Foundation models come with broad language and reasoning capabilities across use cases and modalities based on the training datasets used. Models understand language and can follow instructions, but specialized workflows often require context that is restricted, specialized, or proprietary. Customizing an agent solves this challenge by shaping how the agent reasons under constraints, which tools it selects, how it structures its outputs, and how reliably it executes domain workflows.
Mastering Agentic Techniques: AI Agent Customization | NVIDIA Technical Blog… This photorealistic data is crucial for post-training policy models, ensuring smooth simulation-to-reality transfer and supporting model training for perception AI and specialized robot models like GR00T N1 . …
… Discuss 0 Discuss 0 Tags Agentic AI / Generative AI | Developer Tools & Techniques | General | NeMo | Intermediate Technical | Deep dive | AI Agent | featured | GB300 | Megatron | NVIDIA Research | Training AI Models About the Authors About Hao Wu Hao Wu is a distinguished GPU architect at NVIDIA. …
… We show the local training code on the left and the federated version on the right, highlighting: import, flare.init , receive , send . train.py train.py import torch import torchvision import torchvision.transforms as transforms from model import Net batch size = 4 epochs = 1 lr = 0.01 model = Net… …
… He has participated in the release of Falcon-H1, Falcon-Edge, Falcon 3, FalconTiny and Falcon-Mamba, working across infrastructure, data pipelines, and large-scale training. His work spans both pretraining and post-training, supporting efficient system scaling and robust model deployment. …
… When to use Working with accessible data for well-defined tasks with output examples Customizing a model for a low-resource domain where labelled examples are limited, and high-quality synthetic data can be generated to bootstrap the fine-tuning dataset Requiring the model to reliably produce speci… …
… Nemotron 3 Ultra is available through an ecosystem of partners: Model customization services: Applied Compute , Prime Intellect , Unsloth Inference software: SGLang , TRT-LLM , vLLM Cloud service providers: Amazon SageMaker JumpStart , Google Cloud, Microsoft Foundry , Oracle Cloud Inference servic… …
… Fine-tuning cookbooks Explore our Nemotron 3 Super customization cookbooks to efficiently fine-tune for your domain LoRA/SFT or advance its agentic reasoning capabilities GRPO/DAPO : LoRA SFT on Nemotron 3 Super using NVIDIA NeMo Megatron-Bridge LoRA SFT on Nemotron 3 Super using NVIDIA NeMo Automo… …
… Discuss 0 Discuss 0 Tags Agentic AI / Generative AI | Data Science | MLOps | General | Blackwell | NeMo | Intermediate Technical | Tutorial | featured | LLMs | Training AI Models About the Authors About Guyue Huang Guyue Huang is a deep learning architect at NVIDIA, specializing in post-training RL… …
… Using synthetic training data generated by large teacher models, developers can distill character behaviors into lightweight, deployable LoRA-powered performances that run locally on RTX hardware. …
… Skild AI is building a general-purpose robotics foundation model that spans legged, wheeled and humanoid robots, using Isaac Lab for locomotion and dexterous manipulation tasks training and NVIDIA Cosmos world foundation models for generating training datasets. …
