@FinanceYF5: What surprised me most: Dyna-2 never trained on a single robot trajectory, yet the more human video it saw, the better …
Summary
Dyna Robotics introduces Dyna-2, a world-action model pre-trained on one million hours of human video, revealing scaling laws and suggesting the embodiment gap is an adaptation problem rather than a knowledge problem.
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Cached at: 08/12/26, 08:35 AM
What surprised me most: Dyna-2 never trained on a single robot trajectory, yet the more human video it saw, the better it got at robot tasks.
The embodiment gap looks less like a “knowledge problem” than an “adaptation problem.” That distinction could rewrite robot pretraining.
Dyna Robotics (@DynaRobotics): Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws:
• world-action models exhibit scaling law on human data across four orders of magnitude, from 1000
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