Architecting memory and storage in the AI era

MIT Technology Review · 1 month ago · 5 ● 2 sources

Insights from Tirias Research founder Jim McGregor argues that AI inference and agentic AI require data centers to be rearchitected so memory, storage, and networking are optimized together rather than in isolation. The article says data movement has become the most pressing constraint due to workloads like retrieval-augmented generation that need immediate access to large databases in real time. Enterprises should shift procurement and system design toward workload-aware, modular, efficiency-focused infrastructure to reduce memory/storage bottlenecks and stay flexible as demands and technology change.