国产“大算力”在手，乘胜追击万亿参数大模型？

Core Viewpoint - The development of domestic AI computing power is crucial for the evolution of large AI models, with the recent establishment of a significant domestic AI computing pool marking a historical convergence in this field [1][3]. Group 1: Domestic AI Computing Power - The recent "National AI Computing Power Pool" in Zhengzhou has become the largest domestic AI computing pool with a deployment of 30,000 cards, operational as of February 5 [1]. - The demand for large AI models is driving the evolution of domestic computing power towards "ten-thousand card" level computing clusters, as AI models with trillions of parameters are becoming the new standard [3][4]. Group 2: Growth of Large Models - By December 2025, the number of large models registered with China's National Cyberspace Administration is expected to reach 748, with many models exceeding the trillion-parameter scale [4]. - The scaleX ten-thousand card super cluster has been deployed for training trillion-parameter models and high-throughput inference, indicating a significant advancement in AI computing capabilities [4]. Group 3: Challenges and Innovations - Despite the growth of domestic computing power, challenges remain, such as the late start of domestic AI chips compared to NVIDIA GPUs and the need for additional adaptation for open-source models [5]. - The current computing ecosystem is fragmented, with barriers between intelligent computing centers, which limits the performance of domestic computing infrastructure in heterogeneous environments [5]. Group 4: Collaborative Innovation - A consensus is forming around an open collaborative approach in the AI industry, with stakeholders from model vendors and computing infrastructure providers working together on a joint initiative for "domestic large computing power + domestic large models" [6]. - The concept of "open collaboration" is becoming a central theme in the evolution of AI computing in China, potentially leading to a restructuring of competitive rules in the industry [7].