@seclink: Robot World Models (New Dimension, 0 Deduplication = New Information) Core Projects: - Awesome-WAM (OpenMOSS): Comprehensive Paper List of World Action Models, including DreamDojo (General-Purpose Robot World Model Learned from Human Videos) - awe…

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Summary

Introduces two projects related to robot world models: Awesome-WAM (OpenMOSS) includes papers such as World Action Models and DreamDojo; awesome-physical-ai curates a collection of papers on VLA models, world models, and embodied foundation models (including NVIDIA Cosmos Predict2.5).

Robot World Models (New Dimension, 0 Deduplication = New Information) Core Projects: - Awesome-WAM (OpenMOSS): Comprehensive Paper List of World Action Models, including DreamDojo (General-Purpose Robot World Model Learned from Human Videos) - awesome-physical-ai: Collection of papers on VLA models, world models, and embodied foundation models, including NVIDIA Cosmos Predict2.5 -
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Robot World Models (New Dimension, 0 Deduplication = Fresh Information)

Core Projects:

  • Awesome-WAM (OpenMOSS): A comprehensive paper list on World Action Models, including DreamDojo (a general robot world model learned from human videos)
  • awesome-physical-ai: A collection of papers on VLA models, world models, and embodied foundation models, including NVIDIA Cosmos Predict2.5

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World Models Explained: What Every AI Is Missing

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The article explains the concept of world models in detail, comparing them to LLMs, introduces two major camps (pixel prediction and meaning prediction) and representative works such as Dreamer v3, GameNGen, Genie, and JEPA, discusses applications in autonomous driving and robotics, and points out that world models are a key component of physical AI.

@dotey: https://x.com/dotey/status/2053351712149135385

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NVIDIA's Jim Fan spoke at Sequoia AI Ascent 2026, declaring the VLA architecture obsolete and proposing World Action Models (WAM) as a new paradigm for robotics. He introduced key technologies including DreamZero, EgoScale, and the neural simulator Dream Dojo.

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NVIDIA's head of robotics, Jim Fan, gave a public talk, advocating that robots should directly replicate the successful path of large language models. He proposed directions such as World Action Model (WAM), a data revolution based on human first-person video, and neural simulation, and predicted a 95% probability of achieving the endgame of general-purpose physical robots by 2040.

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This article reviews the latest world model algorithms in the field of embodied intelligence, including Fast-WAM and its low-latency decoupling mechanism, and introduces several open-source projects such as GeoSem-WAM, CLAW, WALL-X, etc., providing technical features and code links.