Core Viewpoint - Goer Microelectronics has re-applied for listing on the Hong Kong Stock Exchange, reflecting the company's strategic ambitions and expectations after a previously withdrawn IPO application in A-shares [1][2]. Group 1: Listing Journey - Goer Micro's journey began in November 2020 when its parent company announced plans for a spin-off listing. The company received approval for its IPO in December 2021 and passed the listing committee meeting in October 2022, but did not submit the registration until it withdrew its application in May 2024 [1][2]. - The company re-applied for listing on July 21, 2025, with several financial institutions acting as joint sponsors, indicating a strong commitment to pursue a listing in Hong Kong [1][2]. Group 2: Market Position and Performance - Goer Micro is a leading player in the global MEMS market, ranking among the top ten MEMS manufacturers from 2018 to 2021, and is the only Chinese company in this category. In 2020, it achieved a 32% market share in MEMS acoustic sensors, surpassing its competitors [3]. - The sensor business is a core pillar for Goer Micro, with revenues of 2.541 billion yuan, 2.092 billion yuan, and 2.515 billion yuan for the years 2022, 2023, and the first nine months of 2024, respectively. In the first nine months of 2024, sensor revenue accounted for 77% of total revenue [3]. - Goer Micro has maintained a consistent R&D investment of around 8%, supporting technological innovation and product upgrades to meet the increasing demands of AI terminal devices [3]. - The cumulative shipment of sensors by Goer Micro has exceeded 5 billion units, and it is the fourth largest sensor provider globally with a market share of 4.3%, while holding the title of the largest acoustic sensor provider with a market share of 43.0% [3].

Core Viewpoint - The article discusses the implications of the U.S. government's recent decision to allow NVIDIA to sell its H20 AI chips to China, highlighting potential political motives and risks associated with this move [1][2][3]. Group 1: U.S. Government's Decision - The U.S. government lifted the ban on the H20 chip, which was previously imposed in April, citing that Chinese companies like Huawei can now produce comparable chips [2]. - The H20 chip is described as a downgraded version of NVIDIA's high-end chips, with only 15% of the performance of the advanced models, indicating that the U.S. still maintains strict control over superior technology [3]. - The decision to allow H20 sales appears to be a strategy to undermine Chinese competitors by flooding the market with a less capable product [4]. Group 2: Risks of H20 Chip - The introduction of the H20 chip poses significant risks for Chinese companies, particularly regarding the potential for embedded backdoors that could allow U.S. surveillance [5][6]. - The U.S. Congress has proposed the "Chip Security Act," which mandates that all high-performance chips have mechanisms for location verification, raising concerns about privacy and security for Chinese enterprises [5][6]. - There are fears that if many Chinese companies purchase the H20 chip, it could lead to widespread vulnerabilities in China's AI sector, potentially jeopardizing national security [7]. Group 3: Importance of Self-Reliance - The article emphasizes the necessity for China to develop its own core technologies to ensure security and independence from foreign influence [8][10]. - It argues that true progress in AI and technology can only be achieved through self-reliance and collaboration among Chinese entities, rather than dependence on foreign companies like NVIDIA [9][10].

Core Viewpoint - Nvidia has received U.S. government approval to resume supply of its AI chip H20 to China, but supply may take up to 9 months due to production capacity issues [1][2] Group 1: H20 Chip Supply and Production - Nvidia plans to launch a new AI chip B30 in Q4 of this year, which will replace HBM with GDDR7, resulting in 10% to 20% lower AI performance compared to H20, but at a price reduction of 30% to 40% [1] - Following the ban of H20 in April, Nvidia canceled customer orders and withdrew its production capacity from TSMC, which has since been allocated to other clients [1] - There is an estimated inventory of about 1 million H20 chips in Taiwan's semiconductor supply chain, with approximately 700,000 being finished chips [2] Group 2: Market Strategy and Challenges - Nvidia is likely to only sell existing inventory of H20 chips and will not increase production capacity for H20 to promote sales of the B30 [2] - Nvidia's CEO Jensen Huang indicated that recovering some of the canceled inventory may be challenging, as there may be a mismatch between customer demand and available stock [2]

以下文章来源于橙子不糊涂 ，作者橙子 橙子不糊涂 . 88年，集成电路背景，主要写科技，偶尔聊聊宏观和新鲜事儿。 今天交易时段就有彭博的信息，胜宏科技拟赴港上市。晚上公司正式披露公告： 其实没什么好聊的，说5个产业方面的观点： 1， 对于之前传统PCB⾏业，大规模扩产对于投资来说100%是坏事… 过去PCB行业的景气周期是2年， 扩产周期也基本就是1年多，客户产品需求出来，产能扩出价格就掉的比较糟糕。 过去若干年除了国内5G的2年周期，其他主要领域是消费电子、汽车电子等缺乏超级创新的行业，本身 就很"传统"， 在技术上缺乏门槛，什么有价值的新玩意儿都没有，毫无know-how可言 ，大厂小厂拼的 是对周期、客户需求的理解，以及够"狂野"，看到机会够狠、够卷。 2，目前PCB拼的是高端PCB的技术+产能储备，以及新材料、高多层以及HDI的Konw-how储备， 门槛 极高，且技术迭代和升级极快。 （1） 高端货奇缺 。客户看中的是你能承诺多少产能，多少良率； （2） 只有极少数几个巨头可以扩产 （设备周期至少10个月）。其他连扩产的资格都没有，因为既采购 不到设备，又没办法完成巨头客户的认证。 3，在这个超级周 ...

加入"中国IC独角兽联盟"，请点击进入 7月20日，台积电嘉义科学园区的建筑工地发生一起板车倾覆事故。涉事车辆当时载重约 50 吨，目前暂 无人员伤亡消息。 由于短期连续爆出四起重大事故，台湾地区当局"职安署"已全面叫停台积电在嘉义科学园区的机电工程 作业。 转自：国芯网 7月21日消息，据台媒报道， 由于台积电短期内连续爆出四起重大安全事故，台湾省当局已全面叫停台 积电在嘉义科学园区的工程作业！ 7月16日，台积电嘉义厂区工地发生一起意外，厂房高空安装重达数百公斤的机电用冰水管过程中，冰 水管意外掉落，直接砸中下方女工人，造成其头部重创，救护人员到场后紧急将其送往医院治疗，但18 日上午被宣告死亡。报道说，这是该厂区两个月以来第四起工业安全意外。 事故发生于16日16时左右，台积电嘉义科学园区先进封装厂AP7厂房内，当时工人正在进行机电用冰水 管安装作业，一个重达200至500公斤的冰水管，疑未完全固定，从5至6米高处意外坠落砸中地面的一名 女性工人。女子随后被紧急送往医院救治，因脑部出血持续接受治疗，于18日死亡。 台媒报道称，台积电嘉义厂区两个月内发生4起工业安全事故，已造成2死2伤。 报道回顾这两个月 ...

Core Viewpoint - The preliminary investigation report of the Air India Flight AI171 accident highlights critical details regarding engine fuel switch malfunction and pilot communications, while also sparking a debate on the reliability of BGA (Ball Grid Array) packaging technology in aviation applications [1][3][12]. Group 1: Accident Investigation Findings - The Air India AI171 accident report was released 30 days post-incident, adhering to ICAO guidelines, and includes key operational records and data anomalies [1]. - The report attributes the accident to fuel control switch misoperation, but alternative theories regarding engine control system failures have emerged [2][12]. Group 2: BGA Technology Insights - BGA packaging technology has revolutionized electronic device design, allowing for high-density connections, which are crucial in aviation electronics [5][10]. - The GEnx-1B engine's EEC utilizes a 144-ball BGA package, significantly improving heat dissipation compared to traditional packaging, thus enhancing operational safety [7][10]. Group 3: Reliability Challenges - BGA technology faces reliability issues in extreme aviation environments, with potential solder joint failures due to thermal cycling and vibration [8][12]. - The solder joint void rate for aviation-grade BGA must be below 5%, contrasting with consumer electronics standards, highlighting the critical nature of solder integrity in flight [7][8]. Group 4: Mitigation Strategies - Advanced materials and design strategies are being employed to enhance BGA reliability, such as using titanium-nickel alloy solder balls and ceramic substrates to reduce thermal stress [10][11]. - Redundant design strategies in avionics, such as dual-channel BGA architectures, are implemented to minimize the impact of potential failures [11][12]. Group 5: Future Innovations - NASA is developing "self-healing BGA" technology that can autonomously repair solder joint cracks, showcasing potential for future aerospace applications [13].

Core Viewpoint - The article discusses the rise of artificial intelligence (AI) and its implications for companies like NVIDIA, highlighting the importance of computing power, algorithms, and data in AI development [2][3][4]. Group 1: NVIDIA's Market Position - NVIDIA holds over 70% market share in the AI chip market, significantly influencing the computing power available for AI applications [3]. - Since 2012, NVIDIA's market capitalization has increased by over 500 times, making it the first company to surpass a market value of $4 trillion [5]. - The introduction of the H20 chip, which has only 20% of the inference capability of the H100, raises concerns about whether this will put companies using it at a disadvantage in AI development [6][7]. Group 2: The "Computing Power Anxiety" - The concept of "computing power anxiety" has emerged, questioning whether computing power is more critical than algorithms and data in AI development [7][8]. - The stock price of NVIDIA experienced a significant drop of nearly 17% in one day due to the emergence of DeepSeek, which demonstrated that AI models could perform efficiently with less computing power [10]. - A shift in focus towards computing power occurred after the U.S. government imposed export restrictions on high-performance chips to China, which was seen as an attempt to stifle China's AI development [14][15]. Group 3: The Role of Saif Khan - Saif Khan, a key figure in U.S. semiconductor policy, argues that controlling the supply chain of advanced AI chips is essential for maintaining a competitive edge in AI [20][21]. - His views have influenced U.S. policies, including the CHIPS and Science Act, aimed at limiting China's access to advanced AI technologies [22]. Group 4: Changing Narratives in AI Development - Recent reports indicate a shift in the narrative surrounding AI leadership, moving from a focus solely on computing power to a more balanced view that includes algorithms and technology diffusion [35]. - The U.S. government's decision to allow NVIDIA to export the H20 chip suggests a recognition of the need to adapt policies in response to evolving global AI dynamics [37]. Group 5: Different Development Philosophies - The article contrasts the "closed-source" approach of U.S. AI development, which protects proprietary models, with China's "open-source" strategy that encourages innovation through free access to large models [41]. - The potential success of these differing approaches remains uncertain, but China's model may offer more opportunities for widespread application and innovation in AI [42]. Group 6: Future Prospects - The upcoming World Artificial Intelligence Conference in China will showcase various AI applications across multiple industries, indicating a growing ecosystem for AI development [43]. - Historical examples suggest that the ultimate success in technology revolutions is often determined by the ability to build a robust application ecosystem rather than merely having the fastest technology [47].

Core Viewpoint - The article discusses the upcoming fundraising by Cambrian and highlights the company's focus on cloud-based revenue growth, which is expected to see significant increases starting from Q4 2024 [1]. Group 1: Cambrian's Financial Projections - Cambrian's cloud product line revenue is projected to reach approximately 110.9 million in Q1 2025, accounting for 99.94% of total revenue, compared to 9.1 million in 2022, which was only 12.80% of total revenue [1]. - The company anticipates a substantial increase in revenue due to alleviated supply chain issues, with a total revenue of 110.97 million expected in Q1 2025 [1]. Group 2: Market Dynamics and Competitors - Morgan Stanley estimates that the domestic cloud AI chip market will reach 48 billion by 2027, with the majority of the market share held by a leading competitor [3]. - Goldman Sachs has a more optimistic view on Cambrian, predicting revenues of 5.5 billion this year and 24.7 billion by 2027, which surpasses the combined revenue of all other GPU companies as estimated by Morgan Stanley [6]. Group 3: Production Capacity and Supply Chain - Cambrian's production capacity is currently limited, primarily serving a major client, with rumors of a significant order of 100,000 units from this client [9]. - The company is expected to see an increase in production capacity as supply chain issues are resolved, leading to improved revenue and profit margins [9]. - Inventory levels are a key focus, with an anticipated turning point in Q3 2024, after which revenue is expected to surge [9].

Core Viewpoint - The U.S. Department of Commerce announced a 93.5% anti-dumping duty on imported graphite from China, resulting in a total tariff rate of 160%, significantly impacting $347.1 million worth of imports in 2023 [1][2]. Group 1: Tariff Impact - The anti-dumping duty is based on claims that Chinese graphite products, essential for electric vehicle batteries, are sold below fair market value in the U.S. [1]. - The trade organization representing U.S. active anode material manufacturers argues that this practice undermines the competitiveness of local suppliers [4]. Group 2: Market Dynamics - Graphite is a critical material in the manufacturing of electric vehicle batteries, specifically as the main component of battery anodes [4]. - The U.S. relies heavily on imports for graphite, with approximately 180,000 tons imported last year, two-thirds of which came from China [4]. Group 3: Future Uncertainty - The preliminary ruling by the U.S. Department of Commerce is not final, with a conclusive decision expected by December 5, creating uncertainty for U.S. automakers [4]. - Anticipation of increased graphite prices due to tariffs poses challenges for automotive manufacturers, whose profit margins are already declining [4].

Core Viewpoint - The article discusses the competitive landscape of AI models, particularly focusing on DeepSeek and its challenges in maintaining user engagement and market position against emerging competitors like Kimi and others in the "AI Six Dragons" group [3][4][8]. Group 1: DeepSeek's Performance and Challenges - DeepSeek experienced a significant decline in monthly active users, dropping from a peak of 169 million in January to 160 million by May, a decrease of 5.1% [3][4]. - The app's download ranking has plummeted, falling out of the top 30 in the Apple App Store, indicating a loss of user interest [4]. - The user engagement rate for DeepSeek has decreased from 7.5% at the beginning of the year to 3% by the end of May, with website traffic also down by 29% [4][5]. Group 2: Competition and Market Dynamics - Competitors like Kimi and others are rapidly releasing new models, with Kimi K2 being highlighted for its performance and open-source nature, achieving state-of-the-art results in various benchmarks [10][11]. - The pricing strategy of Kimi K2 aligns closely with DeepSeek's, offering competitive rates for API usage, which could further erode DeepSeek's market share [11]. - Other players in the market are also emphasizing cost-effectiveness and performance, challenging DeepSeek's previously established reputation for value [10][11]. Group 3: Technological and Strategic Implications - DeepSeek's R2 model has faced delays due to supply chain issues related to the NVIDIA H20 chip, which has impacted its computational capabilities [5][7]. - The lack of significant updates to DeepSeek's models has led to a perception of stagnation, with competitors rapidly advancing in both performance and features [8][10]. - The article suggests that DeepSeek needs to quickly release new models and enhance its capabilities to regain market interest and user engagement [17][19].