The era of AI reasoning has arrived, and real-time analysis of massive amounts of data has become a practical requirement in fields such as healthcare and customer service. Enterprises need to redesign their infrastructure architectures, breaking away from isolated optimizations of memory, storage, and networks to achieve system-level collaboration. Jim McGregor points out that AI is not a single workload; it involves millions or even billions of different tasks, requiring the infrastructure to be fully optimized in terms of performance, latency, bandwidth, and scalability. Data centers must support continuous, distributed real-time AI services, and data transfer has become a key bottleneck and competitive opportunity. Technologies such as Retrieval-Augmented Generation (RAG) require frequent scanning of large databases, making data transfer a major constraint. Enterprises need to gain a clear understanding of their workloads, treat data centers as an integrated system, optimize memory and storage systems to meet actual operational needs, and achieve a balance between performance, efficiency, cost, and scalability.
The era of AI inference has arrived, and real-time analysis of massive amounts of data has become a practical requirement in fields such as healthcare and customer service. Companies need to redesign their infrastructure architectures, breaking away from isolated optimizations of memory, storage, and networks to achieve system-level collaboration. Jim McGregor points out that AI is not a single workload; it involves millions or even billions of different tasks, requiring the infrastructure to be fully optimized in terms of performance, latency, bandwidth, and scalability. Data centers must support continuous, distributed real-time AI services, and data transfer has become a key bottleneck and competitive opportunity. Technologies such as Retrieval-Augmented Generation (RAG) require frequent scanning of large databases, making data transfer a major constraint. Companies need to have a clear understanding of their workloads, treat data centers as an integrated system, optimize memory and storage systems to meet actual operational needs, and achieve a balance between performance, efficiency, cost, and scalability.