Edge AI Architecture: From Cloud Dependency to On-Device Inference

Running AI at the edge requires rethinking the entire model lifecycle — from training in the cloud to deploying compressed models on constrained hardware. Understanding the deployment pipeline, tradeoffs, and tooling is essential for engineers building real-world edge AI systems today.