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生成式AI驱动“边缘演进” 超八成 CIO寻求边缘云服务
Zhong Guo Jing Ying Bao· 2025-09-23 18:44
Group 1 - The core viewpoint of the articles emphasizes that traditional centralized cloud services are inadequate for the low-latency, high-concurrency, and cost-effective computing demands of generative AI, leading to a shift towards edge computing as a solution [1][2][3] - A recent study by Akamai and IDC indicates that 31% of surveyed organizations in the Asia-Pacific region have deployed generative AI in production, while 64% are in testing or pilot phases [2][3] - The existing cloud architecture reveals significant deficiencies, particularly in handling massive intelligent computing demands, resulting in latency issues and bottlenecks [3][4] Group 2 - Companies face challenges in managing multi-cloud environments due to inconsistent tools, fragmented data management, and the need for seamless data transfer across platforms, especially in cross-border scenarios [4][5] - The report highlights that many enterprises are constrained by legacy infrastructure that cannot adapt quickly to the explosive demands of generative AI applications [4][5] - The edge computing market is experiencing significant growth, with organizations recognizing the need to integrate edge services into their infrastructure strategies to remain competitive and compliant [5][6] Group 3 - Edge computing is defined as an open platform that integrates network, computing, storage, and application capabilities close to data sources, addressing key needs in digital transformation [6][7] - The architecture of edge services allows for distributed computing, reducing latency and enhancing service stability by processing data closer to users [7][8] - Predictions indicate that by 2028, the annual compound growth rate (CAGR) for public cloud services at the edge will reach 17%, with total spending expected to hit $29 billion [7][8]