A.I. Artificial Intelligence, also known as A.I., is a 2001 science fiction drama film directed, produced and co-written by Steven Spielberg. Based on Brian Aldiss' short story "Super-Toys Last All Summer Long", the film stars Haley Joel Osment, Jude Law, Frances O'Connor, Sam Robards, Jake Thomas and William Hurt. Set sometime in the future, A.I. tells the story of David, a child-like android uniquely programmed with the ability to love.

Development of A.I. originally began with director Stanley Kubrick in the early 1970s. Kubrick hired a series of writers up until the mid-1990s, including Brian Aldiss, Bob Shaw, Ian Watson and Sara Maitland. The film languished in development hell for years, partly because Kubrick felt computer-generated imagery was not advanced enough to create the David character, whom he believed no child actor would believably portray. In 1995, Kubrick handed A.I. to Steven Spielberg, but the film did not gain momentum until Kubrick's death in 1999. Spielberg remained close to Watson's film treatment for the screenplay. A.I. was greeted with generally positive reviews from critics. This film was dedicated to Kubrick's memory after the end credits, saying "For Stanley Kubrick".

Plot[link]

In the 22nd century, severe global warming has led to melting polar ice caps, flooded coastlines, and a drastic reduction of the human population. There is a new class of robots called Mecha, advanced humanoids capable of emulating thoughts and emotions. David (Haley Joel Osment), a prototype model created by Cybertronics of New York, is designed to resemble a human child and to display love for its human owners. They test their creation with one of their employees, Henry Swinton (Sam Robards), and his wife Monica (Frances O'Connor). The Swintons' son, Martin (Jake Thomas), was placed in suspended animation until a cure can be found for his rare disease. Although Monica is initially frightened of David, she eventually warms to him after activating his imprinting protocol, which irreversibly causes David to project love for her, the same as any child would love a parent. He is also befriended by Teddy (Jack Angel), a robotic teddy bear, who takes it upon himself to care for David's well being.

A cure is found for Martin and he is brought home; a sibling rivalry ensues between Martin and David. Martin convinces David to go to Monica in the middle of the night and cut off a lock of her hair, but the parents wake up and are very upset. At a pool party, one of Martin's friends activates David's self-protection programming by poking him with a knife. David clings to Martin and they both fall into the pool, where the heavy David sinks to the bottom while still clinging to Martin. Martin is saved from drowning, but Henry in particular is shocked by David's actions, becoming concerned that David's capacity for love has also given him the ability to hate. Henry persuades Monica to return David to Cybertronics, where David will be destroyed. However, Monica cannot bring herself to do this, and instead abandons David in the forest (alongside Teddy) to hide as an unregistered Mecha. David is captured for an anti-Mecha Flesh Fair, an event where obsolete Mecha are destroyed in front of cheering crowds. David is nearly killed, but the crowd is swayed by his realistic nature (David, unlike other Mecha, pleads for his life) and he escapes, along with Gigolo Joe (Jude Law), a male prostitute Mecha on the run after being framed for murder.

The two set out to find the Blue Fairy, whom David remembers from the story The Adventures of Pinocchio. He is convinced that the Blue Fairy will transform him into a human boy, allowing Monica to love him and take him home. Joe and David make their way to Rouge City. Information from a holographic answer engine called "Dr. Know" (Robin Williams) eventually leads them to the top of Rockefeller Center in partially underwater Manhattan. They fly to New York via a flying submersible vehicle called an amphibicopter they stole from the police, who are still chasing Joe. David meets his human creator, Professor Hobby (William Hurt), who excitedly tells David that finding him was a test, which has demonstrated the reality of his love and desire. It also becomes clear that many copies of David are already being manufactured, along with female versions. David sadly realizes he is not unique. A disheartened David attempts to commit suicide by falling from a ledge into the ocean, but Joe rescues him with the amphibicopter. David tells Joe he saw the Blue Fairy underwater, and wants to go down to her. At that moment, Joe is captured by the authorities with the use of an electromagnet. David and Teddy take the amphibicopter to the fairy, which turns out to be a statue from a submerged attraction at Coney Island. Teddy and David become trapped when the Wonder Wheel falls on their vehicle. Believing the Blue Fairy to be real, David asks to be turned into a real boy, repeating his wish without end, until the ocean freezes in another ice age and his internal power source drains away.

Two thousand years later, humans are extinct and Manhattan is buried under several hundred feet of glacial ice.^[1] Mecha have evolved into a highly advanced alien-looking humanoid form.^[2] They find David and Teddy and discover they are functional Mecha who knew living humans, making them special and unique. David is revived and walks to the frozen Blue Fairy statue, which cracks and collapses as he touches it. Having received and comprehended his memories, the advanced Mecha use them to reconstruct the Swinton home and explain to David via an interactive image of the Blue Fairy (Meryl Streep) that it is not possible to make him human. However, at David's insistence, they recreate Monica from DNA in the lock of her hair which had been saved by Teddy. Unfortunately, she can only live for a single day and the process cannot be repeated. David spends the happiest day of his life with Monica and Teddy, and Monica tells David that she loves him and has always loved him as she drifts to sleep for the final time. David lies down next to her, closes his eyes and goes "to that place where dreams are born". Teddy enters the scene, climbs onto the bed and watches as David and Monica lay peacefully together.

Cast[link]

• Haley Joel Osment as David, an innovative Mecha created by Cybertronics and programmed with the ability to love. He is adopted by Henry and Monica Swinton, but a sibling rivalry ensues once their son Martin comes out of suspended animation. Osment was Spielberg's first and only choice for the role. Osment avoided blinking his eyes to perfectly portray the character, and "programmed" himself with good posture for realism.^[3]
• Jude Law as Gigolo Joe, a male prostitute Mecha programmed with the ability to mimic love, like David, but in a different sense. To prepare for the role, Law studied the acting of Fred Astaire and Gene Kelly.^[4]
• Frances O'Connor as Monica Swinton, David's adopted mother who reads him The Adventures of Pinocchio. She is first displeased to have David in her home but soon starts loving him.
• Sam Robards as Henry Swinton, an employee at Cybertronics and husband of Monica. Henry is reluctant to take David home, and soon sees David as dangerous to his family.
• Jake Thomas as Martin Swinton, Henry and Monica's first son, who was placed in suspended animation. When Martin comes back, he convinces David to cut off a lock of Monica's hair.
• William Hurt as Professor Allen Hobby, responsible for shepherding the creation of David. He resides in New York City, which is crippled by the effects of global warming but still functioning as Cybertronics' headquarters. David is modeled after Hobby's own son, also named David, who died at a young age.
• Brendan Gleeson as Lord Johnson-Johnson, the owner and master of ceremonies of the Flesh Fair.

Voices

• Jack Angel as Teddy, David's robotic teddy bear.
• Ben Kingsley as narrator and the leader of the futuristic Mecha. He also appears briefly as one of the technicians who repairs David after he eats spinach.
• Robin Williams as Dr. Know, a holographic answer engine. (Cameo)
• Meryl Streep as Blue Fairy. (Cameo)
• Chris Rock as a Mecha killed at the Flesh Fair. (Cameo)

Production[link]

Kubrick began development on an adaptation of "Super-Toys Last All Summer Long" in the early 1970s, hiring the short story's author, Brian Aldiss to write a film treatment. In 1985, Kubrick brought longtime friend Steven Spielberg on board to produce the film,^[5] along with Jan Harlan. Warner Bros. agreed to co-finance A.I. and cover distribution duties.^[6] The film labored in development hell, and Aldiss was fired by Kubrick over creative differences in 1989.^[7] Bob Shaw served as writer very briefly, leaving after six weeks because of Kubrick's demanding work schedule, and Ian Watson was hired as the new writer in March 1990. Aldiss later remarked, "Not only did the bastard fire me, he hired my enemy [Watson] instead." Kubrick handed Watson The Adventures of Pinocchio for inspiration, calling A.I. "a picaresque robot version of Pinocchio".^[6][8]

Three weeks later Watson gave Kubrick his first story treatment, and concluded his work on A.I. in May 1991 with another treatment, at 90 pages. Gigolo Joe was originally conceived as a GI Mecha, but Watson suggested changing him to a male prostitute. Kubrick joked, "I guess we lost the kiddie market."^[6] In the meantime, Kubrick dropped A.I. to work on a film adaptation of Wartime Lies, feeling computer animation was not advanced enough to create the David character. However, after the release of Spielberg's Jurassic Park (with its innovative use of computer-generated imagery), it was announced in November 1993 that production would begin in 1994.^[9] Dennis Muren and Ned Gorman, who worked on Jurassic Park, became visual effects supervisors,^[7] but Kubrick was displeased with their previsualization, and at the expense of hiring Industrial Light & Magic.^[2]

In early 1994, the film was in pre-production with Christopher "Fangorn" Baker as concept artist, and Sara Maitland assisting on the story, which gave it "a feminist fairy-tale focus".^[6] Maitland said that Kubrick never referred to the film as A.I., but as Pinocchio.^[2] Chris Cunningham became the new visual effects supervisor. Some of his unproduced work for A.I. can be seen on the DVD, The Work of Director Chris Cunningham.^[11] Aside from considering computer animation, Kubrick also had Joseph Mazzello do a screen test for the lead role.^[2] Cunningham helped assemble a series of "little robot-type humans" for the David character. "We tried to construct a little boy with a movable rubber face to see whether we could make it look appealing," producer Jan Harlan reflected. "But it was a total failure, it looked awful." Hans Moravec was brought in as a technical consultant.^[2]

Meanwhile, Kubrick and Harlan thought A.I. would be closer to Steven Spielberg's sensibilities as director.^[12][13] Kubrick handed the position to Spielberg in 1995, but Spielberg chose to direct other projects, and convinced Kubrick to remain as director.^[10][14] The film was put on hold due to Kubrick's commitment to Eyes Wide Shut (1999).^[15] After the filmmaker's death in March 1999, Harlan and Christiane Kubrick approached Spielberg to take over the director's position.^[16][17] By November 1999, Spielberg was writing the screenplay based on Watson's 90-page story treatment. It was his first solo screenplay credit since Close Encounters of the Third Kind (1977).^[18] Spielberg remained close to Watson's treatment, but removed various sex scenes with Gigolo Joe, which Kubrick had in mind.^[13] Pre-production was briefly halted during February 2000, because Spielberg pondered directing other projects, which were Harry Potter and the Philosopher's Stone, Minority Report and Memoirs of a Geisha.^[15][19] When he decided to fast track A.I., Spielberg brought Chris Baker back as concept artist.^[14]

The original start date was July 10, 2000,^[13] but filming was delayed until August.^[20] Aside from a couple weeks shooting on location in Oregon, A.I. was shot entirely using sound stages at Warner Bros. Studios. The Swinton house was constructed on Stage 16, while Stage 20 was used for Rouge City and other sets.^[21][22] Spielberg copied Kubrick's obsessively secretive approach to filmmaking by refusing to give the complete script to cast and crew, banning press from the set, and making actors sign confidentiality agreements. Social robotics expert Cynthia Breazeal served as technical consultant during production.^[13][23] Haley Joel Osment and Jude Law applied prosthetic makeup daily in an attempt to look shinier and robotic-like.^[3] Costume designer Bob Ringwood (Batman, Troy) studied pedestrians on the Las Vegas Strip for his influence on the Rouge City extras.^[24] Spielberg found post production on A.I. difficult because he was simultaneously preparing to shoot Minority Report.^[25]

Soundtrack[link]

The film's soundtrack was released by Warner Bros. Records in 2001. The original score was composed by John Williams and featured singers Lara Fabian on two songs and Josh Groban on one. The film's score also had a limited release as an official "For your consideration Academy Promo" -- this two CD set commands top dollar prices on e-bay and is the holy grail among fans of the composer, John Williams. Academy Promos have now been discontinued, but they were generally sent out by the studios to other composers and members of the music branch of the Academy of Motion Picture Arts and Sciences for consideration as Best Original Score at the Oscars. The two CD set features many tracks that are unreleased, and not available on the original single CD edition which makes it a must-have collectible.

Release[link]

Marketing[link]

Warner Bros. used an alternate reality game titled The Beast to promote the film. Over forty websites were created by Atomic Pictures in New York City (kept online at Cloudmakers.org) including the website for Cybertronics Corp. The Cybertronics CEO is voiced by Topie Nguyen. There were to be a series of video games for the Xbox video game console that followed the storyline of The Beast, but they went undeveloped. To avoid audiences mistaking A.I. for a family film, no action figures were created, although Hasbro released a talking Teddy following the film's release in June 2001.^[13]

A.I. had its premiere at the Venice Film Festival in 2001.^[26]

Box office[link]

The film opened in 3,242 theaters in the United States on June 29, 2001, earning $29,352,630 during its opening weekend. A.I went on to gross $78.62 million in US totals as well as $157.31 million in foreign countries, coming to a worldwide total of $235.93 million.^[27] A.I. earned twice as much money overseas as it did in North America, which was fairly unusual for 2001, when foreign grosses had not yet begun to regularly amount to the heavy majority of the receipts for Hollywood films. The film was not clearly a financial success, since the producers collected only a fraction of the listed gross revenue (in particular, studios typically redeem less than half of foreign receipts) against a production and marketing budget of over $100 million.

Critical response[link]

The film received generally positive reviews. Based on 181 reviews collected by Rotten Tomatoes, 73% of the critics gave the film positive notices with a score of 6.6 out of 10. The website described the critical consensus perceiving the film as "a curious, not always seamless, amalgamation of Kubrick's chilly bleakness and Spielberg's warm-hearted optimism. [The film] is, in a word, fascinating."^[28] By comparison, Metacritic collected an average score of 65, based on 32 reviews, which is considered favorable.^[29]

Producer Jan Harlan stated that Kubrick "would have applauded" the final film, while Kubrick's widow Christiane also enjoyed A.I.^[30] However, Brian Aldiss was vocally displeased with the film, stating, "It's crap. Science fiction has to be logical, and it's full of lapses in logic."^[31] Richard Corliss heavily praised Spielberg's direction, as well as the cast and visual effects.^[32] Roger Ebert awarded the film 3 out of 4 stars, saying that it was "Audacious, technically masterful, challenging, sometimes moving [and] ceaselessly watchable. [But] the movie's conclusion is too facile and sentimental, given what has gone before. It has mastered the artificial, but not the intelligence."^[33] On July 8, 2011, Ebert reviewed A.I. again when he added it to his "Great Movies" pantheon. Leonard Maltin gives the film a not-so-positive review in his Movie Guide, giving it two stars out of four, writing: "[The] intriguing story draws us in, thanks in part to Osment's exceptional performance, but takes several wrong turns; ultimately, it just doesn't work. Spielberg rewrote the adaptation Stanley Kubrick commissioned of the Brian Aldiss short story "Super Toys Last All Summer Long"; [the] result is a curious and uncomfortable hybrid of Kubrick and Spielberg sensibilities." However, he calls John Williams' music score "striking". Jonathan Rosenbaum compared A.I. to Solaris (1972), and praised both "Kubrick for proposing that Spielberg direct the project and Spielberg for doing his utmost to respect Kubrick's intentions while making it a profoundly personal work."^[34] Film critic Armond White, of the New York Press, praised the film noting that "each part of David’s journey through carnal and sexual universes into the final eschatological devastation becomes as profoundly philosophical and contemplative as anything by cinema’s most thoughtful, speculative artists–Borzage, Ozu, Demy, Tarkovsky."^[35]

James Berardinelli found the film "consistently involving, with moments of near-brilliance, but far from a masterpiece. In fact, as the long-awaited 'collaboration' of Kubrick and Spielberg, it ranks as something of a disappointment." He particularly criticized the ending: "The film's final half-hour is a curiosity, and not a successful one — a prolonged, needless epilogue which force-feeds us a catharsis that feels as false as it is extraneous to an otherwise fine story."^[36] Mick LaSalle gave a largely negative review. "A.I. exhibits all its creators' bad traits and none of the good. So we end up with the structureless, meandering, slow-motion endlessness of Kubrick combined with the fuzzy, cuddly mindlessness of Spielberg." Dubbing it Spielberg's "first boring movie", LaSalle also believed the robots at the end of the film were aliens, and compared Gigolo Joe to the "useless" Jar Jar Binks, yet praised Robin Williams for his portrayal of a futuristic Albert Einstein.^[37] Peter Travers gave a mixed review, concluding "Spielberg cannot live up to Kubrick's darker side of the future." But he still put the film on his top ten list that year for best movies.^[38] David Denby in The New Yorker criticized A.I. for not adhering closely to his concept of the Pinocchio character. Spielberg responded to some of the criticisms of the film, stating that many of the "so called sentimental" elements of A.I., including the ending, were in fact Kubrick's and vice-versa the darker elements were his own.^[39] However, Sara Maitland, who worked on the project with Kubrick in the 1990s, claimed that one of the reasons Kubrick never started production on A.I. was because he had a hard time making the ending work.^[40]

Screenwriter Ian Watson has speculated, "Worldwide, A.I. was very successful (and the 4th highest earner of the year) but it didn't do quite so well in America, because the film, so I'm told, was too poetical and intellectual in general for American tastes. Plus, quite a few critics in America misunderstood the film, thinking for instance that the Giacometti-style beings in the final 20 minutes were aliens (whereas they were robots of the future who had evolved themselves from the robots in the earlier part of the film) and also thinking that the final 20 minutes were a sentimental addition by Spielberg, whereas those scenes were exactly what I wrote for Stanley and exactly what he wanted, filmed faithfully by Spielberg."^[41]

"People pretend to think they know Stanley Kubrick, and think they know me, when most of them don't know either of us," Spielberg told film critic Joe Leydon in 2002. "And what's really funny about that is, all the parts of A.I. that people assume were Stanley's were mine. And all the parts of A.I. that people accuse me of sweetening and softening and sentimentalizing were all Stanley's. The teddy bear was Stanley's. The whole last 20 minutes of the movie was completely Stanley's. The whole first 35, 40 minutes of the film – all the stuff in the house – was word for word, from Stanley's screenplay. This was Stanley's vision."

"Eighty percent of the critics got it all mixed up. But I could see why. Because, obviously, I've done a lot of movies where people have cried and have been sentimental. And I've been accused of sentimentalizing hard-core material. But in fact it was Stanley who did the sweetest parts of A.I., not me. I'm the guy who did the dark center of the movie, with the Flesh Fair and everything else. That's why he wanted me to make the movie in the first place. He said, 'This is much closer to your sensibilities than my own.'"^[42]

Accolades[link]

Visual effects supervisors Dennis Muren, Stan Winston, Michael Lantieri and Scott Farrar were nominated for the Academy Award for Visual Effects, while John Williams was nominated for Original Music Score.^[43] Steven Spielberg, Jude Law and Williams received nominations at the 59th Golden Globe Awards.^[44] The visual effects department was once again nominated at the 55th British Academy Film Awards.^[45] A.I. was successful at the Saturn Awards. Spielberg (for his screenplay), the visual effects department, Williams and Haley Joel Osment (Performance by a Younger Actor) won in their respective categories. The film also won Best Science Fiction Film and for its DVD release. Frances O'Connor and Spielberg (as director) were also nominated.^[46]

American Film Institute Lists

• AFI's 100 Years of Film Scores – Nominated^[47]
• AFI's 10 Top 10 – Nominated Science Fiction Film^[48]

References[link]

Further reading[link]

• Jane M. Struthers, ed. (2009). A.I. Artificial Intelligence: From Stanley Kubrick to Steven Spielberg: The Vision Behind the Film. Thames & Hudson. ISBN 978-0-500-51489-4. 

External links[link]

Wikiquote has a collection of quotations related to: A.I. Artificial Intelligence

• Official website
• A.I. Artificial Intelligence at the Internet Movie Database
• A.I. Artificial Intelligence at AllRovi
• A.I. Artificial Intelligence at Rotten Tomatoes
• A.I. Artificial Intelligence at Box Office Mojo
• Jude Law Interview by Charlie Rose
• Spielberg's AI: Another Cuddly No-Brainer by Stevan Harnad

v t e Films directed by Stanley Kubrick 1950s Fear and Desire (1953) Killer's Kiss (1955) The Killing (1956) Paths of Glory (1957) 1960s Spartacus (1960) Lolita (1962) Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1964) 2001: A Space Odyssey (1968) 1970s A Clockwork Orange (1971) Barry Lyndon (1975) 1980s The Shining (1980) Full Metal Jacket (1987) 1990s Eyes Wide Shut (1999) Shorts Day of the Fight (1951) Flying Padre (1951) The Seafarers (1953) Related World Assembly of Youth (1952) A.I. Artificial Intelligence (2001) Stanley Kubrick: A Life in Pictures (2001) Colour Me Kubrick (2006) Stanley Kubrick's Boxes (2008) Room 237 (2012) Other Archive Political and religious beliefs Unrealized projects

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents"^[1] where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.^[2] John McCarthy, who coined the term in 1955,^[3] defines it as "the science and engineering of making intelligent machines."^[4]

AI research is highly technical and specialized, deeply divided into subfields that often fail to communicate with each other.^[5] Some of the division is due to social and cultural factors: subfields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. There are subfields which are focussed on the solution of specific problems, on one of several possible approaches, on the use of widely differing tools and towards the accomplishment of particular applications. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.^[6] General intelligence (or "strong AI") is still among the field's long term goals.^[7] Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. There are an enormous number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others.

The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.^[8] This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues which have been addressed by myth, fiction and philosophy since antiquity.^[9] Artificial intelligence has been the subject of optimism,^[10] but has also suffered setbacks^[11] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.^[12]

History[link]

Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the bronze robot of Hephaestus, and Pygmalion's Galatea.^[13] Human likenesses believed to have intelligence were built in every major civilization: animated cult images were worshipped in Egypt and Greece^[14] and humanoid automatons were built by Yan Shi, Hero of Alexandria and Al-Jazari.^[15] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān, Judah Loew and Paracelsus.^[16] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).^[17] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods".^[9] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.

Mechanical or "formal" reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematician Alan Turing and others. Turing's theory of computation suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable (imaginable) act of mathematical deduction.^[18][19] This, along with concurrent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.^[20]

The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.^[21] The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades.^[22] They and their students wrote programs that were, to most people, simply astonishing:^[23] Computers were solving word problems in algebra, proving logical theorems and speaking English.^[24] By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense^[25] and laboratories had been established around the world.^[26] AI's founders were profoundly optimistic about the future of the new field: Herbert Simon predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".^[27]

They had failed to recognize the difficulty of some of the problems they faced.^[28] In 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off all undirected exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called the "AI winter".^[29]

In the early 1980s, AI research was revived by the commercial success of expert systems,^[30] a form of AI program that simulated the knowledge and analytical skills of one or more human experts. By 1985 the market for AI had reached over a billion dollars. At the same time, Japan's fifth generation computer project inspired the U.S and British governments to restore funding for academic research in the field.^[31] However, beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer lasting AI winter began.^[32]

In the 1990s and early 21st century, AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence is used for logistics, data mining, medical diagnosis and many other areas throughout the technology industry.^[12] The success was due to several factors: the increasing computational power of computers (see Moore's law), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and a new commitment by researchers to solid mathematical methods and rigorous scientific standards.^[33]

On 11 May 1997, Deep Blue became the first computer chess-playing system to beat a reigning world chess champion, Garry Kasparov.^[34] In 2005, a Stanford robot won the DARPA Grand Challenge by driving autonomously for 131 miles along an unrehearsed desert trail.^[35] Two years later, a team from CMU won the DARPA Urban Challenge when their vehicle autonomously navigated 55 miles in an Urban environment while adhering to traffic hazards and all traffic laws.^[36] In February 2011, 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.^[37]

The leading-edge definition of artificial intelligence research is changing over time. One pragmatic definition is: "AI research is that which computing scientists do not know how to do cost-effectively today." For example, in 1956 optical character recognition (OCR) was considered AI, but today, sophisticated OCR software with a context-sensitive spell checker and grammar checker software comes for free with most image scanners. No one would any longer consider already-solved computing science problems like OCR "artificial intelligence" today.

Low-cost entertaining chess-playing software is commonly available for tablet computers. DARPA no longer provides significant funding for chess-playing computing system development. The Kinect which provides a 3D body–motion interface for the Xbox 360 uses algorithms that emerged from lengthy AI research,^[38] but few consumers realize the technology source.

AI applications are no longer the exclusive domain of U.S. Department of Defense R&D, but are now commonplace consumer items and inexpensive intelligent toys.

In common usage, the term "AI" no longer seems to apply to off-the-shelf solved computing-science problems, which may have originally emerged out of years of AI research.

Problems[link]

The general problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention.^[6]

Deduction, reasoning, problem solving[link]

Early AI researchers developed algorithms that imitated the step-by-step reasoning that humans use when they solve puzzles or make logical deductions.^[39] By the late 1980s and '90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.^[40]

For difficult problems, most of these algorithms can require enormous computational resources – most experience a "combinatorial explosion": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem-solving algorithms is a high priority for AI research.^[41]

Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model.^[42] AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied agent approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that give rise to this skill; statistical approaches to AI mimic the probabilistic nature of the human ability to guess.

Knowledge representation[link]

An ontology represents knowledge as a set of concepts within a domain and the relationships between those concepts.

Knowledge representation^[43] and knowledge engineering^[44] are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects;^[45] situations, events, states and time;^[46] causes and effects;^[47] knowledge about knowledge (what we know about what other people know);^[48] and many other, less well researched domains. A representation of "what exists" is an ontology (borrowing a word from traditional philosophy), of which the most general are called upper ontologies.^[49]

Among the most difficult problems in knowledge representation are:

Default reasoning and the qualification problem

Many of the things people know take the form of "working assumptions." For example, if a bird comes up in conversation, people typically picture an animal that is fist sized, sings, and flies. None of these things are true about all birds. John McCarthy identified this problem in 1969^[50] as the qualification problem: for any commonsense rule that AI researchers care to represent, there tend to be a huge number of exceptions. Almost nothing is simply true or false in the way that abstract logic requires. AI research has explored a number of solutions to this problem.^[51]

The breadth of commonsense knowledge

The number of atomic facts that the average person knows is astronomical. Research projects that attempt to build a complete knowledge base of commonsense knowledge (e.g., Cyc) require enormous amounts of laborious ontological engineering — they must be built, by hand, one complicated concept at a time.^[52] A major goal is to have the computer understand enough concepts to be able to learn by reading from sources like the internet, and thus be able to add to its own ontology.^{[citation needed]}

The subsymbolic form of some commonsense knowledge

Much of what people know is not represented as "facts" or "statements" that they could express verbally. For example, a chess master will avoid a particular chess position because it "feels too exposed"^[53] or an art critic can take one look at a statue and instantly realize that it is a fake.^[54] These are intuitions or tendencies that are represented in the brain non-consciously and sub-symbolically.^[55] Knowledge like this informs, supports and provides a context for symbolic, conscious knowledge. As with the related problem of sub-symbolic reasoning, it is hoped that situated AI, computational intelligence, or statistical AI will provide ways to represent this kind of knowledge.^[55]

Planning[link]

Intelligent agents must be able to set goals and achieve them.^[56] They need a way to visualize the future (they must have a representation of the state of the world and be able to make predictions about how their actions will change it) and be able to make choices that maximize the utility (or "value") of the available choices.^[57]

In classical planning problems, the agent can assume that it is the only thing acting on the world and it can be certain what the consequences of its actions may be.^[58] However, if the agent is not the only actor, it must periodically ascertain whether the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty.^[59]

Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence.^[60]

Learning[link]

Machine learning^[61] has been central to AI research from the beginning.^[62] In 1956, at the original Dartmouth AI summer conference, Ray Solomonoff wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".^[63] Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. In reinforcement learning^[64] the agent is rewarded for good responses and punished for bad ones. These can be analyzed in terms of decision theory, using concepts like utility. The mathematical analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory.^[65]

Natural language processing[link]

A parse tree represents the syntactic structure of a sentence according to some formal grammar.

Natural language processing^[66] gives machines the ability to read and understand the languages that humans speak. A sufficiently powerful natural language processing system would enable natural language user interfaces and the acquisition of knowledge directly from human-written sources, such as Internet texts. Some straightforward applications of natural language processing include information retrieval (or text mining) and machine translation.^[67]

A common method of processing and extracting meaning from natural language is through semantic indexing. Increases in processing speeds and the drop in the cost of data storage makes indexing large volumes of abstractions of the users input much more efficient.

Motion and manipulation[link]

The field of robotics^[68] is closely related to AI. Intelligence is required for robots to be able to handle such tasks as object manipulation^[69] and navigation, with sub-problems of localization (knowing where you are), mapping (learning what is around you) and motion planning (figuring out how to get there).^[70]

Perception[link]

Machine perception^[71] is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic) to deduce aspects of the world. Computer vision^[72] is the ability to analyze visual input. A few selected subproblems are speech recognition,^[73] facial recognition and object recognition.^[74]

Social intelligence[link]

Kismet, a robot with rudimentary social skills^[75]

Affective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects.^[76][77] It is an interdisciplinary field spanning computer sciences, psychology, and cognitive science.^[78] While the origins of the field may be traced as far back as to early philosophical enquiries into emotion,^[79] the more modern branch of computer science originated with Rosalind Picard's 1995 paper^[80] on affective computing.^[81][82] A motivation for the research is the ability to simulate empathy. The machine should interpret the emotional state of humans and adapt its behaviour to them, giving an appropriate response for those emotions.

Emotion and social skills^[83] play two roles for an intelligent agent. First, it must be able to predict the actions of others, by understanding their motives and emotional states. (This involves elements of game theory, decision theory, as well as the ability to model human emotions and the perceptual skills to detect emotions.) Also, in an effort to facilitate human-computer interaction, an intelligent machine might want to be able to display emotions--even if it does not actually experience them itself--in order to appear sensitive to the emotional dynamics of human interaction.

Creativity[link]

A sub-field of AI addresses creativity both theoretically (from a philosophical and psychological perspective) and practically (via specific implementations of systems that generate outputs that can be considered creative, or systems that identify and assess creativity). Related areas of computational research are Artificial intuition and Artificial imagination.^{[citation needed]}

General intelligence[link]

Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.^[7] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.^[84][85]

Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. For example, even a straightforward, specific task like machine translation requires that the machine follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's intention (social intelligence). Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it.^[86]

Approaches[link]

There is no established unifying theory or paradigm that guides AI research. Researchers disagree about many issues.^[87] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence by studying psychology or neurology? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?^[88] Can intelligent behavior be described using simple, elegant principles (such as logic or optimization)? Or does it necessarily require solving a large number of completely unrelated problems?^[89] Can intelligence be reproduced using high-level symbols, similar to words and ideas? Or does it require "sub-symbolic" processing?^[90] John Haugeland, who coined the term GOFAI (Good Old-Fashioned Artificial Intelligence), also proposed that AI should more properly be referred to as synthetic intelligence,^[91] a term which has since been adopted by some non-GOFAI researchers.^[92][93]

Cybernetics and brain simulation[link]

In the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.^[20] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.