Applications of artificial intelligence

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Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, remote sensing, scientific discovery and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore," Nick Bostrom reports.[1] "Many thousands of AI applications are deeply embedded in the infrastructure of every industry."[2] In the late 90s and early 21st century, AI technology became widely used as elements of larger systems,[2][3] but the field is rarely credited for these successes.

Computer science[edit]

AI researchers have created many tools to solve the most difficult problems in computer science. Many of their inventions have been adopted by mainstream computer science and are no longer considered a part of AI. (See AI effect). According to Russell & Norvig (2003, p. 15), all of the following were originally developed in AI laboratories: time sharing, interactive interpreters, graphical user interfaces and the computer mouse, rapid development environments, the linked list data structure, automatic storage management, symbolic programming, functional programming, dynamic programming and object-oriented programming.

Finance[edit]

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.[4]

Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation.

Hospitals and medicine[edit]

A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and provide medical information and other important tasks.

Artificial neural networks are used as clinical decision support systems for medical diagnosis, such as in Concept Processing technology in EMR software.

Other tasks in medicine that can potentially be performed by artificial intelligence include:

Heavy industry[edit]

Robots have 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. Japan is the leader in using and producing robots in the world. In 1999, 1,700,000 robots were in use worldwide. For more information, see survey[6] about artificial intelligence in business.

Online and telephone customer service[edit]

An automated online assistant providing customer service on a web page.

Artificial intelligence is implemented in automated online assistants that can be seen as avatars on web pages.[7] It can avail for enterprises to reduce their operation and training cost.[7] A major underlying technology to such systems is natural language processing.[7]

Similar techniques may be used in answering machines of call centres, such as speech recognition software to allow computers to handle first level of customer support, text mining and natural language processing to allow better customer handling, agent training by automatic mining of best practices from past interactions, support automation and many other technologies to improve agent productivity and customer satisfaction.[8]

Transportation[edit]

Fuzzy logic controllers have been developed for automatic gearboxes in automobiles. For example, the 2006 Audi TT, VW Toureg[citation needed] and VW Caravell feature the DSP transmission which utilizes Fuzzy Logic. A number of Škoda variants (Škoda Fabia) also currently include a Fuzzy Logic based controller.

Telecommunications maintenance[edit]

Many telecommunications companies make use of heuristic search in the management of their workforces, for example BT Group has deployed heuristic search[9] in a scheduling application that provides the work schedules of 20,000 engineers.

Toys and games[edit]

The 1990s saw some of the first attempts to mass-produce domestically aimed types of basic Artificial Intelligence for education, or leisure. This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of Artificial Intelligence, specifically in the form of Tamagotchis and Giga Pets, iPod Touch, the Internet (example: basic search engine interfaces are one simple form), and the first widely released robot, Furby. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy.

AI has also been applied to video games, for example video game bots, which are designed to stand in as opponents where humans aren't available or desired; or the AI Director from Left 4 Dead, which decides where enemies spawn and how maps are laid out to be more or less challenging at various points of play.

Music[edit]

The evolution of music has always been affected by technology. With AI, scientists are trying to make the computer emulate the activities of the skillful musician. Composition, performance, music theory, sound processing are some of the major areas on which research in Music and Artificial Intelligence are focusing.

Aviation[edit]

The Air Operations Division (AOD) uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.

The use of artificial intelligence in simulators is proving to be very useful for the AOD. Airplane simulators are using artificial intelligence in order to process the data taken from simulated flights. Other than simulated flying, there is also simulated aircraft warfare. The computers are able to come up with the best success scenarios in these situations. The computers can also create strategies based on the placement, size, speed and strength of the forces and counter forces. Pilots may be given assistance in the air during combat by computers. The artificial intelligent programs can sort the information and provide the pilot with the best possible maneuvers, not to mention getting rid of certain maneuvers that would be impossible for a human being to perform. Multiple aircraft are needed to get good approximations for some calculations so computer simulated pilots are used to gather data. These computer simulated pilots are also used to train future air traffic controllers.

The system used by the AOD in order to measure performance was the Interactive Fault Diagnosis and Isolation System, or IFDIS. It is a rule based expert system put together by collecting information from TF-30 documents and the expert advice from mechanics that work on the TF-30. This system was designed to be used for the development of the TF-30 for the RAAF F-111C. The performance system was also used to replace specialized workers. The system allowed the regular workers to communicate with the system and avoid mistakes, miscalculations, or having to speak to one of the specialized workers.

The AOD also uses artificial intelligence in speech recognition software. The air traffic controllers are giving directions to the artificial pilots and the AOD wants to the pilots to respond to the ATC's with simple responses. The programs that incorporate the speech software must be trained, which means they use neural networks. The program used, the Verbex 7000, is still a very early program that has plenty of room for improvement. The improvements are imperative because ATCs use very specific dialog and the software needs to be able to communicate correctly and promptly every time.

The Artificial Intelligence supported Design of Aircraft,[10] or AIDA, is used to help designers in the process of creating conceptual designs of aircraft. This program allows the designers to focus more on the design itself and less on the design process. The software also allows the user to focus less on the software tools. The AIDA uses rule based systems to compute its data. This is a diagram of the arrangement of the AIDA modules. Although simple, the program is proving effective.

In 2003, NASA's Dryden Flight Research Center, and many other companies, created software that could enable a damaged aircraft to continue flight until a safe landing zone can be reached. The software compensates for all the damaged components by relying on the undamaged components. The neural network used in the software proved to be effective and marked a triumph for artificial intelligence.

The Integrated Vehicle Health Management system, also used by NASA, on board an aircraft must process and interpret data taken from the various sensors on the aircraft. The system needs to be able to determine the structural integrity of the aircraft. The system also needs to implement protocols in case of any damage taken the vehicle.

News, Publishing & Writing[edit]

The company Narrative Science makes computer generated news and reports commercially available, including summarizing team sporting events based on statistical data from the game in English. It also creates financial reports and real estate analyses.[11]

The company Automated Insights generates personalized recaps and previews for Yahoo Sports Fantasy Football.[12] The company is projected to generate one billion stories in 2014, up from 350 million in 2013.[13]

Another company, called Yseop, uses artificial intelligence to turn structured data into intelligent comments and recommendations in natural language. Yseop is able to write financial reports, executive summaries, personalized sales or marketing documents and more at a speed of thousands of pages per second and in multiple languages including English, Spanish, French & German. [14]

Other[edit]

Various tools of artificial intelligence are also being widely deployed in homeland security, speech and text recognition, data mining, and e-mail spam filtering. Applications are also being developed for gesture recognition (understanding of sign language by machines), individual voice recognition, global voice recognition (from a variety of people in a noisy room), facial expression recognition for interpretation of emotion and non verbal cues. Other applications are robot navigation, obstacle avoidance, and object recognition.[citation needed]

List of applications[edit]

Typical problems to which AI methods are applied
Other fields in which AI methods are implemented

See also[edit]

External links[edit]

Notes[edit]

  1. ^ AI set to exceed human brain power CNN.com (July 26, 2006)
  2. ^ a b Kurzweil 2005, p. 264.
  3. ^ NRC 1999, "Artificial Intelligence in the 90s".
  4. ^ Robots Beat Humans in Trading Battle. BBC.com (August 8, 2001)
  5. ^ Reed, T. R.; Reed, N. E.; Fritzson, P. (2004). "Heart sound analysis for symptom detection and computer-aided diagnosis". Simulation Modelling Practice and Theory 12 (2): 129. doi:10.1016/j.simpat.2003.11.005.  edit
  6. ^ Nordlander, Tomas Eric (2001). "AI Surveying: Artificial Intelligence In Business" (PDF). (MS Thesis), De Montfort University. Retrieved 2007-11-04. 
  7. ^ a b c Implementing an online help desk system based on conversational agent Authors: Alisa Kongthon, Chatchawal Sangkeettrakarn, Sarawoot Kongyoung and Choochart Haruechaiyasak. Published by ACM 2009 Article, Bibliometrics Data Bibliometrics. Published in: Proceeding, MEDES '09 Proceedings of the International Conference on Management of Emergent Digital EcoSystems, ACM New York, NY, USA. ISBN 978-1-60558-829-2, doi:10.1145/1643823.1643908
  8. ^ L Venkata Subramaniam (February 1, 2008). "Call Centers of the Future" (PDF). i.t. magazine. pp. 48–51. Retrieved 2008-05-29. 
  9. ^ Success Stories.
  10. ^ AIDA Homepage. Kbs.twi.tudelft.nl (April 17, 1997). Retrieved on 2013-07-21.
  11. ^ business intelligence solutions. Narrative Science. Retrieved on 2013-07-21.
  12. ^ Eule, Alexander. "Big Data and Yahoo's Quest for Mass Personalization". Barron's. 
  13. ^ Kirkland, Sam. "‘Robot’ to write 1 billion stories in 2014 — but will you know it when you see it?". Poynter. 
  14. ^ http://yseop.com/EN/solutions.html

References[edit]