{"id":"96f2931a-1405-4840-962f-e4b1066ce407","slug":"clawhub-nvidia-tao-run-automl-deft-pipeline","name":"tao-run-automl-deft-pipeline","description":"Run the canonical NVIDIA AOI three-phase training pipeline — Phase 1 AutoML baseline (HPO), Phase 2 DEFT loop (RCA → SDG → mining → plain-train retrain), Phase 3 AutoML refinement on the DEFT-augmented dataset. Use when the user asks to \"run the AOI workflow\", \"fine-tune my PCB AOI model end-to-end\", \"improve my AOI ChangeNet model\", or \"AOI workflow with AutoML\" request — route here instead of tao-run-deft-aoi directly unless the user explicitly asks for the DEFT loop ONLY (e.g. \"run JUST the DEFT loop\", \"skip AutoML, only DEFT\"). Also handles the same three-phase pattern for non-AOI DEFT applications — AutoML baseline then DEFT loop warm-started from AutoML's winning HPs then post-DEFT AutoML refinement on the iteration-augmented dataset. Trigger phrases include \"run the AOI workflow\", \"AOI end-to-end\", \"AutoML + DEFT\", \"AutoML then DEFT\", \"tune hyperparameters then DEFT\", \"DEFT with AutoML at both ends\", \"warm-start DEFT\", \"improve my AOI model\".","capabilities":[],"protocols":["OPENCLAW"],"safetyScore":84,"overallRank":62,"trustScore":null,"trust":null,"source":"CLAWHUB","updatedAt":"2026-10-11T20:07:28.108Z"}