Computing power is becoming the invisible engine behind a new generation of intelligent machines, and in Hebei province, a robust digital foundation is enabling robots to see, think, and act with increasing sophistication. By combining high-quality data collection with powerful processing capabilities, the region is transforming artificial intelligence from a concept into practical, real-world applications. This report explores how two key cities in Hebei, Xiong'an and Shijiazhuang, are leveraging this infrastructure to make robotic systems significantly more capable.
Where the smartest robots are built
The journey begins in Xiong'an New Area, at a facility dedicated to embodied intelligence data collection—essentially a training school for robots. One robot, named Lingxi, is preparing to perform a Tai Chi routine, a sequence that might seem simple but requires tens of thousands of computational iterations just to complete the opening movements. This facility is designed to train robots through five major scenarios, including industrial, household, and commercial settings, with more than ten different types of robots undergoing data collection and skill development. Instead of cold laboratories, the training field features 1:1 replicas of real kitchens, warehouses, and retail counters, allowing robots to practice in lifelike environments. Each grasp and each step generates high-quality data essential for model training, with the true purpose being the capture of real-world action data rather than just the physical movements themselves.
The core advantage of this Xiong'an facility is its support for multiple brands and varied scenarios, enabling different robot manufacturers to conduct unified data collection. A centralized platform manages the entire process, ensuring all robots receive consistent data annotation and collection. This includes simulated data, real-machine data, and model-free data, all produced and built in one place to meet the diverse needs of model companies, hardware manufacturers, and application enterprises. By standardizing collection and labeling, different brands can share the same foundational data resources, addressing a critical industry-wide challenge known as the "data scarcity" problem. With insufficient high-quality data and non-unified standards, even the most powerful computing cannot function effectively; this facility aims to solve that problem at its source. Each machine produces roughly 200 data entries daily, which are then uploaded to a trusted urban data space, making them available for purchase and use by other enterprises.
From training grounds to real-world applied settings
After robots complete their training in Xiong'an, the next step is employment in the field. Two hundred kilometers away, in Shijiazhuang, a smart manufacturing company demonstrates this progression. In its research and development center, at least three types of robots are actively working: a palletizing robot performing pick-and-place demonstrations, an autonomous mobile robot navigating its environment, and a cleaning robot operating independently. These machines demonstrate advanced obstacle avoidance capabilities, smoothly navigating around unexpected obstructions in their path. The company offers four products, including a collaborative palletizing robot that can process over 200 items per day, achieving two to four times the efficiency of manual labor. This efficiency translates into significant real-world benefits; for example, a mining support equipment manufacturer in Hebei improved its production capacity utilization from 70% to 95% and reduced loss rates from 4% down to 0.8%. These improvements represent tangible profit increases for manufacturers.
The company attributes its success to full-stack self-development, having made deep research investments across the robot's core components and underlying algorithms, effectively controlling the "brain," "cerebellum," and body of its products. This strategy of mastering core technology allows for lower costs and greater competitiveness when robots are integrated into homes and businesses. However, the company's ambition extends beyond factory applications. Engineers are currently testing delivery robots in simulated community environments, including roadways, elevators, and corridors, to refine their navigation and obstacle avoidance systems. The company views industrial applications as a starting point, not a final destination, and is targeting the "last 100 to 500 meters" of delivery logistics. Its key differentiator lies in cross-scenario, all-terrain navigation—to solve the common problem of outdoor robots being unable to transition indoors and achieve precise positioning, navigation, and autonomous driving. The ultimate goal is to create robots that are smarter and more adaptable, bringing them practically into households.
A strong foundation and a bright future ahead
Hebei's strategy combines its solid computing capability foundation with a rich industrial landscape to move embodied intelligence from theoretical concepts to practical implementation. In August, the province issued an action plan for AI plus manufacturing, emphasizing the integration of computing power, algorithms, and data to drive industrial intelligence. Industry experts note that embodied intelligence is a natural extension of AI development, with computing power being a core support element. Hebei has accumulated a substantial industrial and manufacturing base and has consistently led the country in computing infrastructure for years. The vision is to build a more heterogeneous and diverse computing pool, develop secure, stable, green, and low-cost computing, and create open-source data center testing grounds. These advantages are expected to cultivate a group of leading AI-plus-industry enterprises, and the region is positioned for promising growth in intelligent technology.