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1956年AI作为一门学科被建立起来，后来经历过几段乐观时期<ref name="Simon 1965">Simon, H. A. (1965). The Shape of Automation for Men and Management. New York: Harper & Row.</ref><ref name="Crevier 1993"/><ref name="McCorduck 2004">McCorduck, Pamela (2004), Machines Who Think (2nd ed.), Natick, MA: A. K. Peters, Ltd., ISBN 1-56881-205-1</ref><ref name="Crevier 1993">Crevier, Daniel (1993), AI: The Tumultuous Search for Artificial Intelligence, New York, NY: BasicBooks, ISBN 0-465-02997-3</ref><ref name="Russell & Norvig 2003"/><ref name="NRC 1999">NRC (United States National Research Council) (1999). "Developments in Artificial Intelligence". Funding a Revolution: Government Support for Computing Research. National Academy Press.</ref><ref name="Newquist 1994">{{cite book | last=Newquist |first=HP |year=1994| title=The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think| publisher=Macmillan/SAMS |location=New York| isbn= 978-0-672-30412-5}}</ref>与紧随而来的亏损以及缺乏资金的困境（也就是“AI寒冬”<ref name="Crevier 1993"/><ref name="Russell & Norvig 2003"/><ref name="NRC 1999"/><ref name="Howe 1994">{{cite web |first = J. |last = Howe |date= November 1994|title        = Artificial Intelligence at Edinburgh University: a Perspective |url = http://www.inf.ed.ac.uk/about/AIhistory.html archive-date = 15 May 2007 |archive-url  = https://web.archive.org/web/20070515072641/http://www.inf.ed.ac.uk/about/AIhistory.html |url-status= live}}</ref><ref name="Newquist 1994"/><ref name="McCorduck 2004"/>），每次又找到了新的出路，取得了新的成果和新的投资<ref name="Clark 2015b">{{cite web  |url = https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence |title = Why 2015 Was a Breakthrough Year in Artificial Intelligence |last = Clark |first= Jack |website = Bloomberg.com |url-access  = subscription  |url-status  = live |archive-url  = https://web.archive.org/web/20161123053855/https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence }}</ref>。AI 研究在其一生中尝试并放弃了许多不同的方法，包括模拟大脑、模拟人类问题解决、形式逻辑、大型知识数据库和模仿动物行为。在 21 世纪的头几十年，高度数学的统计机器学习已经主导了该领域，并且该技术已被证明非常成功，有助于解决整个工业界和学术界的许多具有挑战性的问题。<ref name="Russell & Norvig 2003"/><ref name="Kurzweil 2005"/><ref name="NRC 1999"/><ref name="Newquist 1994"/>

1956年AI作为一门学科被建立起来，后来经历过几段乐观时期<ref name="Simon 1965">Simon, H. A. (1965). The Shape of Automation for Men and Management. New York: Harper & Row.</ref><ref name="Crevier 1993"/><ref name="McCorduck 2004">McCorduck, Pamela (2004), Machines Who Think (2nd ed.), Natick, MA: A. K. Peters, Ltd., ISBN 1-56881-205-1</ref><ref name="Crevier 1993">Crevier, Daniel (1993), AI: The Tumultuous Search for Artificial Intelligence, New York, NY: BasicBooks, ISBN 0-465-02997-3</ref><ref name="Russell & Norvig 2003"/><ref name="NRC 1999">NRC (United States National Research Council) (1999). "Developments in Artificial Intelligence". Funding a Revolution: Government Support for Computing Research. National Academy Press.</ref><ref name="Newquist 1994">{{cite book | last=Newquist |first=HP |year=1994| title=The Brain Makers: Genius, Ego, And Greed In The Quest For Machines That Think| publisher=Macmillan/SAMS |location=New York| isbn= 978-0-672-30412-5}}</ref>与紧随而来的亏损以及缺乏资金的困境（也就是“AI寒冬”<ref name="Crevier 1993"/><ref name="Russell & Norvig 2003"/><ref name="NRC 1999"/><ref name="Howe 1994">{{cite web |first = J. |last = Howe |date= November 1994|title        = Artificial Intelligence at Edinburgh University: a Perspective |url = http://www.inf.ed.ac.uk/about/AIhistory.html |archive-url  = https://web.archive.org/web/20070515072641/http://www.inf.ed.ac.uk/about/AIhistory.html |url-status= live}}</ref><ref name="Newquist 1994"/><ref name="McCorduck 2004"/>），每次又找到了新的出路，取得了新的成果和新的投资<ref name="Clark 2015b">{{cite web  |url = https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence |title = Why 2015 Was a Breakthrough Year in Artificial Intelligence |last = Clark |first= Jack |website = Bloomberg.com |url-access  = subscription  |url-status  = live |archive-url  = https://web.archive.org/web/20161123053855/https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence }}</ref>。AI 研究在其一生中尝试并放弃了许多不同的方法，包括模拟大脑、模拟人类问题解决、形式逻辑、大型知识数据库和模仿动物行为。在 21 世纪的头几十年，高度数学的统计机器学习已经主导了该领域，并且该技术已被证明非常成功，有助于解决整个工业界和学术界的许多具有挑战性的问题。<ref name="Russell & Norvig 2003"/><ref name="Kurzweil 2005"/><ref name="NRC 1999"/><ref name="Newquist 1994"/>