算力资源紧张，国产AI如何补上“关键一环”

Core Insights - The announcement from Beijing Zhipu Huazhang Technology Co., Ltd. highlights a significant increase in user demand for AI computing power due to the launch of the GLM-4.7 series model, indicating a temporary strain on computing resources in the AI industry [1] - The AI chip market in China is projected to exceed 1 trillion yuan by 2028, accounting for approximately 30% of the global market, emphasizing the need for high-quality, domestically controlled AI computing power to seize opportunities in the AI sector [1] Group 1: Current State of Computing Power - There is a pronounced computing power gap in China, with foreign manufacturers dominating the AI computing power market, holding nearly 70% of the market share in 2024 [2] - The self-sufficiency rate of AI GPUs in China has increased from less than 10% in 2020 to approximately 34% in 2024, with expectations to reach about 82% by 2027 [2] Group 2: Causes of Supply-Demand Imbalance - The supply of computing resources in China faces multiple constraints, including limitations on high-end chip imports and a lack of competitive performance in domestic GPU chips compared to international products [3] - The fragmentation of computing resources among service providers leads to low utilization rates, exacerbating the supply-demand imbalance [3] - The rapid deployment of AI applications across various industries has resulted in an explosive growth in computing power demand, with over 13,000 projects and more than 30,000 smart factories established nationwide [3] Group 3: Solutions to Computing Power Challenges - To address the computing power challenges, there is a need to fully leverage domestic computing resources and accelerate the development of the domestic chip supply chain [4] - Recent government initiatives aim to optimize the layout of intelligent computing power and enhance service levels to resolve supply-demand issues [4] - Improving the efficiency of computing power utilization and task completion, as well as fostering collaboration among stakeholders in the computing ecosystem, is essential for achieving a competitive edge in the global AI landscape [5]