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Andrew Yan-Tak Ng (Chinese: 吳恩達; born April 18, 1976 [2]) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). [3] Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu , building the company's Artificial Intelligence Group ...
Coursera Inc. (/ k ər ˈ s ɛ r ə /) is an American global massive open online course provider. It was founded in 2012 [2] [3] by Stanford University computer science professors Andrew Ng and Daphne Koller. [4] Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.
The Google Brain project began in 2011 as a part-time research collaboration between Google fellow Jeff Dean and Google Researcher Greg Corrado. [3] Google Brain started as a Google X project and became so successful that it was graduated back to Google: Astro Teller has said that Google Brain paid for the entire cost of Google X.
Geoffrey Everest Hinton (born 6 December 1947) is a British-Canadian computer scientist, cognitive scientist, cognitive psychologist, and Nobel Prize winner in Physics, known for his work on artificial neural networks which earned him the title as the "Godfather of AI".
In 2012, Sutskever spent about two months as a postdoc with Andrew Ng at Stanford University. He then returned to the University of Toronto and joined Hinton's new research company DNNResearch, a spinoff of Hinton's research group. In 2013, Google acquired DNNResearch and hired Sutskever as a research scientist at Google Brain. [25]
President Donald Trump told the New York Post he ordered the revocation of security clearances to officials he's sparred with in court.
Daphne Koller (Hebrew: דפנה קולר; born August 27, 1968) is an Israeli-American computer scientist. She was a professor in the department of computer science at Stanford University [4] and a MacArthur Foundation fellowship recipient. [1]
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal.