The Shape of AI to Come! Yann LeCun at AI Action Summit 2025

The Next AI Revolution: Yann LeCun’s Vision Beyond LLMs At the AI Action Summit in Paris, Yann LeCun underscored a fundamental shift in artificial intelligence—one that moves beyond the brute-force approach of large language models (LLMs). Instead of systems that merely predict the next token, the future of AI hinges on *world models*—structured, adaptive representations that can infer, reason, and plan. This vision holds immense potential for fields like healthcare and biology, where complexity defies exhaustive computation. 🔹 1. Prioritize Key Insights Over Exhaustive Generation In medicine, capturing every molecular interaction is infeasible. The focus should be on critical variables—key biomarkers, for instance—that shape disease progression and treatment response. This is where JEPA (Joint Embedding Predictive Architecture) thrives: predicting essential relationships rather than generating redundant details. 🔹 2. Replace Probability Overload with Efficient Scoring Traditional AI wastes resources computing endless probabilities. Instead, energy-based models assess how likely or “normal” a given state is. In healthcare, this translates to identifying anomalous symptoms or lab results instantly—without brute-force calculations. 🔹 3. Move Beyond Contrastive Learning to More Direct Approaches Contrastive learning hinges on distinguishing “positive vs. negative” examples, often requiring vast datasets. Simpler, more direct methods can recognize meaningful patterns with less data—an advantage in medical research, where data is often scarce. 🔹 4. Shift from Trial-and-Error to Model-Driven Discovery Blindly testing drugs or protein interactions is slow and costly. AI-driven world models can predict biological behavior, allowing experiments to focus only on deviations from expected outcomes. This approach accelerates breakthroughs while reducing inefficiencies. 🔹 5. LLMs Alone Won’t Achieve Human-Level Intelligence While LLMs excel at summarizing and automating documentation, true comprehension—such as understanding disease mechanisms—requires AI that grasps causality, not just linguistic patterns. The next frontier isn’t about scaling transformers but building models that think. LeCun’s vision challenges conventional AI wisdom: instead of merely making models bigger, make them *smarter*. In healthcare and beyond, this shift could redefine how we diagnose, predict, and treat complex conditions. The future of AI isn’t just about processing data—it’s about understanding the world. If you would like to support the channel, please join the membership: https://www.youtube.com/c/AIPursuit/join Subscribe to the channel: https://www.youtube.com/c/AIPursuit?sub_confirmation=1 The video is reposted for educational purposes and encourages involvement in the field of AI research. Source: AI Action Summit 2025