From Prompt to Walking Robot With NVIDIA RTX Spark

Meet Microduck, Hugging Face's robot. Let's teach it to see and walk with NVIDIA RTX Spark. I use Hermes as my agent harness, Nemotron and OpenAI's GPT-4o Astra as my models, and CUDA X accelerated tools FreeCAD, Blender, and Isaac Sim, Newton Physics Engine, and Isaac Lab. I'll run everything on my RTX Spark, except when I need to burst larger workloads to cloud. First, I describe the course and what my Microduck needs to learn. On RTX Spark, Hermes and Nemotron plan the course, listing every object required. Astra takes it from there, using FreeCAD to model 3D objects, Blender to apply materials, and Omniverse SimReady libraries to add physical properties. In IsaacSim, Astra composes the scene. Astra rigs Microduck's joints, actuators, and links. And simulates how Microduck moves with Newton physics engine. Now, training begins. In the cloud, thousands of Microducks train in parallel in Isaac Lab. Every fall, a lesson. Improving the policy every time. Omniverse libraries simulate Microduck's cameras, teaching it to see. With perception and physics working together, my Microduck can avoid obstacles, navigate tight spaces, and adapt to its surroundings. I download the policy to RTX Spark and use Nemotron and Isaac Sim to evaluate my Microduck with multi-robot orchestration. I deploy the validated policy to the real duck and he's on his way. NVIDIA RTX Spark. Build and run AI agents and their accelerated tools right on your laptop.