Core Insights - The rapid development of AI large models is transforming data storage from a "backstage role" in IT systems to a crucial engine of the intelligent economy [1] - The storage industry is facing cyclical fluctuations, with upstream manufacturers reducing capital expenditures, which clashes with the explosive data demand in the AI sector [1] - The establishment of unified standards and collaborative development is key to overcoming challenges in the storage industry [1] Industry Developments - The China Electronics Standardization Association's Data Storage Special Committee, led by Zhongke Shuguang, aims to draft AI storage standards and establish a Future Storage working group to enhance China's competitiveness in the global storage market [1][2] - The committee plans to gradually propose and refine AI storage technology standards, frameworks, and adaptation guidelines, particularly benefiting smaller storage companies [2] Technological Evolution - The storage industry is evolving towards an AI data platform, integrating capabilities beyond traditional data access to include inference acceleration and multi-modal knowledge base generation [4] - AI's diverse workloads demand higher storage performance, necessitating the establishment of standards for both training and inference processes [4] - The shift from traditional storage paradigms to advanced storage capabilities is essential to meet the new challenges posed by AI technologies [8] Market Dynamics - The global data storage market has surpassed 2.6 trillion yuan, highlighting the need for enhanced collaboration and the establishment of independent standards to improve China's storage industry's global competitiveness [8] - The current storage market is experiencing a significant price increase, with some products seeing price hikes of up to 100% [7] Future Directions - The construction of advanced storage centers is expected to meet new requirements, including extreme performance enhancements and seamless integration across various protocols [9] - The focus on data aggregation and flow is crucial for the intelligent transformation of industries, moving away from traditional siloed data management [9] - Collaborations, such as the one between Shuguang Storage and China Mobile, aim to address the complex requirements of data cross-regional collaboration in the AI era [10][11]

Core Insights - The rapid development of advanced computing capabilities is accompanied by a significant push towards optimizing data storage solutions, highlighting the importance of data as a strategic resource for economic growth [1][4]. Group 1: Data Storage Growth - China's data storage capacity is projected to grow at a rate exceeding 20% from 2022 to 2024, reaching a total of 1580 EB by the end of 2024, with an annual increase of 380 EB, representing a 32% year-on-year growth [3]. - The structure of data storage is evolving, with the proportion of flash storage in external storage increasing from 25% in 2023 to 28% in 2024, indicating a shift from capacity-driven to performance-oriented storage systems [3][5]. - The demand for large-scale data storage is driven by the need for low-latency and high-throughput performance, as well as the increasing volume of non-structured data [5][8]. Group 2: Industry Applications and Trends - Various industries, including manufacturing, internet, and finance, are rapidly adopting flash storage solutions, with their market share exceeding 45%, while sectors like education and healthcare are also optimizing their storage structures [3][4]. - The emergence of large model training has created a surge in demand for data storage, necessitating the collection and processing of vast amounts of multi-modal data [4][6]. Group 3: Strategic Recommendations - Recommendations for advancing data storage capabilities include establishing a unified national plan for advanced storage centers, optimizing data storage resource distribution, and enhancing data governance frameworks [6][7]. - The integration of AI data lake storage technology is suggested to unify multi-source data collection and improve data quality through advanced data governance tools [7][8]. - Emphasis is placed on the importance of developing a secure data circulation space and implementing internal storage security mechanisms to protect data throughout its lifecycle [8][9]. Group 4: Industry Experience and Implementation - Companies like Huawei are leading initiatives to build data storage centers in urban areas and create data lakes for enterprises, facilitating the aggregation and management of diverse data types [9][10]. - The focus on creating a trustworthy data circulation space is evident in collaborative projects that aim to enhance data flow and security across various sectors, including automotive and finance [9].