Geoffrey Everest Hinton FRS (born 6 December 1947) is a British-born Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks. As of 2015[update] he divides his time working for Google and University of Toronto. He was one of the first researchers who demonstrated the use of generalized backpropagation algorithm for training multi-layer neural nets and is an important figure in the deep learning community.
Hinton was educated at King's College, Cambridge graduating in 1970, with a Bachelor of Arts in experimental psychology. He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by Christopher Longuet-Higgins.
After his PhD he worked at the University of Sussex, the University of California, San Diego, Carnegie Mellon University. He was the founding director of the Gatsby Charitable Foundation Computational Neuroscience Unit at University College London, and is currently[when?] a professor in the computer science department at the University of Toronto. He holds a Canada Research Chair in Machine Learning. He is the director of the program on "Neural Computation and Adaptive Perception" which is funded by the Canadian Institute for Advanced Research. Hinton taught a free online course on Neural Networks on the education platform Coursera in 2012. Hinton joined Google in March 2013 when his company, DNNresearch Inc, was acquired. He is planning to "divide his time between his university research and his work at Google".
Hinton's research investigates ways of using neural networks for machine learning, memory, perception and symbol processing. He has authored or co-authored over 200 peer reviewed publications in these areas. He was one of the first researchers who demonstrated the use of generalized back-propagation algorithm for training multi-layer neural networks that has been widely used for practical applications. He co-invented Boltzmann machines with Terry Sejnowski. His other contributions to neural network research include distributed representations, time delay neural network, mixtures of experts, Helmholtz machines and Product of Experts. In 2007 Hinton coauthored an unsupervised learning paper titled "Unsupervised learning of image transformations". An accessible introduction to Geoffrey Hinton's research can be found in his articles in Scientific American in September 1992 and October 1993.
Notable former PhD students and postdoctoral researchers from his group include Richard Zemel, Brendan Frey, Radford M. Neal, Ruslan Salakhutdinov, Ilya Sutskever, Yann LeCun and Zoubin Ghahramani.
Honours and awards
|“||Geoffrey E. Hinton is internationally distinguished for his work on artificial neural nets, especially how they can be designed to learn without the aid of a human teacher. This may well be the start of autonomous intelligent brain-like machines. He has compared effects of brain damage with effects of losses in such a net, and found striking similarities with human impairment, such as for recognition of names and losses of categorization. His work includes studies of mental imagery, and inventing puzzles for testing originality and creative intelligence. It is conceptual, mathematically sophisticated and experimental. He brings these skills together with striking effect to produce important work of great interest.||”|
In 2001, Hinton was awarded an Honorary Doctorate from the University of Edinburgh. Hinton was the 2005 recipient of the IJCAI Award for Research Excellence lifetime-achievement award. He has also been awarded the 2011 Herzberg Canada Gold Medal for Science and Engineering. In 2013, Hinton was awarded an Honorary Doctorate from the Université de Sherbrooke.
In 2016, he was elected a foreign member of National Academy of Engineering "For contributions to the theory and practice of artificial neural networks and their application to speech recognition and computer vision". He also received the 2016 IEEE/RSE Wolfson James Clerk Maxwell Award.
He has won the BBVA Foundation Frontiers of Knowledge Award (2016) in the Information and Communication Technologies category “for his pioneering and highly influential work” to endow machines with the ability to learn.
Hinton is the great-great-grandson both of logician George Boole whose work eventually became one of the foundations of modern computer science, and of surgeon and author James Hinton. His father is Howard Hinton.
- HINTON, Prof. Geoffrey Everest. ukwhoswho.com. Who's Who. 2015 (online Oxford University Press ed.). A & C Black, an imprint of Bloomsbury Publishing plc. (subscription required)
- Geoffrey Hinton publications indexed by Google Scholar
- Geoffrey Hinton at the Mathematics Genealogy Project
- Geoffrey E. Hinton's Academic Genealogy
- Gregory, R. L.; Murrell, J. N. (2006). "Hugh Christopher Longuet-Higgins. 11 April 1923 -- 27 March 2004: Elected FRS 1958". Biographical Memoirs of Fellows of the Royal Society. 52: 149. doi:10.1098/rsbm.2006.0012.
- Derthick, Mark (1988). Mundane reasoning by parallel constraint satisfaction. proquest.com (PhD thesis). Carnegie Mellon University. OCLC 243445686.
- Zemel, Richard Stanley (1994). A minimum description length framework for unsupervised learning. proquest.com (PhD thesis). University of Toronto. OCLC 222081343.
- Frey, Brendan John (1998). Bayesian networks for pattern classification, data compression, and channel coding. proquest.com (PhD thesis). University of Toronto. OCLC 46557340.
- Neal, Radford (1995). Bayesian learning for neural networks. proquest.com (PhD thesis). University of Toronto. OCLC 46499792.
- Salakhutdinov, Ruslan (2009). Learning deep generative models. proquest.com (PhD thesis). University of Toronto. ISBN 9780494610800. OCLC 785764071.
- Sutskever, Ilya (2013). Training Recurrent Neural Networks. proquest.com (PhD thesis). University of Toronto. OCLC 889910425.
- Anon (1998). "Professor Geoffrey Hinton FRS". London: Royal Society. Archived from the original on 2015-11-03. One or more of the preceding sentences incorporates text from the royalsociety.org website where:
“All text published under the heading 'Biography' on Fellow profile pages is available under Creative Commons Attribution 4.0 International License.” --Royal Society Terms, conditions and policies at the Wayback Machine (archived 2016-11-11)
- Daniela Hernandez (7 May 2013). "The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI". Wired. Retrieved 10 May 2013.
- "How a Toronto professor’s research revolutionized artificial intelligence". Toronto Star, Kate Allen, Apr 17 2015
- on YouTube
- AMA Geoffrey Hinton (self.MachineLearning) www.reddit.com Ask Me Anything : Geoffrey Hinton
- Hinton, Geoffrey Everest (1977). Relaxation and its role in vision. ethos.bl.uk (PhD thesis). University of Edinburgh. hdl:1842/8121. OCLC 18656113.
- "U of T neural networks start-up acquired by Google" (Press release). Toronto, ON. 12 March 2013. Retrieved 13 March 2013.
- Geoffrey Hinton's publications indexed by the Scopus bibliographic database, a service provided by Elsevier. (subscription required)
- Hinton, Geoffrey E. "Geoffrey E. Hinton's Publications in Reverse Chronological Order".
- "Current and Previous Recipients". David E. Rumelhart Prize.
- Anon (1998). "Certificate of election EC/1998/21: Geoffrey Everest Hinton". London: Royal Society. Archived from the original on 2015-11-05.
- "Artificial intelligence scientist gets M prize". CBC News. 14 February 2011.
- "National Academy of Engineering Elects 80 Members and 22 Foreign Members". NAE. 8 February 2016.
- "2016 IEEE Medals and Recognitions Recipients and Citations" (PDF). IEEE. Retrieved July 7, 2016.
- The Isaac Newton of logic
- Salt, George (1978). "Howard Everest Hinton. 24 August 1912-2 August 1977". Biographical Memoirs of Fellows of the Royal Society. 24 (0): 150–182. doi:10.1098/rsbm.1978.0006. ISSN 0080-4606.