Insights on edge AI testing, on-device performance, and CI/CD for Snapdragon deployments.
We ran MobileNetV2 and ResNet50 100 times each on a Samsung Galaxy S24. Here's the raw data on variance, cold starts, and why median-of-N gating catches what single-run testing misses.
Read morearrow_forwardComplete walkthrough for connecting your ML workflow to Qualcomm AI Hub via EdgeGate — API setup, model submission, pipeline creation, and GitHub Actions integration.
Read morearrow_forwardFP32 to INT8 quantization can silently break your model on real hardware. Learn how to test for accuracy drift, operator fallback, memory spikes, and latency regressions.
Read morearrow_forwardEdge AI regressions cost teams weeks of debugging. Learn why optimized models break on real Snapdragon hardware and how automated quality gates prevent production failures.
Read morearrow_forwardEdge AI inference isn't perfectly repeatable. Learn how median-of-N gating, warmup exclusion, and flake detection bring statistical rigor to hardware testing.
Read morearrow_forwardCryptographically signed evidence bundles give release engineers proof that every model passed quality gates on real hardware. Here's how they work.
Read morearrow_forwardYour model hits 12ms inference in the cloud. On a Snapdragon 8 Gen 3, it takes 47ms. Here's why the gap exists and what to do about it.
Read morearrow_forwardEmulators miss thermal throttling, firmware quirks, and quantization drift. Learn how hardware-in-the-loop testing catches failures before production.
Read morearrow_forwardStep-by-step guide to adding regression gates that test your models on real Snapdragon hardware in every pull request.
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