Runway has introduced GWM-1, its first world model, expanding beyond video generation. This set of autoregressive models allows users to create and explore digital environments in real time, useful for game design, virtual reality, and training AI agents. The second model, GWM Robotics, generates synthetic data for robotics training.

This article discusses the progression of video generation techniques towards creating comprehensive world models that simulate real-world dynamics. It outlines a four-generation taxonomy, highlighting how each generation enhances capabilities like realism, interaction, planning, and stochasticity. The authors emphasize the importance of integrating physical and mental world models for applications in robotics and AI.