Core Viewpoint - The article discusses how artificial intelligence (AI) is reshaping data center architecture due to its immense computational power requirements, leading to a transformation from isolated servers to interconnected computing clusters that operate as unified systems [2][3]. Group 1: AI Interconnect Architecture - The AI interconnect architecture is structured in layers, similar to memory systems, categorized by connection distance, bandwidth, latency, and power consumption [2]. - The Scale-up interconnect focuses on connecting GPUs and AI accelerators (XPUs) with high-performance, ultra-low latency links, transitioning from traditional copper solutions to optical technologies like Linear Pluggable Optics (LPO) [3]. - Scale-out interconnects act as the "optical loom" that weaves together multiple racks and units, relying on PAM4 modulation for high bandwidth and low latency over distances of tens to hundreds of meters [4]. Group 2: Data Center Interconnect (DCI) - Data Center Interconnect (DCI) technology connects computing clusters across cities and continents, utilizing coherent ZR optical technology for high-capacity connections over long distances, such as 800G ZR/ZR+ modules achieving up to 2500 kilometers [6]. Group 3: Future of AI Interconnect - The future of AI interconnect will not rely on a single technology but will integrate various solutions like copper, LPO, CPO, PAM4, coherent-lite, and coherent ZR to create a scalable, energy-efficient, and high-performance AI infrastructure [8]. - Collaboration among chip manufacturers, developers, and cloud service operators is essential to elevate interconnects from auxiliary components to core pillars of system architecture, emphasizing the importance of connectivity in the AI landscape [9].