Difference between revisions of "Artificial intelligence" - New World Encyclopedia

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[[Image:HONDA ASIMO.jpg|250px|thumb|right|Honda's humanoid robot]]
 
[[Image:HONDA ASIMO.jpg|250px|thumb|right|Honda's humanoid robot]]
{{Redirect|AI|other uses of "AI" and "Artificial Intelligence"}}
 
  
'''Artificial intelligence (AI)''' is a branch of [[computer science]] and [[engineering]] that deals with intelligent behavior, learning, and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. Examples include [[control system]]*s; [[automated planning and scheduling]]*; the ability to answer diagnostic and consumer questions; and [[handwriting recognition|handwriting]]*, [[speech recognition|speech]]*, and [[facial recognition system|facial recognition]]*. As such, it has become an engineering discipline, focused on providing solutions to real-life problems, [[Computer software|software]] applications, traditional strategy games like [[computer chess]]*, and various [[video game]]s.
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'''Artificial intelligence (AI)''' is a branch of [[computer science]] and [[engineering]] that deals with intelligent behavior, learning, and adaptation in machines. [[John McCarthy]] coined the term to mean "the science and engineering of making intelligent machines."<ref>John McCarthy, [http://www-formal.stanford.edu/jmc/whatisai/whatisai.html What is Artificial Intelligence?] Retrieved February 22, 2020.</ref> Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. Examples include [[control system]]s; automated planning and scheduling; the ability to answer diagnostic and consumer questions; and [[handwriting]], [[speech]], and [[facial recognition]]. As such, it has become an engineering discipline, focused on providing solutions to real-life problems, [[Computer software|software]] applications, traditional strategy games like [[computer chess]], and various [[video game]]s.
 
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{{toc}}
Artificial intelligence is being used today for many different purposes. With AI, we can create safer environments for workers by using robots for dangerous situations. Robotics are being used throughout the world.  In the future, it we may see AI being used more for human interaction.  For example, when you have a common automated teller, it would actually be able to do visual recognition and respond to you personally.   
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Artificial intelligence is being used today for many different purposes and all throughout the world. It can create safer environments for workers by using robots for dangerous situations. In the future, it may be used more for human interaction; for example, an automated teller would actually be able to do visual recognition and respond to one personally.   
 
 
(For topics relating specifically to full human-like intelligence, see [[Strong AI]].)
 
  
 
==Schools of thought==
 
==Schools of thought==
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AI divides roughly into two schools of thought: Conventional AI and [[Computational Intelligence]] (CI), also sometimes referred to as Synthetic Intelligence.
  
AI divides roughly into two schools of thought: Conventional AI and [[Computational Intelligence]] (CI), also sometimes referred to as [[Synthetic Intelligence]] to highlight the differences.
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'''Conventional AI''' mostly involves methods now classified as machine learning, characterized by formalism and statistical analysis. This is also known as ''symbolic AI, logical AI,'' or ''neat AI.'' Methods include:
 
 
'''Conventional AI''' mostly involves methods now classified as [[machine learning]]*, characterized by [[formalism]]* and [[statistical analysis]]. This is also known as symbolic AI, logical AI, [[Neats|neat AI]]* and [[GOFAI|Good Old Fashioned Artificial Intelligence (GOFAI)]]*.
 
 
 
Methods include:
 
 
*[[Expert system]]s: applies reasoning capabilities to reach a conclusion. An expert system can process large amounts of known information and provide conclusions based on them.
 
*[[Expert system]]s: applies reasoning capabilities to reach a conclusion. An expert system can process large amounts of known information and provide conclusions based on them.
*[[Case based reasoning]] is the process of solving new problems based on the solutions of similar past problems.
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*[[Case-based reasoning]] is the process of solving new problems based on the solutions of similar past problems.
 
*[[Bayesian network]]s represents a set of variables together with a joint probability distribution with explicit independence assumptions.
 
*[[Bayesian network]]s represents a set of variables together with a joint probability distribution with explicit independence assumptions.
*[[Behavior based AI]]:  a modular method of building AI systems by hand.
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*[[Behavior-based AI]]:  a modular method of building AI systems by hand.
'''[[Computational Intelligence]]''' involves [[iterative]] development or learning (e.g. parameter tuning e.g. in  [[connectionist]] systems). Learning is based on [[empirical]] data and is associated with non-symbolic AI, [[Scruffies|scruffy AI]] and [[soft computing]]. Methods mainly include:
 
*[[Artificial neural network|Neural network]]s: systems with very strong [[pattern recognition]] capabilities.
 
*[[Fuzzy system]]s: techniques for [[reasoning under uncertainty]], have been widely used in modern industrial and consumer product control systems.
 
*[[Evolutionary computation]]: applies biologically inspired concepts such as [[population]]s, [[mutation]] and [[survival of the fittest]] to generate increasingly better solutions to the problem. These methods most notably divide into [[evolutionary algorithm]]s (e.g. [[genetic algorithm]]*s) and [[swarm intelligence]]* (e.g. [[ant colony optimization|ant algorithm]]*s).
 
  
With [[hybrid intelligent system]]s attempts are made to combine these two groups. Expert inference rules can be generated through neural network or [[production rule]]*s from statistical learning such as in [[ACT-R]]*. It is thought that the human brain uses multiple techniques to both formulate and cross-check results. Thus, [[A.I. Systems Integration|systems integration]]* is seen as promising and perhaps necessary for true AI.
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'''Computational Intelligence''' involves iterative development or learning. Learning is based on empirical data. It is also known as ''non-symbolic AI, scruffy AI,'' and ''soft computing.'' Methods mainly include:
 +
*[[Artificial neural network|Neural network]]s: systems with very strong pattern recognition capabilities.
 +
*[[Fuzzy system]]s: techniques for reasoning under uncertainty, have been widely used in modern industrial and consumer product control systems.
 +
*[[Evolutionary computation]]: applies biologically inspired concepts such as [[population]]s, [[mutation]], and survival of the fittest to generate increasingly better solutions to the problem. These methods most notably divide into [[evolutionary algorithm]]s and [[swarm intelligence]].
 +
 
 +
'''Hybrid intelligent systems''' attempt to combine these two groups. It is thought that the human brain uses multiple techniques to both formulate and cross-check results. Thus, systems integration is seen as promising and perhaps necessary for true AI.
  
 
==History==
 
==History==
{{main|History of artificial intelligence}}
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Early in the seventeenth century, [[René Descartes]] envisioned the bodies of animals as complex but reducible machines, thus formulating the [[mechanism (philosophy)|mechanistic theory]], also known as the "clockwork paradigm." [[Wilhelm Schickard]] created the first mechanical, digital calculating machine in 1623, followed by machines of [[Blaise Pascal]] (1643) and  [[Gottfried Wilhelm von Leibniz]] (1671), who also invented the [[binary system]]. In the nineteenth century, [[Charles Babbage]] and [[Ada Lovelace]] worked on programmable mechanical calculating machines.
  
Early in the 17th century, [[René Descartes]] envisioned the bodies of animals as complex but reducible machines, thus formulating the [[mechanism (philosophy)|mechanistic theory]], also known as the "clockwork paradigm". [[Wilhelm Schickard]] created the first mechanical digital [[calculating machine]] in 1623, followed by machines of [[Blaise Pascal]] (1643) and  [[Gottfried Wilhelm von Leibniz]] (1671), who also invented the [[binary system]]. In the 19th century, [[Charles Babbage]] and [[Ada Lovelace]] worked on programmable mechanical calculating machines.
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[[Bertrand Russell]] and [[Alfred North Whitehead]] published ''[[Principia Mathematica]]'' in 1910-1913, which revolutionized formal logic. In 1931 [[Kurt Gödel]] showed that sufficiently powerful consistent formal systems contain true theorems not provable by any theorem-proving AI that is systematically deriving all possible theorems from the axioms.  In 1941 [[Konrad Zuse]] built the first working program-controlled computers.  [[Warren McCulloch]] and [[Walter Pitts]] published ''A Logical Calculus of the Ideas Immanent in Nervous Activity'' (1943), laying the foundations for [[neural network]]s. [[Norbert Wiener]]'s ''Cybernetics or Control and Communication in the Animal and the Machine,'' (1948) popularizes the term "cybernetics."   
 
 
[[Bertrand Russell]] and [[Alfred North Whitehead]] published ''[[Principia Mathematica]]'' in 1910-1913, which revolutionized formal logic. In 1931 [[Kurt Gödel]] showed that sufficiently powerful consistent formal systems contain true theorems unprovable by any theorem-proving AI that is systematically deriving all possible theorems from the axioms.  In 1941 [[Konrad Zuse]] built the first working program-controlled computers.  [[Warren McCulloch]] and [[Walter Pitts]] published ''A Logical Calculus of the Ideas Immanent in Nervous Activity'' (1943), laying the foundations for [[neural network]]s. [[Norbert Wiener]]'s ''Cybernetics or Control and Communication in the Animal and the Machine'' ([[MIT Press]], 1948) popularizes the term "[[cybernetics]]".  
 
  
 
===1950s===
 
===1950s===
The 1950s were a period of active efforts in AI. In 1950, [[Alan Turing]] introduced the "[[Turing test]]" as a way of operationalizing a test of intelligent behavior. The first working AI programs were written in 1951 to run on the [[Ferranti Mark I]] machine of the [[University of Manchester]]:  a draughts-playing program written by [[Christopher Strachey]] and a chess-playing program written by Dietrich Prinz.  [[John McCarthy (computer scientist)|John McCarthy]] coined the term "artificial intelligence" at the first conference devoted to the subject, in 1956. He also invented the [[Lisp programming language]]. [[Joseph Weizenbaum]] built [[ELIZA]], a [[chatterbot]] implementing [[Rogerian psychotherapy]].  The birthdate of AI is generally considered to be July 1956 at the [[Dartmouth Conference]], where many of these people met and exchanged ideas.
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The 1950s were a period of active efforts in AI. In 1950, [[Alan Turing]] introduced the "Turing test," a test of intelligent behavior. The first working AI programs were written in 1951 to run on the Ferranti Mark I machine of the University of Manchester:  a draughts-playing program written by Christopher Strachey and a chess-playing program written by Dietrich Prinz.  [[John McCarthy]] coined the term "artificial intelligence" at the first conference devoted to the subject, in 1956. He also invented the Lisp programming language. [[Joseph Weizenbaum]] built ELIZA, a chatterbot implementing Rogerian psychotherapy.  The birth date of AI is generally considered to be July 1956 at the Dartmouth Conference, where many of these people met and exchanged ideas.
  
At the same time, [[John von Neumann]], who had been hired by the [[RAND Corporation]], developed the [[game theory]], which would prove invaluable in the progress of AI research.
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At the same time, [[John von Neumann]], who had been hired by the RAND Corporation, developed the [[game theory]], which would prove invaluable in the progress of AI research.
  
===1960s-1970s===
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===1960s–1970s===
During the 1960s and 1970s, [[Joel Moses]] demonstrated the power of [[symbolic reasoning]] for integration problems in the [[Macsyma]] program, the first successful knowledge-based program in mathematics. [[Leonard Uhr]] and Charles Vossler published "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators" in 1963, which described one of the first machine learning programs that could adaptively acquire and modify features and thereby overcome the limitations of simple perceptrons of [[Frank Rosenblatt|Rosenblatt]]. [[Marvin Minsky]] and [[Seymour Papert]] published ''Perceptrons'', which demonstrated the limits of simple neural nets. [[Alain Colmerauer]] developed the [[Prolog]] computer language. Ted Shortliffe demonstrated the power of rule-based systems for [[knowledge representation]] and inference in medical diagnosis and therapy in what is sometimes called the first expert system. [[Hans Moravec]] developed the first computer-controlled vehicle to [[autonomous vehicle|autonomously]] negotiate cluttered obstacle courses.
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During the 1960s and 1970s, [[Joel Moses]] demonstrated the power of [[symbolic reasoning]] for integration problems in the Macsyma program, the first successful knowledge-based program in mathematics. [[Leonard Uhr]] and Charles Vossler published "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators" in 1963, which described one of the first machine learning programs that could adaptively acquire and modify features. [[Marvin Minsky]] and [[Seymour Papert]] published ''Perceptrons,'' which demonstrated the limits of simple neural nets. [[Alain Colmerauer]] developed the [[Prolog]] computer language. Ted Shortliffe demonstrated the power of rule-based systems for knowledge representation and inference in medical diagnosis and therapy in what is sometimes called the first expert system. [[Hans Moravec]] developed the first computer-controlled vehicle to autonomously negotiate cluttered obstacle courses.
  
 
===1980s===
 
===1980s===
In the 1980s, neural networks became widely used due to the [[backpropagation]] algorithm, first described by [[Paul Werbos]] in 1974. The team of [[Ernst Dickmanns]] built the first robot cars, driving up to 55 mph on empty streets.  
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In the 1980s, neural networks became widely used due to the back propagation algorithm, first described by [[Paul Werbos]] in 1974. The team of [[Ernst Dickmanns]] built the first robot cars, driving up to 55 mph on empty streets.  
  
===1990s & Turn of the Century===
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===1990s and the turn of the century===
The 1990s marked major achievements in many areas of AI and demonstrations of various applications. In 1995, one of Dickmanns' robot cars drove more than 1000 miles in traffic at up to 110 mph. [[Deep Blue]], a chess-playing computer, beat [[Garry Kasparov]] in a famous six-game match in 1997. [[Defense Advanced Research Projects Agency|DARPA]] stated that the costs saved by implementing AI methods for scheduling units in the first [[Gulf War|Persian Gulf War]] have repaid the US government's entire investment in AI research since the 1950s. [[Honda]] built the first prototypes of humanoid robots like the one depicted above.
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The 1990s marked major achievements in many areas of AI and demonstrations of various applications. In 1995, one of Dickmanns' robot cars drove more than 1000 miles in traffic at up to 110 mph. [[Deep Blue]], a chess-playing computer, beat Garry Kasparov in a famous six-game match in 1997. The Defense Advanced Research Projects Agency stated that the costs saved by implementing AI methods for scheduling units in the first [[Gulf War|Persian Gulf War]] have repaid the US government's entire investment in AI research since the 1950s. [[Honda]] built the first prototypes of humanoid robots like the one depicted above.
  
During the 1990s and 2000s AI has become very influenced by probability theory and statistics.  [[Bayesian networks]] are the focus of this movement, providing links to more rigorous topics in statistics and engineering such as [[Markov process|Markov models]] and [[Kalman filter]]s, and bridging the divide between `neat' and `scruffy' approaches. The last few years have also seen a big interest in game theory applied to AI [[decision making]].  This new school of AI is sometimes called `machine learning'.  After the [[September 11, 2001 attacks]] there has been much renewed interest and funding for threat-detection AI systems, including [[machine vision]] research and [[data-mining]].  However despite the hype, excitment about Bayesian AI is perhaps now fading again as successful Bayesian models have only appeared for tiny statistical tasks (such as finding [[principal components]] probabilistically) and appear to be intractable for general perception and decision making.
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During the 1990s and 2000s AI became very influenced by probability theory and statistics.  [[Bayesian networks]] are the focus of this movement, providing links to more rigorous topics in statistics and engineering such as Markov models and Kalman filters, and bridging the divide between ''neat'' and ''scruffy'' approaches. After the September 11, 2001 attacks there has been much renewed interest and funding for threat-detection AI systems, including machine vision research and data-mining.  However despite the hype, excitement about Bayesian AI is perhaps now fading again as successful Bayesian models have only appeared for tiny statistical tasks (such as finding principal components probabilistically) and appear to be intractable for general perception and decision-making.
  
==Challenge & Prize==
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===The 2010s===
The [[DARPA Grand Challenge]] is a race for a $2 million prize where cars drive themselves across several hundred miles of challenging desert terrain without any communication with humans, using [[GPS]], computers and a sophisticated array of sensors. In 2005 the winning vehicles completed all 132 miles of the course in just under 7 hours.  Unfortunately, there will be no prize money awarded to the winners of the 2007 race due to a re-allocation of DARPA funds through a bill signed by George W. Bush in which Congress switched the authority from DARPA to its boss, the Director of Defense Engineering and Research. [http://apnews.myway.com//article/20061020/D8KSENRO0.html]
+
Advanced statistical techniques (loosely known as [[deep learning]]), access to [[big data|large amounts of data]] and [[Moore's law|faster computers]] enabled advances in [[machine learning]] and perception. By the mid 2010s, machine learning applications were used throughout the world.
  
In the post-dot com boom era, some search engine websites such have sprung using a simple form of AI to provide answers to questions by entered by the visitor.
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In a ''[[Jeopardy!]]'' [[quiz show]] exhibition match, [[IBM]]'s [[question answering system]], [[Watson (artificial intelligence software)|Watson]], defeated the two greatest Jeopardy champions, [[Brad Rutter]] and [[Ken Jennings]], by a significant margin.<ref> John Markoff, [http://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html?_r=0 Computer Wins on ‘Jeopardy!’: Trivial, It’s Not] ''The New York Times'', February 16, 2011. Retrieved February 22, 2020.</ref> The [[Kinect]], which provides a 3D body–motion interface for the [[Xbox 360]] and the Xbox One use algorithms that emerged from lengthy AI research,<ref>Harry Fairhead, [http://www.i-programmer.info/news/105-artificial-intelligence/2176-kinects-ai-breakthrough-explained.html Kinect's AI breakthrough explained] ''i-programmer.info'', March 26, 2011. Retrieved February 22, 2020. </ref> as do [[intelligent personal assistant]]s in [[smartphone]]s.<ref>Dan Rowinski, [http://readwrite.com/2013/01/15/virtual-personal-assistants-the-future-of-your-smartphone-infographic Virtual Personal Assistants & The Future Of Your Smartphone] ''Readwrite'', January 15, 2013. Retrieved February 22, 2020.</ref>
Questions such as "What is the tallest building?" Can be entered into the search engine's input form and a list of answers will be returned.
+
 
 +
In March 2016, [[AlphaGo]] won 4 out of 5 games of [[Go (game)|Go]] in a match with Go champion [[Lee Sedol]], becoming the first [[Computer Go|computer Go-playing system]] to beat a professional Go player without [[Go handicaps|handicaps]].<ref>[http://www.bbc.com/news/technology-35785875 Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol] ''BBCNews'', March 12, 2016. Retrieved February 22, 2020.</ref> Other examples include Microsoft's development of a Skype system that can automatically translate from one language to another and Facebook's system that can describe images to blind people.
  
 
==AI in Philosophy==
 
==AI in Philosophy==
{{portalpar|Mind and Brain}}
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The strong AI vs. weak AI debate is a hot topic amongst AI [[philosophy|philosophers]]. This involves the philosophy of the mind and the mind-body problem. Most notably Roger Penrose in his book ''The Emperor's New Mind'' and John Searle with his "Chinese room" thought experiment argue that true [[consciousness]] cannot be achieved by [[formal logic]] systems, while [[Douglas Hofstadter]] in ''Gödel, Escher, Bach'' and [[Daniel Dennett]] in ''Consciousness Explained'' argue in favor of [[functionalism]], which argues that mental states (beliefs, desires, being in pain, etc.) are constituted solely by their functional role. In many strong AI supporters’ opinion, artificial consciousness is considered as the [[holy grail]] of artificial intelligence. [[Edsger Dijkstra]] famously opined that the debate had little importance: "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim."
  
{{main|Philosophy of artificial intelligence}}
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[[Epistemology]], the study of knowledge, also makes contact with AI, as engineers find themselves debating similar questions to philosophers about how best to represent and use knowledge and information.
 
 
The [[strong AI]] vs. [[weak AI]] debate ("can a man-made artifact be conscious?") is still a hot topic amongst AI [[philosopher]]s. This involves [[philosophy of mind]] and the [[mind-body problem]]. Most notably [[Roger Penrose]] in his book ''[[The Emperor's New Mind]]'' and [[John Searle]] with his "[[Chinese room]]" [[thought experiment]] argue that true [[consciousness]] cannot be achieved by [[formal logic]] systems, while [[Douglas Hofstadter]] in ''[[Gödel, Escher, Bach]]'' and [[Daniel Dennett]] in ''[[Consciousness Explained]]'' argue in favour of [[Functionalism (philosophy of mind)|functionalism]]. In many strong AI supporters’ opinion, [[artificial consciousness]] is considered as the [[list of holy grails|holy grail]] of artificial intelligence. [[Edsger Dijkstra]] famously opined that the debate had little importance: "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim."
 
 
 
[[Epistemology]], the study of knowledge, also makes contact with AI, as engineers find themselves debating similar questions to philosophers about how best to represent and use knowledge and information.  (e.g. [[semantic networks]]).
 
  
 
==AI in business==
 
==AI in business==
 +
Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties. In August 2001, robots beat humans in a simulated financial trading competition <ref>[http://news.bbc.co.uk/2/hi/business/1481339.stm Robots beat humans in trading battle] ''BBCNews'', August 8, 2001. Retrieved February 22, 2020.</ref> A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and to provide medical information. Many practical applications are dependent on artificial neural networks—networks that pattern their organization in mimicry of a brain's neurons, which have been found to excel in pattern recognition. [[Financial institution]]s have long used such systems to detect charges or claims outside of the norm, flagging these for human investigation. Neural networks are also being widely deployed in [[homeland security]], speech and text recognition, [[medical diagnosis]], [[data mining]], and [[e-mail spam]] filtering.
  
Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties.  In August 2001, robots beat humans in a simulated [[stock trader|financial trading]]* competition ([[BBC News]]*, 2001).<ref name="xppr">{{cite web
+
[[Robot]]s have also become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive, which may lead to mistakes or accidents due to a lapse in concentration, and other jobs which humans may find degrading. General Motors uses around 16,000 robots for tasks such as painting, welding, and assembly. [[Japan]] is the leader in using robots in the world.
|url=http://news.bbc.co.uk/2/hi/business/1481339.stm
 
|title=Robots beat humans in trading battle
 
|year=August 8, 2001
 
|accessdate=2006-11-02
 
|work=BBC News, Business
 
|publisher=The British Broadcasting Corporation
 
}}</ref> A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and to provide medical information.  Many practical applications are dependent on [[artificial neural networks]] &mdash; networks that pattern their organization in mimicry of a brain's neurons, which have been found to excel in pattern recognition. [[Financial institution]]s have long used such systems to detect charges or claims outside of the norm, flagging these for human investigation. Neural networks are also being widely deployed in [[homeland security]], speech and text recognition, [[medical diagnosis]] (such as in [[Concept Processing]] technology in [[EMR]] software), [[data mining]], and [[e-mail spam]] filtering.
 
 
 
[[Robot]]s have also become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have also proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration, and other jobs which humans may find degrading. General Motors uses around 16,000 robots for tasks such as painting, welding, and assembly. [[Japan]] is the leader in using robots in the world. In 1995, 700,000 robots were in use worldwide; over 500,000 of which were from Japan (Encarta, 2006).
 
 
 
==AI in fiction==
 
In [[science fiction]] AI &mdash; almost always [[strong AI]] &mdash; is commonly portrayed as an upcoming power trying to overthrow human authority as in [[HAL 9000]], [[Skynet]], [[Colossus: The Forbin Project|Colossus]] and [[The Matrix]] or as service [[humanoid]]s like [[C-3PO]], [[Marvin the Paranoid Android|Marvin]], [[Data (Star Trek)|Data]], [[KITT]] and [[KARR (Knight Rider)|KARR]], the [[Bicentennial Man]], the ''Mechas'' in [[A.I. (film)|A.I.]], [[Cortana]] from the [[Halo (video game series)|Halo]] series or Sonny in [[I, Robot (film)|I, Robot]].
 
<!--this is not a list of your favorite sci-fi AI, keep it short and use only famous and clear examples—>
 
 
 
A notable exception is Mike in [[Robert A. Heinlein]]'s ''[[The Moon Is a Harsh Mistress]]'': a supercomputer that becomes aware and aids in a local revolution.
 
 
 
The inevitability of world domination by out-of-control AI is also argued by some fiction writers like [[Kevin Warwick]]. In works such as the Japanese [[manga]] ''[[Ghost in the Shell (manga)|Ghost in the Shell]]'', the existence of intelligent machines questions the definition of life as organisms rather than a broader category of autonomous entities, establishing a notional concept of systemic intelligence.
 
''See [[list of fictional computers]] and [[list of fictional robots and androids]].''
 
 
 
Some fiction writers, such as [[Vernor Vinge]] and [[Ray Kurzweil]], have also speculated that the advent of [[strong AI]] is likely to cause abrupt and dramatic societal change.  The period of abrupt change is sometimes referred to as "[[Technological singularity|the Singularity]]".
 
 
 
Author [[Frank Herbert]] explored the idea of a time when mankind might ban [[strong AI|clever machines]] entirely.  His [[Dune universe|Dune series]] makes mention of a rebellion called the [[Butlerian Jihad]] in which mankind defeats the smart machines of the future and then imposes a death penalty against any who would again create thinking machines.  Often quoted from the fictional [[Orange Catholic Bible]], "Thou shalt not make a machine in the likeness of a human mind."
 
 
 
==See also==
 
*[[American Association for Artificial Intelligence]]
 
*[[Artificial artificial intelligence]]
 
*[[AI effect]]
 
*[[AI winter]]
 
*[[A.I. Systems Integration]]
 
*[[Biosynthetic phylogeny]]
 
*[[Cognitive science]]
 
*[[Fifth generation computer]]
 
*[[German Research Centre for Artificial Intelligence]]
 
*[[History of artificial intelligence]]
 
*[[Intelligent interface]]
 
*[[International Joint Conference on Artificial Intelligence]]
 
*[[Loebner Prize]]
 
*[[Neuromancer]]
 
*[[PEAS]]
 
*[[Predictive analytics]]
 
*[[Robotics]]
 
*[[Three Laws of Robotics]]
 
  
==Applications==
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==Areas of AI Implementation==
Typical problems to which AI methods are applied:
+
[[File:Kismet robot at MIT Museum.jpg|thumb|250px|[[Kismet (robot)|Kismet]], a robot with rudimentary social skills]]
*[[Pattern recognition]]
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*Artificial Creativity
**[[Optical character recognition]]
 
**[[Handwriting recognition]]
 
**[[Speech recognition]]
 
**[[Facial recognition system|Face recognition]]
 
 
 
*[[Artificial Creativity]]
 
*[[Computer vision]], [[Virtual reality]] and [[Image processing]]
 
*[[Diagnosis (Artificial intelligence)|Diagnosis]]
 
*[[Game theory]] and [[Strategic planning]]
 
*[[Game AI]] and [[Computer game bot]]
 
*[[Natural language processing]], [[Translation]] and [[Chatterbot]]s
 
*[[Non-linear control]] and [[Robotics]]
 
 
 
Other fields in which AI methods are implemented:
 
 
*[[Artificial life]]
 
*[[Artificial life]]
 
*[[Automated reasoning]]
 
*[[Automated reasoning]]
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*[[Behavior-based robotics]]
 
*[[Behavior-based robotics]]
 
*[[Bio-inspired computing]]
 
*[[Bio-inspired computing]]
*[[Chatterbot]]
 
 
*[[Cognitive robotics]]
 
*[[Cognitive robotics]]
*[[Colloquis]]
 
 
*[[Concept Mining]]
 
*[[Concept Mining]]
 
*[[Cybernetics]]
 
*[[Cybernetics]]
Line 141: Line 74:
 
*[[Developmental robotics]]
 
*[[Developmental robotics]]
 
*[[Epigenetic robotics]]
 
*[[Epigenetic robotics]]
*[[E-mail spam]] filtering
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*E-mail spam filtering
*[[Evolutionary robotics]]
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*[[Game theory]] and [[Strategic planning]]
 
*[[Hybrid intelligent system]]
 
*[[Hybrid intelligent system]]
 
*[[Intelligent agent]]
 
*[[Intelligent agent]]
Line 148: Line 81:
 
*[[Knowledge Representation]]
 
*[[Knowledge Representation]]
 
*[[Knowledge Acquisition]]
 
*[[Knowledge Acquisition]]
*[[Semantic web]]
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*Natural language processing, Translation, and [[Chatterbot]]s
 
+
*[[Non-linear control]]
Lists of researchers, projects & publications
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*[[Pattern recognition]]
*[[:Category:Artificial intelligence researchers|List of AI researchers]]
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**Optical character recognition
*[[List of notable artificial intelligence projects|List of AI projects]]
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**Handwriting recognition
*[[List of important publications in computer science#Artificial intelligence|List of important AI publications]]
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**Speech recognition
<!--This is not a list of your pet website or article, or favorite AI software & books. please add those to the appropriate links in the see also section. Keep this list short and use only famous and clear examples—>
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**Facial recognition
 +
*[[Semantic web]]  
 +
*[[Virtual reality]] and [[Image processing]]
  
== Footnotes ==
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==Notes==
<!-- ----------------------------------------------------------
 
  See http://en.wikipedia.org/wiki/Wikipedia:Footnotes for a
 
  discussion of different citation methods and how to generate
 
  footnotes using the <ref>, </ref> and  <reference /> tags
 
----------------------------------------------------------- —>
 
 
<references />
 
<references />
  
 
==References==
 
==References==
 
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* Haag, Stephen, Maeve Cummings, and Donald J. McCubbrey. ''Management Information Systems for the Information Age'' 5th ed. New York: McGraw-Hill, 2004. ISBN 0073023884
* Haag, Stephen; Cummings, Maeve; and McCubbrey, Donald J. (2004). ''Management Information Systems for the Information Age'' (5th Edition). New York: McGraw-Hill/Irwin. ISBN 0073023884.
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* Craig, John J. ''Introduction to Robotics: Mechanics and Control.'' Upper Saddle River, NJ: Pearson Prentice Hall, 2003. ISBN 0201543613
 
+
* Fox, John and Das Subrata. ''Safe and Sound: Artificial Intelligence in Hazardous Applications.'' Menlo Park, California: AAAI Press, 2000. ISBN 0262062119
* Craig, John J. (2003). ''Introduction to Robotics: Mechanics and Control''. Upper Saddle River, NJ: Pearson Prentice Hall. ISBN 0201543613.
 
 
 
* Fox, John; Das Subrata (2000). ''Safe and Sound: Artificial Intelligence in Hazardous Applications''. Menlo Park, California: AAAI Press. ISBN 0262062119
 
  
 
==External links==
 
==External links==
 +
All links retrieved November 7, 2021.
  
*[http://www.cam-direct.co.uk/ltk/index2.php?location=Artificial_Intelligence AI overview].
+
*[http://www-formal.stanford.edu/jmc/whatisai/node1.html John McCarthy's frequently asked questions about AI]  
*[http://www.sics.se/~annika/papers/intint.html Intelligent Interface].
+
*Jürgen Schmidhuber [http://www.idsia.ch/~juergen/ai.html Artificial Intelligence History Highlights and Outlook]  
*[http://lis.epfl.ch/podcast Podcast 'Talking Robots' - interviews with high-profile professionals in Robotics and Artificial Intelligence]
+
*Richard Wray, [http://business.guardian.co.uk/story/0,,1781123,00.html Google Users Promised Artificial Intelligence]  
*[http://www.vega.org.uk/video/programme/16 Freeview Video 'Machines with Minds' by the Vega Science Trust and the BBC/OU]
+
*[http://ti.arc.nasa.gov Intelligent Systems Division] National Aeronautics and Space Administration (NASA).  
*[http://www-formal.stanford.edu/jmc/whatisai/node1.html John McCarthy's frequently asked questions about AI]
+
*[https://techjury.net/stats-about/ai/ AI Statistics About Smarter Machines] ''TechJury''.
*[http://www.kurzweilai.net/ Ray Kurzweil's website dedicated to AI including prediction of future development in AI]
+
*[https://kommandotech.com/statistics/artificial-intelligence-statistics/ Astounding Artificial Intelligence Statistics for 2020]  
*[http://www.idsia.ch/~juergen/ai.html AI history & outlook] by [[Jürgen Schmidhuber]]*
 
*[http://www.tuppas.com/Artificial-Intelligence/Artificial-Intelligence.htm Artificial Intelligence in Manufacturing]
 
*[http://www.geocities.com/francorbusetti Heuristics and artificial intelligence in finance and investment]
 
*[http://business.guardian.co.uk/story/0,,1781123,00.html Google Users Promised Artificial Intelligence]
 
*[http://ai50.org/ 50th Anniversary Summit of Artificial Intelligence 9-14 July 2006 Monte Verita Switzerland]
 
*[http://www.synthetic-intelligence.eu/ Research Group Synthetic Intelligence, Europe]
 
*[http://www.pandorabots.com/pandora/talk?botid=f5d922d97e345aa1 Speak with A.L.I.C.E. : An award winning AI chat robot]
 
*[http://groups.google.com/group/comp.ai The AI newsgroup]
 
*[http://www.ilmarefilm.org/W_E_1.htm Documentary film with and about Joseph Weizenbaum and ELIZA. ( "Weizenbaum. Rebel at Work." )]
 
*[http://ti.arc.nasa.gov NASA Ames Research Center's Intelligent Systems Division]
 
*[http://www.iismemphis.org Institute for Intelligent Systems]
 
* [http://archive.salon.com/tech/feature/2000/08/10/turing/index.html "Hello, Are You Human?"] Cocktail hour inversion of the [[Turing Test]]*
 
*[http://www.mindmakers.org Mindmakers.org, an online organization for people building large scale A.I. systems].
 
*[http://www.aaai.org/AITopics/html/welcome.html AI Topics]
 
  
 
[[Category:Physical sciences]]
 
[[Category:Physical sciences]]

Revision as of 13:16, 7 November 2021

Honda's humanoid robot

Artificial intelligence (AI) is a branch of computer science and engineering that deals with intelligent behavior, learning, and adaptation in machines. John McCarthy coined the term to mean "the science and engineering of making intelligent machines."[1] Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. Examples include control systems; automated planning and scheduling; the ability to answer diagnostic and consumer questions; and handwriting, speech, and facial recognition. As such, it has become an engineering discipline, focused on providing solutions to real-life problems, software applications, traditional strategy games like computer chess, and various video games.

Artificial intelligence is being used today for many different purposes and all throughout the world. It can create safer environments for workers by using robots for dangerous situations. In the future, it may be used more for human interaction; for example, an automated teller would actually be able to do visual recognition and respond to one personally.

Schools of thought

AI divides roughly into two schools of thought: Conventional AI and Computational Intelligence (CI), also sometimes referred to as Synthetic Intelligence.

Conventional AI mostly involves methods now classified as machine learning, characterized by formalism and statistical analysis. This is also known as symbolic AI, logical AI, or neat AI. Methods include:

  • Expert systems: applies reasoning capabilities to reach a conclusion. An expert system can process large amounts of known information and provide conclusions based on them.
  • Case-based reasoning is the process of solving new problems based on the solutions of similar past problems.
  • Bayesian networks represents a set of variables together with a joint probability distribution with explicit independence assumptions.
  • Behavior-based AI: a modular method of building AI systems by hand.

Computational Intelligence involves iterative development or learning. Learning is based on empirical data. It is also known as non-symbolic AI, scruffy AI, and soft computing. Methods mainly include:

  • Neural networks: systems with very strong pattern recognition capabilities.
  • Fuzzy systems: techniques for reasoning under uncertainty, have been widely used in modern industrial and consumer product control systems.
  • Evolutionary computation: applies biologically inspired concepts such as populations, mutation, and survival of the fittest to generate increasingly better solutions to the problem. These methods most notably divide into evolutionary algorithms and swarm intelligence.

Hybrid intelligent systems attempt to combine these two groups. It is thought that the human brain uses multiple techniques to both formulate and cross-check results. Thus, systems integration is seen as promising and perhaps necessary for true AI.

History

Early in the seventeenth century, René Descartes envisioned the bodies of animals as complex but reducible machines, thus formulating the mechanistic theory, also known as the "clockwork paradigm." Wilhelm Schickard created the first mechanical, digital calculating machine in 1623, followed by machines of Blaise Pascal (1643) and Gottfried Wilhelm von Leibniz (1671), who also invented the binary system. In the nineteenth century, Charles Babbage and Ada Lovelace worked on programmable mechanical calculating machines.

Bertrand Russell and Alfred North Whitehead published Principia Mathematica in 1910-1913, which revolutionized formal logic. In 1931 Kurt Gödel showed that sufficiently powerful consistent formal systems contain true theorems not provable by any theorem-proving AI that is systematically deriving all possible theorems from the axioms. In 1941 Konrad Zuse built the first working program-controlled computers. Warren McCulloch and Walter Pitts published A Logical Calculus of the Ideas Immanent in Nervous Activity (1943), laying the foundations for neural networks. Norbert Wiener's Cybernetics or Control and Communication in the Animal and the Machine, (1948) popularizes the term "cybernetics."

1950s

The 1950s were a period of active efforts in AI. In 1950, Alan Turing introduced the "Turing test," a test of intelligent behavior. The first working AI programs were written in 1951 to run on the Ferranti Mark I machine of the University of Manchester: a draughts-playing program written by Christopher Strachey and a chess-playing program written by Dietrich Prinz. John McCarthy coined the term "artificial intelligence" at the first conference devoted to the subject, in 1956. He also invented the Lisp programming language. Joseph Weizenbaum built ELIZA, a chatterbot implementing Rogerian psychotherapy. The birth date of AI is generally considered to be July 1956 at the Dartmouth Conference, where many of these people met and exchanged ideas.

At the same time, John von Neumann, who had been hired by the RAND Corporation, developed the game theory, which would prove invaluable in the progress of AI research.

1960s–1970s

During the 1960s and 1970s, Joel Moses demonstrated the power of symbolic reasoning for integration problems in the Macsyma program, the first successful knowledge-based program in mathematics. Leonard Uhr and Charles Vossler published "A Pattern Recognition Program That Generates, Evaluates, and Adjusts Its Own Operators" in 1963, which described one of the first machine learning programs that could adaptively acquire and modify features. Marvin Minsky and Seymour Papert published Perceptrons, which demonstrated the limits of simple neural nets. Alain Colmerauer developed the Prolog computer language. Ted Shortliffe demonstrated the power of rule-based systems for knowledge representation and inference in medical diagnosis and therapy in what is sometimes called the first expert system. Hans Moravec developed the first computer-controlled vehicle to autonomously negotiate cluttered obstacle courses.

1980s

In the 1980s, neural networks became widely used due to the back propagation algorithm, first described by Paul Werbos in 1974. The team of Ernst Dickmanns built the first robot cars, driving up to 55 mph on empty streets.

1990s and the turn of the century

The 1990s marked major achievements in many areas of AI and demonstrations of various applications. In 1995, one of Dickmanns' robot cars drove more than 1000 miles in traffic at up to 110 mph. Deep Blue, a chess-playing computer, beat Garry Kasparov in a famous six-game match in 1997. The Defense Advanced Research Projects Agency stated that the costs saved by implementing AI methods for scheduling units in the first Persian Gulf War have repaid the US government's entire investment in AI research since the 1950s. Honda built the first prototypes of humanoid robots like the one depicted above.

During the 1990s and 2000s AI became very influenced by probability theory and statistics. Bayesian networks are the focus of this movement, providing links to more rigorous topics in statistics and engineering such as Markov models and Kalman filters, and bridging the divide between neat and scruffy approaches. After the September 11, 2001 attacks there has been much renewed interest and funding for threat-detection AI systems, including machine vision research and data-mining. However despite the hype, excitement about Bayesian AI is perhaps now fading again as successful Bayesian models have only appeared for tiny statistical tasks (such as finding principal components probabilistically) and appear to be intractable for general perception and decision-making.

The 2010s

Advanced statistical techniques (loosely known as deep learning), access to large amounts of data and faster computers enabled advances in machine learning and perception. By the mid 2010s, machine learning applications were used throughout the world.

In a Jeopardy! quiz show exhibition match, IBM's question answering system, Watson, defeated the two greatest Jeopardy champions, Brad Rutter and Ken Jennings, by a significant margin.[2] The Kinect, which provides a 3D body–motion interface for the Xbox 360 and the Xbox One use algorithms that emerged from lengthy AI research,[3] as do intelligent personal assistants in smartphones.[4]

In March 2016, AlphaGo won 4 out of 5 games of Go in a match with Go champion Lee Sedol, becoming the first computer Go-playing system to beat a professional Go player without handicaps.[5] Other examples include Microsoft's development of a Skype system that can automatically translate from one language to another and Facebook's system that can describe images to blind people.

AI in Philosophy

The strong AI vs. weak AI debate is a hot topic amongst AI philosophers. This involves the philosophy of the mind and the mind-body problem. Most notably Roger Penrose in his book The Emperor's New Mind and John Searle with his "Chinese room" thought experiment argue that true consciousness cannot be achieved by formal logic systems, while Douglas Hofstadter in Gödel, Escher, Bach and Daniel Dennett in Consciousness Explained argue in favor of functionalism, which argues that mental states (beliefs, desires, being in pain, etc.) are constituted solely by their functional role. In many strong AI supporters’ opinion, artificial consciousness is considered as the holy grail of artificial intelligence. Edsger Dijkstra famously opined that the debate had little importance: "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim."

Epistemology, the study of knowledge, also makes contact with AI, as engineers find themselves debating similar questions to philosophers about how best to represent and use knowledge and information.

AI in business

Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties. In August 2001, robots beat humans in a simulated financial trading competition [6] A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and to provide medical information. Many practical applications are dependent on artificial neural networks—networks that pattern their organization in mimicry of a brain's neurons, which have been found to excel in pattern recognition. Financial institutions have long used such systems to detect charges or claims outside of the norm, flagging these for human investigation. Neural networks are also being widely deployed in homeland security, speech and text recognition, medical diagnosis, data mining, and e-mail spam filtering.

Robots have also become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive, which may lead to mistakes or accidents due to a lapse in concentration, and other jobs which humans may find degrading. General Motors uses around 16,000 robots for tasks such as painting, welding, and assembly. Japan is the leader in using robots in the world.

Areas of AI Implementation

Kismet, a robot with rudimentary social skills
  • Artificial Creativity
  • Artificial life
  • Automated reasoning
  • Automation
  • Behavior-based robotics
  • Bio-inspired computing
  • Cognitive robotics
  • Concept Mining
  • Cybernetics
  • Data mining
  • Developmental robotics
  • Epigenetic robotics
  • E-mail spam filtering
  • Game theory and Strategic planning
  • Hybrid intelligent system
  • Intelligent agent
  • Intelligent control
  • Knowledge Representation
  • Knowledge Acquisition
  • Natural language processing, Translation, and Chatterbots
  • Non-linear control
  • Pattern recognition
    • Optical character recognition
    • Handwriting recognition
    • Speech recognition
    • Facial recognition
  • Semantic web
  • Virtual reality and Image processing

Notes

  1. John McCarthy, What is Artificial Intelligence? Retrieved February 22, 2020.
  2. John Markoff, Computer Wins on ‘Jeopardy!’: Trivial, It’s Not The New York Times, February 16, 2011. Retrieved February 22, 2020.
  3. Harry Fairhead, Kinect's AI breakthrough explained i-programmer.info, March 26, 2011. Retrieved February 22, 2020.
  4. Dan Rowinski, Virtual Personal Assistants & The Future Of Your Smartphone Readwrite, January 15, 2013. Retrieved February 22, 2020.
  5. Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol BBCNews, March 12, 2016. Retrieved February 22, 2020.
  6. Robots beat humans in trading battle BBCNews, August 8, 2001. Retrieved February 22, 2020.

References
ISBN links support NWE through referral fees

  • Haag, Stephen, Maeve Cummings, and Donald J. McCubbrey. Management Information Systems for the Information Age 5th ed. New York: McGraw-Hill, 2004. ISBN 0073023884
  • Craig, John J. Introduction to Robotics: Mechanics and Control. Upper Saddle River, NJ: Pearson Prentice Hall, 2003. ISBN 0201543613
  • Fox, John and Das Subrata. Safe and Sound: Artificial Intelligence in Hazardous Applications. Menlo Park, California: AAAI Press, 2000. ISBN 0262062119

External links

All links retrieved November 7, 2021.

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