Editing History of software engineering (section)

=== Artificial intelligence ===
A wide variety of platforms has allowed different aspects of AI to develop, ranging from [[expert systems]] such as [[Cyc]] to [[deep learning]] to robot platforms such as the [[Roomba]] with open interface.<ref>{{cite web|url=http://hackingroomba.com/|title=Hacking Roomba|work=hackingroomba.com|url-status=live|archive-url=https://web.archive.org/web/20091018023300/http://hackingroomba.com/|archive-date=18 October 2009|df=dmy-all}}</ref> Recent advances in deep [[artificial neural network]]s and distributed computing have led to a proliferation of software libraries, including [[Deeplearning4j]], [[TensorFlow]], [[Theano (software)|Theano]] and [[Torch (machine learning)|Torch]].

A 2011 [[McKinsey & Company|McKinsey Global Institute]] study found a shortage of 1.5 million highly trained data and AI professionals and managers<ref name="McKinsey">{{cite journal |last1=Manyika |first1=James |first2=Michael |last2=Chui |first3=Jaques |last3=Bughin |first4=Brad |last4=Brown |first5=Richard |last5=Dobbs |first6=Charles |last6=Roxburgh |first7=Angela Hung |last7=Byers |title=Big Data: The next frontier for innovation, competition, and productivity |publisher=McKinsey Global Institute |date=May 2011 |url=http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation |access-date=16 January 2016 |url-status=live |archive-url=https://web.archive.org/web/20130306232114/http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation |archive-date=6 March 2013 |df=dmy-all }}</ref> and a number of private bootcamps have developed programs to meet that demand, including free programs like [[The Data Incubator]] or paid programs like [[General Assembly]].<ref>{{cite news
 |title       = NY gets new boot camp for data scientists: It's free but harder to get into than Harvard
 |newspaper   = Venture Beat
 |access-date = 21 February 2016
 |url         = https://venturebeat.com/2014/04/15/ny-gets-new-bootcamp-for-data-scientists-its-free-but-harder-to-get-into-than-harvard/
 |url-status     = live
 |archive-url  = https://web.archive.org/web/20160215235820/http://venturebeat.com/2014/04/15/ny-gets-new-bootcamp-for-data-scientists-its-free-but-harder-to-get-into-than-harvard/
 |archive-date = 15 February 2016
 |df          = dmy-all
}}</ref>

==== Languages ====
{{Main|List of programming languages for artificial intelligence}}
Early symbolic AI inspired [[Lisp (programming language)|Lisp]] and [[Prolog]], which dominated early AI programming. Modern AI development often uses mainstream languages such as [[Python (programming language)|Python]] or [[C++]],<ref name="C++">{{cite web|title=C++ Java|work=InfoWorld |url=https://www.infoworld.com/article/3186599/artificial-intelligence/the-5-best-programming-languages-for-ai-development.html|publisher=infoworld.com|access-date=6 December 2017 |last1=Pointer |first1=Ian }}</ref> or niche languages such as [[Wolfram Language]].<ref>{{cite news|last1=Ferris|first1=Robert|title=How Steve Jobs' friend changed the world of math|url=https://www.cnbc.com/2016/04/07/stephen-wolfram-why-this-brilliant-physicist-ditched-his-job.html|access-date=28 February 2018|work=CNBC|date=7 April 2016}}</ref>