Investment Rating - The report maintains an "Outperform" rating for the communication industry, indicating expected performance above the market benchmark by over 10% [6][46]. Core Insights - The communication industry is experiencing significant growth driven by advancements in AI infrastructure and cloud computing technologies, with companies like AWS and Marvell leading the charge [5][11][18]. - Credo's revenue growth is attributed to the expansion of AI training and inference infrastructure, with a notable increase in demand for AEC and ALC products [3][21]. - Marvell's acquisition of Celestial AI is a strategic move to enhance its capabilities in data center optical interconnect technology, positioning the company for future growth in AI and cloud data centers [2][18]. Summary by Sections Industry News Tracking - AWS successfully hosted its annual re:Invent cloud computing conference, unveiling the next-generation AI training chip Trainium 4, which supports NVLink Fusion technology [11][12]. - Marvell reported a 37% year-over-year revenue increase for FY2026Q3, driven by data center demand and operational efficiency, and announced a $3.25 billion acquisition of Celestial AI to enhance optical interconnect technology [2][13][18]. - Credo's FY2026Q2 revenue reached $268 million, reflecting a 20.2% quarter-over-quarter increase, with ALC expected to drive future growth [3][21]. Market Performance Review - The communication sector index rose by 3.69% this week, outperforming the Shanghai Composite Index, which increased by 1.28% [4][36]. - Key sectors such as satellite internet, optical devices/chips, and IoT controllers showed strong performance, with respective increases of 9.85%, 5.93%, and 4.35% [36]. Investment Recommendations - The report suggests continued focus on AI computing infrastructure development, recommending investments in optical devices, communication equipment, and liquid cooling technologies [5][43]. - The three major telecom operators are highlighted as important assets for dividend allocation, with stable operations and increasing dividend payouts [5][43].

Core Insights - AWS is at a pivotal moment, focusing on transforming AI from an assistant role to a more capable agent role, aiming to deliver real business value to enterprise customers [1][18]. Group 1: Computing Power - AWS has adopted a more pragmatic and aggressive strategy in computing power, significantly reducing costs with self-developed chips and breaking physical boundaries to accommodate large clients who prefer not to migrate to the cloud [4]. - The introduction of Trainium 3 UltraServers has improved inference efficiency by five times compared to its predecessor, with Trainium 4 promising a further sixfold performance increase [4][27]. - AWS AI Factories have been launched to address data sovereignty concerns by allowing clients to build AWS's computing infrastructure directly in their data centers [4]. Group 2: Model Development - AWS has completed its Amazon Nova self-developed model family with the release of the Amazon Nova 2 series, which includes the first multimodal model capable of processing text, images, audio, and video inputs [6]. - The Amazon Nova Forge introduces the concept of "open training models," allowing enterprises to inject proprietary data during the final stages of model pre-training, enhancing the model's capabilities without losing core competencies [6][37]. Group 3: Application Layer - AWS is addressing the uncontrollable nature of AI agents by implementing a robust policy framework, AgentCore Policy, to ensure agents act as reliable productivity tools [7][45]. - The Frontier Agents series has been introduced, which includes autonomous agents capable of performing tasks such as bug fixing and security scanning, indicating a shift in software engineering lifecycle management [7][41]. - The AgentCore platform is designed to facilitate the secure and scalable deployment of agents, with features that allow for real-time monitoring and control of agent actions [41][44]. Group 4: Business Growth and Infrastructure - AWS reported an annual revenue of $132 billion, with a growth rate of 20%, indicating strong business performance and market leadership in cloud computing [10]. - The company has expanded its global data center network, adding 3.8 GW of capacity in the past year, which is the largest in the industry [13]. - AWS's collaboration with various partners, including startups and established companies, highlights its role in driving innovation across multiple sectors [14].

Core Insights - Analysts from Oppenheimer and JPMorgan reaffirmed a positive outlook on Amazon Web Services (AWS), highlighting significant growth opportunities in the cloud computing sector, particularly with the focus on Agentic AI [1][2] - The annual AWS re:Invent event showcased a strong emphasis on Agentic AI, with CEO Matt Garman's keynote defining the evolution of cloud computing and the importance of AI infrastructure [1][3] Group 1: Agentic AI and Infrastructure - Matt Garman identified four key pillars necessary for the realization of Agentic AI: AI Infrastructure, model ecosystem, data foundation, and developer tools [2] - AWS introduced several significant products and enhancements aimed at supporting Agentic AI, including Amazon Trainium3 UltraServers and the Amazon Nova 2 series of models [2][6] - The Amazon Trainium series has become a core business for AWS, with a reported quarterly growth of 150%, emphasizing its importance in building AI infrastructure [4][5] Group 2: Product Innovations - The Amazon Trainium3 UltraServers, designed for intensive parallel workloads, offer substantial performance improvements, including a 4.4 times increase in computational capability compared to its predecessor [6][8] - AWS announced the Amazon Nova 2 series, which includes models tailored for various applications, such as Amazon Nova 2 Lite for everyday workloads and Amazon Nova 2 Omni for multi-modal input and output [15][18] - The introduction of Amazon Nova Forge allows enterprises to create customized models by integrating their proprietary data with AWS's pre-trained models [24] Group 3: Developer Tools and Agentic AI - AWS emphasized the importance of developers in the AI landscape, introducing updates to Amazon Bedrock AgentCore that allow for clearer boundaries on AI capabilities [25][27] - The launch of three Frontier Agents—Kiro Autonomous Agent, Amazon Security Agent, and Amazon DevOps Agent—demonstrates AWS's commitment to enhancing developer experience and operational efficiency [30][31] - The focus on private data as a critical differentiator for enterprises was highlighted, with AWS advocating for the integration of proprietary data into AI models to enhance their effectiveness [21][22]