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So excited to finally talk about this work! Veo is a surprisingly strong world simulator. We fine-tuned Veo on action-conditioned, multi-view robotics data. Key result: running a policy in the world model is strongly correlated with real-world results. A few important take-aways: 1) Veo Robotics models real-world physics and robot interactions 2) The base model's world knowledge is retained after fine-tuning and can model OOD scenarios not seen in the robotics data 3) The world model can be used to score task success or failure for a given policy 4) This proves useful for predictive red teaming: simulate dangerous or rare scenarios that would be difficult or irresponsible to execute on the real robot, and judge its performance I couldn't be more excited about where generalist video models are headed.

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    "text": "Generalist robots need a generalist evaluator. But how do you test safety without breaking things? πŸ’₯\n\n🌎 Introducing our new work from @GoogleDeepMind: \nEvaluating Gemini Robotics Policies in a Veo World Simulator\nhttps://t.co/ZjvpYXFddZ\n\nπŸ§΅πŸ‘‡ https://t.co/h2ZbeEKYEn",
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