光子学具有巨大的潜力，因为光波的传播和干涉无需消耗能量，因此可以通过工程设计来实现可扩展的功能，而无需增加能耗。硅光子学在过去二十年中 得到了广泛的发展，如今已完全具备提供近乎理想的平台的能力，从而释放其巨大的潜力。事实上，硅光子学能够提供高效的高密度互连，实现高带宽和 长距离链路；能够实现低能耗的光路切换，且不受信号带宽的限制；以及能够进行光速计算的光子神经网络，从而加速人工智能计算。 在本文中，我们将回顾这些光子技术的发展趋势和进展，我们将论证，为了使这些光子技术成为人工智能时代可持续基础设施的重要组成部分，硬件和软 件以及电子和光子学需要以互补的方式进行开发。 光收发器和交换机 近年来，生成式人工智能的迅猛发展导致全球范围内超大规模人工智能集群的部署速度空前加快。随着摩尔定律的放缓，只有通过并行计算才能实现更高 的性能，因此，数据处理和/或传输性能的提升必然导致能耗的增加。也就是说，人工智能基础设施的快速增长带来了严重的能源危机。如图 1 所示，随 着数据量的指数级增长，所需的能源供应量也将呈指数级增长。从这个意义上讲，解决这一能源问题的唯一有效途径是开发一种能够将能源增长与数据增 长分离的技术。 A. ...

Core Viewpoint - The article discusses the current state and future potential of Co-Packaged Optics (CPO) technology in the AI infrastructure landscape, emphasizing that while CPO is seen as a next-generation technology, its widespread adoption is not imminent due to existing technological limitations and market dynamics [1][24]. Group 1: Current Industry Sentiment on CPO - Broadcom's CEO Hock Tan stated that silicon photonics will not play a significant role in data centers in the short term, indicating that CPO is not a leapfrog technology but rather a last resort when existing technologies reach their limits [1][24]. - Major industry players, including Arista, Credo, Marvell, and Lumentum, echoed similar sentiments at the Barclays Global Technology Conference, suggesting a cautious approach towards CPO adoption [1][24]. Group 2: Shift in Industry Focus - The AI industry has shifted its focus from merely increasing computing power to addressing interconnectivity and system-level architecture, as the bottleneck has moved from computational capacity to interconnect capabilities [3][4]. - Companies are now prioritizing terms like Scale-Out, Scale-Up, and Scale-Across, indicating a deeper understanding of the infrastructure bottlenecks in AI [4]. Group 3: Horizontal and Vertical Scaling - Horizontal scaling (Scale-Out) is currently dominated by pluggable optics, with CPO technology not yet widely adopted due to the existing 800G and 1.6T technologies still being the main focus [7][8]. - Vertical scaling (Scale-Up) was initially seen as a promising application for CPO, but its timeline has been pushed back, with large-scale deployment expected around 2027-2028 [9][10]. Group 4: Challenges Facing CPO - CPO faces significant challenges, including higher costs, reliability issues, and power consumption concerns, which have delayed its mass production [18][24]. - The complexity of system design and the need for a mature supply chain are also major obstacles to the widespread adoption of CPO technology [19][24]. Group 5: Alternative Solutions - Transition solutions like LPO, AEC, and ALC are increasingly being recognized as viable alternatives to CPO, with many companies focusing on these technologies to meet current demands [15][25]. - LPO technology has already seen large-scale deployment, providing cost and power advantages, while AEC and ALC are being developed to offer reliability similar to copper cables with the bandwidth of optical solutions [15][25]. Group 6: Future Outlook - Industry predictions suggest that CPO will begin to see deployment in specific high-density systems around 2028, but the current focus remains on optimizing existing technologies [26][27]. - The industry consensus is that CPO will not be the immediate solution until existing technologies reach their limits in terms of power, density, and reliability [27].

公众号记得加星标⭐️，第一时间看推送不会错过。 激光雷达（LiDAR）传感器曾经被认为是高度自动化车辆不可或缺的部件，但在过去几年中，尤其是 在西方，其声望有所下降。 这一逆转让汽车领域的一些人开始思考，西方激光雷达供应商是否还有第二次生命。 克莱门特·努维尔（Clement Nouvel ）曾是法国一级汽车零部件供应商法雷奥公司的"激光雷达先 生"。他现在是纽约Voyant Photonics公司的首席执行官。他认为，像基于硅光子模块的调频连续波 （FMCW）激光雷达这样的新技术，可能会改变全球激光雷达的格局。 Nouvel 认为，成立六年的初创公司 Voyant 可以开辟许多新的激光雷达应用领域，包括仓库中的叉 车、自动导引车 (AGV) 和自主移动机器人 (AMR)。 尝试转向 尽管许多激光雷达公司都尝试将激光雷达应用于汽车以外的领域，但结果却令人失望。问题在于，一 旦你承诺为汽车OEM厂商提供激光雷达服务，你就几乎没有余力去做其他事情了。 传统的基于飞行时间 (ToF) 的激光雷达虽然取得了进步，但众所周知，它在可靠性（串扰和光晕）、 集成限制和成本方面存在问题。 市场力量也导致了激光雷达行业的剧烈波 ...

Core Viewpoint - Samsung is heavily investing in silicon photonics technology to disrupt the AI chip foundry landscape and challenge TSMC by enhancing data transmission speeds using light [1][2][3]. Group 1: Technology Overview - Silicon photonics is seen as a disruptive technology for the future AI semiconductor market, utilizing light for information transmission, which offers advantages such as higher speed, lower heat generation, and reduced energy consumption [1][2]. - The technology combines silicon, a primary semiconductor material, with photonics, allowing for faster and more efficient data transmission by using light instead of electrical signals [3][4]. - The capacity for data transmission is expected to increase from gigabytes (GB) to terabytes (TB), with speed improvements exceeding 1000 times [3]. Group 2: Market Dynamics - Major semiconductor companies like NVIDIA, AMD, and Intel are shifting towards silicon photonics to meet the growing demand for rapid data processing in AI applications [2][3]. - The silicon photonics market is projected to grow to $10.3 billion (approximately 15 trillion KRW) by 2030, indicating significant market potential [2]. - TSMC is currently the leader in the Co-Packaged Optics (CPO) market, with NVIDIA actively developing silicon photonics technology [6][7]. Group 3: Samsung's Strategy - Samsung has identified silicon photonics as a key technology to attract more large foundry customers and to compete effectively against TSMC in advanced packaging markets [7]. - The company is expanding its global R&D network, particularly in Singapore, to enhance its capabilities in silicon photonics [6][7]. - Samsung plans to commercialize CPO technology by 2027, with competition against TSMC expected to intensify from that point onward [7].

Core Viewpoint - GlobalFoundries has acquired Advanced Micro Foundry (AMF), a Singapore-based chip manufacturer specializing in silicon photonics, a rapidly growing field relevant to AI data centers and quantum computers [1][3]. Group 1: Acquisition Details - The financial details of the acquisition have not been disclosed by GlobalFoundries [1]. - The acquisition is expected to position GlobalFoundries as the largest manufacturer of silicon photonic devices globally [3]. Group 2: Technology and Market Implications - Silicon photonics technology integrates traditional computing chip technology with optical network technology that uses light pulses for data transmission [3]. - Companies like NVIDIA are collaborating with TSMC to package network chips with optical connections, indicating a trend towards advanced data transmission technologies [3]. - Several well-funded Silicon Valley startups, including Ayar Labs, Celestial AI, and Lightmatter, are focusing on optical interconnect technology, with some choosing GlobalFoundries as their chip manufacturer [3]. Group 3: Future Developments - GlobalFoundries plans to establish a new R&D center in Singapore following the acquisition of AMF [3]. - The CEO of GlobalFoundries, Tim Breen, emphasized the importance of high-speed, precise, and energy-efficient data transmission for AI data centers and advanced telecom networks [3].

Core Viewpoint - Tower Semiconductor, a chip manufacturer that nearly sold for $5 billion to Intel two years ago, has seen its market value double to $10 billion, indicating strong performance and growth potential in the semiconductor industry [2][3]. Financial Performance - Tower Semiconductor reported a strong Q3 performance with revenue of $396 million, a 6% increase from the previous quarter, and a net profit of $54 million, equating to $0.48 per share, both exceeding market expectations [3]. - The company generated $139 million in cash flow from operations during the same quarter [3]. Future Outlook - Tower Semiconductor plans to invest $300 million to expand production capacity across four global manufacturing facilities, including one in Israel, to increase the output of next-generation analog chips that support AI applications [2]. - The company anticipates reaching a record revenue of $440 million by Q4 2025, driven by a 14% compound annual growth rate, projecting annual revenue of $1.5 billion by the end of 2025 [3]. Market Reaction - On November 10, Tower Semiconductor's stock surged by 16.69% to $98.10, marking the highest price since 2004, with a year-to-date increase of 90.45% [3].

Core Insights - The article discusses the significant impact of AI hardware, particularly GPUs, on the market, highlighting NVIDIA's rise to become one of the highest-valued companies globally due to its dominance in AI chip technology [1][3]. - It raises questions about the future of AI hardware, the trends shaping its development, and the emergence of new players in the market [1][3]. AI Hardware Market Dynamics - The AI boom continues despite fluctuations, with substantial investments from the U.S. government and the EU aimed at enhancing AI capabilities [3][4]. - NVIDIA holds approximately 90% of the global gaming GPU and data center GPU market, with a projected revenue growth of over 50% in 2025 compared to 2024, which already saw a record revenue of $130.4 billion [4][3]. GPU Demand and Alternatives - The demand for GPUs in AI is driven by their parallel processing architecture, which allows for rapid handling of large datasets, crucial during the AI training phase [6][7]. - Alternatives to GPUs include Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Arrays (FPGAs), each with distinct advantages and limitations [7][8]. Competitive Landscape - The competitive landscape is evolving, with AMD and Intel as key competitors to NVIDIA, though NVIDIA's CUDA programming environment offers significant advantages over AMD's ROCm [10][11]. - Intel's Gaudi 3 chip, aimed at competing with NVIDIA, has faced challenges in gaining market traction due to NVIDIA's established dominance [12]. Emerging Players and Innovations - Companies like Google are developing their own chips, such as TPUs, to reduce reliance on NVIDIA, indicating a shift in the competitive dynamics of the AI hardware market [12][13]. - Startups like Cerebras, SambaNova, and Groq are emerging with innovative solutions that could challenge NVIDIA's position in the long term [14][15]. Future Trends in AI Hardware - The future of AI hardware may involve a hybrid model combining GPUs, ASICs, FPGAs, and new chip architectures, driven by the need for differentiation based on workload types [18]. - Key technological advancements such as silicon photonics, neuromorphic computing, and quantum computing are expected to influence the AI chip market, although their specific impacts remain uncertain [17][18].

Core Viewpoint - Optical technology has matured in long-distance communication, but its service distance is shrinking, particularly in data centers, with a shift from fiber optics to more compact solutions like waveguides [2]. Group 1: Current Trends in Optical Technology - Vertical-cavity surface-emitting lasers (VCSELs) are driving short fiber links, and there is ongoing research to bring fiber optics closer to data center servers [2]. - The transition of fiber optics from card edges to onboard and now to packaging indicates a significant evolution in optical communication [2]. Group 2: Integration Challenges - The integration of lasers with silicon faces challenges related to reliability, temperature sensitivity, and energy consumption [4]. - Current optical devices rely on distributed feedback lasers (DFB), which are effective for long-distance fiber optics but are more expensive compared to other types [6]. Group 3: Temperature Management - Temperature control is a major challenge for laser developers, as precise temperature management is crucial for maintaining signal integrity [8]. - Experts suggest that isolating lasers from high-temperature chips can enhance performance and reliability [9]. Group 4: VCSEL Applications and Limitations - VCSELs are cost-effective and suitable for short-distance connections, particularly in data centers, but they face challenges in wavelength compatibility with existing optical systems [14]. - Recent advancements have improved the bandwidth of O-band VCSELs, reigniting interest in their use for single-mode fiber applications [15]. Group 5: Future Research Directions - Ongoing research is focused on integrating III-V materials into silicon substrates, although these technologies have not yet reached mass production levels [12]. - Quantum dot (QD) lasers, which are less temperature-sensitive, are also being explored, but their output power remains a limitation [12].

Core Insights - The article discusses the growing importance of integrated semiconductor optical modules, specifically On-Board Optical (OBO), Near-Package Optical (NPO), and Co-Packaged Optical (CPO) solutions, which are expected to see a compound annual growth rate of 50% in shipment volume by 2033 [2][4]. Group 1: Market Trends - Integrated optical solutions are significantly improving transmission capacity and processing for AI systems, providing higher bandwidth at lower power consumption [2][4]. - The transition from copper to optical solutions is anticipated to lead to a non-linear performance enhancement, with potential performance increases of up to 80 times compared to existing solutions [7]. Group 2: Key Players and Future Projections - Major companies like NVIDIA, Intel, Marvell, and Broadcom are currently leading the development of CPO technology, which is expected to drive substantial revenue growth and shipment volume by 2027 [4]. - By 2033, it is projected that over half of the revenue and shipment volume will come from integrated semiconductor optical I/O solutions [4].

Core Viewpoint - A multidisciplinary academic team has successfully integrated quantum light sources and electronic devices into a single silicon chip, marking a significant advancement in quantum technology [3][4]. Group 1: Technological Breakthrough - The researchers developed the first chip that integrates electronic, photonic, and quantum components, utilizing standard 45-nanometer semiconductor manufacturing processes [3][4]. - This integrated technology enables the chip to produce a continuous stream of correlated photon pairs, which are fundamental for many quantum applications [4]. Group 2: Future Implications - The breakthrough signifies an important step towards the mass production of "quantum light factory" chips and the development of more complex quantum systems composed of multiple interconnected chips [4]. - The research indicates that quantum computing, communication, and sensing could transition from concept to reality over the next few decades [4]. Group 3: System Design and Stability - The chip features a system that actively stabilizes the quantum light sources, specifically the silicon micro-ring resonators, which are sensitive to temperature and manufacturing variations [6][7]. - Each chip contains 12 parallel-operating quantum light sources, with integrated photodiodes to monitor and maintain the alignment of the incident laser [7]. Group 4: Collaborative Efforts - The project required interdisciplinary collaboration among fields such as electronics, photonics, and quantum measurement, essential for transitioning quantum systems from the lab to scalable platforms [4][8]. - The chip is manufactured using a commercial 45-nanometer complementary metal-oxide-semiconductor (CMOS) platform, developed in collaboration with various institutions and companies [7][8]. Group 5: Industry Impact - The advancements in silicon photonics and quantum technology are expected to serve as a foundation for technologies ranging from secure communication networks to advanced sensing and ultimately quantum computing infrastructure [8]. - Several researchers involved in the project have moved into the industry, reflecting the growing momentum of silicon photonics and its potential in expanding AI computing infrastructure and scalable quantum systems [8].