{"id":224716,"date":"2026-05-17T19:48:58","date_gmt":"2026-05-17T19:48:58","guid":{"rendered":"https:\/\/teknomers.com\/en\/some-chinese-humanoid-robots-are-already-attending-school-the-goal-is-to-prepare-them-for-real-world-work\/"},"modified":"2026-05-17T19:49:00","modified_gmt":"2026-05-17T19:49:00","slug":"some-chinese-humanoid-robots-are-already-attending-school-the-goal-is-to-prepare-them-for-real-world-work","status":"publish","type":"post","link":"https:\/\/teknomers.com\/en\/some-chinese-humanoid-robots-are-already-attending-school-the-goal-is-to-prepare-them-for-real-world-work\/","title":{"rendered":"Some Chinese Humanoid Robots Are Already Attending “School”: The Goal is to Prepare Them for Real-World Work"},"content":{"rendered":"\n
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Chinese Humanoid Robots Enter “School” to Learn Real-World Skills<\/h2>\n

Recent advancements in artificial intelligence have focused largely on algorithms that can summarize text, generate programming code, or create images. However, the transition of AI into the physical realm brings a new set of challenges. Unlike traditional models, humanoid robots must do more than just process data; they must actively observe, imitate, make mistakes, and gather data on real movements<\/strong>. Consequently, the next frontier in robotics lies not merely in crafting more agile bodies or refined hands, but in developing comprehensive systems that allow them to function effectively outside controlled laboratory settings.<\/p>\n

The Data Collection Factory in Fujian<\/h2>\n

This innovative system is coming to fruition in Fujian province, where the first large-scale data collection facility has recently entered the test phase. Located in Area D of Fuzhou Software Park, this facility, established by Fujian Jufu Technology, is home to nearly 30 robots being trained through real-world tasks such as cleaning tables, sorting fruits and vegetables, and disposing of parcel boxes. Operators, referred to as \u201cteachers\u201d by local sources, utilize virtual reality devices to guide the robots through these exercises, allowing them to replicate specific actions. When an operator raises their arm, the robot mirrors the movement to successfully interact with objects like a paper cup. Each action is meticulously recorded using cameras and sensors, capturing details such as joint angles and grip pressure.<\/p>\n

The Intricacies of Robot Training<\/h2>\n

The fascinating aspect of this “school” is the level of sophistication involved. According to data collection engineer Jiao Shiwei, even the smallest movements require extensive learning through data accumulation. Each action must be tailored to the robot’s unique characteristics to determine the most effective trajectory for movement. The concept of \u201cgeneralization\u201d becomes crucial here\u2014the robot must apply learned skills in varied environments, as real-life conditions are rarely identical. For example, while picking up a glass or cleaning a table seems straightforward, variations such as different glass shapes or sizes, surfaces, and types of stains challenge the robot’s adaptability.<\/p>\n

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Addressing the Data Bottleneck<\/h2>\n

The essence of this training emphasizes that robots are now in a “race for data.” Unlike AI advancements that have previously relied on available digital materials, the field of robotics demands the generation of novel examples through real-world interactions. As reported by Xinhua, the limitations of humanoid robots now lie not just in their hardware, but also in refining their cognitive frameworks through training in practical environments.<\/p>\n

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Building an Ecosystem for Humanoid Robots<\/h2>\n

The industrial implications of this initiative reveal why seemingly simple tasks can lead to substantial infrastructure evolution. According to Jufu Technology CEO Chen Yishi, these factories enable support for end-to-end models and applications in varied environments. The objective is to transition AI robots from functioning like traditional machinery restricted to fixed sequences, to becoming guided systems capable of making autonomous decisions<\/strong> based on real-life learning experiences.<\/p>\n

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Founded in September 2025, Jufu Technology is positioned as a combination of data generation and self-development. Its ambitions extend beyond merely accumulating movement examples; the aim is to create a robust ecosystem that encompasses algorithmic expertise, data resources, and collaboration within the industrial framework. Yishi hints that future products may focus on industrial manufacturing, safety inspections, research, and education, portraying these as long-term goals rather than immediate deliverables.<\/p>\n

In conclusion, the integration of humanoid robots into learning environments represents an innovative approach to bridging the gap between AI theory and practical application, heralding a new era for robotics.<\/p>\n<\/div>\n


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General News – 2<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Chinese Humanoid Robots Enter “School” to Learn Real-World Skills Recent advancements in artificial intelligence have focused largely on algorithms that can summarize text, generate programming code, or create images. However, the transition of AI into the physical realm brings a new set of challenges. Unlike traditional models, humanoid robots must do more than just process […]<\/p>\n","protected":false},"author":1,"featured_media":224717,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36399],"tags":[4367,2394,1135,30870,4791,51158,21073,148,319],"class_list":["post-224716","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology","tag-attending","tag-chinese","tag-goal","tag-humanoid","tag-prepare","tag-realworld","tag-robots","tag-school","tag-work"],"_links":{"self":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/224716","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/comments?post=224716"}],"version-history":[{"count":1,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/224716\/revisions"}],"predecessor-version":[{"id":224718,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/posts\/224716\/revisions\/224718"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media\/224717"}],"wp:attachment":[{"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/media?parent=224716"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/categories?post=224716"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/teknomers.com\/en\/wp-json\/wp\/v2\/tags?post=224716"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}