VideoWorld is a deep generative model focused on learning complex knowledge from pure visual inputs (unlabelled videos). It explores how to learn task rules, reasoning, and planning abilities using only visual information through autoregressive video generation techniques. The model's core advantage lies in its innovative Latent Dynamic Model (LDM), which efficiently represents multi-step visual transformations, significantly enhancing learning efficiency and knowledge acquisition capability. VideoWorld performs exceptionally well in video Go and robotic control tasks, showcasing its strong generalization ability and capacity to learn complex tasks. The research background of this model is inspired by the way biological entities learn knowledge through vision rather than language, aiming to pave new pathways for knowledge acquisition in artificial intelligence.