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    DeepMind introduces AI agent that learns to complete various tasks in a scalable world model

    October 26, 2025, Categories  Physics, Technology/Electronics

    DeepMind introduces an AI agent that learns to complete various tasks in a scalable world model
    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 transformed how artificial intelligence (AI) agents perceive and act in digital environments, allowing them to master board games, control simulated robots and reliably tackle various other tasks...

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