商汤全面出击，冲在“AI 国产化”第一线

Core Viewpoint - The emergence of "Moore Threads IPO" alongside DeepSeek R1 signals China's capability to achieve self-reliance in AI technology, from foundational computing power to advanced models, reducing dependence on foreign technologies [2] Group 1: AI Chip Development - Moore Threads, as the first domestic GPU stock, saw its market value soar to approximately 450 billion yuan within five days of its IPO, reflecting market optimism towards China's technological self-innovation [2] - Domestic chip performance, while currently inferior to Nvidia, has shown potential for AI model training and inference through collaborative hardware-software ecosystems [2] Group 2: Model and Computing Power Integration - DeepSeek represents a focus on model-level innovation but relies on Nvidia GPUs for its computing power, highlighting the need for a comprehensive domestic solution that includes both model and computing power [3] - SenseTime is noted as the only AI-native company achieving significant results in both model and computing power, emphasizing the importance of a unified approach to AI development [5] Group 3: Strategic Collaborations - SenseTime's collaboration with Cambricon aims to optimize model core capabilities and enhance computing efficiency, which is crucial for advancing AGI in multi-modal fields [9] - The partnership with Moore Threads allows SenseTime to leverage full-function GPUs for both AI computation and graphics rendering, meeting the demands of large model training [9] Group 4: Technological Innovations - SenseTime's NEO architecture demonstrates significant capabilities, requiring only 1/10 of the data volume compared to industry standards to achieve top-tier visual perception [17] - The LightX2V framework enables real-time video generation and supports various domestic hardware, facilitating the large-scale application of AI models [18] Group 5: Systematic Approach to Domestic Innovation - The comprehensive domesticization strategy of SenseTime encompasses foundational computing power, model architecture innovation, and secure application deployment, addressing the industry's need for self-reliance [19] - The integration of domestic hardware with AI models is seen as essential for reducing reliance on foreign technologies and fostering innovation across the industry [19]