Editing Artificial intelligence (section)

{{Short description|Intelligence of machines}}
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{{Artificial intelligence}}<!-- portal -->

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'''Artificial intelligence''' ('''AI''') is the capability of [[computer|computational systems]] to perform tasks typically associated with [[human intelligence]], such as learning, reasoning, problem-solving, perception, and decision-making. It is a [[field of research]] in [[computer science]] that develops and studies methods and [[software]] that enable machines to [[machine perception|perceive their environment]] and use [[machine learning|learning]] and [[intelligence]] to take actions that maximize their chances of achieving defined goals.{{Sfnp|Russell|Norvig|2021|pp=1–4}}

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High-profile [[applications of AI]] include advanced [[web search engine]]s (e.g., [[Google Search]]); [[recommendation systems]] (used by [[YouTube]], [[Amazon (company)|Amazon]], and [[Netflix]]); [[virtual assistant]]s (e.g., [[Google Assistant]], [[Siri]], and [[Amazon Alexa|Alexa]]); [[autonomous vehicles]] (e.g., [[Waymo]]); [[Generative artificial intelligence|generative]] and [[Computational creativity|creative]] tools (e.g., [[ChatGPT]] and [[AI art]]); and [[Superintelligence|superhuman]] play and analysis in [[strategy game]]s (e.g., [[chess]] and [[Go (game)|Go]]). 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 [[AI effect|not labeled AI anymore]]."<ref>[http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/ AI set to exceed human brain power] {{Webarchive|url=https://web.archive.org/web/20080219001624/http://www.cnn.com/2006/TECH/science/07/24/ai.bostrom/|date=2008-02-19}} CNN.com (July 26, 2006)</ref><ref>{{Cite journal |last1=Kaplan |first1=Andreas |last2=Haenlein |first2=Michael |date=2019 |title=Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence |journal=Business Horizons |volume=62 |pages=15–25 |doi=10.1016/j.bushor.2018.08.004 |issn=0007-6813 |s2cid=158433736}}</ref>

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Various subfields of AI research are centered around particular goals and the use of particular tools. The traditional goals of AI research include learning, [[automated reasoning|reasoning]], [[knowledge representation]], [[Automated planning and scheduling|planning]], [[natural language processing]], [[Machine perception|perception]], and support for [[robotics]].{{Efn|name="Problems of AI"}} To reach these goals, AI researchers have adapted and integrated a wide range of techniques, including [[state space search|search]] and [[mathematical optimization]], [[formal logic]], [[artificial neural network]]s, and methods based on [[statistics]], [[operations research]], and [[economics]].{{Efn|name="Tools of AI"}} AI also draws upon [[psychology]], [[linguistics]], [[Philosophy of artificial intelligence|philosophy]], [[neuroscience]], and other fields.<ref>{{Harvtxt|Russell|Norvig|2021|loc=§1.2}}.</ref> Some companies, such as [[OpenAI]], [[Google DeepMind]] and [[Meta Platforms|Meta]], aim to create [[artificial general intelligence]] (AGI)—AI that can complete virtually any cognitive task at least as well as a human.<ref>{{Cite web |date=2024-04-04 |title=Tech companies want to build artificial general intelligence. But who decides when AGI is attained? |url=https://apnews.com/article/agi-artificial-general-intelligence-existential-risk-meta-openai-deepmind-science-ff5662a056d3cf3c5889a73e929e5a34 |access-date=2025-05-20 |website=AP News |language=en}}</ref>

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Artificial intelligence was founded as an academic discipline in 1956,<ref name="Dartmouth workshop"/> and the field went through multiple cycles of optimism throughout [[History of artificial intelligence|its history]],<ref name="Succ1"/><ref name="Fund01"/> followed by periods of disappointment and loss of funding, known as [[AI winter]]s.<ref name="First AI Winter"/><ref name="Second AI Winter"/> Funding and interest vastly increased after 2012 when [[Graphics processing unit|graphics processing units]] started being used to accelerate neural networks, and [[deep learning]] outperformed previous AI techniques.<ref name="Deep learning revolution"/> This growth accelerated further after 2017 with the [[transformer architecture]].{{Sfnp|Toews|2023}} In the 2020s, the period of rapid [[Progress in artificial intelligence|progress]] marked by advanced generative AI became known as the [[AI boom]]. Generative AI and its ability to create and modify content exposed several unintended consequences and harms in the present and raised [[Ethics of artificial intelligence|ethical concerns]] about [[AI aftermath scenarios|AI's long-term effects]] and potential [[Existential risk from artificial intelligence|existential risks]], prompting discussions about [[Regulation of artificial intelligence|regulatory policies]] to ensure the [[AI safety|safety]] and benefits of the technology.