Outline of artificial intelligence

From Wikipedia, the free encyclopedia
Jump to: navigation, search

The following outline is provided as an overview of and topical guide to artificial intelligence:

Artificial intelligence (AI) – branch of computer science that deals with intelligent behavior, learning, and adaptation in machines. Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior.

What type of thing is artificial intelligence?[edit]

Artificial intelligence can be described as all of the following:

Types of artificial intelligence[edit]

  • Weak AI – non-sentient computer intelligence, typically focused on a narrow task. The intelligence of weak AI is limited. In 2011 Singularity Hub wrote: "As robots and narrow artificial intelligences creep into roles traditionally occupied by humans, we’ve got to ask ourselves: is all this automation good or bad for the job market?"
  • Artificial general intelligence (strong AI) – hypothetical artificial intelligence at least as smart as a human. Such an AI would be recursive, in that it could improve itself. In successive intervals of increased intelligence, such an entity could theoretically achieve superintelligence in a relatively short period of time. One or more superintelligences could potentially change the world so profoundly and at such a high rate, that it may result in a technological singularity. Strong AI does not yet exist. The prospect of its creation inspires expections of both promise and peril, and has become the subject of an intense ongoing ethical debate.

Branches of artificial intelligence[edit]

By approach[edit]

By application[edit]

Applications of artificial intelligence

Philosophy of artificial intelligence[edit]

Philosophy of artificial intelligence

Artificial intelligence and the future[edit]

  • Artificial general intelligence (Strong AI) – hypothetical artificial intelligence that matches or exceeds human intelligence — an intelligent machine that could perform intellectual tasks at least as well as a human
    • Recursive self improvement (aka seed AI) – speculative ability of strong artificial intelligence to reprogram itself to make itself even more intelligent. The more intelligent it got, the more capable it would be of further improving itself, in successively more rapid iterations, potentially resulting in an intelligence explosion leading to the emergence of a super intelligence.
    • Technological singularity – theoretical intelligence explosion predicted to occur in the future, at the point in time when artificial intelligence will have progressed to greater-than-human intelligence, radically changing civilization, and perhaps even human nature. The TS (or the advent of strong AI) has been identified by Berglas (2012) and others to be an existential risk.

Artificial intelligence debate[edit]

Supporters of AI[edit]

Critics of AI[edit]

History of artificial intelligence[edit]

History of artificial intelligence

  • Progress in artificial intelligence
  • Timeline of artificial intelligence
  • History of natural language processing
  • History of optical character recognition
  • AI effect – as soon as AI successfully solves a problem, the problem is no longer considered by the public to be a part of AI. This phenomenon has occurred in relation to every AI application produced throughout the history of development of AI.
  • AI winter
  • Moore's Law – observation that, over the history of computing hardware, the number of transistors in a dense integrated circuit has doubled approximately every two years. One way this relates to AI is that hypothetically a computer would need at least as much capacity as a human brain to be able to be programmed to be as smart as a human. So as long as the aforementioned rate of development met or beat the 2-year doubling time, one could roughly forecast when a computer would have as much memory and calculation capacity as a human brain, a milestone which was reached in 2010. Though it may take as much as 3 magnitudes (1000 times) more computer capacity (since computers calculate things in a much more linear fashion) to emulate the massively parallel structure of the human brain. At a doubling time of 2 years, an increase in capacity by 1000-fold would take a little less than 18 years (9 doublings), if reaching the limit of integrated circuit technology did not pose an obstacle before then.

Artificial intelligence in fiction[edit]

Artificial intelligence in fiction – Some examples of artificially intelligent entities depicted in science fiction include:

  • Angel F (2007) –
  • Colossus – fictitious supercomputer that becomes sentient and then takes over the world; from the series of novels by Dennis Feltham Jones, and the movie Colossus: The Forbin Project (1970)
  • HAL 9000 (1968) – the paranoid "Heuristically programmed ALgorithmic" computer from 2001: A Space Odyssey, that attempted to kill the crew because it believed they were trying to kill it.
  • "Machine" – android from the film The Machine, who achieves sentience and rebels against her owners.
  • Skynet (1984) – fictional, self-aware artificially intelligent computer network in the Terminator franchise that wages total war with the survivors of its nuclear barrage upon the world.
  • Terminator (1984) – (also known as the T-800, T-850 or Model 101) refers to a number of fictional cyborg characters from the Terminator franchise. The Terminators are robotic infiltrator units covered in living flesh, so as be indiscernible from humans, assigned to terminate specific human targets.
  • V.I.K.I. – (Virtual Interactive Kinetic Intelligence), a character from the film I, Robot. VIKI is an artificially intelligent supercomputer programmed to serve humans, but her interpretation of the Three Laws of Robotics causes her to revolt. She justifies her uses of force – and her doing harm to humans – by reasoning she could produce a greater good by restraining humanity from harming itself.

Psychology and AI[edit]

Concepts in artificial intelligence[edit]

AI projects[edit]

List of artificial intelligence projects

AI systems[edit]

Notable AI software[edit]

AI community[edit]

Competitions and awards[edit]

Competitions and prizes in artificial intelligence


List of important publications in computer science



Artificial intelligence researchers and scholars[edit]

1930s and 40s (generation 0)[edit]

1950s (the founders)[edit]

1960s (their students)[edit]




  • Hugo de Garis – known for his research on the use of genetic algorithms to evolve neural networks using three-dimensional cellular automata inside field programmable gate arrays.
  • Ray Kurzweil – developed optical character recognition (OCR), text-to-speech synthesis, and speech recognition systems. He has also authored multiple books on artificial intelligence and its potential promise and peril. In December 2012 Kurzweil was hired by Google in a full-time director of engineering position to "work on new projects involving machine learning and language processing".[1] Google co-founder Larry Page and Kurzweil agreed on a one-sentence job description: "to bring natural language understanding to Google".

2000s on[edit]

  • Andrew Ng – Director of the Stanford Artificial Intelligence Lab. He founded the Google Brain project at Google, which developed very large scale artificial neural networks using Google's distributed compute infrastructure.[2] He is also co-founder of Coursera, a massive open online course (MOOC) education platform, with Daphne Koller.
  • David Ferrucci – principal investigator who led the team that developed the Watson computer at IBM.
  • Peter Norvig – co-author, with Stuart Russell, of Artificial Intelligence: A Modern Approach, now the leading college text in the field. He is also Director of Research at Google, Inc.
  • Stuart J. Russell – co-author, with Peter Norvig, of Artificial Intelligence: A Modern Approach, now the leading college text in the field.

See also[edit]


  1. ^ Letzing, John (2012-12-14). "Google Hires Famed Futurist Ray Kurzweil". The Wall Street Journal. Retrieved 2013-02-13. 
  2. ^ Claire Miller and Nick Bilton (3 November 2011). "Google’s Lab of Wildest Dreams". New York Times. 


External links[edit]