A 34-page investor research note on why KV-cache residency, memory tiering, and power — not just silicon supply — are becoming the binding constraints in AI infrastructure.
Written after Nicole’s Bloomberg Intelligence discussion on AI inference, TurboQuant, and the memory wall, this report turns the panel framework into a sourced investor note — with updated analysis on DeepSeek, Cursor, Rubin NVL72, and the emerging market for inference-state management.
AI Infra Research covers the physical and economic layer of AI — memory, serving systems, accelerators, power, and datacenter constraints — for people who need a clear framework rather than another headline summary.
This report is an independent research note, not investment advice. It uses public sources, technical papers, company materials, and market coverage to separate what is known, what is estimated, and what is still uncertain.
See the report →A short note when new research, updates, or live briefings are available. No spam.