A world model is an AI system that learns a predictive representation of how an environment changes over time. It can use observations, actions, or language to estimate future states and possible outcomes before an agent acts. World models support planning in model-based reinforcement learning, robotics, embodied AI, autonomous driving, and interactive simulation. This site catalogs these systems with model records, research papers, benchmark context, and source links. Start with the world models database, compare systems on the leaderboard, or read the Performance Index methodology.
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world-models.io is an independent informational knowledge hub about AI world models. Its pages organize editorial summaries, source links, model records, benchmark context, and research navigation. Model names, trademarks, papers, logos, and laboratory materials remain the property of their respective owners.
The site aims to keep summaries accurate and source-linked, but fast-moving research can contain incomplete, corrected, or disputed claims. Readers should verify consequential technical, legal, commercial, or safety decisions against the original paper, technical report, product documentation, or benchmark maintainer.
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