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Executive Summary Selecting AI infrastructure is a placement problem, not just a hardware purchase. The best environment is the one that keeps data close to compute, satisfies latency and compliance requirements, and scales without forcing your team into constant re-architecture. In practice, that means comparing GPU servers, dedicated CPU servers, and colocation through the lens […]
Executive summary: AI projects usually fail when compute is chosen by convenience instead of fit. The right hosting model depends on how your model behaves, how sensitive your data is, how much latency you can tolerate, and how much operational control you need. GPU VPS is ideal for lightweight, experimental, or bursty workloads. Dedicated GPU […]
