Yann LeCun, Chief AI Scientist at Meta and Turing Award winner, dives into the transformative power of open-source AI. He discusses the real-world limits of large language models, emphasizing the need for sensory experiences in developing true intelligence. LeCun also outlines the intricacies of AI's hierarchical planning and the importance of diverse perspectives in AI development. The conversation navigates the delicate balance between innovation and ethical considerations, urging for a collective approach in shaping the future of artificial intelligence.

Yann LeCun, Chief AI Scientist at Meta and a pioneer in neural networks, engages in a lively discussion about open-source AI. He shares insights on the financial race in AI, where tech giants invest heavily in advancements. Yann tackles the risks of open-sourcing powerful models and advocates for guidelines to ensure ethical development. He also voices his thoughts on AI regulation and explains the necessity of transparency in research. Known for his candidness, he isn’t shy about sharing his views on figures like Elon Musk and Donald Trump.

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/craigssEye on A.I. Twitter: https://twitter.com/EyeOn_AI

This week Connor Shorten, Yannic Kilcher and Tim Scarfe reacted to Yann LeCun's keynote speech at this year's ICLR conference which just passed. ICLR is the number two ML conference and was completely open this year, with all the sessions publicly accessible via the internet. Yann spent most of his talk speaking about self-supervised learning, Energy-based models (EBMs) and manifold learning. Don't worry if you hadn't heard of EBMs before, neither had we! Thanks for watching! Please Subscribe! Paper Links: ICLR 2020 Keynote Talk: https://iclr.cc/virtual_2020/speaker_7.html A Tutorial on Energy-Based Learning: http://yann.lecun.com/exdb/publis/pdf/lecun-06.pdf Concept Learning with Energy-Based Models (Yannic's Explanation): https://www.youtube.com/watch?v=Cs_j-oNwGgg Concept Learning with Energy-Based Models (Paper): https://arxiv.org/pdf/1811.02486.pdf Concept Learning with Energy-Based Models (OpenAI Blog Post): https://openai.com/blog/learning-concepts-with-energy-functions/ #deeplearning #machinelearning #iclr #iclr2020 #yannlecun

Join Yann LeCun, Meta’s Chief AI Scientist and Turing Award winner, as he discusses the future of AI. He explains the revolutionary Joint Embedding Predictive Architecture (JEPA) and its potential to enhance real-world modeling. LeCun dives into the limitations of current AI, comparing it to human understanding and instincts. He also stresses the importance of aligning AI with human values and preventing a loss of control over advanced systems. Tune in for insights into how AI might transform education and our daily lives!

Yoshua Bengio, a pioneer of generative AI, and Eliezer Yudkowsky, a research lead at the Machine Intelligence Research Institute, discuss the existential risk of superintelligent AI. Yann LeCun, head of AI at Meta, disagrees and points out the potential benefits of superintelligent AI. Topics include the dangers of superintelligent machines, aligning AI systems with human values, and the potential and misuse of superintelligent AI.

Yann LeCun, a leading computer scientist, discusses AI dynamics and regulation. Topics include open source's role in AI development, scaling AI models, market dynamics, Meta's long-term strategy, the impact of chip manufacturers on AI companies, and the European AI Act. The conversation explores the future of AI, regulatory challenges, and the competition in the AI chip market.

Host Boz talks to Meta's VP of AI Research Joelle Pineau and Chief AI Scientist Yann LeCun about FAIR, Meta's Fundamental AI Research Lab, and the importance of open research and collaboration. They discuss the limitations of current AI systems, theory of mind and world models in AI research, the concept of consciousness, and their online presence on different social media platforms.

In this episode, Yann LeCun, an AI expert, discusses the concept of a world model and the challenges of training diverse models. He also explores embodied Turing tests and augmented language models. The podcast addresses concerns about AI misuse and highlights the importance of neuro AI and collaboration in the future of AI systems.

A panel of luminaries join us live on stage at MIT Technology Review’s flagship conference, EmTech MIT, and discuss the path forward for AI research.We Meet:Will Douglas Heaven, Senior Editor of AI at MIT Technology ReviewAshley Llorens, Vice President & Managing Director at Microsoft ResearchRaia Hadsell, Senior Director of Research and Robotics at DeepMindYann LeCun, NYU Professor, VP & Chief AI Scientist at MetaCredits:This episode was recorded in front of a live audience at the MIT Media Lab in Cambridge, Massachusetts with special thanks to Will Douglas Heaven, Amy Lammers and Brian Bryson. It was produced by Jennifer Strong, Emma Cillekens and Anthony Green, directed by Erin Underwood, edited by Mat Honan and mixed by Garret Lang.