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  • Component-owned guidance for CDF Simulation requests submitted directly or through Airflow-triggered DIG Flow Catalog prompts — golden THT board, THT pin-geometry variation, good/clean SMT images, structural pose defects, and solder texture defects, from
    Skill
  • Physical AI & Robotics
    Enterprise

    Build a Digital Twin for Interactive Fluid Simulation

    This NVIDIA Omniverse™ Blueprint demonstrates how commercial software vendors can create interactive digital twins.
    Blueprint
  • Telecom
    LaunchableDeveloper Example

    AI Agent for Telecom Network Configuration Planning

    Automate and optimize the configuration of radio access network (RAN) parameters using agentic AI and a large language model (LLM)-driven framework.
    Blueprint
  • Physical AI & Robotics
    Enterprise

    NVIDIA Omniverse DSX Blueprint for AI Factory Digital Twins

    Design, simulate, and optimize AI factory infrastructure with digital twins.
    Blueprint
  • Cadence

    fidelity

    Run computational-fluid dynamics (CFD) simulations
    Model
  • Ansys

    fluent

    Run computational-fluid dynamics (CFD) simulations
    Model
  • Siemens

    simcenter-star-ccm+

    Run computational-fluid dynamics (CFD) simulations
    Model
  • Cadence

    spectre-x

    Run large-scale electronics and chip design verification simulations
    Model
  • Intermediate30 MIN

    Set Up Isaac Sim and Isaac Lab

    Realistic robot simulation and RL training before real-world deployment
    Playbook

  • Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.
    Skill

  • Connect the Newton physics engine to an Omniverse simulation or ovstage with ovnewton. Use when importing a populated ovstage into Newton, stepping its physics, synchronizing stage edits, or publishing simulation state for Omniverse rendering.
    Skill
  • NVIDIA
    Free Endpoint

    cosmos-transfer2.5-2b

    Generates physics-aware video world states for physical AI development using text prompts and multiple spatial control inputs derived from real-world data or simulation.
    Model

  • Generate synthetic PCB inspection images on Kubernetes with the SMT Defect Image Generation (DIG) DAG in CDF Orchestration. The DAG renders components in simulation, turns the renders into realistic golden images (sim2real), and uses AnomalyGen to add tex
    Skill

  • Use for agent-assisted Auto-FL optimization of an existing NVFLARE job in simulation, POC, or production. Do not use for code conversion, diagnosis-only work, or deployment setup.
    Skill

  • Use when the user asks why a reported NVFLARE job failure signal occurred: the job failed, stalled, timed out, lost clients, ended with EXECUTION_EXCEPTION, or produced suspicious errors. Diagnose in simulation, POC, or production by collecting bounded ev
    Skill

  • Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation
    Skill

  • Choose a physics engine and integration for robot learning, manipulation, assembly, differentiable optimization, or other Physical AI simulation. Compare Newton, PhysX, MuJoCo/MJX, Bullet/PyBullet, VSim Robotics, Genesis, and Drake. Evaluate Newton first
    Skill

  • Evaluate whether an existing hot path is a credible NVIDIA Warp candidate. Use for irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. CPU-only code and absent GPU
    Skill
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