Yann LeCun

Interview of Yann LeCun by the Bocconi AI and Neuroscience Association (BAINSA) during the World AI Cannes Festival of 2024 #AI #ML #meta #yannlecun #WAICF #Neuroscience #artificialintelligence #machinelearning #cannes #festival #technology @instituteeuropia621

Yann LeCun, 2022 Princess of Asturias Award for Technical and Scientific Research, during the press conference given in the Reconquista Hotel.

In this episode Stephen Jose Hanson talks with Yann Le Cun on his recent work on world modeling in effect DL 2.0.

Fireside Chat with Aparna Ramani & Yann LeCun | Yann LeCun

Fireside Chat | Yann LeCun & Ludovic Hauduc

In this episode, Yann LeCun, a renowned computer scientist and AI researcher, shares his insights on the limitations of large language models and how his new joint embedding predictive architecture could help bridge the gap. While large language models have made remarkable strides in natural language processing and understanding, they are still far from perfect. Yann LeCun points out that these models often cannot capture the nuances and complexities of language, leading to inaccuracies and errors. To address this gap, Yann LeCun introduces his new joint embedding predictive architecture - a novel approach to language modelling that combines techniques from computer vision and natural language processing. This approach involves jointly embedding text and images, allowing for more accurate predictions and a better understanding of the relationships between original concepts and objects. Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

My guest is Yann LeCun, a pioneering French-American computer scientist, known for his groundbreaking work in machine learning, computer vision, and neural networks. Yann is the Silver Professor at the Courant Institute of Mathematical Sciences at New York University and serves as the Vice President and Chief AI Scientist at Meta. Yann is one of the world’s most influential computer scientists. He has accumulated over 350,000 citations on Google Scholar, he is one of the founding figures in the field of deep learning thanks to its contribution to convolutional neural networks and backpropagation algorithms, and he is a vocal proponent of open source. In recognition of his significant contributions to artificial intelligence, he was awarded the Turing Award in 2018, often referred to as the “Nobel Prize of Computing.” Our conversation is structured into three distinct parts. We begin by discussing the overarching dynamics in the AI space, then narrow our focus to the firm level, and finally, we conclude with an exploration of the challenges that lie ahead. By the end of this discussion, you will learn whether open source has a chance to make it in AI, the key factors for scaling an AI foundation model, the role ecosystems play in market dynamics, Meta long term strategy in the space, how concentration among chip manufacturers impacts AI companies, the current effect of the European AI Act on AI companies, what Yann would like to see regulators doing, and more. I hope you enjoy the conversation. Find me on X at @ProfSchrepel⁠⁠⁠. Also, be sure to subscribe to the Scaling Theory podcast; it helps its growth. This episode is also available on: ➝ Spotify: https://open.spotify.com/episode/7G... ➝ Apple Podcast: https://podcasts.apple.com/fr/podca...

Yann LeCun, one of the brightest minds in machine learning today, talks about his first computer, about how music led him into computer science, and about his work on self-supervised learning, which he believes will take us to human-level intelligence in machines.

Plus fort que ChatGPT, JEPA. Une intelligence artificielle avancée, capable de raisonner et d'apprendre plus, à la manière des humains, voilà le projet que nous a présenté Yann Le Cun, prix Turing, Chef AI Scientist chez Meta et un des plus grands chercheurs en intelligence artificielle. Pour lui, actuellement « L’intelligence artificielle générative est 50 fois moins intelligente qu’un enfant de 4 ans ». Celle qu'il espère et souhaite construire pourrait comprendre les conséquences de ses actions, raisonne, comprendre le monde, se poser des questions par exemple sur la dangerosité d'une action avant d’agir, tout comme réfléchir aux conséquences de ses actes. Un entretien exceptionnel #AI #IA #artificialIntelligence #IntelligenceArtificielle #ChatGPT Suivez nous sur : - Youtube : https://www.youtube.com/c/lepoint/ - Facebook : https://www.facebook.com/lepoint.fr... - Twitter : https://twitter.com/LePoint - Instagram : https://www.instagram.com/lepointfr - Tik Tok : https://www.tiktok.com/@lepointfr - LinkedIn : https://www.linkedin.com/company/le... - www.lepoint.fr

Fireside chat with Yann LeCun (Turing Award Recipient and Senior Vice President, Meta Platforms) hosted by Gaurav Aggarwal, iSPIRT

Full Video: https://www.youtube.com/watch?v=4P3...

Turing Award winner and Meta Chief AI Scientist Yann LeCun will join Zetta's Jocelyn Goldfein for a fireside chat on what's next for AI. Yann is one of the leading voices in AI today and is considered a godfather of deep learning thanks to his development of deep neural networks (with Geoffrey Hinton and Yoshua Bengio). At Facebook (now Meta) he has overseen the development of the leading ML frameworks and models and with the release of LLaMA has made Meta a champion of open-source AI.

Read about our latest advance in the field of AI and mathematics: https://bit.ly/3NuYenO Joelle Pineau, Managing Director of FAIR, sat down for a discussion with Timothy Gowers and Yann LeCun to discuss the current state of field in AI mathematics, the role that it can play in learning and exploration of where they expect the field to go in the future. -- Subscribe: https://www.youtube.com/facebookai?... Learn more about our work: https://ai.facebook.com Follow us on Twitter: https://twitter.com/MetaAI Follow us on Facebook: https://www.facebook.com/MetaAI Connect with us on LinkedIn: https://www.linkedin.com/showcase/m... Meta AI focuses on bringing the world together by advancing AI, powering meaningful and safe experiences, and conducting open research.

Geoffrey Hinton, Yann Lecun, Yoshua Bengio y Demis Hassabis son los Premios Princesa de Asturias de Investigación Científica y Técnica 2022. Dos de los cuatro padrinos de la inteligencia artificial están en Oviedo para recoger el galardón. Son expertos en sistemas que imitan el funcionamiento del cerebro humano. Su compleja investigación es de esas que pueden servir para mejorar el presente y futuro de la población. Un tipo de inteligencia artificial que no solo ha venido para facilitarnos la vida, sino también a protegerla. #premiosprincesa #princesadeAsturias #Oviedo #ciencia #cerebro #investigacion #inteligenciaartificial #news #LiveNews #StreamingNews #españa #noticiasenespañol 👉👉 Más noticias: https://www.rtve.es/noticias ➤SUSCRÍBETE a RTVE Noticias en YouTube: https://bit.ly/2WtyvUx ✔️Síguenos en Instagram: https://www.instagram.com/rtvenotic... ✔️Síguenos en Twitter: https://twitter.com/rtvenoticias ✔️Síguenos en Facebook: https://www.facebook.com/RTVENotici...

A Conversation with Yann LeCun AI: Lifeline or Landmine?

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Yann LeCun is the chief AI scientist at Meta, a professor of computer science at NYU, and a pioneer of deep learning. He joins Big Technology Podcast to put Generative AI in context, discussing whether ChatGPT and the like are a step toward human-level artificial intelligence, or something completely different. Join us for a fun, substantive discussion about this technology, the makeup of OpenAI, and where the field heads next. Stay tuned for the second half, where we discuss the ethics of using others' work to train AI models.

Will AI Lead Us to Our End?

This episode is sponsored by Oracle. AI is revolutionizing industries, but needs power without breaking the bank. Enter Oracle Cloud Infrastructure (OCI): the one-stop platform for all your AI needs, with 4-8x the bandwidth of other clouds. Train AI models faster and at half the cost. Be ahead like Uber and Cohere. If you want to do more and spend less like Uber, 8x8, and Databricks Mosaic - take a free test drive of OCI at https://oracle.com/eyeonai Welcome to episode 150 of the ‘Eye on AI’ podcast. In this episode, host Craig Smith sits down with Yann LeCun, a Turing Award winner who has been instrumental in advancing convolutional neural networks and whose work spans machine learning, computer vision, and more. Tune is as Craig and Yann explore the intricacies of AI, world models, and the challenges of continuous learning. In this episode, Yann delves deep into the concept of a "world model" - systems that can predict the world's future states, allowing agents to make informed decisions. The discussion transitions to the challenges of training these models, particularly when dealing with diverse data like text and images. We then discuss the computational demands of modern AI models, with Yann highlighting the nuances between generative models for videos and language. He also touches upon the idea of the "Embodied Turing Tests" and how augmented language models can bridge the gap between human-like behavior and computational efficiency.The spotlight then shifts to pressing concerns surrounding the open-source nature of AI models, with Yann articulating the legal ramifications and the future of open-source AI. Drawing from global perspectives, including China's stance on open-source, Yann underscores the imperative for a collaborative approach in the AI space, ensuring it's reflective of diverse global needs. Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI 00:00 Preview, Oracle and Introduction 02:42 Decoding The World Model and Gaia 1 07:43 Energy and Computational Demands of AI 08:06 Video vs. Text Processing & True AI Capabilities 11:17 Embodied Turing Test & Augmented LLMs 15:38 Is AI a Threat To Society? 25:04 Where is AI Development Headed? 31:06 Interplay of Neuroscience and AI 33:33 Yann's Vision, JEPA, and Learning Challenges 39:05 Yann's Career, AI Progress, and Challenges 44:47 The Open Source Debate in AI 55:30 Oracle Cloud Infrastructure

Support us! https://www.patreon.com/mlst Yann LeCun is a French computer scientist known for his pioneering work on convolutional neural networks, optical character recognition and computer vision. He is a Silver Professor at New York University and Vice President, Chief AI Scientist at Meta. Along with Yoshua Bengio and Geoffrey Hinton, he was awarded the 2018 Turing Award for their work on deep learning, earning them the nickname of the "Godfathers of Deep Learning". Dr. Randall Balestriero has been researching learnable signal processing since 2013, with a focus on learnable parametrized wavelets and deep wavelet transforms. His research has been used by NASA, leading to applications such as Marsquake detection. During his PhD at Rice University, Randall explored deep networks from a theoretical perspective and improved state-of-the-art methods such as batch-normalization and generative networks. Later, when joining Meta AI Research (FAIR) as a postdoc with Prof. Yann LeCun, Randall further broadened his research interests to include self-supervised learning and the biases emerging from data-augmentation and regularization, resulting in numerous publications. Pod version: https://anchor.fm/machinelearningst... Note: We have another full interview with Randall, which we will release soon as part of a show focussed on Spline Theory of NNs. TOC: [00:00:00] LeCun interview [00:18:25] Randall Balestriero interview (mostly on spectral SSL paper, first ref) References: [Randall Balestriero, Yann LeCun] Contrastive and Non-Contravention Self-Supervised Learning Recover Global and Local Spectral Embedding Methods https://arxiv.org/abs/2205.11508 [Randall Balestriero, Ishan Misra, Yann LeCun] A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments https://arxiv.org/abs/2202.08325 [Bobak Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd] projUNN: efficient method for training deep networks with unitary matrices https://arxiv.org/abs/2203.05483 [Randall Balestriero, Richard G. Baraniuk]A Spline Theory of Deep Networks https://proceedings.mlr.press/v80/b... Learning in High Dimension Always Amounts to Extrapolation [Randall Balestriero, Jerome Pesenti, Yann LeCun] https://arxiv.org/abs/2110.09485 https://www.youtube.com/watch?v=86i... [MLST special edition show on extrapolation and this/spline paper] [Mathilde Caron et al] DINO - Emerging Properties in Self-Supervised Vision Transformers https://arxiv.org/abs/2104.14294 [Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton] A Simple Framework for Contrastive Learning of Visual Representations (SIMCLR) https://arxiv.org/abs/2002.05709 MLST show with Simon Kornblith: https://www.youtube.com/watch?v=1Eq... [Yann LeCun] A Path Towards Autonomous Machine Intelligence Version https://openreview.net/pdf?id=BZ5a1... [Patrice Y. Simard, Yann A. LeCun et al] Transformation Invariance in Pattern Recognition – Tangent Distance and Tangent Propagation https://link.springer.com/chapter/1... [Kaiming He et al] Masked Autoencoders Are Scalable Vision Learners https://arxiv.org/abs/2111.06377 [Radford et al] Whisper - Robust Speech Recognition via Large-Scale Weak Supervision https://cdn.openai.com/papers/whisp... RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank [Quentin Garrido, Randall Balestriero, Laurent Najman, Yann Lecun] https://arxiv.org/abs/2210.02885 [David Silver, Satinder Baveja, Doina Precup, Richard Sutton] Reward is Enough https://www.deepmind.com/publicatio...

In this episode, Yann LeCun, a renowned computer scientist and AI researcher, shares his insights on the limitations of large language models and how his new joint embedding predictive architecture could help bridge the gap. While large language models have made remarkable strides in natural language processing and understanding, they are still far from perfect. Yann LeCun points out that these models often cannot capture the nuances and complexities of language, leading to inaccuracies and errors. To address this gap, Yann LeCun introduces his new joint embedding predictive architecture - a novel approach to language modelling that combines techniques from computer vision and natural language processing. This approach involves jointly embedding text and images, allowing for more accurate predictions and a better understanding of the relationships between original concepts and objects. Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

En mars, 1000 sommités comme Elon Musk, Yuval Noah Harari et Yoshua Bengio ont demandé un moratoire sur la recherche en intelligence artificielle. « Les systèmes d’intelligence artificielle posent un grand risque pour l'humanité », ont-ils écrit. Un des plus grands chercheurs sur la question, le patron de la recherche en intelligence artificielle chez Facebook, n'a pas signé toutes ces mises en garde alarmistes. Yann Le Cun a remporté le prix Turing et demeure résolument optimiste. Patrice Roy l’a rencontré. #TJ18h -- Rendez-vous sur notre site web pour consulter tous nos contenus : https://ici.radio-canada.ca/info Abonnez-vous à nos comptes : Facebook : https://www.facebook.com/radiocanad... Instagram : https://www.instagram.com/radiocana... Twitter : https://twitter.com/RadioCanadaInfo TikTok : https://www.tiktok.com/@radio.canad...

Yann LeCun is VP & Chief AI Scientist at Meta and Silver Professor at NYU affiliated with the Courant Institute of Mathematical Sciences & the Center for Data Science. He was the founding Director of FAIR and of the NYU Center for Data Science. After a postdoc in Toronto he joined AT&T Bell Labs in 1988, and AT&T Labs in 1996 as Head of Image Processing Research. He joined NYU as a professor in 2003 and Meta/Facebook in 2013. He is the recipient of the 2018 ACM Turing Award for “conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing”. Huge thanks to David Marcus for helping to make this happen. ------------------------------------------ Timestamps: 0:00 Introduction 0:32 Yann LeCun's Journey to Chief AI Scientist at Meta: A History of AI 6:25 The Rapid Progress of AI Today 12:31 Prophecies of Doom: Debunking AI Misconceptions 21:19 Open vs Closed-Models of AI; Where does the value go? 25:01 How does Meta win the AI race? 29:50 Incumbents vs Startups: Profiting in the AI Era 36:41 AI Will Create More Jobs Than It Destroys 43:36 Why Humans Love AI Doom Scenarios 45:40 Jeff Dean's Exit from Google & His AI Warning 51:38 Elon Musk Is Wrong About AI 54:40 Quick-Fire Round ------------------------------------------ In Today’s Episode with Yann LeCun: 1.) The Road to AI OG: How did Yann first hear about machine learning and make his foray into the world of AI? For 10 years plus, machine learning was in the shadows, how did Yann not get discouraged when the world did not appreciate the power of AI and ML? What does Yann know now that he wishes he had known when he started his career in machine learning? 2.) The Next Five Years of AI: Hope or Horror: Why does Yann believe it is nonsense that AI is dangerous? Why does Yann think it is crazy to assume that AI will even want to dominate humans? Why does Yann believe digital assistants will rule the world? If digital assistants do rule the world, what interface wins? Search? Chat? What happens to Google when digital assistants rule the world? 3.) Will Anyone Have Jobs in a World of AI: From speaking to many economists, why does Yann state “no economist thinks AI will replace jobs”? What jobs does Yann expect to be created in the next generation of the AI economy? What jobs does Yann believe are under more immediate threat/impact? Why does Yann expect the speed of transition to be much slower than people anticipate? Why does Yann believe Elon Musk is wrong to ask for the pausing of AI developments? 4.) Open or Closed: Who Wins: Why does Yann know that the open model will beat the closed model? Why is it superior for knowledge gathering and idea generation? What are some core historical precedents that have proved this to be true? What did Yann make of the leaked Google Memo last week? 5.) Startup vs Incumbent: Who Wins: Who does Yann believe will win the next 5 years of AI; startups or incumbents? How important are large models to winning in the next 12 months? In what ways does regulation and legal stop incumbents? How has he seen this at Meta? Has his role at Meta ever stopped him from being impartial? How does Yann deal with that? ------------------------------------------ Subscribe on Spotify: https://open.spotify.com/show/3j2KM... Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podca... Follow Harry Stebbings on Twitter: https://twitter.com/HarryStebbings Follow Yann LeCun on Twitter: https://twitter.com/ylecun Follow 20VC on Instagram: https://www.instagram.com/20vc_reel... Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/c... ------------------------------------------ #YannLeCun #Meta #HarryStebbings

Yann Le Cun, directeur du laboratoire d’Intelligence Artificielle de Meta, professeur d’informatique et de neurosciences à l’université de New York, auteur de Quand la machine apprend. "La révolution des neurones artificiels et de l’apprentissage profond" (Odile Jacob), est l'invité de 7h50. Plus d'info : https://www.radiofrance.fr/francein...

Meta’s Chief AI Scientist Yann LeCun discusses why he supports open source large learning models and why models need to live in the world to achieve autonomy. Subscribe to FORBES: https://www.youtube.com/user/Forbes... Fuel your success with Forbes. Gain unlimited access to premium journalism, including breaking news, groundbreaking in-depth reported stories, daily digests and more. Plus, members get a front-row seat at members-only events with leading thinkers and doers, access to premium video that can help you get ahead, an ad-light experience, early access to select products including NFT drops and more: https://account.forbes.com/membersh... Stay Connected Forbes newsletters: https://newsletters.editorial.forbe... Forbes on Facebook: http://fb.com/forbes Forbes Video on Twitter: http://www.twitter.com/forbes Forbes Video on Instagram: http://instagram.com/forbes More From Forbes: http://forbes.com Forbes covers the intersection of entrepreneurship, wealth, technology, business and lifestyle with a focus on people and success.

Meta's Chief AI Scientist Yann LeCun is considered one of the "Godfathers of AI." But he now disagrees with his fellow computer pioneers about the best way forward. He recently discussed his vision for the future of artificial intelligence with CBS News' Brook Silva-Braga at Meta's offices in Menlo Park, California. "CBS Saturday Morning" co-hosts Jeff Glor, Michelle Miller and Dana Jacobson deliver two hours of original reporting and breaking news, as well as profiles of leading figures in culture and the arts. Watch "CBS Saturday Morning" at 7 a.m. ET on CBS and 8 a.m. ET on the CBS News app. Subscribe to “CBS Mornings” on YouTube: https://www.youtube.com/CBSMornings Watch CBS News: http://cbsn.ws/1PlLpZ7c Download the CBS News app: http://cbsn.ws/1Xb1WC8 Follow "CBS Mornings" on Instagram: https://bit.ly/3A13OqA Like "CBS Mornings" on Facebook: https://bit.ly/3tpOx00 Follow "CBS Mornings" on Twitter: https://bit.ly/38QQp8B Subscribe to our newsletter: http://cbsn.ws/1RqHw7T​ Try Paramount+ free: https://bit.ly/2OiW1kZ For video licensing inquiries, contact: licensing@veritone.com

Yann LeCun is the Chief AI Scientist at Meta, professor at NYU, Turing Award winner, and one of the seminal researchers in the history of machine learning. Please support this podcast by checking out our sponsors: - Public Goods: https://publicgoods.com/lex and use code LEX to get $15 off - Indeed: https://indeed.com/lex to get $75 credit - ROKA: https://roka.com/ and use code LEX to get 20% off your first order - NetSuite: http://netsuite.com/lex to get free product tour - Magic Spoon: https://magicspoon.com/lex and use code LEX to get $5 off EPISODE LINKS: Yann's Twitter: https://twitter.com/ylecun Yann's Facebook: https://www.facebook.com/yann.lecun Yann's Website: http://yann.lecun.com/ Books and resources mentioned: Self-supervised learning (article): https://bit.ly/3Aau1DQ PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast... Full episodes playlist: https://www.youtube.com/playlist?li... Clips playlist: https://www.youtube.com/playlist?li... OUTLINE: 0:00 - Introduction 0:36 - Self-supervised learning 10:55 - Vision vs language 16:46 - Statistics 22:33 - Three challenges of machine learning 28:22 - Chess 36:25 - Animals and intelligence 46:09 - Data augmentation 1:07:29 - Multimodal learning 1:19:18 - Consciousness 1:24:03 - Intrinsic vs learned ideas 1:28:15 - Fear of death 1:36:07 - Artificial Intelligence 1:49:56 - Facebook AI Research 2:06:34 - NeurIPS 2:22:46 - Complexity 2:31:11 - Music 2:36:06 - Advice for young people SOCIAL: - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfrid... - Facebook: https://www.facebook.com/lexfridman - Instagram: https://www.instagram.com/lexfridma... - Medium: https://medium.com/@lexfridman - Reddit: https://reddit.com/r/lexfridman - Support on Patreon: https://www.patreon.com/lexfridman

A novel intelligence has roared into the mainstream, sparking euphoric excitement as well as abject fear. Explore the landscape of possible futures in a brave new world of thinking machines, with the very leaders at the vanguard of artificial intelligence. The Big Ideas Series is supported in part by the John Templeton Foundation. Participants: Sébastien Bubeck Tristan Harris Yann LeCun Moderator: Brian Greene SHARE YOUR THOUGHTS on this program through a short survey: https://survey.alchemer.com/s3/7619... 00:00 - Introduction 07:32 - Yann lecun Introduction 13:35 - Creating the AI Brian Greene 20:55 - Should we model AI on human intelligence? 27:55 - Schrodinger's Cat is alive 37:25 - Sébastien Bubeck Introduction 44:51 - Asking chatGPT to write a poem 52:26 - What is happening inside GPT 4? 01:02:56 - How much data is needed to train a language model? 01:11:20 - Tristan Harris Introduction 01:17:13 - Is profit motive the best way to go about creating a language model? 01:23:41 - AI and its place in social media 01:29:33 - Is new technology to blame for cultural phenomenon? 01:36:34 - Can you have a synthetic version of AI vs the large data set models? 01:44:27 - Where will AI be in 5 to 10 years? 01:54:45 - Credits WSF Landing Page Link: https://www.worldsciencefestival.co... - SUBSCRIBE to our YouTube Channel and "ring the bell" for all the latest videos from WSF - VISIT our Website: http://www.worldsciencefestival.com - LIKE us on Facebook: https://www.facebook.com/worldscien... - FOLLOW us on Twitter: https://twitter.com/WorldSciFest #worldsciencefestival #ai #artificialintelligence #briangreene