AIHacker Noonabout 14 hours ago
Latency Budgets Beat Raw Speed in ML Serving
11 min read
Latency optimization becomes counterproductive in ML-driven serving platforms, where faster responses sacrifice decision quality. Mature systems treat latency as a budget, using cascaded inference and request hedging to clamp tail latency. Average latency metrics mislead; P95 and P99 spikes dominate user perception.
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