Why world models are AI’s next frontier

World models are emerging as a potential successor to LLMs on the path toward AGI. Unlike LLMs that predict text patterns, world models learn physical, spatial, and causal relationships in environments. They consist of three modules: perception, prediction, and planning. Key advantages over LLMs include continuous reinforcement learning, spatial awareness, causal reasoning, long-term planning, and multimodal I/O. Yann LeCun has staked his career on world models becoming the dominant AI architecture within 3-5 years. Practical applications span immersive gaming, robotics training, hyper-realistic video generation, scientific simulation, autonomous vehicles, and complex decision-making. Notable examples include Meta's JEPA, Google DeepMind's Genie 3, DreamerV3, NVIDIA's Cosmos, and World Labs' Marble.