Use when the user wants to orchestrate defect image generation with NVIDIA Cosmos AnomalyGen (Cosmos-Predict2-derived) on OSMO for PCBA, metal surface, and glass inspection. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and A
Use when running video data augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: video data augmentation, data enrichment, auto labeling, VDA demo, OSMO
Use when running people attribute search (PAS) image augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: people attribute search, PAS, person augmentat
Distill and deploy domain-specific AI models from unstructured financial data to generate market signals efficiently—scaling your workflow with the NVIDIA Data Flywheel Blueprint for high-performance, cost-efficient experimentation.
Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, work
Learn how to create videos using LTX-2 in ComfyUI, accelerated on RTX. Learn how to take control of visual generative AI, creating high resolution video on RTX.
Deploy an AI-powered coding assistant on DGX Spark that delivers expert CUDA-aware chat, real-time code completion, and retrieval-augmented generation grounded in authoritative GPU programming knowledge—powered by NVIDIA NIM microservices.
Many people explore local generative AI for privacy and to avoid token limits, but newer models require significant memory and compute—leading some to adopt multi-GPU setups.
Fine-tune popular AI models faster in Unsloth with NVIDIA RTX AI PCs, RTX PRO workstations, and DGX Spark—plus explore the new Nemotron Nano 3 family of open models.
