LeCun bets on flexible AI that learns the real world
Yann LeCun argues current large language models like ChatGPT lack real-world understanding and unveils AMI Labs’s Joint Embedding Predictive Architecture (JEPA) to build abstractions that predict outcomes of actions, aiming to tackle robotics and household tasks; the effort has drawn over $1 billion in seed funding, with researchers like Ingmar Posner pursuing mechanistic world models, underscoring a shift toward more explainable, flexible AI that can generalize beyond text.
