In recent years, Hohhot City and Lingel New Area of Inner Mongolia Autonomous Region have vigorously cultivated electronic information technology industry clusters featuring big data and cloud computing.
The picture shows the staff inspecting the equipment at the China Mobile Hohhot data center. Photo by Xinhua News Agency reporter Li Zhipeng.
* The Economic Work Conference emphasized the need to "widely apply digital intelligence technology and green technology" and "use disruptive technologies and cutting-edge technologies to give birth to new industries, new models, new kinetic energy, and develop new quality productivity". The application of digital intelligence integration takes the diffusion of digital intelligence technology as the basic fulcrum and the use of data elements as the internal form, so as to realize the leap of productivity in the application scenario of the industrial system, which is a representative form of new quality productivity.
Accelerate the iteration and application of digital intelligence technology
Strengthen the internal driving force of digital intelligence integration
In the era of digital economy, the integration, iteration and diffusion of a new generation of digital intelligence technologies such as artificial intelligence, blockchain, deep learning, and the Internet of Things have penetrated into all aspects of R&D and design, manufacturing, and customer service, bringing full-angle, all-round, and full-chain transformation to production technology and production methods, comprehensively improving the level of automation, digitalization, and intelligence in the industry, and providing a key driving force for promoting the integration and application of digital intelligence and accelerating the formation of new quality productivity.
First of all, as a general technology, digital intelligence technology has significant externality characteristics, showing strong commonality and migration between different fields, which can adapt to multi-level and multi-field needs, and realize efficient flow, transfer and integration between different industries. Secondly, the integrated application of digital intelligence technology clusters can intelligently match and visually read existing knowledge and information, enhance the interaction and matching degree of information and resources in production processes such as R&D and design, manufacturing, and logistics, effectively improve the lack of coordination and connection barriers in the production process of traditional production processes, accelerate the cross-integration of production technology and production methods, and promote the transformation of production methods to automation, digitalization and intelligence. Finally, digital intelligence technology brings higher network connectivity and organizational synergy, enhances the flexibility and adaptability of the real economy, makes business boundaries softer, fuzzier and more dynamic, strengthens the interconnection and collaboration between different fields, accelerates the transformation of business organizations to networking, flattening and platform, and promotes business entities in different industries, different industries and different regions to achieve vertical, horizontal and end-to-end business integration and deep integration.
The key to strengthening the internal driving force of digital intelligence integration is to accelerate the iteration and application of digital intelligence technologies such as artificial intelligence, big data, and cloud computing.
The first is to speed up the key research of key core technologies. Aiming at the key core technologies in the integration of digital intelligence such as high-end chips, industrial software, and quantum computing, we will increase investment in the research and development of key digital core technologies, actively deploy cutting-edge technologies and emerging industries, especially disruptive technologies, improve the source innovation power and ability of digital intelligence technology, deepen the innovative application and continuous iteration of digital intelligence technology in production, service and other fields, and accelerate the transformation of digital intelligence science and technology innovation achievements into real productivity.
The second is to build an open-source digital innovation ecosystem. Use technical means such as open application programming interfaces and open source projects to build an ecosystem of data sharing and collaborative innovation for enterprises, entrepreneurs and research institutions, establish an in-depth cooperation mechanism between industry, academia and research, promote enterprises, universities and research institutions to participate in the research and development of digital intelligence technology, strengthen the economic connection between different subjects of digital intelligence technology, generate innovation activities that connect and gather multiple subjects, and promote the innovation, diffusion and collaborative application of different digital intelligence technologies.
The third is to improve the public's digital intelligence literacy and tap the potential of the deep integration and application of digital intelligence technology. Formulate human capital policies that stimulate the vitality of digital intelligence innovation and cultivate digital intelligence skills of workers, actively train workers in digital intelligence skills and professional skills, create high-level compound digital intelligence talents, and provide practical digital intelligence application projects, interactive learning platforms and applications to simulate real scenarios, and improve the public's ability to apply digital intelligence technology.
Accelerate the release of the value of data elements
Consolidate the internal form of digital intelligence integration
As a new type of key production factor stored and processed by computer equipment in an immaterial form in the era of digital economy, data elements have technical and economic characteristics such as non-competitiveness, low replication cost, non-exclusivity, and strong externalities, which can be reused by different subjects, and generate the integration value of "data + algorithm + computing power" through deconstruction, reorganization, convergence and integration, etc., which provides basic strategic resources for consolidating the internal form of digital intelligence integration and accelerating the formation of new quality productivity.
On the one hand, the organic integration and application of data elements and traditional production factors enriches the expression form of digital intelligence integration, and shifts the mode of digital intelligence integration from geographical space to digital space. As the basic production factors of information and communication, software development, cloud computing, etc., digital elements make the production tools of the real economy change from industrial technology to digital intelligence technology, the production carrier of labor factors from production workshops to Internet platforms, and the capital factors from physical capital to digital capital, and the transformation of the form of production factors leads to the transformation of geographical space agglomeration to virtual space agglomeration, resulting in the separation of technical space and social space, and promoting the formation of a networked spatial production structure of the real economy. Enhance the synergy of digital intelligence technology and digital space network of the real economy.
On the other hand, data elements play a "medium" role in the reconfiguration and recombination of traditional production factors, resulting in a new factor processing mode and giving birth to a new form of digital intelligence integration. The embedded application of data elements has achieved more efficient, safe and transparent business operations, optimized the digital decision-making process of the real economy, realized digital intelligent production, digital intelligent management, digital intelligent marketing, etc., formed a new integrated manufacturing model such as platform design and intelligent manufacturing based on the industrial Internet, and derived new service industries such as smart logistics, smart life, and service-oriented extension, as well as new formats and models such as digital agriculture, digital exhibition, and unmanned distribution.
The key to consolidating the intrinsic form of digital intelligence integration lies in realizing the safe and orderly flow and full sharing of data elements on a large scale as possible, and accelerating the release of the value of data elements.
The first is to improve the rules for the trading of data elements and the construction of the market. Based on the nature of the data, clearly stipulate the boundaries of data ownership and the principles of income distribution in different situations, promote the structural separation and orderly circulation of data property rights, establish a unified and standardized data management system, as well as transaction technical standards and reference specifications, and expand the scope of market-oriented allocation of data elements and channels for participation in distribution according to value contributions. On this basis, a data traceability and tracking mechanism will be established, supporting third-party institutions and intermediary service organizations to strengthen the formulation of data collection and quality assessment standards, strengthening the supervision and punishment of the data trading market, and optimizing the circulation environment for accelerating the release of the value of data elements.
The second is to break down barriers to the flow of data elements and improve the level of public data openness. Accelerate the advancement of open systems for public data and mechanisms for confirming and authorizing rights, unify technical standards for cross-regional and cross-departmental data exchange and sharing, accelerate the sharing, coordination, and open development of public data foundations, and break down "data silos". In addition, the security of the use of public data is guaranteed in the system, and efforts are made to explore data transactions and interactions that open up the whole domain, the whole chain and the whole ecology, so as to realize the recreation and value enhancement of data.
The third is to speed up the improvement of laws, regulations, and institutional systems for personal privacy and data and information security. Strengthen the establishment of a data security assurance system, determine the boundaries and scales for protecting personal privacy and maintaining national network data security in the flow of data elements, strictly abide by the bottom line of data security, and formulate corresponding laws and systems to clarify the review responsibilities of third-party professional service institutions and data trading platforms, weaken the risk of privacy infringement such as data leakage and data theft, and integrate security throughout the entire process of creating and realizing the value of data elements.
Build an industrial ecology of digital and intelligent integration
Expand the application scenarios of digital intelligence integration
The application of digital technology and data elements in the industrial system enables the industry to develop from the original linear relationship between upstream and downstream, production, supply and marketing to three-dimensional, multi-dimensional networking and intelligence, which can promote the formation of a digital intelligence industry ecosystem that integrates and grows, couples and symbiosis, and multi-faces, thereby providing basic support for expanding the application scenarios of digital intelligence integration and accelerating the formation of new quality productivity.
Specifically, the digital intelligence industry ecosystem provides application scenarios for collaborative linkage and value co-creation between industries. The digital intelligence industry ecosystem is a complex ecological network based on the industrial Internet and composed of value subjects such as innovation ecosystem, production ecosystem, infrastructure, first-class institutions and users. The industrial population in the digital industry ecosystem continuously strengthens the ability of resource collection and transformation through symbiotic relationship, carries out the digital and intelligent transformation and digital intelligent management of the whole chain of traditional industries, promotes the interconnection and comprehensive perception of people, data and industry in traditional industries, realizes the organic combination of design, production, circulation, marketing, consumption and after-sales service, promotes the integration and in-depth expansion between the Internet digital industry, industry, agriculture and service industry, and realizes value co-creation through complementary advantages. Comprehensively improve the quality, efficiency and competitiveness of China's industrial development.
At the same time, the digital intelligence industry ecosystem provides application scenarios for the development of new industrialization. With the industrialization of digital intelligence as the main line, the digital intelligence industry ecosystem is driven by digital technologies such as digital platforms and digital intelligence services to realize the digital intelligence development and multi-chain integration of industrial chains, first-class chains, and value chains, so as to promote the industry to move from low value-added links to high value-added links, promote the upgrading of industrial basic capabilities and the modernization of industrial chains, improve the value chain support of new industrialization, and accelerate the construction and development of new industrialization.
The basic goal of expanding the application scenarios of digital intelligence integration is to accelerate the ecological construction of the digital intelligence industry with chain-network integration according to the requirements of the digital intelligence industry.
The first is to actively build a digital intelligence industry ecological information database. With national parks and development zones such as the National Digital Economy Innovation and Development Pilot Zone as carriers, the collection, integration, classification, and structuring of user information are carried out according to user needs, and a system for the traceability, entry, registration, reporting, integration, and classification of ecological information in the digital intelligence industry is established. On this basis, we should increase support for platform-based industrial innovation organizations, support the construction of carriers such as industrial incubators, industrial accelerators, and industrial Internet, and support the development of innovative organizations such as industrial innovation communities and industrial ecology.
The second is to build a value chain that can realize the decoupling and reorganization of production, operation, products and other links, so as to provide basic conditions for building a digital intelligence industry ecosystem with chain-network integration. Explore new opportunities for digital intelligence integration from different value chain links such as value input, value creation, and value output, promote the collaborative integration of data elements and traditional production factors in the value input link, drive the networking, digitization, and intelligence of the manufacturing and service process with digital intelligence technology in the value creation link, and continuously meet the needs of a higher level of intelligent life with the continuous iteration of digital value in the value output link, so that user needs can truly become the core of value.
The third is to create a high-quality development environment and realize the synergy and symbiosis of all entities in the digital industry ecosystem. Improve financing services, market promotion, legal consultation, etc., and provide necessary technical support for the synergy and symbiosis of all entities. Build a digital intelligence industry symbiosis network around digital infrastructure, strengthen the construction of digital infrastructure such as cloud computing, artificial intelligence, industrial Internet, and data centers, promote the efficient complementarity and collaborative linkage of all entities in the digital industry ecosystem, and expand the application scenarios of digital intelligence integration.
The authors: Xiaojing Chao is a professor at the School of Economics and Management, Northwest University, and Rujing Yuan is a doctoral candidate at the School of Economics and Management, Northwest University
*: Economic Information Daily.