China has begun transforming farmland into a major tech hub, aiming to strengthen its role in artificial intelligence. On a 760-acre island on the Yangtze River, vast rice fields in the city of Wuhu are being cleared for server farms. An executive linked with a supplier for one of these projects described the effort as building the “Stargate of China,” referencing a $500 billion U.S. data center plan by Oracle, OpenAI, and SoftBank. While smaller in scale, it supports Beijing’s strategy to centralize scattered data facilities. Remote data centers will train LLMs while server farms near cities will handle inference In March, Beijing set out a plan to utilize existing data centers in remote areas to train LLMs. In comparison, the newly built server farms are set up closer to big population hubs. Those will handle “inference” with proximity to speed up apps for end users. Ryan Fedasiuk, former state department adviser on China, said, “China is starting to triage scarce compute for maximum economic output.” One example is Wuhu’s “Data Island”, which hosts four AI data centers run by China Telecom, Huawei, China Mobile and China Unicom . From there, the cluster is expected to serve cities in the Yangtze River Delta, including Shanghai, Nanjing Hangzhou, and Suzhou. Farther south, Guizhou will supply Guangzhou, while Qingyang in central Gansu will serve Chongqing and Chengdu. According to a city notice, 15 companies so far have put up data centers across Wuhu, with a combined investment of $37 billion. The local government is offering subsidies to cover AI chip procurement costs. The push for tighter coordination is also meant to soften China’s weaknesses against its global rival. United States export restrictions have cut Chinese groups off from modern processors and systems made by Nvidia. Local chipmakers, including Cambricon and Huawei , have faced challenges to fill the gap, in part because China’s manufacturing capacity is limited. Washington has also restricted Samsung and TSMC from manufacturing advanced artificial intelligence chips for Chinese customers. Meanwhile, U.S. tech leaders are racing ahead with hardware orders. Google, Meta, and xAI are deploying 10 of 1000 of Nvidia’s newest chips. China aims to link data centers to offset chip limitations Many Chinese artificial intelligence data centers rely on weaker chips or build advanced systems via the black market. Several people familiar with the trade say a system of intermediaries has grown across China to source Nvidia GPUs restricted for export to the country. Beijing is also trying to tap the already existing idle resources. The AI boom from 2022 onward concentrated data centers in energy-rich provinces such as Inner Mongolia and Gansu. But shortages of skilled staff and limited local demand left valuable processors sitting unused even as need spiked elsewhere. The chip purchases have been financed by the local government in many cases. They are reluctant to let go of those assets because the equipment feeds into local GDP. Moving the servers is also costly and slow. Hence, “a technical solution has to be found. That is connecting data centers,” said Edison Lee, an analyst at Jefferies. Beijing has ordered the use of networking equipment from Huawei and China Telecom to link together processors at multiple sites and form unified computing pools. China’s telecom groups are using the same mix of switches, routers, transponders, and software to shift computing power from western regions to eastern demand centers. Huawei is also working on a fix for the efficiency drag. The company is using its telecom and AI hardware expertise on a new networking approach called UB-Mesh, which it says can increase the training efficiency of LLMs over numerous computing clusters by assigning tasks more effectively over the network. Want your project in front of crypto’s top minds? Feature it in our next industry report, where data meets impact.
