Description
NVIDIA Cosmos 3 is a new open world reasoning vision-language model (VLM). NVIDIA TAO 7 is a suite of agent skills and tools for fine-tuning vision AI models like Cosmos 3 with coding agents and natural language prompts. In this tutorial, you’ll learn how to install TAO skills in Codex, customize NVIDIA Cosmos 3 reasoning VLM for any domain, and automatically optimize hyperparameters with AutoML to deliver the best accuracy for your use case.
Chapter
00:00 Introduction to TAO Agent Skills
01:36 Installing & Configuring TAO Skills
02:53 LoRA Fine-Tuning
04:33 Optimizing with TAO AutoML
06:08 Final Results & Experiment Report
06:54 Conclusion
Q: What is NVIDIA Cosmos 3 and what makes it unique?
A: Cosmos 3 is a frontier, open-world omnimodel for physical AI that natively unifies text, image, video, audio, and actions under a single Mixture-of-Transformers architecture.
Q: How can I use natural language to fine-tune a vision language model (VLM) to improve KPI?
A: Install the TAO Skills, then describe your task in plain language, the agent selects the right skill, runs fine-tuning, and reports results automatically.
Q: How do I make a vision language model (VLM) more accurate?
A: Leverage the TAO AutoML skill to execute structured, parallel parameter sweeps.
Q: What is the benefit of LoRA over full-parameter SFT for video data?
A: Resource optimization. LoRA freezes base weights to prevent general knowledge regression while requiring roughly 7x fewer GPU-hours than full-parameter SFT.
Resources
Tech Blog: https://nvda.ws/4wkbku1
Livestream- Post-Train NVIDIA Cosmos 3 In a Day with NVIDIA TAO Agent Skills: https://www.youtube.com/watch?v=lKaqbYa0HUE
Cosmos Web Page: https://nvda.ws/3RuLqV0
TAO Product Page: https://nvda.ws/4vcIr1Z
TAO skills on GitHub: https://nvda.ws/4uHMcf5