Developing smart economy according to local conditions

This image is suspected to be AI-generated This year's government work report first proposed "creating a new form of intelligent economy." As a higher-level form of the digital economy, the intelligent economy will undoubtedly become an important support for promoting a leap in new quality productivity. China has unique advantages in developing the intelligent economy but also faces some bottlenecks. We should base our strategies on local resource endowments and industrial foundations, implement precise policies tailored to local conditions, continuously promote high-quality development of the intelligent economy, and unleash new momentum for economic growth. Developing the intelligent economy is a systematic project that requires the collaborative support of algorithms, computing power, scenarios, energy, and data. After years of accumulation, China has already established a certain foundation in these areas. In terms of algorithms, China is close to the world's forefront in the application of algorithms, with the core performance of open-source models reaching the international mainstream level. In terms of computing power, the "East Data West Computing" project is progressing in an orderly manner, and intelligent computing clusters are accelerating their layout. In terms of scenarios, relying on a comprehensive real economy system, China has seen initial results in the application of intelligent production lines, digital twin platforms for cultural tourism, financial technology, and smart healthcare. In the energy sector, China's photovoltaic capacity ranks globally, and the abundant green electricity resources in the western provinces provide low-carbon support for computing power development. In terms of data elements, China has the largest number of internet users globally and active practices in industrial digitalization, with vast amounts of Chinese data and industry data providing essential support for the training and iteration of AI models. At the same time, we still face many structural issues in algorithms, data, talent, and other areas. In terms of algorithms, most current algorithms focus on application-level optimization and are relatively lagging in disruptive technology exploration. In some regions, there is severe algorithm homogeneity, lacking deep adaptation to local industries. In the data field, the governance of data elements is still imperfect, with prominent "data island" issues in some industries, non-unified data standards, and incomplete toolchains, which restrict the release of data element value. In terms of talent, there is a shortage of high-end algorithm research and development talent, professional data labeling talent, and composite talent who understand both industry and intelligence. Additionally, the significant fragmentation of industry scenarios also restricts the large-scale implementation of intelligent technologies. These structural issues determine that the development of the intelligent economy must be based on regional differences and industrial characteristics, adopting differentiated and innovative strategies rather than a "one-size-fits-all" approach. At the regional level, the eastern regions should leverage their advantages in research and development and talent, focusing on original research and development of underlying algorithms, the integration of embodied intelligence with manufacturing, and the clustering of high-quality data labeling industries, aiming for high-end breakthroughs. The central and western regions should rely on abundant green energy to create computing power hubs, focusing on agriculture, energy, and other fields, developing dedicated algorithms that adapt to local scenarios, and tapping into local data value to assist in the coordinated linkage of national computing and electricity data. The old industrial base in Northeast China should focus on industrial restructuring, developing adaptive algorithms around the ice and snow economy, and building and expanding application scenarios. At the industrial level, different fields should innovate ideas to solve adaptation difficulties regarding algorithms, data, and other pain points. For example, the industrial sector could focus on pain points in safety inspections, equipment maintenance, and supply chains, integrating production and operational data, and using intelligent scheduling algorithms to optimize production processes In the agricultural sector, combining regional characteristics, integrating data on climate, soil, and planting, developing specialized algorithms for precise irrigation and pest warning, can solve the dilemma of "relying on the weather for food." In the financial sector, optimizing risk identification algorithms, establishing compliant data collection and usage mechanisms, and developing professional intelligent agents to strengthen risk prevention and control. In the cultural and tourism sector, integrating data on scenic spots, transportation, and cultural tourism resources, using AI algorithms to create high-precision virtual tour scenarios. In the medical field, integrating diagnostic data from grassroots medical institutions, developing lightweight diagnostic algorithms suitable for grassroots scenarios, promoting the implementation of AI-assisted diagnosis at the grassroots level, and helping to balance medical resources. Additionally, sectors such as transportation, catering services, and education can also be transformed through the empowerment of artificial intelligence technology, giving rise to new models and new formats, significantly improving operational efficiency and reducing operational costs. In summary, the development of the intelligent economy is a profound economic and social transformation. Based on local resource endowments, focusing on industrial needs, and breaking through technological bottlenecks, we can promote the deep integration of the intelligent economy with the real economy, becoming an "accelerator" for high-quality development in various regions, and helping our country seize the initiative in global competition. (Author: Hu Qimu, Deputy Secretary-General of the China Digital and Real Economy Integration 50 Forum) Economic Daily - China Economic Net Commentary Theory Channel is open for submissions. Original comments and theoretical articles can be sent to cepl#ce.cn (replace # with @). For details, see Economic Daily - China Economic Net Commentary Theory Channel Call for Papers.