Applications of artificial intelligence: Difference between revisions

Revision as of 17:42, 23 August 2022

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== Games ==

{{See also|Video game bot}}

Games have been a major application{{relevance inline|date=May 2022|reason=Demonstration of capabilities is not an application by itself or is it?}} of AI's capabilities since the 1950s. In the 21st century, AIs have produced superhuman results in many games, including [[Computer chess|chess]] ([[IBM Deep Blue|Deep Blue]]), ''[[Jeopardy!]]'' ([[Watson (artificial intelligence software)|Watson]]),<ref>{{cite news|last=Markoff|first=John|date=16 February 2011<!-- corrected 24 February 2011-->|title=Computer Wins on 'Jeopardy!': Trivial, It's Not|work=[[The New York Times]]|url=https://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html|url-status=live|access-date=25 October 2014|archive-url=https://web.archive.org/web/20141022023202/http://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html|archive-date=22 October 2014}}</ref> [[Go (game)|Go]] ([[AlphaGo]]),<ref name="bbc-alphago">{{cite web|url=https://deepmind.com/alpha-go.html|title=AlphaGo – Google DeepMind |url-status=live|archive-url=https://web.archive.org/web/20160310191926/https://www.deepmind.com/alpha-go.html |archive-date=10 March 2016}}</ref><ref>{{cite news|title=Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol|url=https://www.bbc.com/news/technology-35785875|access-date=1 October 2016 |work=BBC News |date=12 March 2016|url-status=live|archive-url=https://web.archive.org/web/20160826103910/http://www.bbc.com/news/technology-35785875|archive-date=26 August 2016}}</ref><ref>{{cite magazine|url=https://www.wired.com/2017/05/win-china-alphagos-designers-explore-new-ai/|title=After Win in China, AlphaGo's Designers Explore New AI |magazine=Wired|date=27 May 2017|url-status=live|archive-url=https://web.archive.org/web/20170602234726/https://www.wired.com/2017/05/win-china-alphagos-designers-explore-new-ai/|archive-date=2 June 2017 |last1=Metz |first1=Cade}}</ref><ref>{{cite web|url=http://www.goratings.org/|title=World's Go Player Ratings|date=May 2017|url-status=live|archive-url=https://web.archive.org/web/20170401123616/https://www.goratings.org/|archive-date=1 April 2017}}</ref><ref>{{cite web|title=柯洁迎19岁生日 雄踞人类世界排名第一已两年|url=http://sports.sina.com.cn/go/2016-08-02/doc-ifxunyya3020238.shtml |language=zh |date=May 2017|url-status=live|archive-url=https://web.archive.org/web/20170811222849/http://sports.sina.com.cn/go/2016-08-02/doc-ifxunyya3020238.shtml|archive-date=11 August 2017}}</ref><ref>{{Cite web|title=MuZero: Mastering Go, chess, shogi and Atari without rules|url=https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rules|access-date=1 March 2021|website=Deepmind}}</ref><ref>{{cite news|author1=Steven Borowiec|author2=Tracey Lien|title=AlphaGo beats human Go champ in milestone for artificial intelligence|url=https://www.latimes.com/world/asia/la-fg-korea-alphago-20160312-story.html|access-date=13 March 2016|work=[[Los Angeles Times]]|date=12 March 2016}}</ref> [[poker]] ([[Pluribus (poker bot)|Pluribus]]<ref>{{Cite web|url=https://www.smithsonianmag.com/smart-news/poker-playing-ai-knows-when-hold-em-when-fold-em-180972643/|title=This Poker-Playing A.I. Knows When to Hold 'Em and When to Fold 'Em|first=Meilan|last=Solly|website=Smithsonian|quote=Pluribus has bested poker pros in a series of six-player no-limit Texas Hold'em games, reaching a milestone in artificial intelligence research. It is the first bot to beat humans in a complex multiplayer competition.}}</ref> and [[Cepheus (poker bot)|Cepheus)]],<ref>{{Cite journal|last1=Bowling|first1=Michael|last2=Burch|first2=Neil|last3=Johanson|first3=Michael|last4=Tammelin|first4=Oskari|date=9 January 2015|title=Heads-up limit hold'em poker is solved|url=https://www.science.org/doi/10.1126/science.1259433|journal=Science|language=en|volume=347|issue=6218|pages=145–149|doi=10.1126/science.1259433|issn=0036-8075|pmid=25574016|bibcode=2015Sci...347..145B|s2cid=3796371}}</ref> [[Esports|E-sports]] ([[StarCraft]]),<ref>{{cite journal|last1=Ontanon|first1=Santiago|last2=Synnaeve|first2=Gabriel|last3=Uriarte|first3=Alberto|last4=Richoux|first4=Florian|last5=Churchill|first5=David|last6=Preuss|first6=Mike|date=December 2013|title=A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft|journal=IEEE Transactions on Computational Intelligence and AI in Games|volume=5|issue=4|pages=293–311|citeseerx=10.1.1.406.2524|doi=10.1109/TCIAIG.2013.2286295|s2cid=5014732}}</ref><ref>{{cite news|year=2017|title=Facebook Quietly Enters StarCraft War for AI Bots, and Loses|magazine=WIRED|url=https://www.wired.com/story/facebook-quietly-enters-starcraft-war-for-ai-bots-and-loses/|access-date=7 May 2018}}</ref> and [[general game playing]] ([[AlphaZero]]<ref>{{Cite journal|first1 = David|last1 = Silver |author-link1=David Silver (programmer)|first2 = Thomas |last2 = Hubert|first3 = Julian |last3 = Schrittwieser|first4 = Ioannis |last4 = Antonoglou|first5 = Matthew |last5 = Lai|first6 = Arthur |last6 = Guez |first7 = Marc |last7 = Lanctot |first8 = Laurent |last8 = Sifre |first9 = Dharshan |last9 = Kumaran |first10 = Thore |last10 = Graepel |first11 = Timothy |last11 = Lillicrap |first12 = Karen |last12 = Simonyan |first13 = Demis |last13 = Hassabis |author-link13=Demis Hassabis |title = A general reinforcement learning algorithm that masters chess, shogi, and go through self-play |journal = [[Science (journal)|Science]] |pages = 1140–1144|volume = 362|issue = 6419|doi = 10.1126/science.aar6404|pmid = 30523106|date = 7 December 2018|bibcode = 2018Sci...362.1140S|doi-access = free}}</ref><ref>{{cite news|last1=Sample|first1=Ian|date=18 October 2017|title='It's able to create knowledge itself': Google unveils AI that learns on its own|language=en|work=The Guardian|url=https://www.theguardian.com/science/2017/oct/18/its-able-to-create-knowledge-itself-google-unveils-ai-learns-all-on-its-own|access-date=7 May 2018}}</ref><ref>{{cite journal |last1=Jaderberg |first1=M. |last2=Czarnecki |first2=W. M. |last3=Dunning |first3=I. |last4=Marris |first4=L. |last5=Lever |first5=G. |last6=Castañeda |first6=A. G. |last7=Beattie |first7=C. |last8=Rabinowitz |first8=N. C. |last9=Morcos |first9=A. S. |last10=Ruderman |first10=A. |last11=Sonnerat |first11=N. |last12=Green |first12=T. |last13=Deason |first13=L. |last14=Leibo |first14=J. Z. |last15=Silver |first15=D. |last16=Hassabis |first16=D. |last17=Kavukcuoglu |first17=K. |last18=Graepel |first18=T. |date=2019 |title=Human-level performance in 3D multiplayer games with population-based reinforcement learning |url=https://doi.org/10.1126/science.aau6249 |journal=Science |volume=364 |pages=859-865 | pmid=31147514 | doi=10.1126/science.aau6249}}</ref><ref>{{cite news|date=5 July 2017|title=The AI revolution in science|language=en|work=Science {{!}} AAAS|url=https://www.science.org/content/article/ai-revolution-science|access-date=7 May 2018}}</ref> and [[MuZero]]).<ref>{{cite news|title=The superhero of artificial intelligence: can this genius keep it in check?|url=https://www.theguardian.com/technology/2016/feb/16/demis-hassabis-artificial-intelligence-deepmind-alphago|access-date=26 April 2018|work=The Guardian|date=16 February 2016|archive-date=23 April 2018|archive-url=https://web.archive.org/web/20180423220101/https://www.theguardian.com/technology/2016/feb/16/demis-hassabis-artificial-intelligence-deepmind-alphago|url-status=live}}</ref><ref>{{cite journal |last1=Mnih |first1=Volodymyr|last2=Kavukcuoglu|first2=Koray|last3=Silver|first3=David|last4=Rusu|first4=Andrei A. |last5=Veness|first5=Joel |last6=Bellemare|first6=Marc G.|last7=Graves|first7=Alex|last8=Riedmiller |first8=Martin|last9=Fidjeland|first9=Andreas K. |last10=Ostrovski|first10=Georg|last11=Petersen |first11=Stig|last12=Beattie|first12=Charles|last13=Sadik |first13=Amir|last14=Antonoglou|first14=Ioannis |last15=King|first15=Helen|last16=Kumaran|first16=Dharshan|last17=Wierstra|first17=Daan|last18=Legg |first18=Shane|last19=Hassabis|first19=Demis|title=Human-level control through deep reinforcement learning |journal=Nature |date=26 February 2015|volume=518|issue=7540|pages=529–533 |doi=10.1038/nature14236 |pmid=25719670|bibcode=2015Natur.518..529M|s2cid=205242740}}</ref><ref>{{cite news |last1=Sample|first1=Ian |title=Google's DeepMind makes AI program that can learn like a human |url=https://www.theguardian.com/global/2017/mar/14/googles-deepmind-makes-ai-program-that-can-learn-like-a-human|access-date=26 April 2018 |work=The Guardian |date=14 March 2017|archive-date=26 April 2018|archive-url=https://web.archive.org/web/20180426212908/https://www.theguardian.com/global/2017/mar/14/googles-deepmind-makes-ai-program-that-can-learn-like-a-human |url-status=live}}</ref><ref>{{Cite journal|last1=Schrittwieser|first1=Julian|last2=Antonoglou|first2=Ioannis|last3=Hubert|first3=Thomas|last4=Simonyan|first4=Karen|last5=Sifre|first5=Laurent|last6=Schmitt|first6=Simon|last7=Guez|first7=Arthur|last8=Lockhart|first8=Edward|last9=Hassabis|first9=Demis|last10=Graepel|first10=Thore|last11=Lillicrap|first11=Timothy|date=23 December 2020|title=Mastering Atari, Go, chess and shogi by planning with a learned model|url=https://www.nature.com/articles/s41586-020-03051-4|journal=Nature|language=en|volume=588|issue=7839|pages=604–609|doi=10.1038/s41586-020-03051-4|pmid=33361790|issn=1476-4687|arxiv=1911.08265|bibcode=2020Natur.588..604S|s2cid=208158225}}</ref> AI has replaced hand-coded algorithms in most chess programs.<ref>{{Cite web|last=K|first=Bharath|date=2 April 2021|title=AI In Chess: The Evolution of Artificial Intelligence In Chess Engines|url=https://towardsdatascience.com/ai-in-chess-the-evolution-of-artificial-intelligence-in-chess-engines-a3a9e230ed50|access-date=6 January 2022|website=Medium|language=en}}</ref> Unlike [[Go (game)|go]] or [[chess]], poker is an [[imperfect information|imperfect-information]] game, so a program that plays poker has to reason under uncertainty. The general game players work using feedback from the game system, without knowing the rules.

== Economic and social challenges ==