Post-Train NVIDIA Cosmos 3 In a Day with NVIDIA TAO Agent Skills | Cosmos Labs

Last-mile accuracy remains a challenge in physical AI, with training data bottlenecks and slow post-training iteration cycles slowing teams down. NVIDIA Cosmos 3 is the open frontier omni-model for physical AI — and now with NVIDIA TAO agentic skills, you can solve that last-mile accuracy challenge. This livestream shows how to post-train Cosmos 3 in a day, with just a few natural language prompts - taking Cosmos 3 Nano video question answering from 54.41% to 93.35% accuracy with AutoML. What You'll Learn: · Why post-train and which method to choose (LoRA vs. SFT) · How to run an end-to-end post-training pipeline for Cosmos 3 with a single prompt · How TAO AutoML eliminates manual hyperparameter tuning · How to deploy your post-trained model with NVIDIA NIM Have questions about how to post-train and deploy NVIDIA Cosmos 3? Drop them live — the NVIDIA team will answer them in real time. Access more NVIDIA Cosmos developer resources and join our developer community: 📄 Read How To Post-Train NVIDIA Cosmos 3 in a Day → https://nvda.ws/4wDWJJi 📆 Join Our Office Hour on Discord → https://www.addevent.com/calendar/ss55fmjpm04t 📺 Watch a Tutorial on YouTube → https://www.youtube.com/watch?v=9AQkVbx3fKA 📚 Explore Models & Datasets on GitHub → https://github.com/nvidia/Cosmos ⬇️ Download Cosmos on Hugging Face → https://huggingface.co/collections/nvidia/cosmos3 👥 Join the Cosmos Community → https://discord.com/invite/nvidiaomniverse