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Quoc V. Le

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Quoc V. Le
Born
Lê Viết Quốc

1982 (age 41–42)
Hương Thủy, Thừa Thiên Huế, Vietnam
EducationAustralian National University
Stanford University
Known forseq2seq
doc2vec
Neural architecture search
Google Neural Machine Translation
Scientific career
FieldsMachine learning
InstitutionsGoogle Brain
Thesis Scalable feature learning  (2013)
Doctoral advisorAndrew Ng
Other academic advisorsAlex Smola

Lê Viết Quốc (born 1982),[1] or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec[2] and seq2seq[3] models in natural language processing. Le also initiated and lead the AutoML initiative at Google Brain, including the proposal of neural architecture search.[4][5][6][7]

Education and career

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Le was born in Hương Thủy in the Thừa Thiên Huế province of Vietnam.[5] He attended Quốc Học Huế High School[8] before moving to Australia in 2004 to pursue a Bachelor’s degree at the Australian National University. During his undergraduate studies, he worked with Alex Smola on Kernel method in machine learning.[9] In 2007, Le moved to the United States to pursue graduate studies in computer science at Stanford University, where his PhD advisor was Andrew Ng.

In 2011, Le became a founding member of Google Brain along with his then advisor Andrew Ng, Google Fellow Jeff Dean, and researcher Greg Corrado.[5] He led Google Brain’s first major breakthrough: a deep learning algorithm trained on 16,000 CPU cores, which learned to recognize cats by watching YouTube videos—without being explicitly taught the concept of a "cat."[10][11]

In 2014, Le co-proposed two influential models in machine learning. Together with Ilya Sutskever, Oriol Vinyals, he introduced the seq2seq model for machine translation, a foundational technique in natural language processing. In the same year, in collaboration with Tomáš Mikolov, Le developed the doc2vec model for representation learning of documents. Le was also a key contributor of Google Neural Machine Translation system.[12]

In 2017, Le initiated and led the AutoML project at Google Brain, pioneering the use of neural architecture search.[13] This project significantly advanced automated machine learning.

In 2020, Le contributed to the development of Meena, later renamed LaMDA, a conversational large language model based on the seq2seq architecture.[14] In 2022, Le and coauthors published chain-of-thought prompting, a method that enhances the reasoning capabilities of large language models.[15]

Honors and awards

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Le was named MIT Technology Review's innovators under 35 in 2014.[16] He has been interviewed by and his research has been reported in major media outlets including Wired,[6] the New York Times,[17] the Atlantic,[18] and the MIT Technology Review.[19] Le was named an Alumni Laureate of the Australian National University School of Computing in 2022.[20]

See also

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References

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  1. ^ "'Quái kiệt' AI Lê Viết Quốc - người đứng sau thuật toán Transformers của ChatGPT". Viettimes - tin tức và phân tích chuyên sâu kinh tế, quốc tế, y tế (in Vietnamese). 2023-02-09. Retrieved 2023-07-03.
  2. ^ Le, Quoc V.; Mikolov, Tomas (2014-05-22). "Distributed Representations of Sentences and Documents". arXiv:1405.4053 [cs.CL].
  3. ^ Sutskever, Ilya; Vinyals, Oriol; Le, Quoc V. (2014-12-14). "Sequence to Sequence Learning with Neural Networks". arXiv:1409.3215 [cs.CL].
  4. ^ Zoph, Barret; Le, Quoc V. (2017-02-15). "Neural Architecture Search with Reinforcement Learning". arXiv:1611.01578 [cs.LG].
  5. ^ a b c "Le Viet Quoc, a young Vietnamese engineer who holds Google's brain". tipsmake.com. 24 May 2019. Retrieved 2022-11-24.
  6. ^ a b Hernandez, Daniela. "A Googler's Quest to Teach Machines How to Understand Emotions". Wired. ISSN 1059-1028. Retrieved 2022-11-25.
  7. ^ Chow, Rony (2021-06-07). "Quoc V. Le: Fast, Furious and Automatic". History of Data Science. Retrieved 2022-11-26.
  8. ^ "Fulbright scholars Vietnam - Le Viet Quoc".
  9. ^ "Meet Le Viet Quoc, a Vietnamese talent at Google". Tuoi Tre News. 2019-02-15. Retrieved 2022-11-25.
  10. ^ Markoff, John (June 25, 2012). "How Many Computers to Identify a Cat? 16,000". The New York Times.
  11. ^ Ng, Andrew; Dean, Jeff (2012). "Building High-level Features Using Large Scale Unsupervised Learning". arXiv:1112.6209 [cs.LG].
  12. ^ "A Neural Network for Machine Translation, at Production Scale". Google Research Blog. 2016-09-27. Retrieved 2023-07-02.
  13. ^ Zoph, Barret; Le, Quoc V. (2017-02-15). "Neural Architecture Search with Reinforcement Learning". arXiv:1611.01578 [cs.LG].
  14. ^ Adiwardana, Daniel; Luong, Minh-Thang; So, David R.; Hall, Jamie; Fiedel, Noah; Thoppilan, Romal; Yang, Zi; Kulshreshtha, Apoorv; Nemade, Gaurav; Lu, Yifeng; Le, Quoc V. (2020-01-31). "Towards a Human-like Open-Domain Chatbot". arXiv:2001.09977 [cs.CL].
  15. ^ "Language Models Perform Reasoning via Chain of Thought". Google Research Blog. 2022-05-22. Retrieved 2023-07-02.
  16. ^ "Quoc Le". MIT Technology Review. Retrieved 2022-11-24.
  17. ^ Lewis-Kraus, Gideon (2016-12-14). "The Great A.I. Awakening". The New York Times. ISSN 0362-4331. Retrieved 2022-11-26.
  18. ^ Madrigal, Alexis C. (2012-06-26). "The Triumph of Artificial Intelligence! 16,000 Processors Can Identify a Cat in a YouTube Video Sometimes". The Atlantic. Retrieved 2022-11-26.
  19. ^ "AI's Language Problem". MIT Technology Review. Retrieved 2022-11-26.
  20. ^ "Celebrating 50 years of teaching computer science at ANU". ANU College of Engineering, Computing and Cybernetics. Retrieved 2023-07-02.
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