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🤖 Another zero-shot reward model is now in LeRobot: ROBOMETER. A general-purpose, zero-shot video-language reward model from @UofSC, @UT_Dallas, @MIT, @UW, @allen_ai, and @nvidia that predicts frame-level task progress. Trained on 1M+ trajectories from 21 robot embodiments, generalizes zero-shot to unseen tasks, scenes, and robots. 2.4–4.5x better downstream success rates across online RL, offline RL, data filtering, failure detection, and data retrieval for IL. Project: https://t.co/rkKUcYamYT
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single-purpose robots keep winning:1. they pick one task and nail it2. they don’t need a foundation model to be useful3. every run generates data that makes the next one better4. the operator ratio flips from 1:1 to 1:many5. the customer forgets it’s a robotthis is happening across every major industry
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We’ve made huge strides in narrow AI: robots can assemble cars, sort packages, and perform repetitive factory tasks with impressive precision. But we’re still very far from replacing humans broadly. Today’s robots struggle with anything that requires common sense, adaptability, or working in unpredictable environments like a messy home. General-purpose humanoid robots are in very early stages, mostly research prototypes that still need a lot of human oversight. So while specific jobs are being a
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