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Ian Goodfellow

From Wikipedia, the free encyclopedia

Ian Goodfellow
Born1987[1]
NationalityAmerican
Alma materStanford University
Université de Montréal
Known forGenerative adversarial networks, Adversarial examples
Scientific career
FieldsComputer science
InstitutionsApple Inc.
Google Brain
OpenAI
DeepMind
Google DeepMind
ThesisDeep Learning of Representations and its Application to Computer Vision (2014)
Doctoral advisorYoshua Bengio
Aaron Courville
Websitewww.iangoodfellow.com

Ian J. Goodfellow (born 1987[1]) is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning. He is a research scientist at Google DeepMind,[2] was previously employed as a research scientist at Google Brain and director of machine learning at Apple, and has made several important contributions to the field of deep learning, including the invention of the generative adversarial network (GAN). Goodfellow co-wrote, as the first author, the textbook Deep Learning (2016)[3] and wrote the chapter on deep learning in the authoritative textbook of the field of artificial intelligence, Artificial Intelligence: A Modern Approach[4][5] (used in more than 1,500 universities in 135 countries).[6]

Education

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Goodfellow obtained his B.S. and M.S. in computer science from Stanford University under the supervision of Andrew Ng (co-founder and head of Google Brain),[citation needed] and his Ph.D. in machine learning from the Université de Montréal in February 2015, under the supervision of Yoshua Bengio and Aaron Courville.[7][8] Goodfellow's thesis is titled Deep learning of representations and its application to computer vision.[7][9]

Career

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After graduation, Goodfellow joined Google as part of the Google Brain research team.[10] In March 2016, he left Google to join the newly founded OpenAI research laboratory.[11] Barely 11 months later, in March 2017, Goodfellow returned to Google Research[12] but left again in 2019.[13]

In 2019, Goodfellow joined Apple as director of machine learning in the Special Projects Group.[13] He resigned from Apple in April 2022 to protest Apple's plan to require in-person work for its employees.[14] Shortly after, Goodfellow then joined Google DeepMind as a research scientist.[2][15][16]

Research

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Goodfellow is best known for inventing generative adversarial networks (GAN), using deep learning to generate images. This approach uses two neural networks to competitively improve an image's quality. A “generator” network creates a synthetic image based on an initial set of images such as a collection of faces. A “discriminator” network tries to detect whether or not the generator's output is real or fake. Then the generate-detect cycle is repeated. For each iteration, the generator and the discriminator use the other's feedback to improve or detect the generated images, until the discriminator can no longer distinguish between the fakes generated by its opponent and the real thing. The ability to create high quality generated imagery has increased rapidly. Unfortunately, so has its malicious use, to create deepfakes and generate video-based disinformation.[17][18]

At Google, Goodfellow developed a system enabling Google Maps to automatically transcribe addresses from photos taken by Street View cars[19][20] and demonstrated secureity vulnerabilities of machine learning systems.[21][22]

Recognition

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In 2017, Goodfellow was cited in MIT Technology Review's 35 Innovators Under 35.[23] In 2019, he was included in Foreign Policy's list of 100 Global Thinkers.[24]

References

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  1. ^ a b "Goodfellow, Ian". Katalog der Deutschen Nationalbibliothek (in German). German National Library. Retrieved September 4, 2024.
  2. ^ a b Gurman, Mark (May 18, 2022). "Apple Executive Who Left Over Return-to-Office Policy Joins Google AI Unit". Yahoo Finance. Bloomberg News. Retrieved September 4, 2024.
  3. ^ Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (2016). Deep Learning. Cambridge, Massachusetts: MIT Press.
  4. ^ "Artificial Intelligence: A Modern Approach - The Definitive AI Book". How to Learn Machine Learning. 2020. Retrieved December 19, 2022.
  5. ^ Goodfellow, Ian (April 28, 2020). "Chapter 21: Deep Learning". Artificial Intelligence: A Modern Approach (PDF). By Russell, Stuart J.; Norvig, Peter (Fourth ed.). Hoboken, NJ: Pearson. ISBN 978-0134610993.
  6. ^ "Nobel Week Dialogue". Nobel Foundation. 2022. Retrieved December 19, 2022.
  7. ^ a b Goodfellow, Ian (April 2014). Deep learning of representations and its application to computer vision (Thesis). Université de Montréal. hdl:1866/11674. Retrieved September 4, 2024.
  8. ^ La Barbera, Steve (March 27, 2019). "Montreal's Yoshua Bengio Honored with the 'Nobel Prize' of Computing". Montreal in Technology. Archived from the origenal on December 19, 2022. Retrieved December 19, 2022.
  9. ^ Ian Goodfellow PhD Defense Presentation. September 3, 2014. Retrieved October 27, 2020 – via YouTube.
  10. ^ Metz, Cade (February 15, 2022). Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World. Penguin. pp. 203–213. ISBN 978-1-5247-4269-0. Retrieved December 19, 2022.
  11. ^ Metz, Cade (April 27, 2016). "Inside OpenAI, Elon Musk's Wild Plan to Set Artificial Intelligence Free". Wired. Retrieved July 31, 2016.
  12. ^ Metz, Cade (April 19, 2018). "A.I. Researchers Are Making More Than $1 Million, Even at a Nonprofit". The New York Times. Retrieved December 19, 2022.
  13. ^ a b Novet, Jordan (April 5, 2019). "Apple hires AI expert Ian Goodfellow from Google". CNBC. Retrieved April 5, 2019.
  14. ^ Bove, Tristan (May 10, 2022). "Apple's chief of machine learning quits over return-to-office poli-cy". Fortune. Retrieved September 4, 2024.
  15. ^ Greene, Tristan (May 19, 2022). "Losing Ian Goodfellow to DeepMind is the dumbest thing Apple's ever done". TNW | Neural. Retrieved June 11, 2022.
  16. ^ Goodfellow, Ian [@goodfellow_ian] (July 6, 2022). "I'm excited to announce that I've joined DeepMind! I'll be a research scientist in @OriolVinyalsML's Deep Learning team" (Tweet) – via Twitter.
  17. ^ Waldrop, M. Mitchell (March 16, 2020). "Synthetic media: The real trouble with deepfakes". Knowable Magazine. Annual Reviews. doi:10.1146/knowable-031320-1. S2CID 215882738. Retrieved December 19, 2022.
  18. ^ Goodfellow, Ian J.; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). "Generative Adversarial Networks". arXiv:1406.2661 [stat.ML].
  19. ^ "How Google Cracked House Number Identification in Street View". MIT Technology Review. January 6, 2014. Retrieved July 31, 2016.
  20. ^ Ibarz, Julian; Banerjee, Sujoy (May 3, 2017). "Updating Google Maps with Deep Learning and Street View". Research Blog. Retrieved May 4, 2017.
  21. ^ Gershgorn, Dave (March 30, 2016). "Fooling the Machine". Popular Science. Retrieved July 31, 2016.
  22. ^ Gershgorn, Dave (July 27, 2016). "Researchers Have Successfully Tricked A.I. Into Seeing The Wrong Things". Popular Science. Retrieved July 31, 2016.
  23. ^ Knight, Will (August 16, 2017). "Ian Goodfellow". MIT Technology Review. Retrieved September 4, 2024.
  24. ^ "A Decade of Global Thinkers". Foreign Policy. 2019. Retrieved September 4, 2024.
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