Optimizing AI Agents with NVIDIA's Data Flywheel Blueprint

NVIDIA has released the AI Blueprint for Building Data Flywheels, a workflow to optimize AI agents by automated experimentation. The blueprint uses NVIDIA NeMo and NIM microservices to distill, fine-tune, and evaluate smaller models using real production data. It integrates with existing AI infrastructure and supports multi-cloud, on-prem, and edge environments. The process involves ingesting and curating logs, experimenting with existing and newer models, deploying and improving continuously, and using automated experimentation to find efficient models that reduce inference costs and improve latency.