近几年射频前端市场异常火爆，多家射频前端公司应运而生，其中不乏有卓胜微、唯捷创芯两 家优秀的射频前端公司，并分别于2019年和2022年上市成功。昂瑞微也在今年申报IPO并获 得受理，目前处于二反问询中。2025年开始，射频前端市场出现了一个比较反常的现象，领 头羊卓胜微上市后出现首次亏损，唯捷创芯和慧智微扣非净利润也是负的，三家上市公司业绩 变脸，客观上对于昂瑞微IPO冲关可能会造成一定的压力。借此机会，我们刚好可以分析一下 昂瑞微的增长空间在哪里？ 根据Yole已披露的信息，全球移动设备领域射频前端相关市场，2024年为154亿美元（约1100亿元 人民币），预计到2030年将增长到170亿美元（约1200亿元人民币），如果考虑到汽车、国防等全 部市场，整个射频前端规模在2030年将增长到700亿美元（约5000亿元人民币）左右，市场空间巨 大，目前国内射频前端厂家的销售额都很低，最大一家卓胜微的销售额只有40亿元左右，远远低于 美国的Skyworks、Qorvo、高通及博通公司的销售额，总体成长空间较大。当前射频前端公司未能 大幅盈利的主要原因还是研发投入和设备折旧过大，研发费用率普遍偏高，由于现在手机 ...

公众号记得加星标⭐️，第一时间看推送不会错过。 但郑周三表示，这个想法并未纳入最新一轮的双边谈判。目前尚不清楚台积电是否参与了美台之间的 谈判。 来源 ： 内容 编译自 CNN 。 中国台湾誓言抵制华盛顿的压力，将其一半的芯片产能转移到美国，向特朗普政府发出挑战。 华盛顿越来越担心其对台湾的严重依赖，台湾芯片巨头台积电为人工智能芯片设计商 Nvidia 和苹果 等主要客户供应了全球绝大多数先进半导体。但台湾的许多人认为，其芯片制造实力是一道"硅盾"。 中国台湾副院长郑丽君周三表示，台湾"不会同意"在美国本土生产 50% 的半导体，而这些半导体对 于从电子产品和 iPhone 到训练人工智能和武器系统等所有产品都至关重要。 她在结束新一轮关税谈判从美国回国后对媒体表示："我们的谈判团队从来没有做出过对半分芯片的 承诺，所以公众可以放心。" 美国商务部长霍华德·卢特尼克（Howard Lutnick）周末在电视采访中要求台湾将芯片生产在国内和 美国工厂之间平均分配，此举引发台湾民众担忧，给正在进行的美台贸易谈判增添了新的紧张局势。 除了台北方面的反击外，反对党官员和专家也对此提出了批评。 在 NewsNation ...

公众号记得加星标⭐️，第一时间看推送不会错过。 来源 ： 内容 综合自路透社 。 Arm Holdings 周二表示，计划对法官在与高通的许可纠纷中的裁决提起上诉，该裁决维持了高通在 陪审团中的胜利。 高通去年在美国特拉华州联邦法院取得了一项关键胜利，陪审团裁定其子公司 Nuvia 生产的中央处 理器单元已根据与 Arm 达成的协议获得适当许可。 陪审团对三项指控中的两项达成了裁决，但在第三项指控上陷入僵局，导致审判无效。 Arm 曾请求法官 Maryellen Noreika 撤销高通胜诉的两项指控的判决，或进行重新审判。法官拒绝 了 Arm 的两项请求。 Arm 在一份声明中表示："Arm 对其在与高通持续纠纷中的地位充满信心，并将立即提起上诉，寻求 推翻判决。" 高通日前宣布，在与 Arm Holdings 的纠纷中胜诉，该纠纷涉及高通收购 Nuvia 并将其知识产权用 于其用于客户端 PC 的骁龙 X 处理器，违反了其架构许可协议 (ALA) 和技术许可协议 (TLA) 的条 款。然而，尽管高通被判无罪，但陪审团未能就 Nuvia 是否违反其与 Arm 的许可条款达成一致。因 此，据 彭博社报道，这一 ...

Core Insights - The article highlights that Angstrem, a state-owned microchip manufacturer in Russia, has been ranked as the most significant loss-making company in Russia for 2024, with a net loss of 236.3 billion rubles (approximately 2.86 billion USD) [2] - The majority of the losses stem from acknowledging a debt to its parent company, VEB, amounting to 238.2 billion rubles (approximately 2.88 billion USD) [2] - Angstrem's revenue was only 5 billion rubles (approximately 60.5 million USD), indicating that its net loss is nearly 47 times its revenue [2] Financial Performance - Angstrem's losses surpass those of other major state-owned enterprises, including Russian Trust Bank (130.7 billion rubles, about 1.58 billion USD), Russian Railways (116.9 billion rubles, about 1.41 billion USD), and the Moscow Metro (107.7 billion rubles, about 1.3 billion USD) [2] - The total losses of the top ten state-owned enterprises reached 652.8 billion rubles (approximately 7.91 billion USD), accounting for 70% of the total losses in the sector [2] Historical Context - The financial troubles of Angstrem can be traced back to 2008 when the factory was controlled by a company linked to former communications minister Leonid Reiman, which borrowed 815 million euros from VEB for production purposes [2] - By 2014, tax authorities indicated that Angstrem had effectively lost its operational capability [3] - In January 2019, VEB seized the factory's equipment and shares, filing for bankruptcy with total debts reaching 1.3 billion euros [3] Recent Developments - A court recently removed the factory's debt guarantee obligations, transferring its assets to VEB for a nominal price of one ruble (0.01 USD) [3] - Leonid Reiman has distanced himself from this failed venture and his new company, Rutek, has received government support to build a new factory in the Saransk economic zone, focusing on import substitution for various electronic devices [3] - Rutek's previous import substitution efforts have faced scrutiny, particularly regarding the R-Phone, which was found to be a rebranded device from Bangladesh sold at three times the original price [3]

Core Insights - President Trump announced a plan to make the U.S. a leader in AI and machine learning by removing restrictions on companies developing future technologies [2] - Major chip manufacturers like Nvidia, Intel, and AMD are actively developing new processors to meet increasing AI performance demands, indicating a promising market for AI chips [2] - The AI chip market is expected to grow significantly, but market maturity and consolidation may limit opportunities for new entrants [2] AI Processor Market Growth - Omdia predicts that the AI data center chip market will continue to grow rapidly, with an annual growth rate of over 250% from 2022 to 2024, but slowing to about 67% from 2024 to 2025 [4] - AI infrastructure spending is expected to peak in 2026, driven primarily by AI, before gradually decreasing by 2030 [4] - Precedence Research forecasts the AI chip market will grow from $94.31 billion in 2025 to $931.26 billion by 2034, with a compound annual growth rate of 28% [5] GPU and ASIC Dominance - GPUs remain dominant in the AI chip market due to their parallel processing capabilities, essential for training and inference tasks in data centers [5] - ASICs are expected to drive future growth in the AI chip market due to their efficiency in specific AI functions, particularly in inference-heavy environments [6] Major Developments by Chip Manufacturers - AMD launched the Instinct MI350 series GPUs, offering significant performance improvements and cost-effectiveness for AI solutions [9] - Intel introduced new Xeon 6 series CPUs designed to enhance the performance of GPU-driven AI systems [10] - Nvidia released the Rubin CPX GPU, designed for high-speed processing of large amounts of data, and integrated it into the new Vera Rubin NVL144 CPX platform [11] Cloud and Edge Computing Trends - By 2024, cloud AI processing is expected to dominate the market with a 52% share, driven by investments from major cloud providers [13] - Edge AI processing is rapidly growing due to the demand for low-latency, device-side intelligence in applications like autonomous vehicles and smart city infrastructure [12] Industry Consolidation and Collaboration - Jon Peddle Research predicts that by 2030, the AI processor market will consolidate to about 25 key players, with IoT and edge computing suppliers likely to survive due to their larger market potential [14] - OpenAI and Nvidia have formed a strategic partnership to deploy NVIDIA systems for training next-generation AI models, with Nvidia planning to invest up to $100 billion [14][15] Technical Challenges in AI Processing - The performance demands of AI processors are creating challenges for existing memory configurations, leading to the adoption of new memory designs to meet data and speed requirements [16] - Liquid cooling solutions are being explored to manage the heat generated by high-performance processors, although they add complexity and cost [17]

Core Viewpoint - Apple's acquisition of chip companies has significantly strengthened its position in the semiconductor industry, with a history of strategic purchases that enhance its technological capabilities and product offerings [2][4][14]. Group 1: Recent Acquisition - Apple has secretly acquired IC Mask Design Limited, a company specializing in IC layout design services and training, which has collaborated with over 250 tech companies globally [4][5]. - The acquisition is expected to provide Apple with expertise in VDSM technology nodes, potentially aiding in the optimization of its chips and enhancing energy efficiency [5][6]. Group 2: Historical Acquisitions - The acquisition of PA Semi in 2008 marked a turning point for Apple, laying the foundation for its future chip development across various devices [2]. - Subsequent acquisitions include Intrinsity in 2010, which improved microprocessor core development, and Anobit Technologies in 2012, enhancing NAND flash memory performance for Apple devices [8][9]. - Apple also acquired AuthenTec in 2012, which specialized in fingerprint scanning technology, and Passif in 2013, focusing on low-power communication chips [10][12]. - In 2018, Apple purchased Dialog Semiconductor's power management IC business, gaining control over PMIC development [11]. - The acquisition of Intel's smartphone modem business in 2019 added significant wireless technology patents to Apple's portfolio [12]. Group 3: Current Chip Development - Apple has developed multiple chip series, including A, C, H, M, N, S, and U series, showcasing its extensive capabilities in the semiconductor field [14]. - The company's aggressive patent filing strategy, averaging around 1,000 CPC G06F patents annually, reflects its commitment to innovation in chip technology [14]. - The competitive landscape in the semiconductor industry is intensifying, with other tech giants also increasing their capabilities through acquisitions, indicating a trend that Apple is likely to continue [14].

Core Viewpoint - Meta is set to acquire RISC-V chip startup Rivos to enhance its chip development team and reduce reliance on Nvidia GPU hardware [2][6][12] Group 1: Acquisition Details - The acquisition of Rivos is aimed at accelerating Meta's internal AI chip development, highlighting the company's increasing investment in custom chip design [6][7] - Rivos was recently valued at $2 billion, and the acquisition price is expected to be in the nine to ten-figure range [3] - The deal is not finalized, and the current status of negotiations is unclear [3] Group 2: Strategic Importance - The acquisition signifies a trend among major tech companies towards vertical integration and custom chip development, emphasizing the critical role of dedicated hardware in unleashing advanced AI potential [8][9] - Meta's CEO Mark Zuckerberg has expressed the need to accelerate internal chip development, recognizing the strategic importance of custom chips for AI advancements [7][8] Group 3: Market Impact - The acquisition could trigger a chain reaction in the semiconductor market, potentially challenging the dominance of established players like Nvidia [6][9] - Competitors in social media and AI may accelerate their own custom hardware development in response to Meta's move [9] Group 4: Future Outlook - Post-acquisition, Meta will focus on integrating Rivos' talent and technology into its existing hardware and AI departments, aiming for faster development and deployment of custom AI chips [10][12] - The long-term goal is to significantly reduce capital expenditures related to third-party AI hardware procurement, allowing for more resources to be allocated to AI research and development [10][12]

来源 ： 内容 编译自 etnews 。 公众号记得加星标⭐️，第一时间看推送不会错过。 特斯拉和苹果正在探索引入半导体玻璃基板。随着人工智能（AI）需求的不断增长，此举被解读为试 图通过玻璃基板提升半导体和数据中心性能。作为两家全球领先的科技公司，他们的采用预计将对行 业产生重大影响。 据报道，特斯拉和苹果近期与一家正在准备玻璃基板的制造商会面，了解了半导体玻璃基板技术，并 讨论了合作计划。目前尚未达成具体的合同或技术合作，但据悉，双方在合作中表达了广泛的兴趣和 意见。 据信，苹果也在探索将玻璃基板作为人工智能技术。苹果曾因应对人工智能时代不足而受到批评，但 据信其目标是实现以 iPhone 为中心的人工智能服务。预计苹果将在其人工智能基础设施（包括服务 器和数据中心）中使用玻璃基板。 多位知情人士表示："虽然尚未进入具体讨论阶段，但双方对玻璃基板的需求，包括对该技术的技术 理解，达成了共识。他们可能会重新审视技术开发流程，并决定是否采用。" 苹果公司的主要高管不仅拜访了玻璃基板制造商，还拜访了拥有相关工艺技术的设备供应商，以了解 玻璃基板技术。 玻璃基板由于其与传统塑料相比翘曲度更小，并且易于实现微电路， ...

第第九九届届国国际际先先进进光光刻刻技技术术研研讨讨会会 （（ IIWWAAPPSS 22002255 ）） --IIWWAAPPSS 22002255-- 第九届国际先进光刻技术研讨会（IWAPS）将于10月14-15日在深圳隆重举行！本次研 讨会由中国集成电路创新联盟、中国光学学会主办，中国科学院微电子研究所、深圳市半导 体与集成电路产业联盟（深芯盟）、南京诚芯集成电路技术研究院有限公司联合承办，诚邀 全球业界精英共赴这场光刻技术领域的学术盛宴！ 国际先进光刻技术研讨会（IWAPS），依托中国创新沃土，搭建全球交流平台。在国内 外光刻专家的鼎力支持下，在全球企业、高校、协会等的共同推动下，IWAPS持续构建覆盖 光刻设备、工艺制程、计量检测、掩模材料、计算光刻、系统协同优化及新型技术等全产业 链的尖端技术对话平台。 本届盛会特别依托深芯盟的产业集群优势，汇聚深圳及湾区半导体企业、高校与科研机 构的协同力量；同时联动湾芯展的产业生态资源，为全球领军企业提供展示创新蓝图的舞 台，为科研院所搭建核心技术攻关的交流通道，为青年学者创造技术思辨的活跃氛围，更为 投资机构提供洞察粤港澳大湾区半导体机遇的前瞻窗口。 第 ...

Core Viewpoint - Nvidia's stock price reached a new high, increasing nearly 3%, with a market capitalization exceeding $4.5 trillion, driven by its strong position in the AI infrastructure market and investments in OpenAI [3][4]. Group 1: Stock Performance and Market Position - Nvidia's stock has risen approximately 39% year-to-date, attracting investors as the company accelerates its trading pace and solidifies its role in the AI boom [3]. - Citigroup raised Nvidia's target price from $200 to $210, citing the company's expansion in the AI infrastructure market and its recent investment in OpenAI [3]. - KeyBanc increased Nvidia's target price from $230 to $250 while maintaining a buy rating, reflecting positive sentiment following OpenAI's announcement [3][4]. Group 2: Investments and Partnerships - OpenAI announced that Nvidia would invest up to $100 billion in the AI startup and build data centers worth hundreds of billions, equipped with Nvidia's GPUs [3]. - Nvidia's CEO Jensen Huang stated that Nvidia's products account for about 70% of new AI data center spending [3]. - OpenAI and Oracle are collaborating to build five large data centers, expected to house hundreds of thousands of GPUs, as part of the "Stargate" project, which will cost $500 billion [3]. Group 3: Future Projections and Analyst Insights - Analysts from Evercore ISI raised Nvidia's sales forecast for the second half of 2026 by $5.5 billion, increasing the target price from $214 to $225 [4]. - Concerns were raised by Bernstein's Stacy Rasgon regarding a "circular investment" where Nvidia invests in startups that subsequently purchase its GPUs, although demand remains strong [4]. - Huang refuted bearish long-term forecasts from Wall Street analysts, asserting that they underestimate the scale of AI demand [5]. Group 4: CEO's Perspective on AI Demand - Huang expressed confidence in Nvidia's ability to exceed performance targets regularly and highlighted a significant divergence between Wall Street's predictions and the actual growth in AI applications [5]. - He emphasized that the rapid increase in the number of AI tool users and the exponential growth in computing needs per user indicate a low likelihood of oversupply in the market [5]. - Huang defended Nvidia's $100 billion investment in OpenAI as one of the smartest investments imaginable, predicting that OpenAI could become a multi-trillion-dollar company [6].