Edge Computing Patterns for AI Inference
Running AI inference in the cloud is easy until it isn’t. The moment you need real-time responses — autonomous vehicles, industrial quality control, AR applications — that 50-200ms round trip becomes unacceptable. Edge computing puts the model where the data lives. Here’s how to architect AI inference at the edge without drowning in complexity. The Latency Problem A typical cloud inference call: Capture data (camera, sensor) → 5ms Network upload → 20-100ms Queue wait → 10-50ms Model inference → 30-200ms Network download → 20-100ms Action → 5ms Total: 90-460ms ...