Geoffrey Hinton

Geoffrey Hinton
Born
Geoffrey Everest Hinton

(1947-12-06) 6 December 1947 (age 76)[11]
Wimbledon, London, England
Education
Known for
Awards
Scientific career
Fields
Institutions
ThesisRelaxation and its role in vision (1977)
Doctoral advisorChristopher Longuet-Higgins[2][3][4]
Doctoral students
Other notable students
Websitewww.cs.toronto.edu/~hinton/ Edit this at Wikidata

Geoffrey Everest Hinton CC FRS FRSC[12] (born 6 December 1947) is a British-Canadian computer scientist and cognitive psychologist, most noted for his work on artificial neural networks. From 2013 to 2023, he divided his time working for Google (Google Brain) and the University of Toronto, before publicly announcing his departure from Google in May 2023, citing concerns about the risks of artificial intelligence (AI) technology.[13] In 2017, he co-founded and became the chief scientific advisor of the Vector Institute in Toronto.[14][15]

With David Rumelhart and Ronald J. Williams, Hinton was co-author of a highly cited paper published in 1986 that popularized the backpropagation algorithm for training multi-layer neural networks,[16] although they were not the first to propose the approach.[17] Hinton is viewed as a leading figure in the deep learning community.[18][19][20][21][22] The dramatic image-recognition milestone of the AlexNet designed in collaboration with his students Alex Krizhevsky[23] and Ilya Sutskever for the ImageNet challenge 2012[24] was a breakthrough in the field of computer vision.[25]

Hinton received the 2018 Turing Award, often referred to as the "Nobel Prize of Computing", together with Yoshua Bengio and Yann LeCun, for their work on deep learning.[26] They are sometimes referred to as the "Godfathers of Deep Learning",[27][28] and have continued to give public talks together.[29][30]

In May 2023, Hinton announced his resignation from Google to be able to "freely speak out about the risks of A.I."[31] He has voiced concerns about deliberate misuse by malicious actors, technological unemployment, and existential risk from artificial general intelligence.[32]

  1. ^ Cite error: The named reference googlescholar was invoked but never defined (see the help page).
  2. ^ Geoffrey Hinton at the Mathematics Genealogy Project
  3. ^ "Geoffrey E. Hinton's Academic Genealogy". Archived from the original on 23 March 2017. Retrieved 15 December 2013.
  4. ^ 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: 149–166. doi:10.1098/rsbm.2006.0012.
  5. ^ Zemel, Richard Stanley (1994). A minimum description length framework for unsupervised learning (PhD thesis). University of Toronto. OCLC 222081343. ProQuest 304161918.
  6. ^ Frey, Brendan John (1998). Bayesian networks for pattern classification, data compression, and channel coding (PhD thesis). University of Toronto. OCLC 46557340. ProQuest 304396112.
  7. ^ Neal, Radford (1995). Bayesian learning for neural networks (PhD thesis). University of Toronto. OCLC 46499792. ProQuest 304260778.
  8. ^ Whye Teh, Yee (2003). Bethe free energy and contrastive divergence approximations for undirected graphical models. utoronto.ca (PhD thesis). University of Toronto. hdl:1807/122253. OCLC 56683361. ProQuest 305242430. Archived from the original on 30 March 2023. Retrieved 30 March 2023.
  9. ^ Salakhutdinov, Ruslan (2009). Learning deep generative models (PhD thesis). University of Toronto. ISBN 978-0-494-61080-0. OCLC 785764071. ProQuest 577365583.
  10. ^ Sutskever, Ilya (2013). Training Recurrent Neural Networks. utoronto.ca (PhD thesis). University of Toronto. hdl:1807/36012. OCLC 889910425. ProQuest 1501655550. Archived from the original on 26 March 2023. Retrieved 30 March 2023.
  11. ^ Anon (2015) "Hinton, Prof. Geoffrey Everest". Who's Who (online Oxford University Press ed.). A & C Black. (Subscription or UK public library membership required.) doi:10.1093/ww/9780199540884.013.20261
  12. ^ Anon (1998). "Professor Geoffrey Hinton FRS". Royal Society. London. Archived from the original on 3 November 2015. 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". Archived from the original on 11 November 2016. Retrieved 9 March 2016.

  13. ^ Douglas Heaven, Will (1 May 2023). "Deep learning pioneer Geoffrey Hinton quits Google". MIT Technology Review. Archived from the original on 1 May 2023. Retrieved 1 May 2023.
  14. ^ Hernandez, Daniela (7 May 2013). "The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI". Wired. Archived from the original on 8 February 2014. Retrieved 10 May 2013.
  15. ^ "Geoffrey E. Hinton – Google AI". Google AI. Archived from the original on 9 November 2019. Retrieved 15 June 2018.
  16. ^ Cite error: The named reference backprop was invoked but never defined (see the help page).
  17. ^ Cite error: The named reference schmidhuber was invoked but never defined (see the help page).
  18. ^ Mannes, John (14 September 2017). "Geoffrey Hinton was briefly a Google intern in 2012 because of bureaucracy – TechCrunch". TechCrunch. Archived from the original on 17 March 2020. Retrieved 28 March 2018.
  19. ^ Somers, James (29 September 2017). "Progress in AI seems like it's accelerating, but here's why it could be plateauing". MIT Technology Review. Archived from the original on 20 May 2018. Retrieved 28 March 2018.
  20. ^ Sorensen, Chris (2 November 2017). "How U of T's 'godfather' of deep learning is reimagining AI". University of Toronto News. Archived from the original on 6 April 2019. Retrieved 28 March 2018.
  21. ^ Sorensen, Chris (3 November 2017). "'Godfather' of deep learning is reimagining AI". Phys.org. Archived from the original on 13 April 2019. Retrieved 28 March 2018.
  22. ^ Lee, Adrian (18 March 2016). "Geoffrey Hinton, the 'godfather' of deep learning, on AlphaGo". Maclean's. Archived from the original on 6 March 2020. Retrieved 28 March 2018.
  23. ^ Gershgorn, Dave (18 June 2018). "The inside story of how AI got good enough to dominate Silicon Valley". Quartz. Archived from the original on 12 December 2019. Retrieved 5 October 2018.
  24. ^ Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey E. (3 December 2012). "ImageNet classification with deep convolutional neural networks". In F. Pereira; C. J. C. Burges; L. Bottou; K. Q. Weinberger (eds.). NIPS'12: Proceedings of the 25th International Conference on Neural Information Processing Systems. Vol. 1. Curran Associates. pp. 1097–1105. Archived from the original on 20 December 2019. Retrieved 13 March 2018.
  25. ^ Allen, Kate (17 April 2015). "How a Toronto professor's research revolutionized artificial intelligence". Toronto Star. Archived from the original on 17 April 2015. Retrieved 13 March 2018.
  26. ^ Chung, Emily (27 March 2019). "Canadian researchers who taught AI to learn like humans win $1M award". Canadian Broadcasting Corporation. Archived from the original on 26 February 2020. Retrieved 27 March 2019.
  27. ^ Ranosa, Ted (29 March 2019). "Godfathers Of AI Win This Year's Turing Award And $1 Million". Tech Times. Archived from the original on 30 March 2019. Retrieved 5 November 2020.
  28. ^ Shead, Sam (27 March 2019). "The 3 'Godfathers' Of AI Have Won The Prestigious $1M Turing Prize". Forbes. Archived from the original on 14 April 2020. Retrieved 5 November 2020.
  29. ^ Ray, Tiernan (9 March 2021). "Nvidia's GTC will feature deep learning cabal of LeCun, Hinton, and Bengio". ZDNet. Archived from the original on 19 March 2021. Retrieved 7 April 2021.
  30. ^ "50 Years at CMU: The Inaugural Raj Reddy Artificial Intelligence Lecture". Carnegie Mellon University. 18 November 2020. Archived from the original on 2 March 2022. Retrieved 2 March 2022.
  31. ^ Cite error: The named reference :2 was invoked but never defined (see the help page).
  32. ^ ""Godfather of artificial intelligence" talks impact and potential of new AI". CBS News. 25 March 2023. Archived from the original on 28 March 2023. Retrieved 28 March 2023.

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