公众号记得加星标⭐️，第一时间看推送不会错过。 在AI基础设施被资本与产业合力推向发展高潮的当下，凡是与"光""互联""带宽""功耗"挂钩的技 术方向，都极易被贴上"下一代核心技术"的标签，迅速成为市场追逐的焦点，其中共封装光学 （CPO），正是这股热潮中最具代表性的存在。 然而，就在行业对 CPO 的讨论热度节节攀升之际，博通首席执行官陈福阳（Hock Tan）却在2025 财年第四季度财报电话会议上，为这股狂热情绪浇下一盆冷水。 "硅光子学在短期内不会在数据中心发挥实质性作用。" 陈福阳并未简单粗暴地否定这项先进技术地未来，他在后续问答中解释，硅光子、CPO 绝非对现有 技术的"跳跃式"替代方案，而是需要在既有互联技术路径的潜力被彻底榨干后，才会被产业被动启用 的终极选择。他将整个互联技术的演进逻辑清晰梳理：首先是机架级铜互联的规模化落地，随后是可 插拔光模块（Pluggable Optics）的持续迭代升级，唯有当这两条技术路径均触及物理性能与经济成 本的双重极限，硅光子 / CPO 才会真正成为行业刚需。 "这一天一定会到来，但不是现在。" 当然，给CPO降温的并非只有博通一家。在最新的巴克莱第 23 ...

Core Insights - The AI semiconductor industry is expected to experience significant growth in 2026, with a shift in investment logic from upstream to downstream infrastructure [2][10] - The bottleneck in AI development has transitioned from chip manufacturing and packaging to downstream components such as data center space, power supply, and cooling systems [2][5] Upstream Capacity No Longer the Sole Bottleneck - Chip manufacturing and packaging have significantly expanded, alleviating previous supply concerns [4] - TSMC reported stronger-than-expected AI demand and a quick ramp-up in CoWoS capacity, indicating flexibility in the supply chain [4] - Despite ongoing tightness in advanced node wafer front-end capacity, AI semiconductors are prioritized over other applications like cryptocurrency ASICs [4] Bottleneck Shift - The current constraints are now focused on data center space, power availability, and supporting infrastructure, which have longer construction cycles than chip manufacturing [6] - The deployment of large-scale GPU clusters presents challenges in power consumption and heat dissipation, leading to a shift towards liquid cooling and high-voltage direct current (HVDC) solutions [6] Storage and Memory - AI workloads demand high-speed data storage and access, with companies like Meta opting for QLC NAND flash for cost efficiency [8] - The global demand for HBM (High Bandwidth Memory) is projected to surge, with NVIDIA expected to consume 54% of the total HBM by 2026 [8] Racks and Networking - OCP has introduced standardized blueprints for "AI Open Data Centers" and "AI Open Cluster Designs" to facilitate large-scale deployments [9] - Companies like Alibaba are focusing on pluggable optics for their cost-effectiveness and flexibility, while new technologies like CPO/NPO are gaining attention [9] Demand Forecast Indicates Explosive Growth for Downstream Components - Global cloud service capital expenditure is expected to grow by 31% in 2026, reaching $582 billion, significantly exceeding market expectations [11] - AI server capital expenditure could see approximately 70% year-over-year growth if its share in overall capital spending increases [11] AI Chip Demand Breakdown - NVIDIA is projected to dominate the CoWoS capacity consumption with a 59% share, followed by Broadcom, AMD, and AWS [12] - In AI computing wafer consumption, NVIDIA leads with a 55% share, followed by Google, AMD, and AWS [12] Investment Focus Shift - The signals from the OCP conference and industry data indicate a new direction for AI hardware investment, emphasizing the importance of downstream infrastructure [13] - Investors are encouraged to broaden their focus from individual chip companies to the entire data center ecosystem, identifying key players in power, cooling, storage, memory, and networking [13]