Pegasus 1.6 by TwelveLabs - Transforms egocentric video into robot training data
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Pegasus 1.6 is the TwelveLabs model that understands video from a first-person point of view, built for the egocentric and teleoperated footage robotics and physical AI teams already collect. It recognizes entities more accurately, and produces persistent metadata across segment types. Point it at raw teleoperation or wearable footage and get back labeled, timestamped, robot-ready data. No manual labeling pass required.
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"no manual labeling pass required" is the line that gives me pause more than it reassures me. for next-action prediction specifically, a mislabeled hand-object interaction isn't a cosmetic error, it's training signal a downstream policy will actually learn from, and without a human check somewhere the model's blind spots just become the robot's blind spots, quietly and at scale. is there any sampled human QA on the output metadata, or is the pitch literally zero review from raw footage to labeled training data
turning teleop footage into labeled robot data without manual work is huge 🤖 which robotics teams are using it so far?