The '2024 China Intelligent Computing Cloud Ecosystem Influence Matrix Report' is now available

The '2024 China Intelligent Computing Cloud Ecosystem Influence Matrix Report' comprehensively evaluates key dimensions such as market trends, technical paths, and strategic layouts, and establishes core roles including 'Full-Service Leader', 'Technology Pioneer', 'Strategic Visionary', and 'Market Dominant'. The matrix aims to clarify the development stages of the intelligent computing cloud industry and the strategic positioning of service providers, align the perspectives of both supply and demand sides, guide the growth direction of enterprises, and promote the high-quality development of the intelligent computing cloud industry. The research work provides strategic references for intelligent computing cloud procurement, quickly recognizes the core capabilities of service providers, enhances the market influence of leading service providers, constructs a complete intelligent computing cloud service supply system, and forms an efficient and healthy market ecosystem.

Source: Analysis by China Information and Communications Technology Research Institute and Frost & Sullivan

The '2024 China AI Cloud Ecosystem Influence Matrix Report' covers three core dimensions: technical strength, market performance, and strategic planning. It combines quantitative scores and characteristics of various AI cloud service providers to establish multiple roles such as full-stack leaders, technology pioneers, strategic visionaries, and market winners. This report provides a precise portrait of AI cloud service providers for enterprises, helping them make informed decisions in the complex market environment. Currently, the matrix has formed a three-dimensional panoramic view, including a multi-dimensional matrix display of sub-capability evaluation models and AI cloud service provider supply capabilities.

According to Frost & Sullivan and the China Academy of Information and Communications Technology, the current development of intelligent computing cloud services exhibits the following characteristics:

1.In terms of the market, the diversified applications of intelligent computing power are profoundly changing various industries, especially the internet and service sectors. They greatly enhance business efficiency and innovation capabilities through efficient data processing and enhanced decision support.The application of intelligent computing power in various industries is showing significant diversity, with the internet industry leading at 53.27%, mainly focusing on big data processing and real-time content recommendation. The service industry (17.8%) and government (8.67%) respectively utilize intelligent computing power to optimize customer services and public management efficiency. The manufacturing and telecommunications industries each account for 4.16%, driving intelligent manufacturing and network performance, respectively. Education (4.00%) and finance (3.67%) are concentrated on personalized learning and risk management. Although the proportion in other industries is smaller, the widespread application of intelligent computing power is continuously driving innovative development in various fields.

2,In terms of technology, the optimization of the efficiency of intelligent computing infrastructure depends on the improvement of communication and storage capabilities to ensure that large-scale GPU clusters operate efficiently in distributed training.The computing power efficiency of intelligent computing infrastructure is significantly affected by cluster utilization, high-speed interconnect networks, and storage optimization. To effectively enhance computing power, it is necessary to break through bottlenecks in communication and storage by increasing communication performance, expanding storage capacity, and optimizing bandwidth. Especially in distributed training, the improvement of acceleration ratios depends on reducing inter-card communication latency and increasing bandwidth. In addition, network stability and scalability, as well as efficient operation and maintenance management, are key factors in ensuring the efficient operation of large-scale GPU clusters and the smooth progress of training tasks.

3,In terms of strategy, the competitiveness of the intelligent computing cloud industry depends on strengthening brand trust and resource integration to address operational challenges and expand market applications.The development of the intelligent computing cloud industry relies on high-end technical talents and a stable hardware supply chain. At the same time, it faces the challenges of rapid technological iteration and the 'black box' problem, which makes brand trust the core of corporate competition. A strong brand influence can significantly enhance bargaining power and improve gross profit margins. Currently, the main challenges faced by intelligent computing clouds include high operational costs, substantial investment in core technology research and development, and the immaturity of infrastructure construction. These factors collectively restrict its scale application in broader markets. Looking ahead, the strategic development of intelligent computing clouds will focus on the integration of hardware and software resources. By managing different levels collaboratively, from management to platform to application, it will provide comprehensive computing power services to support the development of the entire industry.

The report also makes the following key findings:

Integrated development of intelligent computing cloud infrastructure, development tools, and application softwareCurrently, the development of artificial intelligence driven by large models is still in its infancy, with scattered industries and insufficient collaborative effects. The purpose of the intelligent computing cloud service is to coordinate and integrate the overall architecture of scattered hardware and software facilities, aiming to minimize efficiency losses caused by heterogeneous resources. The intelligent computing cloud architecture achieves this through the collaboration of intelligent computing management, engineering platform, and application layers, uniformly allocating GPUs, algorithm frameworks, resource management, and AI development platforms. It covers all aspects from computing power management to task scenarios, providing multi-dimensional support including application generation, model training, and security assurance. With this architecture, the intelligent computing cloud can provide integrated and flexible computing support for different industries, promote the implementation of artificial intelligence applications, accelerate industry intelligence upgrades, and strive to provide the highest quality intelligent computing service experience in the era of artificial intelligence.

Source: Analysis by China Information and Communications Technology Research Institute and Frost & Sullivan

The development of intelligent computing cloud needs to overcome challenges in data security, technical standardization, and service management to ensure system stability and promote sustainable development.In its development, intelligent computing cloud faces multiple challenges such as data security, technological innovation and service deepening, as well as cloud service standardization. With the growth in data storage and sharing needs, ensuring data security and privacy has become crucial. This requires enhancing protection levels through technologies such as encryption and hierarchical access control. At the same time, interoperability issues caused by the lack of technical standards limit cross-platform data migration and service expansion. There is an urgent need to strengthen technical interoperability and industry standard construction. In addition, the large-scale deployment of cloud services brings management complexity, performance assurance pressure due to diverse computing tasks, and the need for optimizing network transmission efficiency, all of which pose higher requirements for the stability and efficiency of intelligent computing cloud. In the future, continuous deepening is needed in aspects such as security assurance, standard setting, and technological innovation to promote the sustainable development of the intelligent computing cloud ecosystem.

Source: Analysis by China Information and Communications Technology Research Institute and Frost & Sullivan

With the acceleration of digital and intelligent transformation, the demand for cloud services among large enterprises across the country has increased significantly. This is mainly due to the large amount of data resources accumulated by enterprises during this process, which has led to the formation of a new data-driven decision-making and operational model.This transformation not only reduces operating costs, enhances competitiveness, but also promotes innovation. In contrast, small and medium-sized enterprises (SMEs) face challenges such as resource and budget constraints and insufficient technical capabilities during the cloud adoption process. These factors significantly limit their cloud service adoption rate. To reduce costs and improve efficiency, SMEs urgently need to utilize the pay-as-you-go model and powerful data analysis capabilities of intelligent computing clouds. This not only helps them optimize cost control and operational efficiency but also enables them to accurately identify business opportunities and optimize decision-making processes through machine learning and predictive analysis tools on the intelligent computing cloud platform. It enhances customer experience and market competitiveness, thereby promoting the sustainable development of the intelligent computing cloud industry.

Source: Analysis by China Information and Communications Technology Research Institute and Frost & Sullivan