: the lack of raw computer power,[15] the intractable combinatorial explosion of their algorithms,[16] the difficulty of representing commonsense knowledge and doing commonsense reasoning,[17] the incredible difficulty of perception and motion[18] and the failings of logic.[19] In 1974, in response to the criticism of England's Sir James Lighthill and ongoing pressure from congress to fund more productive projects, DARPA cut off all undirected, exploratory research in AI. This was the first AI Winter.[20]
In the early 80s, the field was revived by the commercial success of expert systems and by 1985 the market for AI had reached more than a billion dollars.[21] Minsky and others warned the community that enthusiasm for AI had spiraled out of control and that disappointment was sure to follow.[22] Minsky was right. Beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, more lasting AI Winter began.[23]
In the 90s AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence was adopted throughout the technology industry, providing the heavy lifting for logistics, data mining, medical diagnosis and many other areas.[24] The success was due to several factors: the incredible power of computers today (see Moore's law), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and above all a new commitment by researchers to solid mathematical methods and rigorous scientific standards.[25]
1961-65 -- A.L.Samuel Developed a program which learned to play checkers at Masters level.
1965 -- J.A.Robinson introduced resolution as an interface method in logic.
1965 -- Work on DENDRAL was begun at Stanford University by J.Lederberg, Edward Feigenbaum and Carl Djerassi. DENDRAL is an expert system which discovers molecule structure given only informaton of the constituents of the compound and mass spectra data. DENDRAL was the first knowledge-based expert system to be developed.
1968 -- Work on MACSYMA was initiated at MIT by Carl Engleman, William Martin and Joel Moses. MACSYMA is a large interactive program which solves numerous types of mathamatical problems. Written in LISP, MACSYMA was a continuation of earlier work on SIN, an indefinite integration solving problem
References on early work in AI include Pamela McCorduck's Machines Who think (1979) and Newell and Simon's Human Problem Solving (1972).
The field was born at a conference on the campus of Dartmouth College in the summer of 1956.[9] Those who attended would become the leaders of AI research for many decades, especially John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, who founded AI laboratories at MIT, CMU and Stanford. They and their students wrote programs that were, to most people, simply astonishing:[10] computers were solving word problems in algebra, proving logical theorems and speaking English.[11] By the middle 60s their research was heavily funded by DARPA,[12] and they were optimistic about the future of the new field:
1965, H. A. Simon: "machines will be capable, within twenty years, of doing any work a man can do"[13]
1967, Marvin Minsky: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved."[14]
These predictions, and many like them, would not come true. They had failed to anticipate the difficulty of some of the problems they faced: the lack of raw computer power,[15] the intractable combinatorial explosion of their algorithms,[16] the difficulty of representing commonsense knowledge and doing commonsense reasoning,[17] the incredible difficulty of perception and motion[18] and the failings of logic.[19] In 1974, in response to the criticism of England's Sir James Lighthill and ongoing pressure from congress to fund more productive projects, DARPA cut off all undirected, exploratory research in AI. This was the first AI Winter.[20]
In the early 80s, the field was revived by the commercial success of expert systems and by 1985 the market for AI had reached more than a billion dollars.[21] Minsky and others warned the community that enthusiasm for AI had spiraled out of control and that disappointment was sure to follow.[22] Minsky was right. Beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, more lasting AI Winter began.[23]
In the 90s AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence was adopted throughout the technology industry, providing the heavy lifting for logistics, data mining, medical diagnosis and many other areas.[24] The success was due to several factors: the incredible power of computers today (see Moore's law), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and above all a new commitment by researchers to solid mathematical methods and rigorous scientific standards.[25]
1961-65 -- A.L.Samuel Developed a program which learned to play checkers at Masters level.
1965 -- J.A.Robinson introduced resolution as an interface method in logic.
1965 -- Work on DENDRAL was begun at Stanford University by J.Lederberg, Edward Feigenbaum and Carl Djerassi. DENDRAL is an expert system which discovers molecule structure given only informaton of the constituents of the compound and mass spectra data. DENDRAL was the first knowledge-based expert system to be developed.
1968 -- Work on MACSYMA was initiated at MIT by Carl Engleman, William Martin and Joel Moses. MACSYMA is a large interactive program which solves numerous types of mathamatical problems. Written in LISP, MACSYMA was a continuation of earlier work on SIN, an indefinite integration solving problem
References on early work in AI include Pamela McCorduck's Machines Who think (1979) and Newell and Simon's Human Problem Solving (1972).
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