<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Robot Data on Fondsites</title><link>https://fondsites.com/tags/robot-data/</link><description>Recent content in Robot Data on Fondsites</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 11 May 2026 11:34:07 +0300</lastBuildDate><atom:link href="https://fondsites.com/tags/robot-data/feed.xml" rel="self" type="application/rss+xml"/><item><title>Robot Data Collection: How Physical AI Learns From Work</title><link>https://fondsites.com/physical-ai-lab/guidebooks/robot-data-collection/</link><pubDate>Mon, 11 May 2026 08:13:55 +0300</pubDate><guid>https://fondsites.com/physical-ai-lab/guidebooks/robot-data-collection/</guid><description>&lt;p&gt;&lt;img
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&lt;p&gt;The robot&amp;rsquo;s most valuable part may not be the arm, the battery, the camera, or the model. It may be the record of what happened when the machine tried to do real work.&lt;/p&gt;
&lt;p&gt;Physical AI learns from contact with a world that does not simplify itself for software. The cup slips because the gripper pads are dusty. The cardboard box bows under pressure. The mobile base hesitates near a glass wall. A human blocks the aisle for a moment, then moves away. A cable appears on the floor after lunch. Each moment can become useful data, but only if the system records enough context to explain what happened.&lt;/p&gt;</description></item></channel></rss>