2026年AI最大的叙事变化是什么？

Core Insights - 2026 is projected to be a pivotal year where AI inference workloads may surpass training workloads, with inference expected to account for the majority of AI capital expenditures by 2030, potentially reaching 75% of the estimated $1.2 trillion [1][4]. Group 1: AI Capital Expenditure and Market Performance - Despite concerns regarding funding, valuations, and interest rate fluctuations, the continuous growth in AI capital expenditures is driving strong performance in the semiconductor sector [1]. - The Philadelphia Semiconductor Index (SOX) has risen approximately 13% year-to-date, marking the second-best January performance in the past 20 years, significantly outperforming the S&P 500's 1% increase [1]. - The recent surge in semiconductor stocks is primarily led by storage chip manufacturers, semiconductor equipment suppliers, and analog chip producers, rather than major players like NVIDIA and Broadcom [1]. Group 2: Differentiated Opportunities for Chip Suppliers - The shift towards inference workloads will create differentiated opportunities for various types of chip suppliers, including GPUs, CPUs, and ASICs, while also impacting storage and semiconductor equipment suppliers [3]. - NVIDIA maintains a leading position with a comprehensive product lineup across both training and inference domains, supported by supply assurance advantages [5]. - AMD is viewed as a reliable second supplier of general-purpose chips, with recent stock price fluctuations attributed to market concerns over TSMC's 2nm process, which is still on track according to analysts [5]. Group 3: Optical Connectivity and Market Dynamics - Demand for optical connectivity is real, but recent price increases may be excessive; optical transceiver and component suppliers are among the strongest performers after storage chips [6]. - The necessity for optical connections is underscored by the expanding scale and bandwidth requirements of AI clusters, with NVIDIA's upcoming photonic switch expected to act as a potential catalyst [6]. - However, evidence of interest in co-packaged optics (CPO) from major cloud service providers is limited, primarily due to operational complexities and control over the bill of materials shifting to NVIDIA and Broadcom [6].