Dreamer 4 learns to solve complex control tasks by reinforcement learning inside of its world model. We decode the imagined training sequences for visualization, showing that the world model has learned to simulate a wide range of game mechanics from low-level mouse and keyboard actions, including breaking blocks, using tools, and interacting with crafting tables. Credit: arXiv (2025). DOI: 10.48550/arxiv.2509.24527 Over the past decade, deep learning has