The Sequence Knowledge #796: Welcome to the World of World Models
Exploring one of the hottest topics in frontier AI.
Today we will Discuss:
An introduction to a new series about World Models.
A review of the groundbreaking DayDreamer paper that set up the foundation for modern world models.
💡 AI Concept of the Day: Welcome to the World of World Models
Today, we are starting a new series about one of the hottest topics in AI.
World models are having a moment because they change the unit of progress in AI. For most of the last decade, we trained models on snapshots of the world: documents, images, videos—static artifacts that are easy to scrape and label. But agents don’t live in snapshots. They live in dynamics: sequences of perception → action → consequence → correction. A world model is an attempt to learn that loop—an internal simulator that can generate, update, and remain coherent as you interact with it.
This matters because “reasoning” is increasingly becoming search over possibilities. The best agents don’t just produce an answer; they explore options, test hypotheses, and commit to actions. World models give agents a place to do that exploration cheaply and repeatedly: generate environments, produce edge cases on demand, roll out trajectories, and measure behavior under distribution shift. If language models are a universal interface, world models are shaping up to be a universal sandbox.