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Calculating machines were built in antiquity and improved throughout history by many mathematicians , including ( once again ) philosopher Gottfried Leibniz . In the early 19th century , Charles Babbage designed a programmable computer ( the Analytical Engine ) , although it was never built . Ada Lovelace speculated t...
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The first modern computers were the massive code breaking machines of the Second World War ( such as Z3 , ENIAC and Colossus ) . The latter two of these machines were based on the theoretical foundation laid by Alan Turing and developed by John von Neumann .
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= = The birth of artificial intelligence 1952 – 1956 = =
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In the 1940s and 50s , a handful of scientists from a variety of fields ( mathematics , psychology , engineering , economics and political science ) began to discuss the possibility of creating an artificial brain . The field of artificial intelligence research was founded as an academic discipline in 1956 .
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= = = Cybernetics and early neural networks = = =
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The earliest research into thinking machines was inspired by a confluence of ideas that became prevalent in the late 30s , 40s and early 50s . Recent research in neurology had shown that the brain was an electrical network of neurons that fired in all @-@ or @-@ nothing pulses . Norbert Wiener 's cybernetics described...
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Examples of work in this vein includes robots such as W. Grey Walter 's turtles and the Johns Hopkins Beast . These machines did not use computers , digital electronics or symbolic reasoning ; they were controlled entirely by analog circuitry .
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Walter Pitts and Warren McCulloch analyzed networks of idealized artificial neurons and showed how they might perform simple logical functions . They were the first to describe what later researchers would call a neural network . One of the students inspired by Pitts and McCulloch was a young Marvin Minsky , then a 24...
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= = = Turing 's test = = =
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In 1950 Alan Turing published a landmark paper in which he speculated about the possibility of creating machines that think . He noted that " thinking " is difficult to define and devised his famous Turing Test . If a machine could carry on a conversation ( over a teleprinter ) that was indistinguishable from a conver...
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= = = Game AI = = =
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In 1951 , using the Ferranti Mark 1 machine of the University of Manchester , Christopher Strachey wrote a checkers program and Dietrich Prinz wrote one for chess . Arthur Samuel 's checkers program , developed in the middle 50s and early 60s , eventually achieved sufficient skill to challenge a respectable amateur . ...
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= = = Symbolic reasoning and the Logic Theorist = = =
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When access to digital computers became possible in the middle fifties , a few scientists instinctively recognized that a machine that could manipulate numbers could also manipulate symbols and that the manipulation of symbols could well be the essence of human thought . This was a new approach to creating thinking ma...
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In 1955 , Allen Newell and ( future Nobel Laureate ) Herbert A. Simon created the " Logic Theorist " ( with help from J. C. Shaw ) . The program would eventually prove 38 of the first 52 theorems in Russell and Whitehead 's Principia Mathematica , and find new and more elegant proofs for some . Simon said that they ha...
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= = = Dartmouth Conference 1956 : the birth of AI = = =
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The Dartmouth Conference of 1956 was organized by Marvin Minsky , John McCarthy and two senior scientists : Claude Shannon and Nathan Rochester of IBM . The proposal for the conference included this assertion : " every aspect of learning or any other feature of intelligence can be so precisely described that a machine...
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= = The golden years 1956 – 1974 = =
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The years after the Dartmouth conference were an era of discovery , of sprinting across new ground . The programs that were developed during this time were , to most people , simply " astonishing " : computers were solving algebra word problems , proving theorems in geometry and learning to speak English . Few at the ...
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= = = The work = = =
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There were many successful programs and new directions in the late 50s and 1960s . Among the most influential were these :
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= = = = Reasoning as search = = = =
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Many early AI programs used the same basic algorithm . To achieve some goal ( like winning a game or proving a theorem ) , they proceeded step by step towards it ( by making a move or a deduction ) as if searching through a maze , backtracking whenever they reached a dead end . This paradigm was called " reasoning as ...
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The principal difficulty was that , for many problems , the number of possible paths through the " maze " was simply astronomical ( a situation known as a " combinatorial explosion " ) . Researchers would reduce the search space by using heuristics or " rules of thumb " that would eliminate those paths that were unlik...
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Newell and Simon tried to capture a general version of this algorithm in a program called the " General Problem Solver " . Other " searching " programs were able to accomplish impressive tasks like solving problems in geometry and algebra , such as Herbert Gelernter 's Geometry Theorem Prover ( 1958 ) and SAINT , writ...
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= = = = Natural language = = = =
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An important goal of AI research is to allow computers to communicate in natural languages like English . An early success was Daniel Bobrow 's program STUDENT , which could solve high school algebra word problems .
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A semantic net represents concepts ( e.g. " house " , " door " ) as nodes and relations among concepts ( e.g. " has @-@ a " ) as links between the nodes . The first AI program to use a semantic net was written by Ross Quillian and the most successful ( and controversial ) version was Roger Schank 's Conceptual depende...
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Joseph Weizenbaum 's ELIZA could carry out conversations that were so realistic that users occasionally were fooled into thinking they were communicating with a human being and not a program . But in fact , ELIZA had no idea what she was talking about . She simply gave a canned response or repeated back what was said ...
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= = = = Micro @-@ worlds = = = =
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In the late 60s , Marvin Minsky and Seymour Papert of the MIT AI Laboratory proposed that AI research should focus on artificially simple situations known as micro @-@ worlds . They pointed out that in successful sciences like physics , basic principles were often best understood using simplified models like frictionl...
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This paradigm led to innovative work in machine vision by Gerald Sussman ( who led the team ) , Adolfo Guzman , David Waltz ( who invented " constraint propagation " ) , and especially Patrick Winston . At the same time , Minsky and Papert built a robot arm that could stack blocks , bringing the blocks world to life ....
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= = = The optimism = = =
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The first generation of AI researchers made these predictions about their work :
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1958 , H. A. Simon and Allen Newell : " within ten years a digital computer will be the world 's chess champion " and " within ten years a digital computer will discover and prove an important new mathematical theorem . "
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1965 , H. A. Simon : " machines will be capable , within twenty years , of doing any work a man can do . "
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1967 , Marvin Minsky : " Within a generation ... the problem of creating ' artificial intelligence ' will substantially be solved . "
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1970 , Marvin Minsky ( in Life Magazine ) : " In from three to eight years we will have a machine with the general intelligence of an average human being . "
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= = = The money = = =
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In June 1963 , MIT received a $ 2 @.@ 2 million grant from the newly created Advanced Research Projects Agency ( later known as DARPA ) . The money was used to fund project MAC which subsumed the " AI Group " founded by Minsky and McCarthy five years earlier . DARPA continued to provide three million dollars a year un...
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The money was proffered with few strings attached : J. C. R. Licklider , then the director of ARPA , believed that his organization should " fund people , not projects ! " and allowed researchers to pursue whatever directions might interest them . This created a freewheeling atmosphere at MIT that gave birth to the ha...
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= = The first AI winter 1974 – 1980 = =
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In the 70s , AI was subject to critiques and financial setbacks . AI researchers had failed to appreciate the difficulty of the problems they faced . Their tremendous optimism had raised expectations impossibly high , and when the promised results failed to materialize , funding for AI disappeared . At the same time ,...
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= = = The problems = = =
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In the early seventies , the capabilities of AI programs were limited . Even the most impressive could only handle trivial versions of the problems they were supposed to solve ; all the programs were , in some sense , " toys " . AI researchers had begun to run into several fundamental limits that could not be overcome...
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Limited computer power : There was not enough memory or processing speed to accomplish anything truly useful . For example , Ross Quillian 's successful work on natural language was demonstrated with a vocabulary of only twenty words , because that was all that would fit in memory . Hans Moravec argued in 1976 that co...
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Intractability and the combinatorial explosion . In 1972 Richard Karp ( building on Stephen Cook 's 1971 theorem ) showed there are many problems that can probably only be solved in exponential time ( in the size of the inputs ) . Finding optimal solutions to these problems requires unimaginable amounts of computer ti...
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Commonsense knowledge and reasoning . Many important artificial intelligence applications like vision or natural language require simply enormous amounts of information about the world : the program needs to have some idea of what it might be looking at or what it is talking about . This requires that the program know...
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Moravec 's paradox : Proving theorems and solving geometry problems is comparatively easy for computers , but a supposedly simple task like recognizing a face or crossing a room without bumping into anything is extremely difficult . This helps explain why research into vision and robotics had made so little progress b...
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The frame and qualification problems . AI researchers ( like John McCarthy ) who used logic discovered that they could not represent ordinary deductions that involved planning or default reasoning without making changes to the structure of logic itself . They developed new logics ( like non @-@ monotonic logics and mo...
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= = = The end of funding = = =
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The agencies which funded AI research ( such as the British government , DARPA and NRC ) became frustrated with the lack of progress and eventually cut off almost all funding for undirected research into AI . The pattern began as early as 1966 when the ALPAC report appeared criticizing machine translation efforts . Af...
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Hans Moravec blamed the crisis on the unrealistic predictions of his colleagues . " Many researchers were caught up in a web of increasing exaggeration . " However , there was another issue : since the passage of the Mansfield Amendment in 1969 , DARPA had been under increasing pressure to fund " mission @-@ oriented ...
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= = = Critiques from across campus = = =
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Several philosophers had strong objections to the claims being made by AI researchers . One of the earliest was John Lucas , who argued that Gödel 's incompleteness theorem showed that a formal system ( such as a computer program ) could never see the truth of certain statements , while a human being could . Hubert Dr...
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These critiques were not taken seriously by AI researchers , often because they seemed so far off the point . Problems like intractability and commonsense knowledge seemed much more immediate and serious . It was unclear what difference " know how " or " intentionality " made to an actual computer program . Minsky sai...
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Weizenbaum began to have serious ethical doubts about AI when Kenneth Colby wrote DOCTOR , a chatterbot therapist . Weizenbaum was disturbed that Colby saw his mindless program as a serious therapeutic tool . A feud began , and the situation was not helped when Colby did not credit Weizenbaum for his contribution to t...
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= = = Perceptrons and the dark age of connectionism = = =
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A perceptron was a form of neural network introduced in 1958 by Frank Rosenblatt , who had been a schoolmate of Marvin Minsky at the Bronx High School of Science . Like most AI researchers , he was optimistic about their power , predicting that " perceptron may eventually be able to learn , make decisions , and transl...
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= = = The neats : logic and symbolic reasoning = = =
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Logic was introduced into AI research as early as 1958 , by John McCarthy in his Advice Taker proposal . In 1963 , J. Alan Robinson had discovered a simple method to implement deduction on computers , the resolution and unification algorithm . However , straightforward implementations , like those attempted by McCarth...
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Critics of the logical approach noted , as Dreyfus had , that human beings rarely used logic when they solved problems . Experiments by psychologists like Peter Wason , Eleanor Rosch , Amos Tversky , Daniel Kahneman and others provided proof . McCarthy responded that what people do is irrelevant . He argued that what ...
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= = = The scruffies : frames and scripts = = =
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Among the critics of McCarthy 's approach were his colleagues across the country at MIT . Marvin Minsky , Seymour Papert and Roger Schank were trying to solve problems like " story understanding " and " object recognition " that required a machine to think like a person . In order to use ordinary concepts like " chair...
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In 1975 , in a seminal paper , Minsky noted that many of his fellow " scruffy " researchers were using the same kind of tool : a framework that captures all our common sense assumptions about something . For example , if we use the concept of a bird , there is a constellation of facts that immediately come to mind : w...
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= = Boom 1980 – 1987 = =
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In the 1980s a form of AI program called " expert systems " was adopted by corporations around the world and knowledge became the focus of mainstream AI research . In those same years , the Japanese government aggressively funded AI with its fifth generation computer project . Another encouraging event in the early 19...
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= = = The rise of expert systems = = =
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An expert system is a program that answers questions or solves problems about a specific domain of knowledge , using logical rules that are derived from the knowledge of experts . The earliest examples were developed by Edward Feigenbaum and his students . Dendral , begun in 1965 , identified compounds from spectromet...
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Expert systems restricted themselves to a small domain of specific knowledge ( thus avoiding the commonsense knowledge problem ) and their simple design made it relatively easy for programs to be built and then modified once they were in place . All in all , the programs proved to be useful : something that AI had not...
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In 1980 , an expert system called XCON was completed at CMU for the Digital Equipment Corporation . It was an enormous success : it was saving the company 40 million dollars annually by 1986 . Corporations around the world began to develop and deploy expert systems and by 1985 they were spending over a billion dollars...
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= = = The knowledge revolution = = =
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The power of expert systems came from the expert knowledge they contained . They were part of a new direction in AI research that had been gaining ground throughout the 70s . " AI researchers were beginning to suspect — reluctantly , for it violated the scientific canon of parsimony — that intelligence might very well...
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The 1980s also saw the birth of Cyc , the first attempt to attack the commonsense knowledge problem directly , by creating a massive database that would contain all the mundane facts that the average person knows . Douglas Lenat , who started and led the project , argued that there is no shortcut ― the only way for ma...
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Chess playing programs HiTech and Deep Thought defeated chess masters in 1989 . Both were developed by Carnegie Mellon University ; Deep Thought development paved the way for the Deep Blue .
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= = = The money returns : the fifth generation project = = =
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In 1981 , the Japanese Ministry of International Trade and Industry set aside $ 850 million for the Fifth generation computer project . Their objectives were to write programs and build machines that could carry on conversations , translate languages , interpret pictures , and reason like human beings . Much to the ch...
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Other countries responded with new programs of their own . The UK began the ₤ 350 million Alvey project . A consortium of American companies formed the Microelectronics and Computer Technology Corporation ( or " MCC " ) to fund large scale projects in AI and information technology . DARPA responded as well , founding ...
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= = = The revival of connectionism = = =
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In 1982 , physicist John Hopfield was able to prove that a form of neural network ( now called a " Hopfield net " ) could learn and process information in a completely new way . Around the same time , David Rumelhart popularized a new method for training neural networks called " backpropagation " ( discovered years ea...
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The new field was unified and inspired by the appearance of Parallel Distributed Processing in 1986 — a two volume collection of papers edited by Rumelhart and psychologist James McClelland . Neural networks would become commercially successful in the 1990s , when they began to be used as the engines driving programs ...
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= = Bust : the second AI winter 1987 – 1993 = =
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The business community 's fascination with AI rose and fell in the 80s in the classic pattern of an economic bubble . The collapse was in the perception of AI by government agencies and investors – the field continued to make advances despite the criticism . Rodney Brooks and Hans Moravec , researchers from the relate...
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= = = AI winter = = =
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The term " AI winter " was coined by researchers who had survived the funding cuts of 1974 when they became concerned that enthusiasm for expert systems had spiraled out of control and that disappointment would certainly follow . Their fears were well founded : in the late 80s and early 90s , AI suffered a series of f...
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The first indication of a change in weather was the sudden collapse of the market for specialized AI hardware in 1987 . Desktop computers from Apple and IBM had been steadily gaining speed and power and in 1987 they became more powerful than the more expensive Lisp machines made by Symbolics and others . There was no ...
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Eventually the earliest successful expert systems , such as XCON , proved too expensive to maintain . They were difficult to update , they could not learn , they were " brittle " ( i.e. , they could make grotesque mistakes when given unusual inputs ) , and they fell prey to problems ( such as the qualification problem...
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In the late 80s , the Strategic Computing Initiative cut funding to AI " deeply and brutally . " New leadership at DARPA had decided that AI was not " the next wave " and directed funds towards projects that seemed more likely to produce immediate results .
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By 1991 , the impressive list of goals penned in 1981 for Japan 's Fifth Generation Project had not been met . Indeed , some of them , like " carry on a casual conversation " had not been met by 2010 . As with other AI projects , expectations had run much higher than what was actually possible .
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= = = The importance of having a body : Nouvelle AI and embodied reason = = =
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In the late 80s , several researchers advocated a completely new approach to artificial intelligence , based on robotics . They believed that , to show real intelligence , a machine needs to have a body — it needs to perceive , move , survive and deal with the world . They argued that these sensorimotor skills are ess...
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The approach revived ideas from cybernetics and control theory that had been unpopular since the sixties . Another precursor was David Marr , who had come to MIT in the late 70s from a successful background in theoretical neuroscience to lead the group studying vision . He rejected all symbolic approaches ( both McCar...
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In a 1990 paper , " Elephants Don 't Play Chess , " robotics researcher Rodney Brooks took direct aim at the physical symbol system hypothesis , arguing that symbols are not always necessary since " the world is its own best model . It is always exactly up to date . It always has every detail there is to be known . Th...
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= = AI 1993 – present = =
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The field of AI , now more than a half a century old , finally achieved some of its oldest goals . It began to be used successfully throughout the technology industry , although somewhat behind the scenes . Some of the success was due to increasing computer power and some was achieved by focusing on specific isolated ...
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= = = Milestones and Moore 's Law = = =
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On 11 May 1997 , Deep Blue became the first computer chess @-@ playing system to beat a reigning world chess champion , Garry Kasparov . The super computer was a specialized version of a framework produced by IBM , and was capable of processing twice as many moves per second as it had during the first match ( which De...
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In 2005 , a Stanford robot won the DARPA Grand Challenge by driving autonomously for 131 miles along an unrehearsed desert trail . Two years later , a team from CMU won the DARPA Urban Challenge by autonomously navigating 55 miles in an Urban environment while adhering to traffic hazards and all traffic laws . In Febr...
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These successes were not due to some revolutionary new paradigm , but mostly on the tedious application of engineering skill and on the tremendous power of computers today . In fact , Deep Blue 's computer was 10 million times faster than the Ferranti Mark 1 that Christopher Strachey taught to play chess in 1951 . Thi...
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= = = Intelligent agents = = =
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