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 BlogIn practice, the most effective agent customization combines multiple techniques in sequence. The stages of a representative pipeline are outlined below. Start with system prompts, tool and skill definitions, and retrieval to establish baseline behavior.
Mastering Agentic Techniques: AI Agent Customization | NVIDIA Technical Blog… Building on RaySim, Keysight’s AI‑RAN Simulation Toolset enables developers to integrate the NVIDIA AI Aerial platform to create hardware testbeds and digital twins that facilitate training and benchmarking of AI-RAN workloads in an integrated, end-to-end workflow. …
… NVIDIA AI Aerial Software Explore open source software libraries and tools for building, training, simulating, and deploying AI-native wireless networks. Access to NVIDIA Aerial software is available on GitHub . Access for NVIDIA Sionna™ is available via the Sionna Developer page . …
… This includes access to hundreds of SDKs, a network of like-minded developers through our community forums, and more. Technical Training NVIDIA Deep Learning Institute DLI offers hands-on training in AI, accelerated computing, and accelerated data science to solve real-world problems. …
… Available providers: Baseten Bitdeer AI Clarifai Crusoe DeepInfra DigitalOcean Eigen AI fal.ai Fireworks AI FriendliAI GMI Cloud Inference.net Lightning AI Modal Nebius Together AI Vultr You can also explore Nemotron model details, documentation, and access paths through the following discovery and… …
… 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… …
… The remaining 20 GPUs from their quota, plus access to the over-quota pool, are available for post-training jobs when the team occasionally needs to improve their models based on customer feedback. …
… This helps accelerate DLI applications by reducing data access latency and training time. Step 3: Simulation and Testing Simulation Simulation of real-world scenarios isn't only critical for training for unforeseen scenarios, but also vital for testing and validation of autonomous vehicles. …
… End-to-end training and evaluation recipes The complete pre-training , post-training , and evaluation recipe for Nemotron 3 Nano Omni is available, covering the full pipeline from pre-training through alignment. …
… Startups get access to training through NVIDIA’s Deep Learning Institute, preferred pricing on hardware through our global network of distributors, invitations to exclusive networking events, and more.
… 4b Online RL post-training PPO via RLinf for precision stages For Assemble Trocar, Rheo provides a turnkey launcher: bash /workspaces/workflows/rheo/scripts/sim/rl/train gr00t assemble trocar.sh train \ --model path /models/ You can scale parallel environments or downshift for memory: scale up/down… …