# Trustworthy AI We believe AI should respect privacy and data protection regulations, operate in a secure and safe way, function in a transparent and accountable manner, and avoid unwanted biases and discrimination. We are committed to safe and trustworthy AI, in line with the White House Voluntary Commitments and other global AI Safety initiatives. ## Our Guiding Principles for Trustworthy AI ### Privacy AI should comply with privacy laws and regulations, and meet societal norms for personal data and information privacy. ### Safety and Security Ensure that AI systems perform as intended and avoid unintended harm and malicious threats. ### Transparency Make AI technology understandable to people. Explain, in non-technical language, how an AI system arrived at its output. ### Nondiscrimination Minimize bias in our AI systems and give all groups an equal opportunity to benefit from AI. ## Methods and Technologies Trustworthy AI principles are foundational to our end-to-end development and essential for the technical excellence that enables partners, customers, and developers to do their best work. We are building [data factories for generative AI services](https://nvidianews.nvidia.com/news/nvidia-partners-with-foxconn-to-build-factories-and-systemsfor-the-ai-industrial-revolution), tools to [curate and validate unbiased datasets for computer vision](https://developer.nvidia.com/blog/curating-data-for-transfer-learning-with-the-nvidia-tao-toolkit-and-innotescus/), libraries for [scaling natural language processing data for large language models](https://developer.nvidia.com/blog/curating-trillion-token-datasets-introducing-nemo-data-curator/), groundbreaking security features like [confidential computing](https://www.nvidia.com/en-us/data-center/solutions/confidential-computing.md), and innovations like open-source [techniques for model alignment](https://developer.nvidia.com/blog/announcing-steerlm-a-simple-and-practical-technique-to-customize-llms-during-inference/) with human feedback. To check out the free, open source templates NVIDIA has provided to support the development of transparent AI documentation, visit the [NVIDIA/Trustworthy-AI GitHub repo](https://github.com/NVIDIA/Trustworthy-AI/tree/main/Model%20Card%2B%2B%20Templates). With these expanded resources, NVIDIA is making it easier for customers and partners to responsibly develop AI and advance transparency and accountability across the AI supply chain. > **Trustworthiness is a fundamental property of our technology.** — Jensen Huang, NVIDIA founder and CEO 1. Quote 1 ## Our Trustworthy AI Solutions ### Model Card Generator AI model cards are the standard for increasing confidence in the development lifecycle, demonstrating compliance, and encouraging transparency. Minimize manual effort and increase efficiency by automating the creation of model cards. [Enhance AI Model Transparency With Minimal Effort](https://www.nvidia.com/en-us/on-demand/session/gtc25-S72399/) ### NVIDIA Halos for AI Safety NVIDIA Halos is a full-stack, comprehensive safety stack that unifies architecture, AI models, chips, software, tools, and services to ensure the safe development of physical AI like autonomous vehicles and robotics. [Learn How NVIDIA Is Building Autonomous Vehicle Safety](https://www.nvidia.com/en-us/ai-trust-center/halos/autonomous-vehicles.md) ### NeMo Guardrails NVIDIA NeMo Guardrails helps ensure that smart applications powered by large language models (LLM) are accurate, appropriate, on topic, and secure. [Learn More About NVIDIA NeMo Guardrails](https://developer.nvidia.com/blog/nvidia-enables-trustworthy-safe-and-secure-large-language-model-conversational-systems) ## Partnering for Trustworthy AI Technology ### Te Hiku Media NVIDIA Inception member Te Hiku Media created a highly accurate bilingual speech recognition system for the Māori language and NZ English, built and owned by its own language community. [Learn More About Te Hiku Media](https://papareo.io/) ### Google DeepMind’s Synth ID NVIDIA is the first external user to embed digital watermarks directly into AI-generated audio, images, text, and video content to safeguard against misinformation and misattribution without compromising video quality. [Learn More About NVIDIA and Google’s Work to Build Trust](https://nvidianews.nvidia.com/news/nvidia-alphabet-and-google-collaborate-on-the-future-of-agentic-and-physical-ai) ### SIGNS NVIDIA is partnering with the American Society for Deaf Children, Hello Monday/DEPT, and the Rochester Institute for Technology to teach and build a publicly available dataset for accessible technologies through the Signs Platform. [Learn and Help Build the World’s Largest Dataset for American Sign Language](https://signs-ai.com/) ## Trustworthy AI in the News ### View All Trustworthy AI Stories [Corporate Blog](https://blogs.nvidia.com/blog/tag/trustworthy-ai/) [Technical Blog](https://developer.nvidia.com/blog/tag/trustworthy-ai/) ## A Commitment to Research Our AI research is focused on developing algorithms and systems that can augment human capabilities, solve complex problems, and improve efficiencies across industries. We work to maintain our guiding principles of privacy, transparency, nondiscrimination, and safety and security in all research practices and methodologies. ### Featured publications and papers: * [A Safety and Security Framework for Real-World Agentic Systems Shaona Ghosh, Barnaby Simkin, Dan Zhao, Nikki Pope, Roopa Prabhu, Michael Demoret, Bartley Richardson, et al.](https://www.arxiv.org/abs/2511.21990) * [Bias in Gender Bias Benchmarks: How Spurious Features Distort Evaluation Yusuke Hirota, Ryo Hachiuma, Boyi Li, Ximing Lu, Michael Ross Boone, Boris Ivanovic, Yejin Choi, Marco Pavone, Yu-Chiang Frank Wang, Noa Garcia, Yuta Nakashima, Chao-Han Huck Yang](https://arxiv.org/abs/2509.07596) * [NVIDIA's Frontier AI Risk Assessment Barnaby Simkin, Nikki Pope, Leon Derczynski, Christopher Parisien](https://images.nvidia.com/content/pdf/NVIDIA-Frontier-AI-Risk-Assessment.pdf) * [NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, Abhinav Khattar, Adithya Renduchintala, Aditya Malte, Akhiad Bercovich, Akshay Hazare, Alejandra Rico, Aleksander Ficek, Alex Kondratenko et al.](https://arxiv.org/abs/2508.14444) * [FourCastNet 3: A Geometric Approach to Probabilistic Machine-Learning Weather Forecasting at Scale Boris Bonev, Thorsten Kurth, Ankur Mahesh, Mauro Bisson, Jean Kossaifi, Karthik Kashinath, Anima Anandkumar, William D. Collins, Michael S. Pritchard, Alexander Keller](https://arxiv.org/abs/2507.12144) * [MambaVision: A Hybrid Mamba-Transformer Vision Backbone Ali Hatamizadeh, Jan Kautz](https://arxiv.org/abs/2407.08083) * [ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids Hannes Stark, Bowen Jing, Tomas Geffner, Jason Yim, Tommi Jaakkola, Arash Vahdat, Karsten Kreis](https://arxiv.org/abs/2503.05025) * [Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning Alisson Azzolini, Junjie Bai, Hannah Brandon, Jiaxin Cao, Prithvijit Chattopadhyay, Huayu Chen, Jinju Chu, Yin Cui, Jenna Diamond, Yifan Ding, Liang Feng, Francesco Ferroni, Rama Govindaraju et al.](https://arxiv.org/abs/2503.15558) * [GR00T N1: An Open Foundation Model for Generalist Humanoid Robots Johan Bjorck, Fernando Castañeda, Nikita Cherniadev, Xingye Da, Runyu Ding, Linxi "Jim" Fan, Yu Fang, Dieter Fox, Fengyuan Hu, Spencer Huang, Joel Jang, Zhenyu Jiang, Jan Kautz, Kaushil Kundalia, Lawrence Lao et al.](https://arxiv.org/abs/2503.14734) [Explore NVIDIA Research](https://www.nvidia.com/en-us/research.md) ## Discover More at the GTC AI Conference Hear from the experts and government leaders paving the way for AI regulation and trustworthiness. Explore NVIDIA GTC [Trustworthy AI sessions](https://www.nvidia.com/gtc/session-catalog/?search=S72680%2C%20S73058%2C%20S71594%2C%20S72399%2C%20S71986%2C%20S72681&tab.catalogallsessionstab=16566177511100015Kus#/) curated to help companies identify and address potential obstacles to developing their own initiatives, including a recent discussion on [Foundational Concepts in AI Safety](https://www.nvidia.com/en-us/on-demand/session/gtcdc25-dc51144/) from GTC DC. [Explore GTC Sessions](https://www.nvidia.com/en-us/on-demand/playlist/playList-48a8cdc5-7d1c-4a4a-bc1e-3c43391a68db/)