Artificial intelligence technology, as a universal technology in various fields and industries, is leading a new round of technological revolution and industrial transformation. Relying on carriers such as the National New Generation Artificial Intelligence Innovation Development Pilot Zone and the National Artificial Intelligence Innovation Application Pilot Zone, Beijing, Guangdong, Zhejiang and other places have accelerated the aggregation of industrial innovation resources around the artificial intelligence industry chain, becoming the highland of China's leading artificial intelligence industry cluster. Recently, the State Council executive meeting approved the "Opinions on Deepening the Implementation of the 'Artificial Intelligence+' Action, 'emphasizing the need to promote the deep integration of artificial intelligence technology innovation and industrial innovation. Relying on the advantages of China's complete industrial system, large market size, and rich application scenarios, building an AI industry cluster with international competitiveness has become the key to building a national competitive advantage. The five major systems of artificial intelligence industry cluster refer to the new organizational form formed by the aggregation of enterprises and related entities in the geographic and digital fields of the artificial intelligence innovation chain and industry chain. An AI industry cluster with international competitiveness should include at least five subsystems: industrial technology innovation subsystem, industrial chain and application innovation subsystem, digital infrastructure subsystem, talent and capital support subsystem, and cluster governance and open collaboration subsystem. The industrial technology innovation subsystem takes knowledge creation and application as its core, linking innovation entities such as universities, research institutions, and enterprise R&D centers, focusing on basic research and cutting-edge breakthroughs in artificial intelligence technology, covering key links such as algorithms, models, chip design, operating systems, and software frameworks, building original innovation capabilities for the future, and ensuring efficient knowledge flow of key core technologies in artificial intelligence. The industrial chain and application innovation subsystem takes value creation and distribution as its core, relying on diverse industry entities such as leading enterprises, platform enterprises, specialized and innovative enterprises, and digital commerce enterprises to jointly build a complete value chain from hardware infrastructure, software platforms to application scenarios, promote the widespread transformation and diffusion of artificial intelligence technology achievements, and ensure the continuous release of value streams. The digital infrastructure subsystem focuses on supporting data essentialization and value. The data center, cloud computing and edge computing platforms, data trading platforms and computing service providers jointly build a digital base for data collection, storage, computing, transmission, governance and sharing, forming a computing network covering "cloud edge end" to ensure the security of data flow. The talent and capital support subsystem focuses on the supply of human capital and financial capital. Through the talent cultivation and flow mechanisms of universities, research institutions, and enterprises, as well as capital support such as venture capital, industry funds, and government guidance funds, it provides composite talents and diversified funding sources for the artificial intelligence industry cluster, ensuring efficient allocation and continuous supply of talent and capital flows. The cluster governance and open collaboration subsystem focuses on institutional supply and open cooperation, and is jointly constructed by government agencies, industry associations, standardization organizations, and international cooperation platforms to establish a sound policy system, standard rules, and governance framework. It creates a responsible and sustainable institutional environment and promotes open collaboration across regions, industries, and borders, ensuring smooth connection and efficient coupling of knowledge flow, value flow, data flow, talent flow, and capital flow inside and outside the cluster. The five subsystems are led by knowledge innovation, centered around industry chain collaboration, based on digital infrastructure, guaranteed by talent and capital, and guided by governance and collaboration. They deeply integrate the innovation chain, value chain, data chain, talent chain, and capital chain to continuously enhance the core competitiveness of the artificial intelligence industry cluster. The three modes of innovative development of industrial clusters to build an AI industrial cluster with international competitiveness need to start from the three dimensions of "technology market system", thus forming three innovative development modes: technology innovation breakthrough driven, application scenario innovation driven, and institutional supply empowerment. The breakthrough driven model of technological innovation is based on the original innovation and cutting-edge breakthroughs of artificial intelligence as the development core. By gathering innovative entities such as research institutions, universities, and leading enterprises, it forms a strong R&D capability and knowledge flow network, and promotes independent breakthroughs in key core technologies such as algorithms, models, chips, operating systems, and frameworks. With the accumulation of technology and the enhancement of spillover effects, it gradually drives the improvement of upstream and downstream supporting facilities in the industrial chain, forming a cluster of artificial intelligence innovation highlands. For example, the artificial intelligence cluster in Silicon Valley, relying on top universities such as Stanford University and the University of California, Berkeley, as well as companies such as OpenAI, NVIDIA, and Google DeepMind, has formed a network for basic research and application of artificial intelligence in Silicon Valley, gradually forming a complete cycle system of "venture capital entrepreneurship incubation technology breakthrough industrial application", and has long occupied the high ground of technological innovation in the artificial intelligence industry. The application scenario innovation driven model emphasizes the use of application demand and scenario openness as the driving force. Through large-scale opening of application scenarios, a market environment driven by real demand is formed, which helps enterprises iterate technology in solving scenario problems, promotes upstream and downstream enterprise clustering and collaboration, and achieves a virtuous cycle of "scenario technology industry". For example, the Hangzhou artificial intelligence industry cluster, which gave birth to the "Six Little Dragons", has accumulated a large number of enterprises, accumulated a large amount of data, and broken through a large number of technologies, gradually becoming a leading and internationally influential artificial intelligence industry cluster in China with a strong foundation in the digital economy, as well as rich application scenarios such as smart cities, smart logistics, medical health, and financial technology. The institutional supply empowerment model focuses on institutional supply and open collaboration, creating a favorable development environment through a sound policy system, standard rules, and ethical governance framework. At the same time, it promotes cross regional, cross industry, and cross-border collaboration, forming a high-level open innovation network. For example, the Canadian government launched the world's first national level artificial intelligence strategy in 2017, providing large-scale funding for AI research, talent development, and ethical standards. With advanced innovative institutional supply, the Montreal artificial intelligence industry cluster in Canada has gathered top scholars from around the world, established a global open partnership organization for artificial intelligence, formed a diverse industrial ecosystem and a thriving entrepreneurial environment, and gradually emerged as a thriving artificial intelligence innovation highland. To build an AI industry cluster with international competitiveness, it is necessary to identify the four key points and achieve a balance between technology driven and scenario driven approaches, effective market and government coordination, and synchronous security and development. One is to strive for innovation and create an AI innovation highland with international competitiveness. We need to fully leverage the advantages of the new national system, establish a resource allocation mechanism that supports breakthroughs in cutting-edge technologies, and ensure the supply of high-quality technology from the source. Strengthen the position of enterprises as the main body of innovation, promote the deep integration of industry, academia and research, establish a group of AI collaborative innovation networks and platforms with enterprises as the main body, and form a group of AI enterprises that master key core technologies. The second is to strengthen the application and accelerate the process of empowering new industrialization with artificial intelligence. We need to fully leverage the advantages of China's complete industrial system, large market size, and rich application scenarios, continuously promote the deep integration of artificial intelligence technology innovation and industrial innovation, focus on key industries to drive industrial chain collaboration and technological iteration through large-scale applications, actively and orderly promote the layout of "going global", and make every effort to climb to the middle and high ends of the value chain, achieving efficient circulation of value streams. The third is to strengthen the foundation and build a high-level digital infrastructure and data flow system. Further improvement is needed in computing power networks, data centers, and cross domain data platforms to achieve controllable data collection, storage, governance, sharing, and security; Establish data markets, data coupons, and cross domain data spaces to ensure efficient operation of data flows within and outside the cluster, supporting technological innovation and application implementation. The fourth is to strengthen the ecosystem and build an industrial ecosystem with international attractiveness and competitiveness. We need to take the integration of education, technology, and talent as the fundamental guidance, establish a multi-level mechanism for cultivating, introducing, and flowing artificial intelligence talents, optimize the layout of government guidance funds, venture capital, and industry funds, improve policies, standards, intellectual property, and ethical and security governance, promote international standard setting and cross-border cooperation, and strengthen compliance and risk management. (New Society)