World Models: The Illusion and Reality of AGI

The latest pursuit in AI research, especially in AGI labs, is the creation of a "world model" – a simplified representation of the environment within an AI system, like a computational snow globe. Leading figures like Yann LeCun, Demis Hassabis, and Yoshua Bengio believe world models are crucial for truly intelligent, scientific, and safe AI. However, the specifics of world models are debated: are they innate or learned? How do we detect their presence? The article traces the concept's history, revealing that current generative AI may rely not on complete world models, but on numerous disconnected heuristics. While effective for specific tasks, these lack robustness. Building complete world models remains crucial, promising solutions to AI hallucinations, improved reasoning, and greater interpretability, ultimately driving progress towards AGI.