存力中国行北京站暨先进存力AI推理工作研讨会顺利召开

Core Insights - The article emphasizes the rapid integration of AI large models across various industries, highlighting the significance of data as a fundamental strategic resource for national development [1][3] - The event organized by the China Academy of Information and Communications Technology focused on the role of advanced storage technologies in enhancing AI model performance and addressing challenges in inference costs and efficiency [1][3] Group 1: Industry Challenges and Developments - The current AI application landscape faces significant challenges in inference costs, efficiency, and quality, making advanced storage a key factor in improving AI inference performance and controlling costs [3] - The Chinese government is prioritizing the development of advanced storage technologies, as outlined in policies like the "Action Plan for High-Quality Development of Computing Power Infrastructure," which aims to accelerate research and application of storage technologies [3] - The meeting resulted in the establishment of a working group focused on advanced storage for AI inference, with recommendations to encourage innovative storage technology development and promote deep integration of storage and computing [3][6] Group 2: Technological Innovations and Solutions - China Mobile shared insights on storage technology trends, addressing challenges such as the need for KV Cache storage upgrades and bandwidth limitations, proposing solutions like hierarchical caching and high-speed data interconnects [4] - Huawei highlighted three major challenges in IT infrastructure for the AI era: managing data effectively, ensuring sufficient computing power, and reducing costs, while introducing their UCM inference memory data management technology [5] - Silicon-based Flow discussed solutions to the slow and costly inference issues of large models, focusing on enhancing computing resource utilization and optimizing performance through intelligent gateways and KV Cache solutions [5]