Yann LeCun

June 26, 2025 DE Curators
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Bloomberg | Credit: Bloomberg via Getty Images

Summary

Yann André Le Cun is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University and Vice President, Chief AI Scientist at Meta.

He is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNNs). He is also one of the main creators of the DjVu image compression technology (together with Léon Bottou and Patrick Haffner). He co-developed the Lush programming language with Léon Bottou.

In 2018, LeCun, Yoshua Bengio, and Geoffrey Hinton, received the Turing Award for their work on deep learning. The three are sometimes referred to as the “Godfathers of AI” and “Godfathers of Deep Learning”.

Source: Wikipedia

Frontiers of AI and Computing: A Conversation With Yann LeCun and Bill Dally | NVIDIA GTC 2025
NVIDIA Developer – 10/04/2025 (53:14)

https://www.youtube.com/watch?v=eyrDM3A_YFc

As artificial intelligence continues to reshape the world, the intersection of deep learning and high performance computing becomes increasingly crucial. This talk brings together Yann LeCun, a pioneer in deep learning and the chief AI scientist at Meta, and Bill Dally, a leading computer architect and chief scientist at NVIDIA, to explore the future of AI models, hardware accelerators, and the evolving computational landscape.

The discussion covers:

  • The next breakthroughs in deep learning and AI architectures
  • How hardware innovation drives AI efficiency and scalability
  • Challenges in training large-scale models and real-time AI inference

Speakers:

  • Bill Dally, Chief Scientist and SVP of Research, NVIDIA
  • Yann LeCun, Chief AI Scientist at Meta, Professor at New York Universit

OnAir Post: Yann LeCun

News

The Academy Recognizes Yann LeCun for Advancing AI
New York Academy of Sciences, Nick Fetty – May 1, 2025

Yann LeCun, VP and Chief AI Scientist at Meta, was one of three Honorees recently recognized by The New York Academy of Sciences (the Academy) for outstanding contributions to science.

Yann LeCun was recently recognized by The New York Academy of Sciences, for his pioneering work in machine learning, computer vision, mobile robotics, and computational neuroscience. He was presented with the Academy’s inaugural Trailblazer Award during the 2025 Spring Soirée, hosted at the University Club of New York.

“His work has been instrumental in setting the terms of how we think about the uses, implications, and impact of AI in all its forms,” said Nick Dirks, President and CEO of the Academy, while introducing LeCun during the Soirée. “Yann, we’re grateful that your view has carried the day and are inspired by the boldness of your vision. A vision that has shaped the evolution of this amazing and transformative technology.”

LeCun, a Turing Laureate, who also serves as the Jacob T. Schwartz Professor of Computer Science for the Courant Institute of Mathematical Sciences at New York University, has been called everything from a “pioneer” to a “godfather” within the field of AI. His connection with the Academy dates back several years when he and Manuela Veloso, Head of AI Research at J.P. Morgan, “agreed to serve as honorary chairs for the launch of a new initiative on applications of AI to critical sectors of the New York City economy.”

 

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About

Publications, Talks, Courses, and Videos

Main Research Interests:
AI, Machine Learning, Computer Vision, Robotics, and Computational Neuroscience. I am also interested Physics of Computation, and many applications of machine learning.

Publications:
Google Scholar
Papers on OpenReview.net
Preprints on ArXiv
Publications up to 2014 with PDF and DjVu

Talks / Slide Decks:
Slides of (most of) my talks

Deep Learning Course:
Deep Learning course at NYU:
Complete course on Deep Learning, with all the material available on line including lectures and practicums, videos, slide decks, homeworks, Jupyter notebooks, and transcripts in several languages.

Videos: Playlists on YouTube:

Talks on VideoLectures: (from 2007 to 2016).

Source: Personal Website

Working Paper

A Path Towards Autonomous Machine Intelligence

(June 2022)

How could machines learn as efficiently as humans and animals? How could machines learn to reason and plan? How could machines learn representations of percepts and action plans at multiple levels of abstraction, enabling them to reason, predict, and plan at multiple time horizons? This position paper proposes an architecture and training paradigms with which to construct autonomous intelligent agents. It combines concepts such as configurable predictive world model, behavior driven through intrinsic motivation, and hierarchical joint embedding architectures trained with self-supervised learning.

Recent lectures on the topic:

  • 2025-04-27: “Shaping the Future of AI”
    Distinguished Lecture at National University of Singapore University.
    Video on YouTube
    Slide deck
  • 2024-10-18: “How could machines reach human-level intelligence?”
    Distinguished Lecture at Columbia University
    Video on Youtube
    Slide deck

Source: Personal Website

Books

Quand La Machine Apprend

La revolution des neurones artificiels et de l’apprentissage profond (Editions Odile Jacob, Octobre 2019)
Exists in Chinese, Japanese, and Russian.

La Plus Belle Histoire de l’Intelligence

Des origines aux neurones artificiels : vers une nouvelle étape de l’évolution
Stanislas Dehaene, Yann Le Cun, Jacques Girardon (Éditions Robert Laffont, Octobre 2018)

Source: Personal Website

Pamphlets and Opinions

How to Build a Vibrant Technology Industry (by attracting scientists to your country) (2025-05-30)

As the US seems set on self-sabotaging its extraordinarily successful system of public research funding, countries in Europe and elsewhere may want to seize the opportunity to reboot their own research ecosystem and jumpstart their technology industry.

Five Ways to Act Deluded, Stupid, Ineffective, or Evil (2025-04-28)

Using ideas from AI researach to explain the failure modes of human behavior, with examples from international trade policy.
Comments on LinkedIn, Threads, Facebook

AI and the Future of Europe, a Defining Moment (2025-02-09)

by Bernhard Schölkopf, Nuria Oliver, and Yann LeCun.

In which we argue that funding from the newly-formed European AI Research Council should go to small groups of talented researchers and not be administered as a large project managed from the top down.

This opinion piece was published in January 2025 simultaneously in Les Échos, Handelsbaltt, and El Pais.

Address to the UN Security Council (2024-12-19)

I was invited by Secretary of State Antony Blinken to speak about AI at the UN Security Council meeting on 2024-12-19. I was followed by Fei-Fei Li, and representatives from UNSC member states.

In my speech, I argued for free/open source foundation models and for international cooperation to train “universal” foundation models that speak all the languages in the world and understand all cultures and value systems.

My speech starts at the 00:12:20 mark in this video

Proposal for a new publishing model in Computer Science (2009-12-01)

Many computer Science researchers are complaining that our emphasis on highly selective conference publications, and our double-blind reviewing system stifles innovation and slow the rate of progress of Science and technology.

This pamphlet proposes a new publishing model based on an open repository and open (but anonymous) reviews which creates a “market” between papers and reviewing entities.

Source: Personal Website

Students and Postdocs

Current PhD Students

Current Postdocs

Former PhD Students

  • Vlad Sobal (2025, NYU CDS) [SSL for planning and control], Amazon
  • Quentin Garrido (2025, FAIR-Université Gustave Eiffel with Laurent Najman) [SSL for images and video] FAIR-Paris.
  • Alexander Rives (2024 NYU CS) [Protein design] FAIR, CEO Evolutionary Scale, MIT EECS & Broad Institute.
  • Katrina Drozdov Evtimova (2024 NYU CDS) [latent variable JEPA]
  • Adrien Bardes (2024 FAIR-INRIA with Jean Ponce) [SSL, VICReg, I-JEPA, V-JEPA]. FAIR
  • Zeming Lin (2023 NYU CS) [Transformers for protein structure]. FAIR, EvolutionaryScale AI
  • Aishwarya Kamath (2023 NYU CDS) [vision-language models] DeepMind
  • Junbo “Jake” Zhao (2019 NYU CS) [energy-based models] faculty Zhejiang University
  • Xiang Zhang (2018 NYU CS) [deep learning for NLP] Element AI, Google AI, startup
  • Mikael Henaff (2018 NYU CS) [deep learning for control] Microsoft Research, FAIR
  • Remi Denton (2018 NYU CS, with Rob Fergus)
  • Sainbayar Sukhbaatar (2018, NYU CS with Rob Fergus) [memory, intrinsic motivation, multiagent communication] FAIR
  • Michael Mathieu (2017 NYU CS) [DL for video prediction and image understanding] DeepMind
  • Jure Zbontar (2016 U. of Ljubljana, co-advised) [DL for stereo vision] NYU, FAIR, OpenAI
  • Sixin Zhang (2016 NYU CS) [paralellized deep learning] ENS-Paris, faculty Institut National Polytechnique de Toulouse
  • Wojciech Zaremba (2016 NYU CS with Rob Fergus) [algorithm synthesis] OpenAI
  • Rotislav Goroshin (2015 NYU CS) [unsupervised representation learning] DeepMind
  • Pierre Sermanet (2014 NYU CS) [DL for vision and mobile robot perception] Google Brain, DeepMind
  • Clément Farabet (2014 U. Gustave Eiffel with Laurent Najman) [dedicated hardware for ConvNets, vision, Torch-7] Twitter, Nvidia, VP of Research DeepMind
  • Fu Jie Huang (2013 NYU CS) [DL for vision] Milabra, Kanerai
  • Kevin Jarrett (2012 NYU Neural Science) [DL models of biological vision] Bridgewater,…,Barclays
  • Matthew Grimes (2012 NYU) [SLAM] Cambridge, DeepMind
  • Y-Lan Boureau (2012, NYU-INRIA with Jean Ponce) [sparse feature learning for vision] Flatiron Institute, FAIR, CEO ThrivePal)
  • Koray Kavukcuoglu (2010, NYU) [sparse auto-encoders for unsupervised feature learning] NEC Labs, VP of GenAI DeepMind
  • Piotr Mirowski (2010 NYU) Bell Labs, Microsoft, DeepMind
  • Ayse Naz Erkan (2010 NYU, with Yasemine Altun) Twitter, Robinhood, CEO Laminar AI.
  • Marc’Aurelio Ranzato (2009 NYU) Google X-Labs, FAIR, DeepMind.
  • Sumit Chopra (2008 NYU) AT&T Labs-Research, FAIR, Imagen, faculty NYU.
  • Raia Hadsell (2008 NYU) SRI, VP Foundations DeepMind
  • Feng Ning (2006 NYU) Bank of America, Société Générale, ScotiaBank, AQR Capital, VP AllianceBernstein.

Former Postdocs

  • Micah Goldblum (NYU 2021-2024), Columbia University
  • Grégoire Mialon (FAIR 2021-2023), Meta-GenAI
  • Randall Balestriero (FAIR 2021-2023), Brown University
  • Nicolas Carion (NYU 2020-2022), FAIR
  • Yubei Chen (FAIR 2020-2022), UC Davis
  • Li Jing (FAIR 2019-2021), OpenAI
  • Jacob Browning (NYU 2019-2023): philosophy and history of AI (Berggruen Transformation of the Human program)
  • Phillip Schmitt (NYU 2019-2021): AI and the visual arts (Berggruen Transformation of the Human program)
  • Stéphane Deny (FAIR 2019-2021), U of Aalto
  • Alfredo Canziani (NYU 2017-2022), NYU: autonomous driving, AI education
  • Behnam Neyshabur (NYU 20172019), Google, DeepMind: deep learning landscape, self-supervised learning
  • Jure Zbontar (NYU 2016-2017). FAIR, OpenAI: temporal prediction
  • Anna Choromanska (NYU 2014-2017) NYU Tandon: applied mathematics
  • Pablo Sprechmann (NYU 2014-2017), DeepMind: applied mathematics and signal processing
  • Joan Bruna (NYU 2012-2014), FAIR, UC Berkeley, NYU: applied mathematics
  • Camille Couprie (NYU 2011-2013), FAIR: computer vision
  • Tom Schaul (NYU 2011-2013), DeepMind: machine learning and optimization
  • Jason Rolfe (NYU 2011-2013), D-Wave, Variational AI: computational neuroscience
  • Leo Zhu (NYU 2010-2011), CEO Yitu: hierarchical vision models.
  • Arthur Szlam (NYU 2009-2011), CUNY, FAIR, DeepMind: applied mathematics.
  • Karol Gregor (NYU 2008-2011), Janelia Farm, DeepMind: machine learning.
  • Trivikraman Thampy (NYU 2008-2009), CEO Play Games24x7: financial modeling and prediction.
  • Joseph Turian (NYU 2007-2007), Founder MetaOptimize: energy-based models.
  • Margarita Osadchy (NEC Labs 2002-2003), University of Haifa: energy-based models, face detection with ConvNets.
  • Yoshua Bengio (AT&T Bell Labs 1992-1993), MILA – Université de Montréal.
  • Patrice Simard (AT&T Bell Labs 1991-1992), AT&T Labs, Microsoft Research.

Source: Personal Website

Honors and Awards

  • Inaugural Trailblazer Award, the New York Academy of Sciences, 2025, [link]
  • Queen Elizabeth Prize for Engineering, 2025 (shared with Yoshua Bengio, Geoffrey Hinton, John Hopfield (Foundations), Bill Dally, Jensen Huang (Hardware), Fei-Fei Li (Data). [link]
  • AMS Josiah Willard Gibbs Lecturer, JMM Seattle, 2025, [link]
  • VinFuture Grand Prize, 2024 (shared with Yoshua Bengio, Geoff Hinton, Jensen Huang, Fei-Fei Li), [link], [acceptance speech], [pictures]
  • Trailblazer in Science Award, New York Hall of Science, 2024, [link]
  • Doctorate Honoris Causa, Université de Genève, 2024, [link], [lecture]
  • Professor Honoris Causa, ESIEE / Université Gustave Eiffel, 2024, [link]
  • Lifetime Honorary Membership, New York Academy of Sciences, 2024, [link]
  • Fellow Association for Computing Machinery, 2024, [link]
  • Great Immigrant, Carnegie Corporation of New York, 2024, [link]
  • TIME 100 Impact Award, 2024, [link], [pictures]
  • Membre d’Honneur, Société Informatique de France, 2024, [link]
  • Chevalier de la Légion d’Honneur, France, 2020/2023, [link], [pictures]
  • Global Swiss AI Award for outstanding global impact in the field of artificial intelligence, 2023, [link], [pictures]
  • Inaugural Professorship, Jacob T. Schwartz Chair in Computer Science, Courant Institute, NYU. 2023, [link]
  • Doctorate Honoris Causa, Hong Kong University of Science and Technology, 2023, [link], [pictures]
  • Doctorate Honoris Causa, Università di Siena, 2023, [link], [pictures]
  • International Association of Engineers Laureate, 2023, [link]
  • Princess of Asturias Award, for Technical and Scientific Research (with Demis Hassabis, Yoshua Bengio, and Geoffrey Hinton), 2022, [link], [pictures]
  • Foreign Member, Académie des Sciences, France, 2022, [link],
  • Fellow, American Association for the Advancement of Science, 2021, [link]
  • Member, US National Academy of Sciences, 2021, [link], [pictures]
  • Doctorate Honoris Causa, Université Côte d’Azur, 2021, [link]
  • Fellow, Association for the Advancement of Artificial Intelligence, 2020, [link]
  • Golden Plate Award, International Academy of Achievement, 2019, [link]
  • ACM A.M. Turing Award, 2018 (shared with Geoffrey Hinton and Yoshua Bengio), [link], [pictures]
  • Doctorate Honoris Causa, Ecole Polytechnique Fédérale de Lausanne, 2018, [link]
  • Holst Medal, Technical University of Eindhoven and Philips Labs, The Netherlands
  • Pender Award, University of Pennsylvania, 2018, [link]
  • Member, US National Academy of Engineering, Class of 2017, [link]
  • Nokia-Bell Labs Shannon Luminary Award, 2017, [interview] [lecture]
  • Annual Chair in Computer Science, Collège de France 2015-2016. [link]
  • Lovie Lifetime Achievement Award, International Academy of Digital Arts and Sciences, 2016. [link to acceptance speech]
  • Inductee, New Jersey Inventor Hall of Fame, 2016. [link]
  • Doctorate Honoris Causa, Instituto Politécnico Nacional, Mexico, 2016. [link]
  • IEEE Pattern Analysis and Machine Intelligence Distinguished Researcher Award, 2015. [link]
  • IEEE Neural Network Pioneer Award, 2014. [link]
  • NYU Silver Professorship, 2008.
  • Fyssen Foundation Fellowship, 1987.

Source: Personal Website

In the Media: podcasts, interviews, press articles

Podcasts (EN)

  • AI Alliance fireside chat, 05/2025 YouTube ” Yann LeCun (Meta) with Anthony Annunziata (IBM)”
  • U Penn Innovation and Impact Podcast with Vijay Kumar, Episode 7, 04/2025 YouTube “The Future of AI with Yann LeCun”
  • AI Inside Podcast with Jeff Jarvis and Jason Howell, 04/2025 YouTube “Human Intelligence is not General Intelligence”
  • Newsweek AI Impact series, 04/2025 Newsweek video “an interview with Marcus Weldon and Gabriel Snyder”
  • Nvidia GTC, 03/2025 YouTube “Frontiers of AI and Computing: A Conversation with Yann LeCun and Bill Dally”
  • This is World with Matt Kawecki, 03/2025 YouTube “AI Needs Physics to Evolve”
  • Big Technology Podcast with Alex Kantrowitz, 03/2025 YouTube “Why Can’t AI Make Its Own Discoveries? — With Yann LeCun”
  • The Economist Babbage 02/2025 The Economist “Machine-learning pioneer Yann LeCun on why “a new revolution in AI” is coming”
  • IEEE TEMS podcast with Stephen Ibaraki, 02/2025 YouTube “Podcast of the IEEE Technology and Enginieering Management Society”
  • Imagination In Action with John Werner, 02/2025 YouTube “Yann LeCun & John Werner on The Next AI Revolution: Open Source & Risks | IIA Davos 2025”
  • Johns Hopkins – Bloomberg Center Discovery Series with Kara Swisher 01/2025 YouTube “Kara Swisher and Meta’s Yann LeCun Interview – Hopkins Bloomberg Center Discovery Series”
  • Nikhil Kamath, 11/2024 YouTube “WTF is Artificial Intelligence Really? | People by WTF Ep #4” history of AI, how deep learning works, LLMs, JEPA, the future of AI…
  • Lex Friedman #416, 03/2024 YouTube “Meta AI, Open Source, Limits of LLMs, AGI & the Future of AI”
  • CBS Mornings, 12/2023 YouTube “Interviews of Yann LeCun Meta’s Chief AI Scientist Yann LeCun talks about the future of artificial intelligence”
  • Twenty Minute VC with Harry Stebbing, 05/2023 Podcast “Yann LeCun on Why Artificial Intelligence Will Not Dominate Humanity…”
  • With Andrew Ng, 04/2023 YouTube “Yann LeCun and Andrew Ng: Why the 6-month AI Pause is a Bad Idea”
  • Big Technology Podcast with Alex Kantrowitz, 01/2023 YouTube “Is ChatGPT A Step Toward Human-Level AI?”
  • Boz to the Future with Andrew Bosworth, 08/2022 Apple Podcasts
  • Eye on AI with Craig Smith #150 podcast “World Models, AI Threats and Open Sourcing”
  • Lex Friedman #258, 01/2022 YouTube “Dark Matter of Intelligence and Self-Supervised Learning”
  • Big Technology Podcast with Alex Kantrowitz, 12/2021 YouTube “Daniel Kahneman and Yann LeCun: How To Get AI To Think Like Humans”
  • The Robot Brains Podcast with Pieter Abbeel, 09/2021 YouTube “Yann LeCun explains why Facebook would crumble without AI”
  • The Gradient Podcast, 08/2021 The Gradient “Yann LeCun on his Start in Research and Self-Supervised Learning”
  • TED with Chris Anderson, 06/2020 Video “Deep learning, neural networks and the future of AI”
  • Lex Friedman #36, 08/2019 YouTube “Deep Learning, ConvNets, and Self-Supervised Learning”
  • Eye on AI with Craig Smith #114 podcast “Filling the gap in LLMs”
  • Eye on AI with Craig Smith #017, 06/2019 video,podcast
  • DeepLearning.ai with Andrew Ng, 04/2018 YouTube, “Heroes of Deep Learning: Yann LeCun”

Podcasts (FR)

  • Generation DIY #397 avec Matthieu Stefani 06/2024 podcast “L’Intelligence Artificielle Générale ne viendra pas de Chat GPT”
  • Monde Numérique avec Jérôme Colombain, 04/2024 YouTube “IA : nous aurons tous des assistants intelligents… dans dix ans”
  • Toutes mes interviews sur France Inter playlist
  • Interview sur Europe1 06/2023 podcast “Yann LeCun : «L’intelligence artificielle va amplifier l’intelligence humaine»”
  • Interview sur France Culture 10/2018 podcast sur YouTube “Yann LeCun : Les émotions sont inséparables de l’intelligence”

Press interviews and articles

Source: Personal Website

Web Links

Videos

Frontiers of AI and Computing: A Conversation With Yann LeCun and Bill Dally | NVIDIA GTC 2025

April 10, 2025 (53:14)
By: NVIDIA Developer

https://www.youtube.com/watch?v=eyrDM3A_YFc

As artificial intelligence continues to reshape the world, the intersection of deep learning and high performance computing becomes increasingly crucial. This talk brings together Yann LeCun, a pioneer in deep learning and the chief AI scientist at Meta, and Bill Dally, a leading computer architect and chief scientist at NVIDIA, to explore the future of AI models, hardware accelerators, and the evolving computational landscape.

The discussion covers:

  • The next breakthroughs in deep learning and AI architectures
  • How hardware innovation drives AI efficiency and scalability
  • Challenges in training large-scale models and real-time AI inference

Speakers:

  • Bill Dally, Chief Scientist and SVP of Research, NVIDIA
  • Yann LeCun, Chief AI Scientist at Meta, Professor at New York University

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