Nvidia · AI Agent · Hugging Face
Part of why NVIDIA rolls out open datasets is to learn with the community to expand upon these various applications
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Open weights matter.
Key facts
- NVIDIA recently highlighted how open models are driving AI research and showing up across the popular International Conference on Machine Learning (ICML), with nearly 145 papers citing Nemotron
- The team hosted a livestream on Tuesday, July 7, 2026 on Why Open Data Matters with an amazing panel
- Access open Nemotron Models on Hugging Face and a collection of NIM microservices and Developer Examples on build.nvidia.com
- As part of Nemotron open data, they've released over 10 trillion pre-training tokens and millions of post-training samples spanning many domains and data shapes
Summary
Building AI agents is hard, because the real world does not behave like a benchmark. An agent that can't recover from a broken API call, or a workflow it has never seen, is not an agent. NVIDIA recently highlighted how open models are driving AI research and showing up across the popular International Conference on Machine Learning (ICML), with nearly 145 papers citing Nemotron models and datasets. Nemotron-CC used synthetics to enhance the popular Common Crawl dataset for pretraining. Nemotron Pretraining is a broad collection spanning general, code, math, and synthetic data across trillions of tokens.