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Progress in artificial intelligence

Artificial intelligence has been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, 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."[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.

To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

Contents

Performance evaluation

The broad classes of outcome for an AI test are:

  • optimal: it is not possible to perform better
  • strong super-human: performs better than all humans
  • super-human: performs better than most humans
  • par-human: performs similarly to most humans
  • sub-human: performs worse than most humans

Optimal

See also solved games.

Super-human

Par-human

Sub-human

See also

External links

References

  1. ^ AI set to exceed human brain power CNN.com (July 26, 2006)
  2. ^ a b Kurtzweil 2005, p. 264
  3. ^ NRC 1999[verification needed] under "Artificial Intelligence in the 90s"
  4. ^ Schaeffer, J.; Burch, N.; Björnsson, Y.; Kishimoto, A.; Müller, M.; Lake, R.; Lu, P.; Sutphen, S. (2007). "Checkers is solved". Science 317 (5844): 1518–1522. Bibcode:2007Sci...317.1518S. doi:10.1126/science.1144079. PMID 17641166. CiteSeerX: 10.1.1.95.5393.  edit
  5. ^ "God's Number is 20"
  6. ^ Tesauro, Gerald (March 1995). "Temporal difference learning and TD-Gammon". Communications of the ACM 38 (3): 58–68. doi:10.1145/203330.203343. 
  7. ^ Computer bridge#Computers versus humans
  8. ^ Computer Chess#Computers versus humans
  9. ^ Proverb: The probabilistic cruciverbalist. By Greg A. Keim, Noam Shazeer, Michael L. Littman, Sushant Agarwal, Catherine M. Cheves, Joseph Fitzgerald, Jason Grosland, Fan Jiang, Shannon Pollard, and Karl Weinmeister. 1999. In Proceedings of the Sixteenth National Conference on Artificial Intelligence, 710-717. Menlo Park, Calif.: AAAI Press.
  10. ^ http://www.physorg.com/news193908598. html
  11. ^ Reversi#Computer_opponents
  12. ^ Sheppard, B. (2002). "World-championship-caliber Scrabble". Artificial Intelligence 134: 241–275. doi:10.1016/S0004-3702(01)00166-7.  edit
  13. ^ Watson beats Jeopardy grand-champions. http://www.nytimes.com/2011/02/17/sci ence/17jeopardy-watson.html
  14. ^ Jackson, Joab. "IBM Watson Vanquishes Human Jeopardy Foes". PC World. IDG News. Retrieved 2011-02-17. 
  15. ^ Markoff, John (October 9, 2010). "Google Cars Drive Themselves, in Traffic". The New York Times. 
  16. ^ There are several ways of evaluating machine translation systems. People competent in a second language frequently outperform machine translation systems but the average person is often less capable. Some machine translation systems are capable of a large number of languages, like google translate, and as a result have a broader competence than most humans. For example, very few humans can translate from Arabic to Polish and French to Swahili and Armenian to Vietnamese. When comparing over several languages machine translation systems will tend to outperform humans.
  17. ^ Rubin, Jonathan; Watson, Ian (2011). "Computer poker: A review". Artificial Intelligence. doi:10.1016/j.artint.2010.12.005.  edit
  18. ^ "Polaris drawing professionals to a stand-still". University of Alberta: Express News. July 20, 2007. 
  19. ^ Ryan Smith (August 9, 2006). "U of A researchers win computer poker title". University of Alberta: Express News. 
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