Core Insights - The rapid development of the AI industry is creating a massive demand for computing power, but the low utilization rate of global computing resources is becoming a significant bottleneck for industry growth [1] - Huawei's new AI container technology, Flex:ai, aims to address the issue of computing resource waste by allowing a single GPU/NPU card to be divided into multiple virtual computing units, improving resource utilization by 30% [1][2] - Flex:ai is positioned to compete with Nvidia's Run:ai, focusing on software innovation to unify management and scheduling of various computing resources without hardware limitations [2] Group 1 - Flex:ai technology can split a single GPU/NPU card into virtual computing units with a precision of 10%, enabling multiple AI workloads to run simultaneously [1] - The technology has been validated in real-world applications, such as the RuiPath model developed in collaboration with Ruijin Hospital, which improved resource utilization from 40% to 70% [3] - Gartner predicts that by 2027, over 75% of AI workloads will be deployed and run using container technology, indicating a shift towards more efficient resource management [3] Group 2 - Flex:ai will be open-sourced in the Magic Engine community, contributing to Huawei's comprehensive ModelEngine open-source ecosystem for AI training and deployment [3] - Unlike Run:ai, which primarily serves the Nvidia GPU ecosystem, Flex:ai supports a broader range of computing resources, including both Nvidia GPUs and Huawei's Ascend NPUs [2]

【导读】华为发布AI领域突破性技术Flex:ai，宣布同步开源至魔擎社区 11月21日，华为正式发布AI领域的突破性技术——Flex:ai。在整卡算力无法得到充分利用的AI工作负载场景下，该技术可将算力资源的平均利 用率提升30%。 Flex:ai是一款基于Kubernetes（开源容器编排平台）构建的XPU（各种类型处理器）池化与调度软件，与英伟达旗下Run:ai公司的核心技术类 似，但具备两个特有优势。 同时，Flex:ai是能够让AI行业化落地的重要工具之一。华为在发布Flex:ai后，会同步开源至魔擎社区，从而构建完整的ModelEngine开源生态。 华为公司副总裁、华为数据存储产品线总裁周跃峰表示，Flex:ai能够释放基础设施潜力，开源加速AI真正走向平民化。 同时，容器技术可以按需挂载GPU（图形处理器）、NPU（神经网络处理器）的算力资源，并且按需分配和回收资源，提升集群整体的资源利 用率。 第三方机构数据显示，目前AI负载大多已容器化部署和运行，预计到2027年，75%以上的AI工作负载将采用容器技术进行部署和运行。 此外，传统容器技术已经无法完全满足AI工作的负载需求，AI时代需要AI容 ...

【导读】华为发布AI领域突破性技术Flex:ai，宣布同步开源至魔擎社区 11月21日，华为正式发布AI领域的突破性技术——Flex:ai。在整卡算力无法得到充分利用的AI工作负载场景下，该技术可将算力资源的平均利 用率提升30%。 Flex:ai是一款基于Kubernetes（开源容器编排平台）构建的XPU（各种类型处理器）池化与调度软件，与英伟达旗下Run:ai公司的核心技术类 似，但具备两个特有优势。 同时，Flex:ai是能够让AI行业化落地的重要工具之一。华为在发布Flex:ai后，会同步开源至魔擎社区，从而构建完整的ModelEngine开源生态。 华为公司副总裁、华为数据存储产品线总裁周跃峰表示，Flex:ai能够释放基础设施潜力，开源加速AI真正走向平民化。 AI时代需要AI容器技术 Flex:ai呈现三方面关键能力 为什么推出Flex:ai？华为方面认为，在大模型时代，容器技术与AI是天然搭档。 容器技术作为一种轻量级虚拟化技术，可以将模型代码、运行环境等打包成一个独立且轻量级的镜像，实现跨平台无缝迁移，解决模型部署存 在环境配置不一致的痛点。 虚拟化与智能调度优势凸显 在AI容器领域，已有 ...

【导读】华为发布 AI 领域突破性技术 Flex:ai ，宣布同步开源至魔擎社区 中国基金报记者 邱德坤 11 月 21 日，华为正式发布 AI 领域的突破性技术 ——Flex:ai 。在整卡算力无法得到充分利用的 AI 工作负载场景下，该技术可将算力资 源的平均利用率提升 30% 。 Flex:ai 是一款基于 Kubernetes （开源容器编排平台）构建的 XPU （各种类型处理器）池化与调度软件，与英伟达旗下 Run:ai 公司的 核心技术类似，但具备两个特有优势。 同时， Flex:ai 是能够让 AI 行业化落地的重要工具之一。华为在发布 Flex:ai 后，会同步开源至魔擎社区，从而构建完整的 ModelEngine 开源生态。 华为公司副总裁、华为数据存储产品线总裁周跃峰表示， Flex:ai 能够释放基础设施潜力，开源加速 AI 真正走向平民化。 AI 时代需要 AI 容器技术 Flex:ai 呈现三方面关键能力 为什么推出 Flex:ai ？华为方面认为，在大模型时代，容器技术与 AI 是天然搭档。 容器技术作为一种轻量级虚拟化技术，可以将模型代码、运行环境等打包成一个独立且轻量级的镜像， ...

Core Viewpoint - The RuiPath pathology model, developed by Ruijin Hospital in collaboration with Huawei, aims to enhance the efficiency and accuracy of pathology diagnostics in China by leveraging AI technology [1][5]. Group 1: Model Development and Features - The RuiPath model is a clinical-grade multimodal pathology model that covers 90% of the annual cancer incidence in China, addressing 19 common cancer types and hundreds of auxiliary diagnostic tasks [1][5]. - The model has achieved state-of-the-art (SOTA) performance in 7 out of 14 auxiliary diagnostic tasks tested against 12 mainstream public datasets, surpassing the performance of Harvard's UNI2 model [4]. - The model's core "visual foundation model" was developed using over one million high-quality digital pathology slides from Ruijin Hospital, utilizing Huawei's AI toolchain for annotation, training, and fine-tuning [2][4]. Group 2: Efficiency and Impact - The implementation of the RuiPath model allows pathologists to increase their daily workload from 200-300 slides to 400-500 or more, significantly improving diagnostic efficiency [5]. - The model aims to standardize digital pathology practices across hospitals in China, enabling easier deployment and reducing training costs for other institutions [5][10]. - The collaboration between Ruijin Hospital and Huawei has streamlined the model training process, allowing for the completion of the RuiPath model development with only a 16-card cluster, making it more accessible for hospitals [10][11]. Group 3: Industry Challenges and Solutions - There is a significant shortage of pathology doctors in China, with only about 20,000 available and a gap of 140,000 needed, highlighting the importance of AI solutions in addressing this challenge [5]. - The partnership has evolved through two phases: digitalization and smart pathology, focusing on data standardization and collaborative model development [7][8]. - The use of Huawei's ModelEngine has transformed the annotation process, allowing pathologists to review over 700 slides in a day, thus enhancing both efficiency and accuracy [10].

Core Insights - The rapid integration of AI technology into the healthcare sector is transforming traditional medical practices, particularly in areas such as imaging, diagnostics, drug development, and health management [1][12] - The Chinese AI+ healthcare market is projected to grow from 31.5 billion yuan in 2023 to over 80 billion yuan by 2025, with a compound annual growth rate of 58.3% [1] - The global AI healthcare market is expected to exceed $1.5 trillion by 2030, with drug development, imaging diagnostics, and health management accounting for over 60% of this growth [1] AI in Pathology - Pathology diagnosis is considered the "gold standard" for disease diagnosis, especially for cancer, but the traditional process is time-consuming and requires high levels of expertise [2] - There is a significant shortage of pathologists in China, leading to unequal distribution of medical resources and increased patient costs [2] RuiPath Model Development - The RuiPath model, developed by Ruijin Hospital in collaboration with Huawei, is a clinical-grade multi-modal pathology model that covers 90% of cancer cases in China and includes over a hundred auxiliary diagnostic tasks [3] - The open-sourced RuiPath model includes a visual foundation model, a multi-cancer test dataset, and a complete practical guide, significantly lowering the barriers for grassroots hospitals to implement AI-assisted diagnostics [4] Global Collaboration and Standardization - Ruijin Hospital has initiated a global multi-center plan to promote the RuiPath model, focusing on improving diagnostic capabilities in resource-poor areas [5] - The collaboration aims to standardize diagnostic results across different centers and enhance the performance and applicability of the RuiPath model [5] Transition to Smart Pathology - The partnership between Huawei and Ruijin Hospital has evolved through clear phases of digitalization and smart pathology, culminating in the development of a large model capable of precise cancer identification [6] - The introduction of Huawei's ModelEngine AI toolchain has transformed the workflow of pathologists, increasing efficiency and reducing the time required for AI application deployment [7][8] Future Implications - The open-sourcing of the RuiPath model is expected to improve pathology diagnosis in grassroots hospitals, alleviating the imbalance in medical resource distribution [12] - Long-term, this collaboration is anticipated to attract more healthcare institutions and tech companies to participate in the development and application of medical AI, enhancing early diagnosis, personalized treatment, and drug development [12][14]