Self-Supervised Learning and the Future of AI - from a lecture given by Yann LeCun

Join us as Turing Award recipient Yann LeCun, Chief Scientist at Meta, critiques the state of AI, arguing that current systems, including Large Language Models (LLMs), are nowhere near matching the learning efficiency observed in humans and animals. LeCun proposes a major architectural shift, advocating that AI must abandon generative models for training and instead focus on building internal "World Models" to enable reasoning and planning. Discover how the Joint Embedding Predictive Architecture (JEPA) uses self-supervised learning to train machines to acquire robust, abstract representations of reality, a crucial step toward achieving common sense and human-level intelligence.

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