大摩：OCP大会焦点，制造和封装已大幅扩产，AI芯片瓶颈转向下游，包括内存、机架、电力等

Core Insights - The core argument of the article is that the bottleneck in AI development has shifted from chip manufacturing and packaging to downstream infrastructure, including data center power, liquid cooling, HBM memory, racks, and optical modules [4][9][19] Group 1: Shifts in Industry Focus - The focus of the market has transitioned from TSMC's CoWoS packaging and advanced processes to downstream supply chain challenges [4][5] - Chip manufacturing and packaging have significantly expanded, alleviating previous supply concerns [5][6] - The demand for AI semiconductors is expected to grow robustly, with the global CoWoS demand projected to reach 1.154 million wafers by 2026, a 70% year-on-year increase [7][14] Group 2: Downstream Infrastructure Challenges - The new bottlenecks are centered around data center space, power supply, and supporting infrastructure, which have longer construction cycles than chip manufacturing [9][10] - The OCP conference highlighted the need for redesigning data centers to accommodate large-scale AI clusters, emphasizing power and cooling requirements [10][18] - The demand for HBM is expected to surge, with global consumption projected to reach 26 billion GB by 2026, where NVIDIA alone is expected to consume 54% [18] Group 3: Investment Opportunities - Investment opportunities are shifting from upstream wafer foundries and packaging to a broader downstream supply chain [4][19] - Companies with robust power and space resources in data centers will have a competitive edge in the AI computing race [4][19] - The report suggests that investors should broaden their focus from individual chip companies to the entire data center ecosystem, identifying key players in power, cooling, storage, memory, and networking [19]