Uploaded August 2026 | Updated September 2026, 2 weeks ago
Take the leap from local models to local agents. In this session, developers learn how to move beyond running a model and deploy a fully autonomous AI assistant on NVIDIA Jetson — no cloud required. OpenClaw provides a local AI assistant framework that connects to chat interfaces, browser-based tools, and multi-step agentic tasks. NemoClaw extends that baseline with sandboxing, inference routing, and policy controls for safer, production-ready edge deployments.
In this stream, you will learn how to move from running a local model to running a fully local autonomous agent on NVIDIA Jetson.
We'll cover:
- Building a local assistant with OpenClaw — build a full local assistant architecture that connects to chat workflows, browser-based tools, and multi-step tasks — running privately on your own hardware, 24/7.
- Why tool-calling models matter — see what changes when an AI system can take actions, use tools, and run autonomously, and what breaks when your model can't do it reliably.
- Safer local agents with NemoClaw — go further with sandboxing, onboarding, inference routing, and policy controls that make local agent deployment more structured and production-ready.
- Real-world use cases — explore what becomes possible: building dynamic browser-based games, prototyping smart computer vision apps, and running long research tasks without any cloud dependency.
Take the leap from local models to local agents. In this session, developers learn how to move beyond running a model and deploy a fully autonomous AI assistant on NVIDIA Jetson — no cloud required. OpenClaw provides a local AI assistant framework that connects to chat interfaces, browser-based tools, and multi-step agentic tasks. NemoClaw extends that baseline with sandboxing, inference routing, and policy controls for safer, production-ready edge deployments.
In this stream, you will learn how to move from running a local model to running a fully local autonomous agent on NVIDIA Jetson.
We'll cover:
- Building a local assistant with OpenClaw — build a full local assistant architecture that connects to chat workflows, browser-based tools, and multi-step tasks — running privately on your own hardware, 24/7.
- Why tool-calling models matter — see what changes when an AI system can take actions, use tools, and run autonomously, and what breaks when your model can't do it reliably.
- Safer local agents with NemoClaw — go further with sandboxing, onboarding, inference routing, and policy controls that make local agent deployment more structured and production-ready.
- Real-world use cases — explore what becomes possible: building dynamic browser-based games, prototyping smart computer vision apps, and running long research tasks without any cloud dependency.
