Group 1 - The core viewpoint of the news highlights the active trading and significant inflow of funds into the E Fund Sci-Tech Chip Design ETF (589030), with a turnover of 10.97% and a transaction volume of 46.7362 million yuan as of January 29, 2026 [1] - As of January 28, the latest scale and share of the E Fund Sci-Tech Chip Design ETF reached a new high since its establishment, with a net inflow of 82.7062 million yuan [1] - Over the past five trading days, there have been net inflows on four days, totaling 141 million yuan, indicating strong investor interest [1] Group 2 - Alibaba has launched its self-developed high-end AI chip "Zhenwu 810E," marking a significant step in its vertical integration strategy, with the chip featuring 96G HBM2e memory and already deployed in multiple clusters for over 400 clients, including State Grid and the Chinese Academy of Sciences [1] - The emergence of super node server clusters is accelerating the penetration of domestic AI infrastructure, with the Huawei Atlas 900 A3 SuperPoD cluster achieving 1.7 times the total performance of NVL72 and a memory capacity 3.6 times greater, with over 300 sets deployed by September 2025 [2] - The newly released Atlas 950 and 960 SuperCluster have achieved scales of over 500,000 and 1 million cards respectively, indicating a systemic leap in domestic AI computing capabilities [2]

Core Viewpoint - The collaboration between Moore Threads and Beijing Zhiyuan Artificial Intelligence Research Institute has successfully completed the full training process of the self-developed embodied brain model RoboBrain 2.5, marking a significant advancement in the usability and efficiency of domestic computing clusters for training large models in the field of embodied intelligence [1] Group 1 - The training utilized the FlagOS-Robo framework and the MTT S5000 computing cluster [1] - This achievement is the first verification of the applicability and efficiency of domestic computing clusters in training embodied intelligence large models within the industry [1] - The development signifies a critical step for domestic AI infrastructure in handling complex multimodal tasks [1]

Core Insights - The article highlights the recent completion of nearly 100 million RMB in Series B funding for Jilv Technology, led by Henan Investment Group and Zhipu Ecological Fund, with continued support from existing investors, indicating strong recognition of the company's long-term value [2] - The funds raised will be utilized for product technology research and development, as well as attracting high-level talent to strengthen the company's technological leadership in the AI computing cluster sector [2] Company Overview - Jilv Technology is recognized as the fastest-growing independent AI computing cluster provider in China, leading innovative developments in AI infrastructure [2] - The company has developed the Galaxy intelligent autonomous computing system, which breaks the closed ecosystem of AI infrastructure, offering high-performance, full-stack intelligent computing cluster products and services [2] Technological Advancements - Jilv Technology has delivered a total computing power scale of 30 clusters, exceeding 76,000 GPUs [3] - The company is continuously developing domestically produced high-throughput unified communication systems, including a fully domestic 102.4T near-light packaged white-box switch, achieving a generational leap in performance from the current 25.6T switch to international mainstream standards [3] - Innovations in priority scheduling, congestion control protocols, and hardware capabilities have led to a 5% performance improvement in end-to-end computing power utilization and 100% rapid diagnosis of cluster faults with automated operations [3] Future Plans - Jilv Technology aims to build a robust, secure, and controllable digital infrastructure for the next generation of domestic AI computing power, providing critical support for a safe and controllable AI industry ecosystem in China [4]