公众号记得加星标⭐️，第一时间看推送不会错过。 本文作者：建木图巴克，转自公众号：建木的传感资本圈。 我们在做传感器行业并购和投融资信息跟踪时，发现近期磁传感器芯片领域资本运作密集，于是基于 公开信息梳理了这个行业 30 多年的发展历程。 30 年里，一项项技术从无到有再突破，一家家企业从小到大再变强，一个个创业者从青涩到成熟再飞 跃。 30 年里，有携手共进的合作共赢，有对簿公堂的江湖恩怨；有起高楼、宴宾客的热闹让人艳羡，也有 楼塌的窘迫令人唏嘘。 2025年8月26日，安徽希磁科技正式向港交所递交上市申请。以2024年收入计算，该公司已在全球磁 性传感器IDM公司中位列第六，TMR传感器领域更是跻身全球第二。同日，必易微发布公告，宣布 收购兴感半导体100%股权；同月，矽睿科技通过反向收购取得上市公司安车检测的控制权；同年3 月，圣邦电子已收购感睿智能67%的股权；去年10月，纳芯微以10亿元估值全面收购麦歌恩。一系列 密集的资本动作，清晰勾勒出中国磁传感器产业整合加速的轮廓——逐步告别以往"小作坊"式的零散 发展，迈入依托资本与战略进行深度重组的新阶段。 本文回顾了过去三十余年，从上世纪90年代至今，中 ...

Core Insights - Meta Platforms aims to design and manufacture its own CPU and XPU accelerators to enhance cost-effectiveness and control over its infrastructure, especially for its applications like Facebook, WhatsApp, and Instagram, which serve 3.5 billion users [2][3][4] Group 1: Meta Platforms' Strategy - Approximately 85% of users are on Facebook, indicating that Meta is still primarily a single-product company, but it is expanding its user base across other applications [3] - The company is investing heavily in R&D and capital expenditures, with projected R&D spending of around $50 billion and capital expenditures between $66 billion to $72 billion by 2025, which is about 61% of its expected revenue of $190 billion to $200 billion [3][4] - Meta's desire to design its own CPU and XPU is driven by the need to reduce infrastructure costs and improve profitability [3][4] Group 2: Development of Custom Chips - Meta has faced challenges in developing custom chips, having started its custom chip work in 2020 and releasing the MTIA v1 in May 2023, which is capable of inference but not training [4][5] - The MTIA v2, set to launch in April 2024, will improve inference capabilities but still lacks training functionality [4][5] - A paper presented at the 2025 International Symposium on Computer Architecture claims that the MTIA 2i chip reduces total cost of ownership (TCO) by 44% compared to Nvidia GPUs for certain AI inference workloads [5] Group 3: Collaboration with Rivos - Meta Platforms has been collaborating with Rivos, a RISC-V computing engine startup, to design the MTIA chips, but Rivos has received acquisition offers that could complicate this partnership [6][8] - Rivos, founded in 2021, is developing its own RISC-V CPU and GPU designs, which are crucial for Meta's future processor strategy [6][12] - Rivos has raised significant funding, including $250 million in Series A and an additional $120 million, with plans for a $500 million Series B round, potentially valuing the company over $2 billion [12][16] Group 4: Technical Aspects and Market Position - Rivos is developing power-optimized chips that combine high-performance RISC-V CPUs with data-parallel accelerators, suitable for large language models and data analysis [16] - The architecture is expected to be compatible with existing software programming models and rack server constraints, similar to Nvidia's Grace-Hopper architecture [16][17] - There are concerns regarding Rivos' compatibility with Nvidia's CUDA-X software stack, which could lead to legal challenges if not managed properly [19][20]

Core Viewpoint - Samsung Electronics and SK Hynix's stock prices surged following their collaboration with OpenAI as part of the Stargate initiative, focusing on advanced memory chips essential for next-generation AI [3][5]. Group 1: Stock Performance - Samsung's stock reached its highest level since January 2021, closing up 3.5%, while SK Hynix's stock soared nearly 10%, hitting its highest level since 2000 [3][5]. - SK Hynix announced readiness to mass-produce its next-generation high-bandwidth memory (HBM) chips, solidifying its leading position in the AI value chain [3]. Group 2: Collaboration Details - OpenAI's collaboration aims to increase the supply of advanced memory chips necessary for AI and expand data center capacity in South Korea [3][5]. - The partnership was announced during a meeting between OpenAI CEO Sam Altman and South Korean President Yoon Suk-yeol, along with executives from Samsung and SK Hynix [3]. Group 3: Market Competition - SK Hynix has reportedly caught up with Samsung in memory revenue, intensifying competition for the top position in the global memory market [4]. - Samsung has traditionally led the memory market but faces challenges from SK Hynix, which has established a strong foothold in the HBM sector [4]. Group 4: Financial Performance - Samsung's second-quarter earnings fell short of expectations, with chip business profits declining nearly 94% year-on-year; however, the CFO anticipates a rebound in profits in the second half of the year [6].

公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ：内容翻译自hpcwire，谢谢。 近日——SiPearl，一家为 HPC、AI 和数据中心设计自主高性能节能处理器的欧洲无晶圆厂设计公司，今天宣布 推出用于双重用途的 Athena1 处理器。 基于欧洲在 Rhea1（SiPearl 第一代处理器，专用于高性能计算）设计方面积累的独特专业知识，Athena1 将提供 专门针对政府、国防和航空航天应用工作负载量身定制的功能。这些功能包括安全通信和情报、密码学和加密、 情报处理、战术网络、电子探测或车辆本地数据处理等。 除了强大的计算能力外，Athena1 还以安全性和完整性著称。Athena1 系列将提供 16、32、48、64 或 80 个 Arm Neoverse V1 核心的型号，具体取决于每个应用所需的功率、散热限制等因素。详细的技术规格将于稍后公布。 Athena1芯片的制造将委托给全球领先的先进半导体独立代工厂台积电（TSMC）。封装工作最初将在中国台湾进 行，但计划将封装转移到欧洲，以助力欧洲产业生态系统的发展。 Athena1 的商业发布计划于 2027 年下半年进行。 SiPearl 首席 ...

公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ： 内容 来源：综合自网络 。 近日，双方宣布已达成最终协议，将以全股票形式进行合并。根据Axcelis和Veeco截至2025年9月30 日的收盘价以及截至2025年6月30日的未偿债务，合并后公司的企业价值预计约为44亿美元。 Axcelis 和 Veeco 合并后将成为一家领先的半导体设备公司，服务于互补、多元化且不断扩展的终端 市场。合并后的公司将拥有极具吸引力的运营状况、强大的研发创新引擎和更丰富的产品组合，并有 机会实现成本和收入协同效应。按 2024 财年的预测，合并后公司的收入为 17 亿美元，非公认会计 准则毛利率为 44%，调整后息税折旧摊销前利润 (EBITDA) 为 3.87 亿美元。这些预测数据并未反映 合并后的预期协同效应。 根据协议条款，Veeco 股东每持有一股 Veeco 股票将获得 0.3575 股 Axcelis 股票。交易完成后， Axcelis 股东预计将持有合并后公司约 58% 的股份，Veeco 股东预计将持有合并后公司约 42% 的股 份（按完全稀释后计算）。合并协议已获得两家公司董事会的一致批准。 Axce ...

公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ：内容翻译自techspot，谢谢。 这种安排也可能符合AMD的政治利益。今年早些时候，华盛顿限制了AMD向中国出口芯片的能力——后来特朗 普政府部分放宽了这些规定。在白宫继续将产业政策与国家安全挂钩的背景下，与美国制造业政策保持密切一致 可能有利。 英特尔工厂在尖端制程技术方面仍落后于台积电，但特朗普政府已敦促美国主要企业至少将部分制造业务转移到 国内工厂。对于像AMD这样的公司来说，与英特尔达成制造协议可以缓解政治压力，同时维护与台积电的高端 生产关系。 英特尔今年花费了大量时间来争取潜在客户和投资者，力图将其代工部门打造为台积电和三星的有力竞争对手。 英特尔曾是个人计算芯片领域的霸主，但在英伟达引领的人工智能竞赛中却落后了。获得 AMD 成为客户，将代 表英特尔制造业务的重大突破，将双方历史性的竞争转化为战略合作伙伴关系。 在美国大力推行国产芯片之际，AMD 正在权衡这一举措 英特尔前首席执行官帕特·基辛格公开呼吁英特尔为所有主要科技公司（包括竞争对手）生产芯片。英特尔现任首 席执行官陈立武表示，如果未能吸引足够的外包需求，公司最终可能会缩减其最先进 ...

Core Viewpoint - The "2025 Electronic Semiconductor Industry Innovation Development Conference and International Electronic Circuit (Greater Bay Area) Exhibition" (CPCA Show Plus) will take place from October 28 to 30, 2025, in Shenzhen, focusing on innovation-driven development in the semiconductor and electronic circuit industries [1]. Industry Growth and Trends - The PCB manufacturing industry in China experienced robust growth in the first half of 2025, with revenue reaching approximately 183 billion RMB, reflecting a year-on-year increase of over 10% driven by terminal demand and the expansion of emerging applications [4]. - The exhibition aims to leverage the advantages of the Greater Bay Area to stimulate the PCB industry's growth in the AI era by connecting upstream and downstream enterprises [4]. Exhibition Highlights - CPCA Show Plus 2025 will feature over 300 renowned exhibitors, showcasing a comprehensive range of products from PCB manufacturing processes to semiconductor and packaging substrates, providing a one-stop procurement and collaboration service [1][4]. - Key exhibitors include leading companies in the PCB manufacturing sector and those covering advanced materials, equipment, and chemicals, emphasizing a full industry chain approach [5]. Technological Innovations - The exhibition will present smart manufacturing solutions such as automated production lines, AI quality inspection systems, and digital twin factories, aimed at enhancing production efficiency and precision management in the electronic circuit and semiconductor industries [5]. - The event will also highlight sustainable development practices, showcasing green materials, energy-efficient production equipment, and clean production processes to support the industry's low-carbon transformation [5]. Networking and Collaboration - CPCA Show Plus 2025 is expected to attract over 45,000 professional attendees from global PCB application enterprises, research institutions, and buyers, facilitating supply-demand matching and technical exchanges [7]. - The exhibition will feature specialized zones for ceramic substrates, top PCB companies, and academic innovation, allowing attendees to focus on industry dynamics and trends [7]. International Promotion - The event has been promoted through various domestic and international media channels to enhance the global presence of China's electronic manufacturing industry, attracting notable companies from the application demand side [10]. Forums and Activities - A series of forums and activities will be held alongside the exhibition, including the 47th Sino-Japanese Electronic Circuit Autumn Conference, focusing on AI empowerment and industry breakthroughs [13]. - Specialized forums will address various topics, including low-altitude economy, commercial aerospace, and AI technology innovations, catering to diverse attendee interests [14]. Invitation to Industry Stakeholders - CPCA Show Plus 2025 serves as a platform for industry stakeholders to explore opportunities and drive upgrades in the semiconductor sector, inviting global enterprises, experts, and partners to participate [16].

公众号记得加星标⭐️，第一时间看推送不会错过。 微软公司与Nebius Group NV的交易将为创建大型语言模型和一款消费者人工智能助手的 内部团队提供计算能力。 这一安排是微软应对人工智能数据中心容量短缺战略的一部分，同时腾出自身的服务器农 场，以便向客户提供利润丰厚的AI服务。 微软已经与包括Nebius、CoreWeave Inc.、Nscale和Lambda在内的新云计算提供商签署了 超过330亿美元的承诺协议，以加速获取以人工智能为核心的计算能力 。 来源 ：内容翻译自bloomberg，谢谢。 前言 微软公司 与新云公司 Nebius Group NV 的交易将为内部团队提供计算能力，用于创建大型语言模型和消费者人工 智能助手。 这项价值高达194亿美元的安排，在 9月8日概述时引发了 NeBius股票的上涨，但公告缺乏具体细节。作为交易的 一部分，微软将获得超过100,000个 Nvidia Corp.'s 最新的GB300芯片，要求匿名讨论内部事务的人士说。 该策略旨在应对人工智能数据中心容量不足的问题，并让微软腾出自身的服务器农场，以向客户提供利润丰厚的 AI服务。 这只是微软与所谓的"新 ...

Core Viewpoint - The rapid development of AI has made storage a critical component in the AI infrastructure, alongside computing power. The demand for storage is surging due to the increasing data volume and inference scenarios driven by large models and generative AI. Three storage technologies—HBM, HBF, and GDDR7—are redefining the future landscape of AI infrastructure [1]. Group 1: HBM (High Bandwidth Memory) - HBM has evolved from a high-performance AI chip component to a strategic point in the storage industry, significantly impacting AI chip performance limits. In less than three years, HBM has achieved over twofold capacity and approximately 2.5 times bandwidth increase [3]. - SK Hynix is leading the HBM market, currently in the final testing phase for the sixth generation (HBM4) and has announced readiness for mass production. In contrast, Samsung is facing challenges in HBM4 supply to Nvidia, with a two-month delay in testing [3][5]. - A notable trend is the customization of HBM, driven by cloud giants developing their AI chips. SK Hynix is shifting towards a fully customized HBM approach, collaborating closely with major clients [4]. Group 2: HBF (High Bandwidth Flash) - HBF aims to address the limitations of traditional storage by combining the capacity of NAND flash with the bandwidth of HBM. Sandisk is leading the development of HBF technology, which is expected to meet the growing storage demands of AI applications [8][9]. - HBF is seen as complementary to HBM, suitable for specific applications requiring large block storage units. It is particularly advantageous in scenarios demanding high capacity but with relatively relaxed bandwidth requirements [10][11]. Group 3: GDDR7 - Nvidia's introduction of the Rubin CPX GPU, utilizing GDDR7 instead of HBM4, reflects a new approach to AI inference architecture. This design optimizes resource allocation by separating the inference process into two stages, effectively utilizing GDDR7 for context building [13]. - The demand for GDDR7 is increasing, with Samsung successfully meeting Nvidia's orders. This flexibility positions Samsung favorably in the graphics DRAM market [14]. - GDDR7's cost-effectiveness may drive the widespread adoption of AI inference infrastructure, potentially increasing overall market demand for high-end HBM due to the proliferation of applications [15]. Group 4: Industry Trends and Future Outlook - The collaborative evolution of storage technologies is crucial for the AI industry's growth. HBM remains essential for high-end training and inference, while HBF and GDDR7 cater to diverse market needs [23]. - The ongoing innovation in storage technology will accelerate as AI applications expand across various sectors, providing tailored solutions for both performance-driven and cost-sensitive users [23].

Core Viewpoint - FuriosaAI, a South Korean chip startup, aims to compete with Nvidia by leveraging its unique Tensor Contraction Processor (TCP) architecture to enhance AI performance and efficiency [2][3]. Group 1: Company Overview - FuriosaAI was founded in 2017 by June Paik, a former engineer at Samsung and AMD, with a vision for dedicated chips for deep learning workloads [2]. - The company launched its first-generation Neural Processing Unit (NPU) in 2021, manufactured by Samsung using a 14nm process, which performed well in MLPerf benchmarks [2]. Group 2: Product Development - The second-generation chip, RNGD (Renegade), is being developed over a three-year project initiated in 2021, focusing on generative AI and language models [3]. - RNGD is manufactured using TSMC's 5nm process, featuring 48GB of HBM3 memory, 1.5TB/s memory bandwidth, and 512 TFLOPS of FP8 performance with a maximum power consumption of 180W [3]. Group 3: System Integration - FuriosaAI is working on a complete system based on the RNGD card, the NXT RNGD server, which will include eight RNGD cards, totaling 384GB of HBM3 memory and 4 petaFLOPS of FP8 performance at a thermal design power (TDP) of 3kW [4]. - The NXT RNGD server aims to outperform traditional GPU-based systems, targeting the same market as Nvidia's H100 GPU [4]. Group 4: Performance Comparison - The Nvidia H100 GPU features 80GB of HBM2 memory, 2TB/s memory bandwidth, and 1513 TFLOPS peak performance, with a TDP of 350W for PCIe versions and up to 700W for SXM versions [5]. - FuriosaAI claims that RNGD's performance exceeds Nvidia's by three times when running large language models on a per-watt basis [5]. Group 5: Architectural Innovation - The TCP architecture is designed to minimize data movement, which is a significant energy consumer, by maximizing data reuse stored in on-chip memory [6]. - The architecture improves abstraction layers to overcome limitations of traditional GPU architectures, ensuring efficient data access and high throughput [7]. Group 6: Market Adoption and Client Engagement - FuriosaAI has gained traction with clients like LG AI Research, which reported that RNGD could deliver approximately 3.5 times the tokens per rack compared to previous GPU solutions [8]. - The company has attracted attention from major cloud computing firms, including Meta, which expressed interest in acquiring FuriosaAI [8]. Group 7: Future Plans and Funding - FuriosaAI completed a $125 million bridge financing round, bringing total funding to $246 million, and is focusing on ramping up RNGD production for global customer engagement by early 2026 [9].