<MPQA autoclass="obj" certainty="17.5">This article is about modelling human thought with computers.</MPQA>
<MPQA autoclass="obj" certainty="9.6">For other uses of the term AI, see Ai.Artificial intelligence, also known as machine intelligence, is defined as intelligence exhibited by anything manufactured (i.e. artificial) by humans or other sentient beings or systems (should such things ever exist on Earth or elsewhere).</MPQA>
<MPQA autoclass="obj" certainty="15.4">It is usually hypothetically applied to general-purpose computers.</MPQA>
<MPQA autoclass="obj" certainty="0.4">The term is also used to refer to the field of scientific investigation into the plausibility of and approaches to creating such systems.</MPQA>
<MPQA autoclass="subj" certainty="11.6">1 Overview 2 Strong AI and <MPQA autoclass="negative">weak</MPQA> AI2.1 Strong <MPQA autoclass="negative">artificial</MPQA> intelligence 2.2 <MPQA autoclass="negative">Weak</MPQA> <MPQA autoclass="negative">artificial</MPQA> intelligence 2.3 Philosophical criticism and support of strong AI 3 History3.1</MPQA>
<MPQA autoclass="obj" certainty="3.6">Development of AI theory 3.2 Experimental AI research 4 Practical applications of AI techniques 5 Hypothetical consequences of AI 6 Sub-fields of AI research 7 Famous figures7.1 Machines displaying some degree of "intelligence" 7.2 AI researchers 8 Resources8.1</MPQA>
<MPQA autoclass="obj" certainty="20.1">Further reading8.1.1 Non-fiction 8.1.2</MPQA>
<MPQA autoclass="obj" certainty="6.9">Fiction8.2 AI related organizations 8.3 Sources 8.4 See also8.4.1 Philosophy 8.4.2 Logic 8.4.3 Science 8.4.4 Applications 8.4.5 Uncategorised8.5 External linksOverviewThe question of what artificial intelligence is can be reduced to two parts: "what is the nature of artifice" and "what is intelligence"?</MPQA>
<MPQA autoclass="subj" certainty="12.5">The first question is fairly easy to answer, though it does point to the question of what it is possible to manufacture (within the <MPQA autoclass="negative">constraints</MPQA> of certain types of system, e.g. classical computational systems, of available processes of manufacturing and of possible limits on human intellect, for instance).</MPQA>
<MPQA autoclass="subj" certainty="26.7">The second is much harder, raising questions of consciousness and self, mind (including the unconscious mind) and the question of what components are involved in the only type of intelligence it is universally agreed we have available to study: that of human beings.</MPQA>
<MPQA autoclass="subj" certainty="7.0">Intelligent behavior in humans is <MPQA autoclass="negative">complex</MPQA> and <MPQA autoclass="negative">difficult</MPQA> to study or understand.</MPQA>
<MPQA autoclass="obj" certainty="9.2">Study of animals and artificial systems that are not just models of what exists already are also <MPQA autoclass="objectiveSpeech">considered</MPQA> widely pertinent.</MPQA>
<MPQA autoclass="obj" certainty="17.7">Several distinct types of artificial intelligence have been elucidated below.</MPQA>
<MPQA autoclass="obj" certainty="6.9">Also, the subject divisions , history, proponents and opponents and applications of research in the subject are <MPQA autoclass="objectiveSpeech">described</MPQA>.</MPQA>
<MPQA autoclass="subj" certainty="20.3">Finally, references to fictional and non-fictional descriptions of AI are provided.</MPQA>
<MPQA autoclass="subj" certainty="10.8">Strong AI and <MPQA autoclass="negative">weak</MPQA> AIOne popular and early definition of <MPQA autoclass="negative">artificial</MPQA> intelligence research, put forth by John McCarthy at the Dartmouth Conference in 1956, is "making a machine behave in ways that would be <MPQA autoclass="speechDirectSubjective">called</MPQA> intelligent if a human were so behaving."</MPQA>
<MPQA autoclass="obj" certainty="8.8">However this definition seems to ignore the possibility of strong AI (see below).</MPQA>
<MPQA autoclass="obj" certainty="0.4">Another definition of artificial intelligence is intelligence arising from an artificial device.</MPQA>
<MPQA autoclass="subj" certainty="26.7">Most definitions could be categorized as <MPQA autoclass="negative"><MPQA autoclass="speechDirectSubjective">concerning</MPQA></MPQA> either systems that <MPQA autoclass="speechDirectSubjective">think</MPQA> like humans, systems that act like humans, systems that <MPQA autoclass="speechDirectSubjective">think</MPQA> rationally or systems that act rationally.</MPQA>
<MPQA autoclass="subj" certainty="27.3">Strong <MPQA autoclass="negative">artificial</MPQA> intelligenceStrong <MPQA autoclass="negative">artificial</MPQA> intelligence research deals with the creation of some form of computer-based <MPQA autoclass="negative">artificial</MPQA> intelligence that can truly reason and solve <MPQA autoclass="negative">problems</MPQA>; a strong form of AI is <MPQA autoclass="speechDirectSubjective">said</MPQA> to be sentient, or self-aware.</MPQA>
<MPQA autoclass="subj" certainty="7.7">In theory, there are two types of strong AI:Human-like AI, in which the computer program thinks and reasons much like a human mind.</MPQA>
<MPQA autoclass="subj" certainty="21.8">Non-human-like AI, in which the computer program develops a totally non-human sentience, and a non-human way of <MPQA autoclass="speechDirectSubjective">thinking</MPQA> and reasoning.</MPQA>
<MPQA autoclass="subj" certainty="30.5">Weak <MPQA autoclass="negative">artificial</MPQA> intelligenceWeak <MPQA autoclass="negative">artificial</MPQA> intelligence research deals with the creation of some form of computer-based <MPQA autoclass="negative">artificial</MPQA> intelligence that cannot truly reason and solve <MPQA autoclass="negative">problems</MPQA>; such a machine would, in some ways, act as if it were intelligent, but it would not possess true intelligence or sentience.</MPQA>
<MPQA autoclass="subj" certainty="9.2">There are several fields of <MPQA autoclass="negative">weak</MPQA> AI, one of which is natural language.</MPQA>
<MPQA autoclass="obj" certainty="17.3">Many weak AI fields have specialised software or programming languages created for them.</MPQA>
<MPQA autoclass="obj" certainty="11.9">For example, the 'most-human' natural language chatterbot A.L.I.C.E. uses a programming language AIML that is specific to its program.</MPQA>
<MPQA autoclass="obj" certainty="17.5">To date, much of the work in this field has been done with computer simulations of intelligence based on predefined sets of rules.</MPQA>
<MPQA autoclass="subj" certainty="20.3">Very little progress has been made in strong AI.</MPQA>
<MPQA autoclass="subj" certainty="38.9">Depending on how one defines one's goals, a moderate amount of progress has been made in <MPQA autoclass="negative">weak</MPQA> AI.Philosophical criticism and support of strong AIThe term "Strong AI" was originally coined by John Searle and was applied to digital computers and other information processing machines.</MPQA>
<MPQA autoclass="subj" certainty="39.2">Searle defined strong AI:"according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind" (J Searle in Minds Brains and Programs.</MPQA>
<MPQA autoclass="obj" certainty="5.6">The Behavioral and Brain Sciences, vol.</MPQA>
<MPQA autoclass="obj" certainty="19.7">3, 1980).</MPQA>
<MPQA autoclass="obj" certainty="9.9">Searle and most others involved in this debate are addressing the problem of whether a machine that works solely through the transformation of encoded data could be a mind, not the wider issue of Monism versus Dualism (ie: whether a biological machine could contain a mind).</MPQA>
<MPQA autoclass="obj" certainty="12.5">Searle <MPQA autoclass="objectiveSpeech">points out</MPQA> in his Chinese Room Argument that information processors carry encoded data which <MPQA autoclass="objectiveSpeech">describe</MPQA> other things.</MPQA>
<MPQA autoclass="obj" certainty="18.7">The encoded data itself is meaningless without a cross reference to the things it <MPQA autoclass="objectiveSpeech">describes</MPQA>.</MPQA>
<MPQA autoclass="obj" certainty="9.4">This leads Searle to <MPQA autoclass="objectiveSpeech">point out</MPQA> that there is no meaning or understanding in an information processor itself.</MPQA>
<MPQA autoclass="subj" certainty="25.1">As a result Searle claims to demonstrate that even a machine that passed the Turing test would not necessarily be conscious in the human sense.</MPQA>
<MPQA autoclass="subj" certainty="35.8">Other philosophers hold <MPQA autoclass="negative">opposing</MPQA> views.</MPQA>
<MPQA autoclass="subj" certainty="49.5">Daniel C. Dennett argues in Consciousness Explained that if there is no <MPQA autoclass="negative">magic</MPQA> spark or soul, then Man is just a machine, and he <MPQA autoclass="speechDirectSubjective">asks</MPQA> why the Man-machine should have a privileged position over all other possible machines when it comes to intelligence.</MPQA>
<MPQA autoclass="subj" certainty="31.8">Dennett goes further than this support for <MPQA autoclass="negative">weak</MPQA> AI, and also proposes that information processors could become minds.</MPQA>
<MPQA autoclass="subj" certainty="12.8">Some philosophers hold that if Weak AI is accepted as possible then so must Strong AI.</MPQA>
<MPQA autoclass="subj" certainty="16.1">The Weak AI position, that intelligence might be apparent but would not be a 'mind', is countered in many ways, but one accessible example can be found in Simon Blackburn introduction to philosophy, <MPQA autoclass="speechDirectSubjective">Think</MPQA>.</MPQA>
<MPQA autoclass="subj" certainty="31.1">Blackburn <MPQA autoclass="speechDirectSubjective">points out</MPQA> that you might appear intelligent but there is no way of telling if that intelligence is real (ie: a 'mind'): We have to take it on trust or faith.</MPQA>
<MPQA autoclass="subj" certainty="12.3">Strong AI seems to involve the following assumptions about the mind:the mind is software, a finite state machine so the Church-Turing thesis applies to itpresentism <MPQA autoclass="speechDirectSubjective">describes</MPQA> the mindthe mind exists exclusively within the brainAnd the following assumption about the brain:the brain is purely hardware (i.e. only follows the rules of a classical computer)Some (including Roger Penrose) <MPQA autoclass="negative">attack</MPQA> the applicability of the Church-Turing thesis.</MPQA>
<MPQA autoclass="obj" certainty="18.4">Others <MPQA autoclass="objectiveSpeech">say</MPQA> the mind is not completely physical.</MPQA>
<MPQA autoclass="subj" certainty="2.8">Roger Penrose's argument rests on the conception of hypercomputation being possible in our universe.</MPQA>
<MPQA autoclass="subj" certainty="22.9">Quantum mechanics and newtonian mechanics do not allow hypercomputation but it is <MPQA autoclass="speechDirectSubjective">thought</MPQA> that some <MPQA autoclass="negative">strange</MPQA> space times would.</MPQA>
<MPQA autoclass="subj" certainty="11.3">However there seems to be agreement that our universe is not sufficiently convoluted to allow such hypercomputation.</MPQA>
<MPQA autoclass="subj" certainty="43.3">Ultimately the truth of Strong AI depends upon whether information processing machines can include all the properties of minds such as Consciousness.</MPQA>
<MPQA autoclass="subj" certainty="52.1">However, Weak AI is independent of the Strong AI <MPQA autoclass="negative">problem</MPQA> and there can be no doubt that many of the features of modern computers such as multiplication or database searching might have been <MPQA autoclass="speechDirectSubjective">considered</MPQA> 'intelligent' only a century ago.</MPQA>
<MPQA autoclass="subj" certainty="26.9">HistoryDevelopment of AI theoryMuch of the (original) focus of <MPQA autoclass="negative">artificial</MPQA> intelligence research draws from an experimental approach to psychology, and emphasizes what may be <MPQA autoclass="speechDirectSubjective">called</MPQA> linguistic intelligence (best exemplified in the Turing test).</MPQA>
<MPQA autoclass="subj" certainty="9.2">Approaches to <MPQA autoclass="negative">artificial</MPQA> intelligence that do not focus on linguistic intelligence include robotics and collective intelligence approaches, which focus on active <MPQA autoclass="negative">manipulation</MPQA> of an environment, or consensus <MPQA autoclass="speechDirectSubjective">decision</MPQA> making, and draw from biology and political science when seeking models of how "intelligent" behavior is organized.</MPQA>
<MPQA autoclass="subj" certainty="5.8"><MPQA autoclass="negative">Artificial</MPQA> intelligence theory also draws from animal studies, in particular with insects, which are easier to emulate as robots (see <MPQA autoclass="negative">artificial</MPQA> life), as well as animals with more <MPQA autoclass="negative">complex</MPQA> cognition, including apes, who resemble humans in many ways but have less developed capacities for planning and cognition.</MPQA>
<MPQA autoclass="subj" certainty="15.5">AI researchers argue that animals, which are simpler than humans, ought to be considerably easier to mimic.</MPQA>
<MPQA autoclass="obj" certainty="6.0">But satisfactory computational models for animal intelligence are not available.</MPQA>
<MPQA autoclass="obj" certainty="25.7">Seminal papers advancing the concept of machine intelligence include A Logical Calculus of the Ideas Immanent in Nervous Activity (1943), by Warren McCulloch and Walter Pitts, and On Computing Machinery and Intelligence (1950), by Alan Turing, and Man-Computer Symbiosis by J.C.R. Licklider.</MPQA>
<MPQA autoclass="obj" certainty="20.7">See cybernetics and Turing test for further discussion.</MPQA>
<MPQA autoclass="subj" certainty="7.1">There were also early papers which <MPQA autoclass="negative"><MPQA autoclass="speechDirectSubjective">denied</MPQA></MPQA> the possibility of machine intelligence on logical or philosophical grounds such as Minds, Machines and Godel (1961) by John Lucas [1] (http://users.ox.ac.uk/~jrlucas/Godel/mmg.html).</MPQA>
<MPQA autoclass="subj" certainty="30.2">With the development of practical techniques based on AI research, advocates of AI have argued that <MPQA autoclass="negative">opponents</MPQA> of AI have repeatedly changed their position on tasks such as computer chess or speech recognition that were previously regarded as "intelligent" in order to <MPQA autoclass="negative"><MPQA autoclass="speechDirectSubjective">deny</MPQA></MPQA> the <MPQA autoclass="negative">accomplishments</MPQA> of AI.</MPQA>
<MPQA autoclass="subj" certainty="7.9">They <MPQA autoclass="speechDirectSubjective">point out</MPQA> that this moving of the goalposts effectively defines "intelligence" as "whatever humans can do that machines cannot".</MPQA>
<MPQA autoclass="subj" certainty="29.5">John von Neumann (<MPQA autoclass="speechDirectSubjective">quoted</MPQA> by E.T. Jaynes) anticipated this in 1948 by <MPQA autoclass="speechDirectSubjective">saying</MPQA>, in response to a comment at a lecture that it was <MPQA autoclass="negative">impossible</MPQA> for a machine to <MPQA autoclass="speechDirectSubjective">think</MPQA>: "You insist that there is something a machine cannot do.</MPQA>
<MPQA autoclass="subj" certainty="33.6">If you will tell me precisely what it is that a machine cannot do, then I can always make a machine which will do just that!". Von Neumann was presumably alluding to the Church-Turing thesis which states that any effective procedure can be simulated by a (generalized) computer.</MPQA>
<MPQA autoclass="obj" certainty="13.2">In 1969 McCarthy and Hayes started the discussion about the frame problem with their essay, "Some Philosophical Problems from the Standpoint of Artificial Intelligence".</MPQA>
<MPQA autoclass="obj" certainty="18.7">Experimental AI researchArtificial intelligence began as an experimental field in the 1950s with such pioneers as Allen Newell and Herbert Simon, who founded the first artificial intelligence laboratory at Carnegie-Mellon University, and McCarthy and Marvin Minsky, who founded the MIT AI Lab in 1959.</MPQA>
<MPQA autoclass="obj" certainty="20.6">They all attended the aforementioned Dartmouth College summer AI conference in 1956, which was organized by McCarthy, Minsky, Nathan Rochester of IBM and Claude Shannon.</MPQA>
<MPQA autoclass="obj" certainty="18.3">Historically, there are two broad styles of AI research - the "neats" and "scruffies".</MPQA>
<MPQA autoclass="subj" certainty="6.8">"Neat", classical or symbolic AI research, in general, involves symbolic <MPQA autoclass="negative">manipulation</MPQA> of abstract concepts, and is the methodology used in most expert systems.</MPQA>
<MPQA autoclass="subj" certainty="25.3">Parallel to this are the "scruffy", or "connectionist", approaches, of which neural networks are the best-known example, which try to "evolve" intelligence through building systems and then improving them through some automatic process rather than systematically designing something to complete the task.</MPQA>
<MPQA autoclass="subj" certainty="7.1">Both approaches appeared very early in AI history.</MPQA>
<MPQA autoclass="subj" certainty="6.1">Throughout the 1960s and 1970s scruffy approaches were <MPQA autoclass="negative">pushed</MPQA> to the background, but interest was regained in the 1980s when the <MPQA autoclass="negative">limitations</MPQA> of the "neat" approaches of the time became clearer.</MPQA>
<MPQA autoclass="subj" certainty="7.7">However, it has become clear that contemporary methods using both broad approaches have <MPQA autoclass="negative">severe</MPQA> <MPQA autoclass="negative">limitations</MPQA>.</MPQA>
<MPQA autoclass="subj" certainty="1.2">Artificial intelligence research was very heavily funded in the 1980s by the Defense Advanced Research Projects Agency in the United States and by the fifth generation computer systems project in Japan.</MPQA>
<MPQA autoclass="subj" certainty="23.0">The <MPQA autoclass="negative">failure</MPQA> of the work funded at the time to produce immediate results, despite the grandiose promises of some AI practitioners, led to correspondingly large cutbacks in funding by government agencies in the late 1980s, leading to a general downturn in activity in the field known as AI winter.</MPQA>
<MPQA autoclass="subj" certainty="21.6">Over the following decade, many AI researchers moved into related areas with more modest goals such as machine learning, robotics, and computer vision, though research in pure AI continued at reduced levels.</MPQA>
<MPQA autoclass="subj" certainty="17.2">Practical applications of AI techniquesWhilst progress towards the ultimate goal of human-like intelligence has been slow, many spinoffs have come in the process.</MPQA>
<MPQA autoclass="subj" certainty="1.5">Notable examples include the languages LISP and Prolog, which were invented for AI research but are now used for non-AI tasks.</MPQA>
<MPQA autoclass="obj" certainty="9.9">Hacker culture first sprang from AI laboratories, in particular the MIT AI Lab, home at various times to such luminaries as McCarthy, Minsky, Seymour Papert (who developed Logo there), Terry Winograd (who abandoned AI after developing SHRDLU).</MPQA>
<MPQA autoclass="obj" certainty="13.2">Many other useful systems have been built using technologies that at least once were active areas of AI research.</MPQA>
<MPQA autoclass="obj" certainty="24.8">Some examples include:Chinook was declared the Man-Machine World Champion in checkers (draughts) in 1994.</MPQA>
<MPQA autoclass="obj" certainty="17.9">Deep Blue, a chess-playing computer, beat Garry Kasparov in a famous match in 1997.</MPQA>
<MPQA autoclass="obj" certainty="16.8"> Fuzzy logic, a technique for reasoning under uncertainty, has been widely used in industrial control systems.</MPQA>
<MPQA autoclass="obj" certainty="5.2">Expert systems are being used to some extent industrially.</MPQA>
<MPQA autoclass="obj" certainty="14.1">Machine translation systems such as SYSTRAN are widely used, although results are not yet comparable with human translators.</MPQA>
<MPQA autoclass="obj" certainty="14.2">Neural networks have been used for a wide variety of tasks, from intrusion detection systems to computer games.</MPQA>
<MPQA autoclass="obj" certainty="0.0">Optical character recognition systems can translate arbitrary typewritten European script into text.</MPQA>
<MPQA autoclass="obj" certainty="14.2">Handwriting recognition is used in millions of personal digital assistants.</MPQA>
<MPQA autoclass="obj" certainty="18.3">Speech recognition is commercially available and is widely deployed.</MPQA>
<MPQA autoclass="obj" certainty="17.6">Computer algebra systems, such as Mathematica and Macsyma, are commonplace.</MPQA>
<MPQA autoclass="obj" certainty="18.3">Machine vision systems are used in many industrial applications ranging from hardware verification to security systems.</MPQA>
<MPQA autoclass="subj" certainty="5.0">The vision of <MPQA autoclass="negative">artificial</MPQA> intelligence replacing human professional judgment has arisen many times in the history of the field, in science fiction and today in some specialized areas where "expert systems" are used to augment or to replace professional judgment in some areas of engineering and of medicine.</MPQA>
<MPQA autoclass="subj" certainty="1.5">Hypothetical consequences of AISome observers foresee the development of systems that are far more intelligent and <MPQA autoclass="negative">complex</MPQA> than anything currently known.</MPQA>
<MPQA autoclass="obj" certainty="7.7">One name for these hypothetical systems is artilects.</MPQA>
<MPQA autoclass="obj" certainty="7.8">With the introduction of artificially intelligent non-deterministic systems, many ethical issues will arise.</MPQA>
<MPQA autoclass="obj" certainty="6.0">Many of these issues have never been encountered by humanity.</MPQA>
<MPQA autoclass="subj" certainty="12.9">Over time, debates have tended to focus less and less on "possibility" and more on "desirability", as emphasized in the "Cosmist" (versus "Terran") debates initiated by Hugo de Garis and Kevin Warwick.</MPQA>
<MPQA autoclass="subj" certainty="17.0">A Cosmist, according to de Garis, is actually seeking to build more intelligent successors to the human species.</MPQA>
<MPQA autoclass="obj" certainty="1.7">The emergence of this debate suggests that desirability questions may also have influenced some of the early thinkers "against".</MPQA>
<MPQA autoclass="subj" certainty="0.0">Some issues that bring up interesting ethical questions are:Determining the sentience of a system we create.</MPQA>
<MPQA autoclass="obj" certainty="2.5">Turing testCognitionWhy do we have a need to categorize these systems at all?</MPQA>
<MPQA autoclass="subj" certainty="7.0">Can AI be defined in a graded sense?</MPQA>
<MPQA autoclass="subj" certainty="51.8">Freedoms and rights for these systemsCan AIs be "smarter" than humans in the same way that we are "smarter" than other animals?</MPQA>
<MPQA autoclass="subj" certainty="52.4">Designing systems that are far more intelligent than any one humanDeciding how many safe-guards to design into these systemsSeeing how much learning capability a system needs to replicate human thought, or how well it could do tasks without it (e.g. expert systems)The SingularityEffect on careers and jobs.</MPQA>
<MPQA autoclass="subj" certainty="9.5">The <MPQA autoclass="negative">problems</MPQA> may resemble <MPQA autoclass="negative">problems</MPQA> seen under free trade.</MPQA>
<MPQA autoclass="obj" certainty="17.3">Sub-fields of AI researchCombinatorial searchComputer visionExpert systemGenetic programmingGenetic algorithmKnowledge representationMachine learningMachine planningNeural networkNatural language processingProgram synthesisRoboticsArtificial lifeArtificial beingDistributed artificial intelligenceSwarm IntelligenceLogic programming was sometimes <MPQA autoclass="objectiveSpeech">considered</MPQA> a field of artificial intelligence, but this is no longer the case.</MPQA>
<MPQA autoclass="obj" certainty="26.3">Famous figuresMachines displaying some degree of "intelligence"There are many examples of programs displaying some degree of intelligence.</MPQA>
<MPQA autoclass="obj" certainty="29.9">Some of these are:The Start Project (http://www.ai.mit.edu/projects/infolab/)</MPQA>
<MPQA autoclass="obj" certainty="6.3">- a web-based system which answers questions in English.</MPQA>
<MPQA autoclass="subj" certainty="14.0">Cyc, a knowledge base with vast collection of facts about the real world and logical reasoning ability.</MPQA>
<MPQA autoclass="obj" certainty="6.3">ALICE, a chatterbotAlan (http://www.a-i.com/alan1),</MPQA>
<MPQA autoclass="obj" certainty="13.4">another chatterbotELIZA, a program which pretends to be a psychotherapist, developed in 1966PAM (Plan Applier Mechanism) - a story understanding system developed by John Wilensky in 1978.</MPQA>
<MPQA autoclass="obj" certainty="21.5">SAM (Script applier mechanism) - a story understanding system, developed in 1975.</MPQA>
<MPQA autoclass="obj" certainty="0.0">SHRDLU - an early natural language understanding computer program developed in 1968-1970.</MPQA>
<MPQA autoclass="subj" certainty="12.8">Creatures, a computer game with breeding, evolving creatures coded from the genetic level upwards using a sophisticated biochemistry and neural network brains.</MPQA>
<MPQA autoclass="obj" certainty="11.1">BBC news story (http://news.bbc.co.uk/1/hi/wales/3521852.stm)</MPQA>
<MPQA autoclass="obj" certainty="30.3">on the creator of Creatures latest creation.</MPQA>
<MPQA autoclass="obj" certainty="29.2">Steve Grand's Lucy.</MPQA>
<MPQA autoclass="obj" certainty="27.5">Eurisko - a language for solving problems which consists of heuristics, including heuristics for how to use and change its heuristics.</MPQA>
<MPQA autoclass="obj" certainty="29.7">Developed in 1978 by Douglas Lenat.</MPQA>
<MPQA autoclass="obj" certainty="31.3">X-Ray Vision for Surgeons (http://www.ai.mit.edu/projects/medical-vision/)</MPQA>
<MPQA autoclass="obj" certainty="28.5">- a group in MIT which researches medical vision.</MPQA>
<MPQA autoclass="obj" certainty="25.8">Neural networks-based programs for backgammon and go (http://www.jellyfish-ai.com).</MPQA>
<MPQA autoclass="obj" certainty="15.1">AI researchersThere are many thousands of AI researchers around the world at hundreds of research institutions and companies.</MPQA>
<MPQA autoclass="subj" certainty="13.7">Among the many who have made significant contributions are:Maggie BodenRodney BrooksBoris KatzDoug LenatJohn McCarthyMarvin MinskyRaj ReddyRoger SchankAlan TuringWolfgang WahlsterTerry WinogradTo some computer scientists, the phrase <MPQA autoclass="negative">artificial</MPQA> intelligence has acquired somewhat of a <MPQA autoclass="negative">bad</MPQA> name due to the large discrepancy between what has been achieved so far in the field and some more usual notions of intelligence.</MPQA>
<MPQA autoclass="subj" certainty="11.9">This <MPQA autoclass="negative">problem</MPQA> has been <MPQA autoclass="negative">aggravated</MPQA> by various popular science writers and media personalities such as Kevin Warwick whose work has raised the expectations of AI research far beyond its current capabilities.</MPQA>
<MPQA autoclass="subj" certainty="4.2">For this reason, some researchers working on topics related to <MPQA autoclass="negative">artificial</MPQA> intelligence <MPQA autoclass="speechDirectSubjective">say</MPQA> they work in cognitive science, informatics, statistical inference or information engineering.</MPQA>
<MPQA autoclass="subj" certainty="16.6">However, progress has in fact been made, and AI is today routinely employed in thousands of industrial systems around the world.</MPQA>
<MPQA autoclass="obj" certainty="3.0">See Raj Reddy's AAAI paper for a huge review of real-world AI systems in deployment today.</MPQA>
<MPQA autoclass="obj" certainty="18.6">ResourcesFurther readingNon-fictionArtificial Intelligence: A Modern Approach by Stuart J. Russell and Peter NorvigGodel, Escher, Bach: An Eternal Golden Braid by Douglas R. HofstadterShadows of the Mind and The Emperor's New Mind by Roger PenroseConsciousness Explained by Dennett.</MPQA>
<MPQA autoclass="obj" certainty="6.3">The Age of Spiritual Machines by Ray KurzweilUnderstanding Understanding: Essays on Cybernetics and Cognition by Heinz von FoersterIn the Image of the Brain: Breaking the Barrier Between Human Mind and Intelligent Machines by Jim JubakToday's Computers, Intelligent Machines and Our Future by Hans Moravec, Stanford UniversityFictionThe following is a list of influential works See also longer lists at:-List of fictional robots and androids:List of fictional computers:HAL 9000 in 2001 A Space OdysseyHARLIE in When H.A.R.L.I.E. was One by David GerroldA.I.: Artificial IntelligenceArtificial intelligence - mainly its philosophical implications and its impact on Humanity -- is a major theme in David Lodge's campus novel Thinks ... (2001).</MPQA>
<MPQA autoclass="obj" certainty="6.8">Rosie and other robots from The JetsonsMike in The Moon is a Harsh Mistress by Robert A. HeinleinWilliam Gibson's NeuromancerIsaac Asimov's I, Robot series, introducing the famous Three Laws of Robotics, is often <MPQA autoclass="objectiveSpeech">considered</MPQA> to be the most accurate fictional depiction of AIAI related organizationsAmerican Association for Artificial Intelligence (http://www.aaai.org/)</MPQA>
<MPQA autoclass="obj" certainty="21.3">European Coordinating Committee for Artificial Intelligence (http://www.eccai.org/)</MPQA>
<MPQA autoclass="obj" certainty="29.9">The Association for Computational Linguistics (http://www1.cs.columbia.edu/~acl/)</MPQA>
<MPQA autoclass="obj" certainty="29.8">Artificial Intelligence Student Union (http://www.dotmotive.com/~aisu/)</MPQA>
<MPQA autoclass="obj" certainty="29.8">German Research Center for Artificial Intelligence, DFKI GmbH (http://www.dfki.de/)</MPQA>
<MPQA autoclass="obj" certainty="31.3">Association for Uncertainty in Artificial Intelligence (http://www.auai.org/)</MPQA>
<MPQA autoclass="obj" certainty="31.7">Singularity Institute for Artificial Intelligence (http://www.singinst.org)</MPQA>
<MPQA autoclass="obj" certainty="31.7">SourcesJohn McCarthy: Proposal for the Dartmouth Summer Research Project On Artificial Intelligence.</MPQA>
<MPQA autoclass="obj" certainty="29.1">[2] (http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html)</MPQA>
<MPQA autoclass="obj" certainty="18.5">See alsoImportant publications in artificial intelligence.</MPQA>
<MPQA autoclass="subj" certainty="8.4">Philosophyfunctionalismsimulated consciousnessSearle's Chinese roomconsciousnessLogicsemanticsSciencecognitive sciencecomputer sciencecyberneticspsychologyApplications<MPQA autoclass="negative">artificial</MPQA> intelligence projects<MPQA autoclass="negative">artificial</MPQA> intelligence agentbio-inspired computingUncategorisedCollective intelligence - the idea that a relatively large number of people co-operating in one process can lead to reliable action.</MPQA>
<MPQA autoclass="subj" certainty="45.8">Quantum mind - the idea that large-scale quantum coherence is necessary to understand the brain.the Singularity - a time at which technological progress accelerates beyond the ability of current-day human beings to understand it, or the point in time of the emergence of smarter-than-human intelligence.</MPQA>
<MPQA autoclass="subj" certainty="46.8">Mindpixel - A project to collect simple true / <MPQA autoclass="negative">false</MPQA> assertions and collaboratively validate them with the aim of using them as a body of human common sense knowledge that can be utilised by a machine.</MPQA>
<MPQA autoclass="subj" certainty="40.1">Game programming AI<MPQA autoclass="negative">artificial</MPQA> consciousnesstruth maintenance systems - by Gerald Jay Sussman and Richard StallmanExternal links (see also #AI-Related Organizations)Programming:AI (http://wikibooks.org/wiki/Programming:AI)</MPQA>
<MPQA autoclass="obj" certainty="9.1">@ Wikibooks.org</MPQA>
<MPQA autoclass="obj" certainty="29.9">University of Berkeley AI Resources (http://www.cs.berkeley.edu/~russell/ai.html)</MPQA>
<MPQA autoclass="obj" certainty="28.0">linking to about 869 other WWW pages about AIAI Depot (http://ai-depot.com/) - community discussion, news, and articlesLoebner Prize website (http://www.loebner.net/Prizef/loebner-prize.html)</MPQA>
<MPQA autoclass="obj" certainty="28.5">AIWiki (http://purl.net/net/AIWiki) - a wiki devoted to AI.AIAWiki (http://ai.squeakydolphin.com/) - AI algorithms and research.</MPQA>
<MPQA autoclass="obj" certainty="29.8">AI web category on Open Directory (http://www.dmoz.org/Computers/Artificial_Intelligence/)</MPQA>
<MPQA autoclass="obj" certainty="31.3">Mindpixel (http://www.mindpixel.com/)</MPQA>
<MPQA autoclass="obj" certainty="29.2">"The Planet's Largest Artificial Intelligence Effort"OpenMind CommonSense (http://commonsense.media.mit.edu/cgi-bin/search.cgi/)</MPQA>
<MPQA autoclass="obj" certainty="10.0">"Teaching computers the stuff we all <MPQA autoclass="objectiveSpeech">know</MPQA>"Artificially Intelligent Ouija Board (http://www.bitesizeinc.net/index.php/ouija.html)</MPQA>
<MPQA autoclass="obj" certainty="8.6">- creative example of human-like AIArtificial Life (http://www.ifi.unizh.ch/ailab/)</MPQA>
<MPQA autoclass="obj" certainty="27.0">- AI Lab, ZurichHeuristics and AI in finance and investment (http://www.geocities.com/francorbusetti/)</MPQA>
<MPQA autoclass="obj" certainty="29.8">SourceForge Open Source AI projects (http://sourceforge.net/softwaremap/trove_list.php?form_cat=133) - 1139 projectsRetrieved from "http://en.wikipedia.org/wiki/Artificial_intelligence"</MPQA>
<MPQA autoclass="obj" certainty="31.3">Categories: Artificial intelligence | Science</MPQA>