Lei Jun and Ubtech Share the Vision: Making Robots Skilled Workers - 让一部分人先看到未来

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Let robots become skilled workers. Lei Jun and Ubtech have the same idea.

源媒汇2026-03-06 20:52

Making money is the top priority.

"Compared with performance shows, humanoid robots should be put to work in factories to do real things." This industry consensus found a more specific foothold at the National Two Sessions in 2026.

At the recent Two Sessions, Lei Jun, a National People's Congress deputy and the founder of Xiaomi Group, submitted five proposals in one go. One of them directly focused on those somewhat clumsy yet futuristic figures in the workshops - humanoid robots. He suggested promoting the transformation of humanoid robots from "apprentices" to "full - time workers" and accelerating their application in intelligent manufacturing. The market's keen perception has already been translated into action. In the past two years, "entering factories to work" has become a training method for leading humanoid robot companies. Products of companies such as UBTECH, Tesla, Xiaomi, Zhipu Robotics, and Unitree have entered different factory scenarios. Undoubtedly, UBTECH, headquartered in Shenzhen, is the benchmark in this "working wave."

In NIO's factory, the 1.7 - meter - tall Walker S series products of UBTECH are conducting quality inspections on door locks with millimeter - level precision. In Geely's 5G smart factory, they are shuttling between the three - dimensional warehouse and the general assembly workshop, coordinating the handling of large - sized material boxes. Thanks to this real - world factory training experience, UBTECH's humanoid products have accumulated thousands of hours of training time and sufficient real - environment data, which has become the core confidence for its technological iteration.

However, there is still room for improvement in the efficiency of humanoid robots. Recently, when being interviewed by the media, Zhou Jian, the founder of UBTECH, admitted that currently, in simple tasks such as loading and unloading and intelligent handling, the completion rate of a single product has reached 99%. But compared with human efficiency, it is expected to reach 60% by 2026.