Robot intelligence is improving fast, but there’s still a major bottleneck: data. Dexterous manipulation requires huge amounts of real-world demonstrations. But collecting that data directly on robots can be expensive, difficult to scale, and heavily dependent on the hardware. TwinDEX is exploring a different approach. Its system combines a wearable manipulation interface with a structurally matched dexterous hand for the X Square Robot, allowing humans to demonstrate complex actions without directly operating the robot. The system captures the motion, contact, and visual information needed for training while keeping the data closely aligned with the robot that will ultimately execute the task. Early results are promising across contact-rich tasks, including tool use, fine manipulation, and coordinated actions. If we want physical AI to scale, better ways of collecting and transferring real-world data may be just as important as better models.

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