公众号记得加星标⭐️，第一时间看推送不会错过。 在刚刚结束的IEDM 2025上，台积电首次证实了采用下一代晶体管技术——互补场效应晶体管 （CFET）的集成电路的运行情况。 根据IEDM 官方此前的预告，台积电在本届大会宣布两项了重要里程碑：首款全功能 101 级 3D 单 片互补场效应晶体管 (CFET) 环形振荡器 (RO)以及全球最小的 6T SRAM 位单元，该位单元同时提 供高密度和高电流设计。 据介绍，基于先前基于纳米片的单片 CFET 工艺架构，台积电研究人员引入了新的集成特性，进一 步将栅极间距缩小至 48nm 以下，并在相邻 FET 之间采用纳米片切割隔离 (NCI) 技术，以及在 6T SRAM 位单元内采用对接接触 (BCT) 互连技术实现反相器的交叉耦合。电学特性分析对比了两种环 形振荡器布局，重点展示了 6T 位单元对性能以及稳健 SRAM 器件指标的影响。 这些进展标志着 CFET 开发的关键性转变，从器件级优化迈向电路级集成。 台积电新进展 CFET 是一种通过垂直堆叠 n 沟道 FET 和 p 沟道 FET（CMOS 器件的基本组件）来提高晶体管密 度的技术，理论上与目前最先 ...

公众号记得加星标⭐️，第一时间看推送不会错过。 几十年来，半导体技术的进步一直以不断缩小的纳米尺寸来衡量。但随着晶体管尺寸缩小速度放缓， 瓶颈已从器件转移到互连，先进封装成为新的前沿领域。采用硅通孔（TSV）的硅中介层实现了高密 度2.5D集成，缩短了信号路径，并支持远超衬底和引线键合所能提供的带宽。 下一阶段的发展趋势与直觉相反：更大的TSV（宽度可达50μm，深度可达300μm）蚀刻到更厚的中 介层中，可带来更好的电气性能、更稳定的电源传输、更佳的散热性能和更高的制造良率。 从引线键合到中介层 在TSV区域和中介层顶层的微凸点之间是重分布层（RDL）。该层包含主要的水平界面连接，用于连 接中介层顶层的元件芯片。RDL中的互连结构类似于HDI PCB中的盲孔/埋孔。 中介层通常由三种材料制成：硅、玻璃或有机衬底。中介层完全由代工厂制造（台积电是主要供应 商），包括与封装衬底和半导体芯片键合的硅通孔 (TSV) 和水平互连。中介层可以设计成两种功 能：作为有源器件或无源器件。 硅中介层的一个主要应用是将高带宽内存 (HBM) 连接到高速处理器（图 2）。每个 HBM 器件本身 都是一个由 TSV 构建的 3D ...

Summary of MKS Instruments FY Conference Call Company Overview - **Company**: MKS Instruments (NasdaqGS: MKSI) - **Industry**: Semiconductor Equipment and Advanced Electronics - **History**: Founded 65 years ago, initially focused on vacuum pressure measurement, expanded into semiconductor equipment, and has maintained a leading market share in vacuum equipment for semiconductors for over 55 years [2][56] Key Points and Arguments Market Position and Strategy - MKS has developed a comprehensive strategy surrounding semiconductor equipment, acquiring Newport Corporation in 2015, which added critical components like lithography, metrology, and inspection, allowing MKS to address 85% of equipment in semiconductor fabs globally [3][56] - The company has expanded into new markets, including laser applications for PCB manufacturing through acquisitions like Electro Scientific Industries and Atotech, aiming to be foundational to advanced electronics beyond just semiconductors [4][57] Growth Drivers - **Electronics and Packaging (E&P)**: MKS expects about 20% growth for the full year, driven by strong demand for chemistry products in the PCB industry, particularly from AI applications [8][61] - **Chemistry and Equipment**: The E&P segment consists of two-thirds chemistry and one-third equipment, with chemistry growing at approximately 10% year-over-year, supported by increased complexity in AI server PCBs [12][65] - **Equipment Orders**: MKS has seen strong bookings for chemistry equipment, with orders booked through the first half of 2026, indicating robust growth potential [16][69] Financial Performance - **Gross Margins**: Current gross margins are impacted by a mix of equipment sales and tariffs, with a target to return to over 47% as the mix normalizes and operational efficiencies improve [19][71] - **Tariff Impact**: Tariffs have negatively affected gross margins by approximately 50 basis points, but MKS is confident in offsetting this through operational excellence [36][71] Semiconductor Market Outlook - MKS anticipates a 10% growth in the semiconductor segment for the year, driven by inventory burn-off in NAND and upgrades in logic, DRAM, and HBM [22][75] - The company is addressing concerns about cleanroom capacity, which could constrain growth, but sees potential upside from NAND upgrades and new greenfield projects [26][78] R&D and Competitive Advantage - MKS emphasizes the importance of R&D investment to maintain a competitive edge, particularly in complex technologies like atomic layer deposition (ALD) and RF power systems [28][32] - The company has doubled its revenue in the optics segment from $150 million to $300 million over five years, indicating successful growth in this area [20][72] Future Expectations - MKS is optimistic about 2026, expecting continued growth driven by strong demand across various semiconductor applications, with a focus on maintaining close communication with major customers to anticipate needs [24][77] - The company aims to achieve a net leverage of 2 to 2.5 times in the next couple of years, focusing on debt repayment and capital allocation strategies [42][43] Additional Important Insights - MKS's unique position in the market allows it to benefit from various semiconductor trends, including the shift towards more complex chip packaging and the integration of AI technologies [5][6] - The company’s strategy of managing a broad portfolio of critical subsystems positions it well to adapt to changing market demands and technological advancements [30][31]

2022年1月4日-2023年1月5日，纳斯达克跌了整整一年，跌幅高达34%，下跌的核心原因是由于高通胀 美联储加息。 那么，是什么原因导致2023年初美股走出熊市的泥潭的呢？ 第一，美联储加息力度减弱。美联储最关注的指标PCE从6月到达峰值的6.8以来一路下滑，最低跌至10 月的6和12月的5，证明美联储的加息抑制住了通胀，加息最大压力的时候已经结束。 第二，人工智能技术创新的大爆发。2022年11月30日，ChatGPT横空出世，5天用户破百万，2023年1月 用户过亿，2月微软宣布对OpenAI进行上百亿美元的战略投资，并将ChatGPT的整合到其Bing搜索和 Office办公软件中。 加息力度减弱，意味着流动性逐步放松，人工智能技术大爆发，带来的科技巨头资本开支集体扩张，为 市场注入基本面动力，于是，美股连涨3年。 很多小伙伴很好奇：为啥美国巨头应对这次创新，可以如此不计回报率的进行大规模资本开支呢？不能 慢慢来吗？ 摩尔定律是指晶体管数量18-24个月会翻倍，即每年增速50%。但是，从2010年开始，摩尔定律其实已 经不适用了，最新的数据显示，目前算力的增速是每年4.3倍，即半年翻倍，这种加速让科 ...

Core Insights - TSMC is set to launch its A14 (1.4nm) process technology in 2028, which shows a 16% performance improvement and a 27% power reduction compared to its previous N2 (2nm) process under the same power and complexity conditions [3][6] - The A14 process is expected to enhance transistor density by approximately 20% while maintaining power efficiency [6][8] - Despite the slowdown of Moore's Law, TSMC's advancements in process technology remain significant, with a projected 1.83 times performance increase and 4.2 times energy efficiency improvement from N7 (2018) to A14 (2028) [8] Process Technology Advancements - TSMC's A14 process is designed to outperform the N2 process, with initial estimates indicating a 10% to 15% performance increase and a 25% to 30% power reduction at the same clock frequency [6][8] - The company emphasizes that each new major process node can reduce power consumption by about 30%, while performance improvements are typically between 15% to 18% [8] EDA Tools and Design Efficiency - Chip designers can leverage AI-enhanced EDA tools like Cadence Cerebrus AI Studio and Synopsys DSO.ai to optimize designs, potentially saving up to 7% in total power consumption through advanced layout and routing techniques [9][12] - These tools utilize reinforcement learning to explore optimization spaces, thereby improving performance, reducing power consumption, and minimizing area [9][12]

Core Insights - The discussion highlights the transformative impact of artificial intelligence (AI) and the role of NVIDIA in driving this technological revolution, emphasizing the importance of GPUs in various applications from gaming to modern data centers [1] - Huang Renxun discusses the risks and rewards associated with AI, the global AI race, and the significance of energy and manufacturing for future innovations [1] Group 1: AI and Technological Competition - The ongoing technological competition has been a constant since the Industrial Revolution, with the current AI race being one of the most critical [10][11] - Huang Renxun emphasizes that technological leadership is essential for national security and economic prosperity, linking energy growth to industrial growth and job creation [7][8] - The conversation touches on the historical context of technological races, including the Manhattan Project and the Cold War, underscoring the continuous nature of these competitions [11] Group 2: AI Development and Safety - Huang Renxun expresses optimism about the gradual development of AI, suggesting that advancements will be incremental rather than sudden [13] - The discussion addresses concerns about AI's potential risks, including the ethical implications of military applications and the need for robust cybersecurity measures [16][20] - Huang Renxun believes that AI's capabilities will increasingly focus on safety and reliability, reducing the occurrence of errors or "hallucinations" in AI outputs [14] Group 3: Future of Work and AI's Impact - The conversation explores the potential for AI to create a future where traditional jobs may become obsolete, leading to a society where individuals receive universal basic income [37] - Huang Renxun acknowledges the challenges of identity and purpose as AI takes over tasks traditionally performed by humans, emphasizing the need for society to adapt to these changes [38] - The discussion highlights the importance of maintaining human engagement and problem-solving in a future dominated by AI technologies [38] Group 4: Quantum Computing and Security - Huang Renxun discusses the implications of quantum computing on encryption and cybersecurity, suggesting that while current encryption methods may become outdated, the industry is actively developing post-quantum encryption technologies [22][23] - The conversation emphasizes the collaborative nature of cybersecurity efforts, where companies share information to enhance collective defenses against threats [20][21] - Huang Renxun asserts that AI will play a crucial role in future cybersecurity measures, leveraging its capabilities to protect against evolving threats [21]

英伟达创始人兼CEO黄仁勋近日在播客节目中进行了一场长达两小时的深度访谈，详细阐述了他对人工智能竞赛、公司经营以及个人成长的看法。 这位全球市值最高科技公司之一的掌门人，以罕见的坦诚揭示了一个令人意外的事实： 尽管英伟达已成为AI时代的核心企业，但他每天醒来仍然感到公司"距 离倒闭还有30天"。 在谈及当前全球关注的AI竞赛时，黄仁勋提出了与主流观点截然不同的看法。他认为，这场竞赛并非如外界想象的那样存在一条明确的"终点线"，也不会出现 某一方突然获得压倒性优势的局面。相反， 技术进步将是渐进式的，所有参与者都将站在AI的肩膀上共同进化。 他认为， 真正的竞争力在于持续迭代能力，而非一次性突破 。过去10年AI算力提升10万倍，但这些算力用于让AI更谨慎思考、检验答案，而非做危险的事。 英伟达2005年推出CUDA时股价暴跌80%，但坚持投入最终成就了今天AI革命的基础设施。迭代不是重复，而是基于第一性原理的持续修正。 黄仁勋还详细回顾了英伟达多次濒临破产的创业经历，包括1995年技术路线选择错误、依靠世嘉500万美元投资和台积电张忠谋的信任才得以生存的惊险时 刻。 这些经历塑造了他对风险、战略和领导力的独特 ...

Core Insights - The article discusses the shift in understanding AI development, emphasizing that intelligence growth is not solely dependent on chip speed but rather on structural reorganization and collaboration among multiple units [1][7][16] Group 1: AI Development and Structure - The traditional view of Moore's Law, which posits that faster chips lead to stronger intelligence, has been challenged as chip speeds plateaued around 2020 [1][7] - Despite the stagnation in chip speed, AI has continued to evolve rapidly, with large models demonstrating unprecedented capabilities [7][8] - The article posits that the enhancement of intelligence is achieved through collective participation in prediction rather than individual acceleration [6][8] Group 2: Collective Intelligence and Collaboration - The concept of collective intelligence is highlighted, where groups, rather than individuals, enhance predictive capabilities through collaboration [6][9] - Modern AI development mirrors natural intelligence evolution, relying on the parallel processing of numerous simple computational units rather than singular advanced capabilities [8][12] - The article introduces the idea of "technical symbiotic generation," where AI's rise is seen as a natural progression in the history of intelligence [6][8] Group 3: Future of Intelligence - The future of intelligence is framed as a collaborative network involving both humans and machines, rather than a competition between them [12][14] - AI is positioned as an integral part of a larger cognitive system, enhancing decision-making capabilities across various complex structures [9][12] - The article concludes that the emergence of AI is a natural extension of intelligence evolution, emphasizing the importance of structural organization and collaboration in achieving higher levels of capability [16][17]

黄仁勋在访谈中指出，AI竞赛无明确终点线，持续迭代能力比一次性突破更重要，技术进步是渐进 的，所有参与者将共同进化。过去10年AI算力提升10万倍，但这些算力用于让AI更谨慎思考、检验答 案，而非做危险的事。黄仁勋还详细回顾了英伟达多次濒临破产的创业经历，包括1995年技术路线选 择错误、依靠世嘉500万美元投资和台积电张忠谋的信任才得以生存的惊险时刻。 英伟达创始人兼CEO黄仁勋近日在播客节目中进行了一场长达两小时的深度访谈，详细阐述了他对人 工智能竞赛、公司经营以及个人成长的看法。 这位全球市值最高科技公司之一的掌门人，以罕见的坦诚揭示了一个令人意外的事实： 尽管英伟达已 成为AI时代的核心企业，但他每天醒来仍然感到公司"距离倒闭还有30天"。 在谈及当前全球关注的AI竞赛时，黄仁勋提出了与主流观点截然不同的看法。他认为，这场竞赛并非 如外界想象的那样存在一条明确的"终点线"，也不会出现某一方突然获得压倒性优势的局面。相反， 技术进步将是渐进式的，所有参与者都将站在AI的肩膀上共同进化。 他认为， 真正的竞争力在于持续迭代能力，而非一次性突破 。过去10年AI算力提升10万倍，但这些 算力用于让AI更谨慎 ...

Core Insights - The core mechanism of generative AI has fundamentally shifted from data retrieval to learning knowledge structures and performing real-time logical reasoning [4] - Data centers are evolving into new factories that input energy and data to produce intelligent tokens on a large scale [4] - Accelerated computing is allowing Moore's Law to be reborn in a different form [4] - Future programming languages will revert to human natural language, significantly lowering technical barriers and empowering individual creativity [4] Group 1: Transition from Retrieval to Reasoning - The transition from "retrieval" to "reasoning" represents a fundamental change in AI capabilities, where AI generates answers based on learned knowledge rather than retrieving pre-stored responses [6] - Deep learning differs from traditional software development, as it involves training a neural network with vast amounts of input-output examples rather than coding algorithms directly [6][11] Group 2: AI as a New Manufacturing Process - Data centers are described as "AI factories," where the input is electricity and data, and the output is tokens, representing a new form of manufacturing [9] - Energy consumption is a significant challenge for AI expansion, but improving chip efficiency is crucial to meet growing demands without exhausting global energy resources [9][11] Group 3: The Future of Programming - The future of programming will not require learning traditional programming languages; instead, individuals will express their intentions in natural language, making programming accessible to everyone [11] - AI is expected to change job roles rather than eliminate them, as it will allow professionals to focus on core tasks while AI handles routine work [11] Group 4: Accelerated Computing and Moore's Law - Traditional Moore's Law, which states that chip performance doubles every two years, is slowing down, but accelerated computing is reviving it in the context of AI [13][15] - The cost of AI computing has decreased by 100,000 times over the past decade, akin to a revitalized version of Moore's Law [15] Group 5: Company History and Challenges - The company faced a near-bankruptcy situation in 1996, only 30 days away from failure, due to a significant technical error in their gaming chip technology [21] - The CEO's honesty in admitting the failure to a partner led to a crucial financial rescue that saved the company [21][23] Group 6: Leadership and Personal Insights - The CEO emphasizes the importance of experiencing challenges and pain as part of the journey to achieving greatness [33] - The CEO maintains a strong work ethic and a sense of urgency, waking up early to manage responsibilities and staying focused on the present [27][31]