World Models: The Architectures of Imagination and the Future of AI
Introduction
For decades, the standard paradigm in Artificial Intelligence has been reactive. Whether through the pattern matching of Large Language Models (LLMs) or the trial-and-error loops of Reinforcement Learning (RL), AI has primarily functioned by mapping inputs directly to outputs. However, a profound shift is underway. Researchers are increasingly converging on the concept of World Models—internal, predictive simulations of reality that allow machines to "dream," plan, and reason about physics before they act. By moving beyond statistical correlation toward an understanding of causal dynamics, world models represent the most viable path toward Artificial General Intelligence (AGI).











