国产算力首证具身大脑模型训练实力。 本文为IPO早知道原创 作者｜ Stone Jin 微信公众号｜ipozaozhidao 据IPO早知道消息，摩尔线程联合北京智源人工智能研究院（以下简称：智源）基于FlagOS-Robo 框架，依托 MTT S5000千卡智算集群 ，近日成功完成智源自研具身大脑模型 RoboBrain 2.5的全 流程训练 。 此次摩尔线程与智源研究院的深度合作，将进一步加速具身智能从实验室走向产业落地的进程，为行 业提供可复制、可规模化的"国产算力训练范式"，为中国具身智能产业提供了一个自主、开放、高 效的算力底座。 值得一提的是，这是行业内首次验证国产算力集群在具身智能大模型训练中的可用性与高效性，标志 着国产AI基础设施在应对复杂多模态任务上迈出了关键一步。通过面向多元芯片的统一AI系统软件栈 FlagOS与MTT S5000硬件集群的高效协作，该解决方案不仅"能训"，而且实现了"训得稳、训得 快"，为具身智能从实验室走向产业落地提供了坚实底座。 其中， RoboBrain是智源面向真实物理场景打造的通用具身大脑， 以统一的视觉—语言多模态架 构，为机器人在感知、认知、推理与决策上 ...

Core Viewpoint - The collaboration between Moore Threads and Beijing Zhiyuan Artificial Intelligence Research Institute has successfully completed the full-process training of the RoboBrain 2.5 model, marking a significant advancement in the field of embodied intelligence and the effectiveness of domestic AI infrastructure [1] Group 1: Technological Advancements - The training utilized the MTT S5000 kilocalorie intelligent computing cluster, demonstrating the capability and efficiency of domestic computing power in training large models for embodied intelligence [1] - The FlagOS-Robo framework, which integrates a unified AI system software stack with the MTT S5000 hardware cluster, enables stable and rapid training processes [1] Group 2: Industry Implications - The successful training of RoboBrain 2.5 signifies a critical step for domestic AI infrastructure in addressing complex multimodal tasks, positioning it as a strategic asset in the next phase of artificial intelligence development [1] - The collaboration highlights the importance of self-controlled underlying computing power as embodied intelligence emerges as a strategic high ground in the AI sector [1]

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]

人民财讯1月13日电，据摩尔线程消息，近日，摩尔线程联合北京智源人工智能研究院(简称"智源")基 于FlagOS-Robo框架，依托MTT S5000千卡智算集群，成功完成智源自研具身大脑模型RoboBrain2.5的 全流程训练。这是行业内首次验证国产算力集群在具身智能大模型训练中的可用性与高效性，标志着国 产AI基础设施在应对复杂多模态任务上迈出了关键一步。 ...

Group 1: Company Overview - Moores Threads has submitted its IPO prospectus to the Sci-Tech Innovation Board, aiming to issue no less than 44.45 million shares, which will account for at least 10% of the total shares post-issue [1] - The company operates under a Fabless model, focusing on the research, design, and sales of full-function GPU chips, while outsourcing manufacturing and testing processes [1] Group 2: Financial Performance - In 2024, the company's revenue exceeded 400 million yuan, with a compound annual growth rate (CAGR) of over 200% in the last three years [2] - Despite rapid revenue growth, the company has not yet achieved profitability, with net losses reported at 1.84 billion yuan in 2022, 1.67 billion yuan in 2023, and 1.49 billion yuan in the most recent period [8] Group 3: Technological Advancements - The company has developed the MUSA architecture, which supports AI computing acceleration, graphics rendering, physical simulation, and ultra-high-definition video processing on a single chip [2][3] - Moores Threads' products are designed to be highly compatible with existing global GPU application ecosystems, significantly reducing migration costs and ensuring stable technology application [3] Group 4: Market Position and Competition - The global integrated circuit industry is dominated by a few foreign companies, with Nvidia and AMD holding significant market shares [2] - The Chinese GPU market has grown rapidly, from 38.48 billion yuan in 2020 to an expected 163.82 billion yuan in 2024, driven by increasing demand for AI applications [7] Group 5: Future Prospects and Challenges - The funds raised from the IPO will be allocated to the development of new AI training and inference chips, graphics chips, and AISoC chips, as well as to supplement working capital [6] - The company faces challenges due to being placed on the U.S. Entity List, which restricts its ability to procure U.S. materials and technologies, potentially impacting its operations [8]