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Rohan Paul@rohanpaul_ai
Agents learn from trial and error. The expensive part is the error. A world model moves the error into simulation, which is the whole case for something like PAN 2.
This is a free, open "action-conditioned world model".
Takes an action you describe, and generates up to 20 seconds of video showing what would physically happen next. Its new trick is splitting the job in 2: a language model first works out the plot, then a 29B video model renders it.
Introducing PAN 2: an open foundation world model for physical intelligence.
A language model predicts the next word. PAN 2 predicts the next world: what happens after each action, grounded in time, physics and space.
Towards AI that simulates “what if?” before it acts.
More details: https://t.co/lUX7igPOiF
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