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人工智能与大模型专题:央国企科技创新系列报告之四
CambriconCambricon(SH:688256) CMS·2025-07-09 13:00

Group 1: AI Industry Development - The AI industry follows a "technology-hardware-terminal-application" development model, with a shift from communication networks to large model theoretical research[1] - Domestic chip manufacturers are accelerating technological breakthroughs, enhancing the application ecosystem, and driving the deep integration of generative AI across multiple industries[2] - The global large model technology is entering a deep competitive phase, with differentiated development paths between China and the US[2] Group 2: AI Chip and Hardware Investment - AI chips are the cornerstone of the large model industry, characterized by long R&D cycles, high technical barriers, and significant investment costs[2] - China has established a basic layout in GPU, ASIC, and FPGA chips, meeting standards for various application scenarios[2] - Investment opportunities exist in the AI industry chain, including optical modules, power distribution technology, and liquid cooling technology[2] Group 3: Market Trends and Opportunities - The domestic AI industry is experiencing a strategic transformation from "software-hardware decoupling" to "full-stack collaboration"[2] - The market for AI software ecosystems is still dominated by foreign open-source frameworks, but domestic companies are accelerating their AI ecosystem layout[2] - The procurement rate of domestic large models in key industries like finance and telecommunications has exceeded 45%[2] Group 4: Risks and Challenges - Risks include slower-than-expected technological iterations, industry growth rates, and potential policy risks[2] - The need for high-quality data and standards in model training remains a challenge for the domestic AI industry[2]