LeCun: AI's next leap will come from world models, controllable by engineering
Yann LeCun, Turing Award winner and founder-chairman of AMI Labs, said at an industrial AI discussion in Seoul that AI's next breakthrough will come from "world models" that can understand, predict and act on the physical world, rather than from simply scaling up large language models. He argued that today's LLMs learn effectively from text, images and video but still lack a reliable grasp of cause and effect in the physical world, noting robots still struggle with everyday chores that a 10-year-old can do untrained. LeCun said his AMI Labs is pursuing this route through Joint-Embedding Predictive Architecture (JEPA), though he acknowledged it remains unproven whether such systems can deliver reliable prediction, autonomous planning and large-scale deployment in complex real environments. Responding to recent cybersecurity incidents involving AI agents, including AI-related attacks on South Korea's financial sector, he said the problems stem mainly from firms lacking security expertise and from flaws in sandboxes, and that the risks can be managed through better system architecture and security engineering.
Coming from a Turing laureate, LeCun's stance that world models matter more than bigger language models — and that AI loss of control is an engineering problem — marks a distinct path from mainstream safety concerns and could shape robotics and industrial AI research.