Editing AI-complete (section)

==History==
The term was coined by [[Fanya Montalvo]] by analogy with [[NP-complete]] and [[NP-hard]] in [[Computational complexity theory|complexity theory]], which formally describes the most famous class of difficult problems.<ref>{{Citation | last=Mallery | first=John C. | year=1988 | url=http://citeseer.ist.psu.edu/mallery88thinking.html | contribution=Thinking About Foreign Policy: Finding an Appropriate Role for Artificially Intelligent Computers | title=The 1988 Annual Meeting of the International Studies Association. | location=St. Louis, MO | access-date=2007-04-27 | archive-date=2008-02-29 | archive-url=https://web.archive.org/web/20080229024012/http://citeseer.ist.psu.edu/mallery88thinking.html | url-status=live }}.</ref> Early uses of the term are in Erik Mueller's 1987 PhD dissertation<ref>Mueller, Erik T. (1987, March). [http://ftp.cs.ucla.edu/tech-report/198_-reports/870017.pdf ''Daydreaming and Computation'' (Technical Report CSD-870017)] {{Webarchive|url=https://web.archive.org/web/20201030213109/http://ftp.cs.ucla.edu/tech-report/198_-reports/870017.pdf |date=2020-10-30 }} PhD dissertation, University of California, Los Angeles. ("Daydreaming is but one more ''AI-complete'' problem: if we could solve anyone artificial intelligence problem, we could solve all the others", p.&nbsp;302)</ref> and in [[Eric S. Raymond|Eric Raymond]]'s 1991 [[Jargon File]].<ref>Raymond, Eric S. (1991, March 22). [http://catb.org/esr/jargon/oldversions/jarg282.txt Jargon File Version 2.8.1] {{Webarchive|url=https://web.archive.org/web/20110604150347/http://catb.org/esr/jargon/oldversions/jarg282.txt |date=2011-06-04 }} (Definition of "AI-complete" first added to jargon file.)</ref>

[[Expert system]]s, that were popular in the 1980s, were able to solve very simple and/or restricted versions of AI-complete problems, but never in their full generality. When AI researchers attempted to "scale up" their systems to handle more complicated, real-world situations, the programs tended to become excessively [[Software brittleness|brittle]] without [[commonsense knowledge]] or a rudimentary understanding of the situation: they would fail as unexpected circumstances outside of its original problem context would begin to appear. When human beings are dealing with new situations in the world, they are helped by their awareness of the general context: they know what the things around them are, why they are there, what they are likely to do and so on. They can recognize unusual situations and adjust accordingly. Expert systems lacked this adaptability and were [[Software brittleness|brittle]] when facing new situations.<ref>{{Citation |last1=Lenat |first1=Douglas |title=Building Large Knowledge-Based Systems |pages=1–5 |year=1989 |publisher=Addison-Wesley |last2=Guha |first2=R. V. |author-link=Douglas Lenat}}</ref>

[[DeepMind]] published a work in May 2022 in which they trained a single model to do several things at the same time. The model, named [[Gato (DeepMind)|Gato]], can "play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens."<ref>{{Cite web |title=A Generalist Agent |url=https://www.deepmind.com/publications/a-generalist-agent |url-status=live |archive-url=https://web.archive.org/web/20220802000307/https://www.deepmind.com/publications/a-generalist-agent |archive-date=2022-08-02 |access-date=2022-05-26 |website=www.deepmind.com |language=en}}</ref> Similarly, some tasks once considered to be AI-complete, like [[machine translation]],<ref>{{Cite magazine |last=Katz |first=Miranda |title=Welcome to the Era of the AI Coworker {{!}} Backchannel |url=https://www.wired.com/story/welcome-to-the-era-of-the-ai-coworker/ |access-date=2024-04-28 |magazine=Wired |language=en-US |issn=1059-1028}}</ref> are among the capabilities of [[large language model]]s.<ref>{{Cite web |title=Unveiling the Power of Large Language Models (LLMs) |url=https://www.unite.ai/large-language-models/ |access-date=2024-04-28 |website=www.unite.ai}}</ref>