AI doesn't have to live in the public cloud: on-prem and edge deployments cut cost and latency
DavidLinthicum · x · 2026-11-13
Cloud commentator David Linthicum argues that AI workloads don't have to run in the public cloud. Deploying models on-prem or at the edge—close to data, users, and critical business processes—can reduce both cost and latency.
The post links to a longer piece on this deployment approach, a useful reference for readers tracking private and edge-side AI infrastructure.
Related event: Analyst: On-Prem AI Can Cost 10x Less Than Cloud(2 posts)→
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