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iNews24 Highlights Haply's Approach to Physical AI and Robot Learning

iNews24's CES 2026 coverage featured Haply alongside Maum AI, positioning haptic force-and-motion data as the missing element in robot imitation learning.

CES 2026 Physical AI MinVerse Robotics & teleoperation Awards

Originally published on haply.co — the canonical version of this article.

Two halves of the Physical AI ecosystem

Korean outlet iNews24 featured Haply alongside Maum AI in its CES 2026 coverage, framing the two companies as complementary parts of the emerging Physical AI ecosystem — one supplying the intelligence, the other supplying the physical interface and the data that trains it.

What visual data can’t teach

The article highlights the core of Haply’s approach: haptic devices capture force and movement data during natural human demonstration. That data describes contact, pressure, and compliance — dimensions of a physical task that video recordings simply do not contain, and that robots need to perform delicate work reliably.

Imitation learning, upgraded

With force-and-motion recordings in the training set, robots can learn complex tasks through imitation learning rather than brittle hand-coded control. A human performs the task through a haptic interface; the robot inherits not just the trajectory but the touch.

Read the original coverage

The full iNews24 article is available at inews24.com.

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