Arm 物联网业务线高级副总裁兼总经理 Paul Williamson 表示："以不起眼的门铃为例。"他补充 说，它从一个简单的蜂鸣器发展成为一个基本的摄像头查看器，现在又发展成为一个更智能的人工智 能驱动设备，能够确定它是否在检测人，甚至识别特定的个人。 如果您希望可以时常见面，欢迎标星收藏哦~ 来源：内容编译自theregister，谢谢。 Arm 预测 AI 推理很快就会无处不在。为了给设备提供所有神经网络处理所需的动力，该公司正在通 过首款针对边缘工作负载的 64 位 Armv9 CPU 内核增强其嵌入式平台。 软银旗下的英国芯片设计公司表示，人工智能发展正在迅速，并声称几年前网络边缘机器学习工作负 载要简单得多，专注于基本的降噪或异常检测。 为了解决这一问题，该处理器设计公司推出了Cortex-A320 CPU 内核，旨在与 Arm 的嵌入式神经处 理单元 (NPU) 加速器 Ethos-U85 搭配用于边缘 AI 片上系统 (SoC) 设计。它可以配置为四个内核的 集群，以扩展并满足各种性能需求。 据称，A320 是"最小的 Armv9 实现"，提供 AArch64 指令集，是一个相对简单的单发射 ...

Financial Data and Key Metrics Changes - Group revenue for the first half of 2024 reached RMB 1,740 million, representing a 21.4% increase year-on-year [6] - Generative AI revenue surged to RMB 1,050 million, accounting for 60% of total group revenue, up from 21% last year [12] - EBITDA loss reduced by 26.5% and overall loss decreased by 21.2% in the first half of 2024 [8][42] - Gross profit margin remained at 44%, consistent with the previous year [42] Business Line Data and Key Metrics Changes - Generative AI revenue increased by 256% year-on-year, becoming the primary driver of revenue growth [39] - Sensors revenue doubled to RMB 1,168 million, accounting for 10% of group revenue [12] - Traditional AI revenue was RMB 520 million, contributing 30% of group revenue, indicating a decline [40] Market Data and Key Metrics Changes - Overseas market revenue grew by 40% year-on-year, now accounting for 18% of total revenue [13][41] - The Chinese intelligent computing services market is projected to grow at a CAGR of over 50% for the next five years, reaching nearly RMB 200 billion by 2028 [21] Company Strategy and Development Direction - The company is focused on generative AI, leveraging deep synergies between large models and infrastructure to enhance model capabilities and reduce costs [7][39] - The strategic pivot towards generative AI has been more successful than anticipated, with significant growth in various sectors including intelligent hardware, electric vehicles, and finance [10][12] - The company aims to expand its operational computing power to 25,000 petabytes by the end of the year [19] Management Comments on Operating Environment and Future Outlook - Management expressed optimism about the generative AI market, highlighting its rapid growth and the need for companies to invest in large models [9][76] - The competitive landscape is described as fierce, with significant investments required to maintain competitiveness [8][39] - Management emphasized the importance of balancing long-term growth with short-term investments [8] Other Important Information - The company has deployed over 50,000 GPUs, with total computing power exceeding 20,000 petabytes, positioning it as a key player in the AI infrastructure market [18] - The SESNOVA large model series has shown significant improvements, with version 5.5 released in July 2024, enhancing capabilities and real-time interaction [24][25] Q&A Session Summary Question: What are the potential applications for edge AI in collaboration with smartphone manufacturers? - Management is optimistic about edge AI prospects, emphasizing the growth of the user base and the potential for new application models beyond smartphones, including IoT devices [52][54] Question: How is the company planning to scale computing power resources? - The company is focusing on improving operational efficiency while expanding computing power, adopting a strategic approach to maintain competitiveness [58][59] Question: What are the core capabilities of the next generation large model? - Management discussed the importance of reasoning and high-order data in enhancing model capabilities, emphasizing the need for better data and model architecture [63][66] Question: Which products or services predominantly contribute to the increase in generative AI revenue? - The company is focusing on the commercialization of its technological expertise in AI infrastructure and large models, which has led to significant growth in generative AI revenue [72][76] Question: What is the current progress in commercializing end-to-end algorithms in the autonomous driving sector? - The company is dedicated to a pure visual technology path for autonomous driving, leveraging its computational resources to support automakers in developing advanced driving technologies [81][84]