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China's central SOEs launch embodied intelligence consortium

Xinhua | Updated: 2026-02-12 15:48
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A humanoid robot conducts box-carrying training at a data collection pre-training center for humanoid robots in Hefei, East China's Anhui province, Dec 4, 2025. [Photo/Xinhua]

BEIJING - State-owned enterprises (SOEs) directly administered by the Chinese central government have formed an embodied intelligence industry consortium in an effort to accelerate the development of artificial intelligence (AI).

Under the guidance of the State-owned Assets Supervision and Administration Commission (SASAC) of the State Council, the consortium brings together central SOEs alongside private companies, universities and research institutes.

It will focus on five priority areas: strategic high-value application scenarios, high-quality datasets, key and core technologies across the industrial chain, coordinated development within the broader industry ecosystem, and the links between industry and finance to support the real economy.

The move comes amid a steady increase in AI investment among China's central SOEs over the last few years.

At a recent meeting, the SASAC said that central SOEs should expand effective investment in computing power, bolster independent innovation, accelerate breakthroughs of core technologies in key areas, and transform more innovations from prototypes to commercial products and viable industries.

Central SOEs should also deepen their open-source collaboration and accelerate their upgrades to a new AI cooperation platform, the Huanxin Community, with the aim of cultivating a mutually beneficial industry ecosystem, according to the SASAC.

The Huanxin Community was launched by the SASAC in July last year and has since seen its user base increase tenfold. It has recently attracted the participation of tech firms such as Huawei, Moore Threads and Unitree Robotics.

The open-source platform offers free public access to 2,200 domestically produced intelligent computing cards, and has aggregated more than 4,700 AI models and 1,200 datasets.

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