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Synthetic Data Generation for Agentic AI Accelerate the development of agentic workflows with high-quality, domain-specific synthetic data. Explore SDG for Agentic AI Overview Technical Implementation Get Started Related Use Cases Overview Overview Technical Implementation Get Started Related Use Cases Overview Technical Implementation Get Started Related Use Cases Explore SDG for Agentic AI Workloads Generative AI / LLMs Conversational AI / NLP Industries All Industries Business Goal Innovation Products NVIDIA NeMo Overview Why Create Synthetic Data? Training specialized agentic systems requires extensive, high-quality datasets that are often scarce, siloed, or sensitive. Synthetic data eliminates this bottleneck by creating diverse datasets at scale for any domain to accelerate AI agent development. Synthetic data can help solve challenges such as: Data scarcity: Domain-specific datasets are typically limited or unavailable. Security concerns: Internal data is often too sensitive to share externally. Cost and time: Manual data collection and labeling are expensive, slow, and prone to bias. Complex requirements: Reasoning large language models (LLMs), multi-agent systems, and multimodal AI assistants require ample training data to be useful and autonomous. Synthetic Data Usage “By 2026, 75% of businesses will use GenAI to create synthetic customer data, up from less than 5% in 2023.” Gartner®, Over 100 Data, Analytics and AI Predictions Through 2030 by Sarah James, Alan D. Duncan, 2 May 2025 GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Quick Links Open Nemotron Personas Synthetic Dataset Learn About NVIDIA NeMo for Managing the AI Agent Lifecycle Try NeMo Data Designer Using Synthetic Data for LLM and Agentic System Development Agentic AI models enable autonomous systems to reason, plan, and take goal-driven actions across digital and real-world environments. Text-based synthetic data is critical for training and evaluating these models safely, efficiently, and at scale. Conversational AI Generative AI can be used to create data for high-quality conversations, capturing domain-specific language, intent variations, and rare edge cases, overcoming the limitations of scarce real-world transcripts. By enriching training data with tailored dialogues, it improves conversational AI accuracy, adaptability, and the ability to handle nuanced, multi-turn interactions. Evaluation and Benchmarks Targeted evaluation and benchmark datasets, such as domain-specific question-answer pairs, can be used to measure and enhance retrieval-augmented generation (RAG) system performance. Side-by-side comparison of multiple models on the same use case ensures consistent, fair evaluation and informed model selection. Low-Resource Adaptation Low-resource domains like proprietary coding languages or underrepresented languages benefit greatly from realistic, complex synthetic text data—enhancing AI models’ reasoning, accuracy, and overall performance. Private & Compliant Data NeMo Safe Synthesizer creates privacy-safe versions of sensitive data with default configurations designed to meet data privacy regulations such as HIPAA and GDPR, providing seamless access to synthetic medical data without regulatory or privacy constraints—enabling vast knowledge sharing both internally and externally. Synthetic Documents Design high-fidelity synthetic document datasets for large-scale AI model training in tax form validation, legal documents, mortgage approvals, and other structured data applications. Technical Implementation Generating Synthetic Data Design Custom Synthetic Datasets from Scratch or Example Data Configure the models you want to use for Synthetic Data Generation (SDG): Connect and customize the models that power your synthetic datasets in NeMo Data Designer. You can use model aliases for easy reference, and fine-tune inference parameters to get the right output quality and style you need. Configure the seed datasets you want to use to diversify your dataset: The most effective way to generate synthetic data that matches your specific domain is to seed the SDG process with your existing (real-world) datasets. By providing real data as a foundation, you can steer the generation process to ensure the synthetic data maintains the patterns, distributions, and characteristics of your actual data. Configure the columns you want to use to diversify your dataset: Design the structure and content of your synthetic datasets by defining columns that work together to produce realistic, high-quality data. Columns are the fundamental building blocks that determine what data you’ll generate and how it will be structured. Configure your LLM-generated columns with prompts and structured outputs: Design the structure and content of your synthetic datasets by defining columns that work together to produce realistic data. Columns are the fundamental building blocks that determine what data you’ll generate and how it will be structured. Data Designer provides powerful capabilities for generating structured data with user-defined schemas. Preview your dataset and iterate on your configuration: Generate a small sample for validation. Refine your design based on preview results. Generate data at scale. Once your design meets your requirements, you can scale up to create a full dataset. Evaluate the quality of your data: Ensure high-quality synthetic data generation with comprehensive validation and evaluation tools in NeMo Data Designer. Validate generated code for correctness and assess overall data quality using automated metrics and LLM-based judges. Quick Links Try NeMo Data Designer Get Started Build your own SDG pipeline for conversational AI, evaluation and benchmarks, and other agentic AI use cases. Get Started Explore NeMo Related Use Cases ManufacturingRobot SafetyWorkload: Computer Vision / Video Analytics, Generative AI / LLMs, RoboticsProducts: NVIDIA IGX, NVIDIA Metropolis, NVIDIA Cosmos, NVIDIA Halos Business Goal: Return on Investment, Risk Mitigation, InnovationSynthetic Data Generation for Agentic AIWorkload: Generative AI / LLMs, Conversational AI/NLPProducts: NVIDIA NeMo Business Goal: InnovationFeaturedHealthcare & Life Sciences, GenomicsGenomics AnalysisWorkload: Generative AI / LLMsProducts: NVIDIA Parabricks Business Goal: Innovation, Return on Investment View More Use Cases Company Information About Us Company Overview Investors Venture Capital (NVentures) NVIDIA Foundation Research Corporate Sustainability Technologies Careers News and Events Newsroom Company Blog Technical Blog Webinars Stay Informed Events Calendar GTC AI Conference NVIDIA On-Demand Popular Links Developers Partners Executive Insights Startups and VCs NVIDIA Connect for ISVs Documentation Technical Training Professional Services for Data Science Follow NVIDIA United States Privacy Policy Your Privacy Choices Terms of Service Accessibility Corporate Policies Product Security Contact Copyright © 2026 NVIDIA Corporation Select Location The AmericasArgentinaBrasil (Brazil)CanadaChileColombiaMéxico (Mexico)PeruUnited StatesEuropeBelgië (Belgium)Belgique (Belgium)Česká Republika (Czech Republic)Danmark (Denmark)Deutschland (Germany)España (Spain)FranceItalia (Italy)Nederland (Netherlands)Norge (Norway)Österreich (Austria)Polska (Poland)România (Romania)Suomi (Finland)Sverige (Sweden)Türkiye (Turkey)United KingdomRest of EuropeAsiaAustralia中国大陆 (Mainland China)India日本 (Japan)대한민국 (South Korea)Singapore台灣 (Taiwan)Middle EastMiddle East NVIDIA and our third-party partners use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in our marketing efforts. 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We and our advertising partners will use this information to make our websites and the advertising displayed on it, more relevant to your interests.Cookies DetailsCookie List Clear checkbox label labelApply CancelConsent Leg.Interest checkbox label label checkbox label label checkbox label labelDecline All Save and Accept --- Génération de données synthétiques pour l'IA agentique Accélérez le développement de workflows agentiques avec des données synthétiques de haute qualité et spécifiques à un domaine. Découvrez les SDG pour l'IA agentique Aperçu Implémentation technique Démarrer Cas d'utilisation associés Aperçu Aperçu Implémentation technique Démarrer Cas d'utilisation associés Aperçu Implémentation technique Démarrer Cas d'utilisation associés Découvrez les SDG pour l'IA agentique Charges de travail IA générative / LLM IA conversationnelle / NLP Industries Tous les secteurs Objectifs commerciaux Innovation Produits NVIDIA NeMo Aperçu Pourquoi créer des données synthétiques ? L'entraînement de systèmes agentiques spécialisés nécessite des jeux de données approfondis et de haute qualité qui sont souvent rares, isolés ou sensibles. Les données synthétiques éliminent ce goulot d'étranglement en créant des jeux de données diversifiés à l'échelle pour n'importe quel domaine afin d'accélérer le développement d'agents d'IA. Les données synthétiques peuvent aider à résoudre des défis tels que : Rareté des données : les jeux de données spécifiques à un domaine sont généralement limités ou indisponibles. Problèmes de sécurité : les données internes sont souvent trop sensibles pour être partagées en externe. Coût et temps : la collecte et l'étiquetage manuels de données sont coûteux, lents et sujets aux biais. Exigences complexes : le raisonnement des grands modèles de langage (LLM), les systèmes multi-agents et les assistants d'IA multimodaux nécessitent d'importantes données d'entraînement pour être utiles et autonomes. Utilisation des données synthétiques "D'ici 2026, 75 % des entreprises utiliseront GenAI pour créer des données clients synthétiques, contre moins de 5 % en 2023." Gartner®, Over 100 Data, Analytics and AI Predictions Through 2030 par Sarah James, Alan D. Duncan, 2 mai 2025 GARTNER est une marque déposée et une marque de service de Gartner, Inc. et/ou de ses filiales aux États-Unis et à l'international et est utilisée ici avec permission. Tous droits réservés. Liens rapides Ouvrez le jeu de données synthétiques Nemotron Personas En savoir plus sur NVIDIA NeMo pour gérer le cycle de vie des agents d'IA Essayez NeMo Data Designer Utilisation de données synthétiques pour le développement de systèmes LLM et agentiques Les modèles d'IA agentique permettent aux systèmes autonomes de raisonner, de planifier et de prendre des actions ciblées dans des environnements numériques et réels. Les données synthétiques basées sur le texte sont essentielles pour entraîner et évaluer ces modèles en toute sécurité, efficacement et à grande échelle. IA conversationnelle L'IA générative peut être utilisée pour créer des données pour des conversations de haute qualité, en capturant un langage spécifique à un domaine, des variations d'intention et des cas rares à l'Edge, en surmontant les limitations des rares transcriptions réelles. En enrichissant les données d'entraînement par des dialogues personnalisés, elle améliore la précision et l'adaptabilité de l'IA conversationnelle ainsi que la capacité à gérer des interactions nuancées et à plusieurs tours. Évaluation et benchmarks Des jeux de données d'évaluation et de benchmarking ciblés, tels que des paires questions-réponses spécifiques à un domaine, peuvent être utilisés pour mesurer et améliorer les performances des systèmes de génération augmentée par récupération (RAG). La comparaison côte à côte de plusieurs modèles sur le même cas d'utilisation garantit une évaluation cohérente et équitable et une sélection de modèles éclairée. Adaptation à faibles ressources Les domaines à faibles ressources tels que les langages de codage propriétaires ou les langages sous-représentés bénéficient grandement de données textuelles synthétiques réalistes et complexes, améliorant le raisonnement, la précision et les performances globales des modèles d'IA. Données privées et conformes NeMo Safe Synthesizer crée des versions sécurisées de données sensibles avec des configurations par défaut conçues pour répondre aux réglementations sur la confidentialité des données telles que HIPAA et GDPR, fournissant un accès sans faille à des données médicales synthétiques sans contraintes réglementaires ou de confidentialité, permettant ainsi un vaste partage de connaissances à la fois en interne et en externe. Documents synthétiques Concevez des jeux de données de documents synthétiques haute fidélité pour l'entraînement de modèles d'IA à grande échelle dans la validation de formulaires fiscaux, de documents juridiques, d'approbations d'hypothèques et d'autres applications de données structurées. Implémentation technique Générer des données synthétiques Concevez des jeux de données synthétiques personnalisés à partir de zéro ou de données d'exemple Configurez les modèles que vous souhaitez utiliser pour la génération de données synthétiques (SDG) : connectez et personnalisez les modèles qui alimentent vos jeux de données synthétiques dans NeMo Data Designer. Vous pouvez utiliser des alias de modèles pour une référence facile et affiner les paramètres d'inférence pour obtenir la qualité et le style de sortie dont vous avez besoin. Configurez les jeux de données d'amorçage que vous souhaitez utiliser pour diversifier votre jeu de données : le moyen le plus efficace de générer des données synthétiques qui correspondent à votre domaine spécifique consiste à amorcer le processus SDG avec vos jeux de données existants (réels). En fournissant des données réelles comme fondation, vous pouvez diriger le processus de génération pour vous assurer que les données synthétiques maintiennent les modèles, les distributions et les caractéristiques de vos données réelles. Configurez les colonnes que vous souhaitez utiliser pour diversifier votre jeu de données : concevez la structure et le contenu de vos jeux de données synthétiques en définissant des colonnes qui travaillent ensemble pour produire des données réalistes et de haute qualité. Les colonnes sont les éléments constitutifs fondamentaux qui déterminent quelles données vous allez générer et comment elles seront structurées. Configurez vos colonnes générées par LLM avec des prompts et des sorties structurées : concevez la structure et le contenu de vos jeux de données synthétiques en définissant des colonnes qui travaillent ensemble pour produire des données réalistes. Les colonnes sont les éléments constitutifs fondamentaux qui déterminent quelles données vous allez générer et comment elles seront structurées. Data Designer fournit de puissantes capacités pour générer des données structurées avec des schémas définis par l'utilisateur. Prévisualisez votre jeu de données et itérez sur votre configuration : générez un petit échantillon pour validation. Affinez votre conception en fonction des résultats d'aperçu. Générez des données à grande échelle. Une fois que votre conception répond à vos exigences, vous pouvez l'étendre pour créer un jeu de données complet. Évaluez la qualité de vos données : garantissez une génération de données synthétiques de haute qualité grâce à des outils de validation et d'évaluation complets dans NeMo Data Designer. Validez le code généré pour en vérifier l'exactitude et évaluez la qualité globale des données à l'aide de métriques automatisées et de juges basés sur des LLM. Liens rapides Essayez NeMo Data Designer Démarrer Développez votre propre pipeline SDG pour l'IA conversationnelle, l'évaluation et les benchmarks, et d'autres cas d'utilisation d'IA agentique. 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Learn More Data Center NVIDIA Launches Vera CPU, Purpose-Built for Agentic AI NVIDIA Vera CPU delivers the highest performance and energy efficiency for data processing, AI training, and agentic inference at scale. Read Press Release Simulation Bringing AI to Design, Engineering, and Manufacturing Industrial software giants are bringing NVIDIA CUDA-X™, Omniverse™, and GPU-accelerated industrial software and tools to their customers. Read Press Release Artificial Intelligence NVIDIA, T-Mobile and Partners Enable Edge AI Agents on AI-RAN This allows billions of devices—from vision AI agents to robots—to see, hear, and act in real time. Read the Press Release Energy NVIDIA and Emerald AI Accelerate Power-Flexible AI Deployment Agentic AI Make Autonomous Agents More Secure by Design With NVIDIA OpenShell Artificial Intelligence NVIDIA Expands Open Models for Agentic and Physical AI Data Center NVIDIA Launches Vera CPU, Purpose-Built for Agentic AI Simulation Bringing AI to Design, Engineering, and Manufacturing Artificial Intelligence NVIDIA, T-Mobile and Partners Enable Edge AI Agents on AI-RAN Previous Next Energy Agentic AI Artificial Intelligence Data Center Simulation Artificial Intelligence NVIDIA GTC Keynote Replay See CEO Jensen Huang's keynote on the new era of inference, AI factories, open source, physical AI, robotics, and more. Watch Replay Artificial Intelligence AI is powering change in every industry. From generative AI and speech recognition to medical imaging and improved supply chain management, AI is providing enterprises that compute power, tools, and algorithms their teams need to do their life's work. Quick Links Overview Data Analytics Machine Learning Predictive Analytics Recommender Systems Speech AI Apache Spark RAPIDS Agentic AI | Blog Make Autonomous Agents More Secure by Design With NVIDIA OpenShell Deploy self-evolving agents with added control, security, and governance. Agentic AI | Blog Building the Future Together: Meet the Nemotron Coalition Mistral AI, Perplexity and more are joining forces to build open frontier models. Data Center | Announcement NVIDIA Dynamo 1.0 Broadly Adopted NVIDIA Dynamo 1.0 is a production-grade, open-source foundation for large-scale inference. Artificial Intelligence | Announcement New Open Physical AI Data Factory Blueprint Accelerate robotics, vision AI agents, and autonomous vehicle development. Artificial Intelligence | Blog L’Oréal Uses NVIDIA ALCHEMI to Accelerate Formulation Discovery L’Oréal and NVIDIA are expanding their collaboration to bring NVIDIA ALCHEMI to skincare. Agentic AI | Announcement Scale Enterprise Productivity With NVIDIA Agent Toolkit Build autonomous agents that perceive, reason, and act on enterprise knowledge within a secure framework. Artificial Intelligence | Blog Build With NemoClaw on NVIDIA DGX Spark and Station NVIDIA DGX Station™ and DGX Spark™ can now run autonomous, long-running agents more safely with NemoClaw. Artificial Intelligence | Announcement NVIDIA Dynamo 1.0 Powers Multi-Node Inference at Production Scale Dynamo integration into vLLM, SGLang, llm-d, and TensorRT LLM enables AI pioneers to power massive-scale production workloads. Artificial Intelligence | Press Release NVIDIA Expands Open Models for Agentic and Physical AI New open models power AI agents, physical AI for robotics, and healthcare research. Artificial Intelligence | Blog RTX AI Garage: NVIDIA Igniting the Next Era of AI With Locally Accelerated Agents The NVIDIA NemoClaw plugin for OpenClaw and NVIDIA Nemotron 3 open models unlock new agentic AI tools and workflows that enable fast, private local assistants—making them faster, safer, and easier to build on NVIDIA RTX PCs and DGX Spark. Previous Next Short Description Make Autonomous Building the Future Together post 1 NVIDIA Dynamo 1.0 post 2 New Open Physical AI GTC26 2 L’Oréal Uses post 1 Scale Enterprise Productivity GTC26 3 Build With OpenShell GTC26 4 NVIDIA Dynamo 1.0 Powers GTC26 5 NVIDIA Expands Open GTC26 1 Creating SFG Design and Simulation NVIDIA accelerated computing, libraries and AI models enable software makers and industry manufacturers to develop products for large-scale, physically accurate simulations and interactive digital twins so teams can efficiently build, train, and test advanced systems before deployment, bringing products to market faster. Quick Links Overview Newsroom Shop Physical AI Industrial AI Computer Aided Engineering Rendering and Visualization Virtual and Augmented Reality Data Center | Announcement New NVIDIA Vera Rubin DSX AI Factory Reference Design The new reference design provides a guide for building codesigned AI infrastructure that delivers maximum token per watt and accelerated time to first production. AR / VR | Announcement NVIDIA RTX-Accelerated Computers Now Connect to Apple Vision Pro CloudXR 6.0 brings native visionOS support, streaming RTX-powered 3D apps to Apple Vision Pro. Artificial Intelligence | Blog Adobe and NVIDIA Announce Strategic Collaboration This collaboration will deliver the next generation of Adobe Firefly models and agentic workflows. Simulation | News Bringing Design, Engineering, and Manufacturing Into the AI Era Industrial software giants are bringing NVIDIA CUDA-X™, Omniverse™, and GPU-accelerated industrial software and tools to their customers. Manufacturing | GTC Session Industrial Engineering Conference Sessions Discover sessions in computer-aided engineering, electronic design automation, and semiconductor engineering. Manufacturing | GTC Session Industrial AI and Manufacturing Conference Sessions Explore sessions for developers, technical practitioners, and business leaders in the industrial and manufacturing sectors. Simulation | Announcement Dassault Systèmes and NVIDIA to Build Next-Gen Industrial AI Platform The partnership combines Dassault Systèmes and NVIDIA technologies to transform industries. Siemens, PepsiCo Simulation | News Siemens and NVIDIA Bring Industrial and Physical AI to Industries Siemens and NVIDIA will bring industrial and physical AI to every industry and industrial workflow. Simulation | Course Customizable OpenUSD Trainings Now Available The Learn OpenUSD curriculum is now open source, empowering you to tailor world-class training content for your community. Semiconductor | Announcement NVIDIA and Synopsys Announce Strategic Partnership Multi-year collaboration will bring together NVIDIA AI and accelerated computing with Synopsys’ engineering solutions to revolutionize engineering and design. Esri, Raleigh, K2K, Milestone, Akila Agentic AI | Blog How Smart City AI Agents Transform Urban Operations Learn how NVIDIA technologies turn fragmented urban infrastructure into intelligent, responsive spaces. Previous Next Short Description New NVIDIA Vera Rubin GTC26 6 NVIDIA RTX-Accelerated GTC post 1 Adobe and NVIDIA Announce GTC26 6 Bringing Design, Engineering GTC26 1 Industrial Engineering Conference Industrial AI and Manufacturing Dassault Systèmes Siemens and NVIDIA Bring Customizable OpenUSD Trainings NVIDIA and Synopsys How Smart City AI Agents High-Performance Computing High-performance computing (HPC) is the ability to process data and perform complex calculations at high speeds. HPC is one of the most essential tools fueling the advancement of computational science. Quick Links HPC Overview SC24 Event Supercomputing Healthcare Public Sector Energy NVIDIA HPC SDK NVIDIA PhysicsNeMo HPC | Announcement Announcing NVIDIA cuEST for Semiconductor Design Industry adoptions from Applied Materials, Samsung, Synopsys, and TSMC. HPC | Announcement NVIDIA Launches Earth-2 Family of Open Models The first fully open, production-ready weather AI stack makes weather AI accessible worldwide. HPC | Announcement NVIDIA Accelerates AI for Over 80 New Science Systems Worldwide NVIDIA drives global scientific discovery with 4,500 exaFLOPS of AI performance across systems. HPC | Announcement NVIDIA Enables Scientific Breakthroughs for Materials Discovery NVIDIA Holoscan and ALCHEMI™ advance nano-imaging and accelerate materials discovery. HPC | Announcement NVIDIA and RIKEN Advance Japan’s Scientific Frontiers NVIDIA GB200 and NVIDIA Quantum-X800 InfiniBand networking boost Japan’s research. HPC | Announcement World’s Leading Scientific Supercomputing Centers Adopt NVQLink NVQLink adopted by supercomputing centers around the globe to advance quantum computing. HPC | Announcement NVIDIA Announces NVQLink for Quantum-GPU Computing GPU-QPU interconnect for AI-quantum supercomputing at six national labs and industry leaders. HPC | Announcement NVIDIA Earth-2 Powers Next-Gen Extreme Weather Simulation MITRE turns sparse data into weather states for risk analysis with new framework. Previous Next Short Description Announcing NVIDIA cuEST GTC26 1 NVIDIA Launches Earth-2 NVIDIA Accelerates AI NVIDIA Enables Scientific NVIDIA and RIKEN World’s Leading NVIDIA Announces NVQLink NVIDIA Earth-2 Powers Gaming and Creating NVIDIA GeForce RTX™ powers the world’s fastest GPUs and the ultimate platform for gamers and creators. Enjoy beautiful ray tracing, AI-powered DLSS, and much more in games and applications, on your desktop, laptop, in the cloud, or in your living room. Quick Links Shop GeForce Graphics Cards Laptops DLSS Reflex NVIDIA Studio GeForce NOW NVIDIA App Game Ready Drivers G-SYNC Games | Announcement Announcing NVIDIA DLSS 5 A breakthrough in visual fidelity for games. Games | News NVIDIA DLSS Accelerating performance in your favorite games. Check out the latest titles. Games | News RTX. It's On. Path tracing and DLSS 4.5 coming to 007 First Light. Games | News RTX Remix Advanced Particle VFX coming next month. Corporate | Event NVIDIA at GDC 2026 Join us at the Game Developers Conference (GDC) to explore how RTX neural rendering and AI are defining the next era of gaming. Gaming Hardware | Product GeForce RTX 50 Series Graphics Cards and Desktops GeForce RTX 50 Series GPUs bring game-changing AI capabilities to gamers and creators. Multiply performance with NVIDIA DLSS 4, generate images at unprecedented speed, and unleash your creativity with NVIDIA Studio. Gaming Hardware | Product GeForce RTX 50 Series Laptops The world’s fastest laptops for gamers and creators. Multiply performance with NVIDIA DLSS 4, generate images at unprecedented speed, and unleash your creativity with NVIDIA Studio. All in the thinnest and longest lasting RTX laptops, optimized by Max-Q. Cloud Gaming | Blog GFN Thursday 'Screamer' and the latest update from 'Honkai Star Rail' are streaming this week on GeForce NOW. Artificial Intelligence | Blog RTX AI Garage: NVIDIA Igniting the Next Era of AI With Locally Accelerated Agents The NVIDIA NemoClaw plugin for OpenClaw and NVIDIA Nemotron 3 open models unlock new agentic AI tools and workflows that enable fast, private local assistants—making them faster, safer, and easier to build on NVIDIA RTX PCs and DGX Spark. Previous Next Short Description DLSS 5 GTC26 1 RTX/DLSS GDC 2 First Light GDC 3 Remix GDC 4 GDC 2026 GDC 5 50 Series Desktop SFG 1 50 Series Laptops SFG 2 GFN GDC 6 Creating GDC 7 Automotive From design and manufacturing to autonomous vehicle development and deployment—and agentic AI that helps build and power the car—NVIDIA delivers the compute, software, and infrastructure to support the entire vehicle lifecycle and drive the future of mobility. Quick Links Automotive Industry Autonomous Vehicles In-Vehicle Computing AI Training AV Simulation Partners DRIVE Videos Automotive | Announcement Leading Automakers Adopt NVIDIA DRIVE Hyperion for L4 Vehicles BYD, Geely, Isuzu, and Nissan build on the NVIDIA end-to-end autonomous vehicle platform. Automotive | Announcement Hyundai, Kia, and NVIDIA Expand Partnership for Next-Gen AV Tech Hyundai Motor Group is integrating NVIDIA DRIVE Hyperion and AI into its software-defined vehicles. Automotive | GTC Session Automotive Special Address: Scaling Autonomous Vehicles Foundation models, Alpamayo reasoning VLAs, and DRIVE Hyperion are advancing Level 4 autonomy. Automotive | GTC Session Automotive GTC Conference Sessions Explore sessions on how NVIDIA is advancing autonomous driving, vehicle design, and in-vehicle AI. Automotive | Blog NVIDIA DRIVE AV Raises the Bar for Vehicle Safety as Mercedes-Benz CLA Earns Top Euro NCAP Award The ​​NVIDIA DRIVE AV software platform and NVIDIA Halos architecture contributed to the CLA’s top safety rating. Automotive | Blog Mercedes-Benz Unveils New S-Class Built on NVIDIA DRIVE AV The S-Class will feature NVIDIA DRIVE Hyperion and NVIDIA DRIVE AV software to support future Uber robotaxi operations. Automotive | Blog NVIDIA DRIVE AV Software Debuts in All-New Mercedes-Benz CLA Level 2++ will enter U.S. production with NVIDIA’s full-stack software across the automaker’s lineup. Automotive | Blog NVIDIA Expands the DRIVE Hyperion Ecosystem for Full Autonomy Partners build on the NVIDIA Level 4, robotaxi-ready platform to advance safe autonomous mobility. Automotive | Blog OpenUSD and NVIDIA Halos Accelerate Physical AI Systems New NVIDIA open datasets, safety frameworks, and technologies are advancing how developers build safe physical AI. Automotive | Announcement NVIDIA and Hyundai Motor Group Team to Power AI-Driven Mobility Solutions HMG will deploy NVIDIA Blackwell AI infrastructure to power breakthroughs in autonomous driving. Previous Next Short Description Leading Automakers Adopt GTC26 1 Hyundai, Kia, and NVIDIA GTC26 2 Automotive Special Address Automotive GTC Conference Sessions NVIDIA DRIVE AV Raises Mercedes-Benz Unveils New NVIDIA DRIVE AV Software NVIDIA Expands the DRIVE CES26 1 OpenUSD and NVIDIA Halos NVIDIA and Hyundai Motor APEC 1 Robotics and Edge AI The NVIDIA Jetson™ and Isaac™ platforms provide end-to-end solutions to develop and deploy AI-powered autonomous machines and edge computing applications across manufacturing, logistics, healthcare, smart cities, and retail. Quick Links Shop Overview Robotics Platform Embedded Edge Robotics Research Isaac Simulation NVIDIA IGX NVIDIA-Certified Systems Ecosystem Partners Robotics | Announcement NVIDIA and Global Robotics Leaders Take Physical AI to the Real World Pioneers in robot brains, industrial robots, and humanoids are powering production-scale physical AI. Robotics | Blog From Model to Machine: Building Robots With NVIDIA The open NVIDIA Isaac platform helps you build and deploy a robot at scale using NVIDIA’s 3-computer solution. Edge Computing | Blog NVIDIA and Telecom Leaders Build AI Grids to Optimize Inference on Distributed Networks As AI‑native applications scale up, telecom networks are the next frontier for distributing AI. Robotics | Blog NVIDIA IGX Thor™ Now Generally Available NVIDIA IGX Thor powers real-time physical AI at the industrial edge, enabling autonomous machines with advanced sensing, reasoning and functional safety. Robotics | Brochure As Open Models Spark AI Boom, NVIDIA Jetson Brings It to Life at the Edge Jetson brings open models to life at the edge, powering real-time, private AI in physical machines and robots. Robotics | GTC Session Physical AI Days at GTC Explore curated sessions on how industrial AI, robotics, automotive, and digital twins are transforming physical AI. Robotics | GTC Session Explore Robotics Sessions at GTC Discover sessions on how AI, simulation, and accelerated computing are enabling robots to see, learn, and make decisions in real time. Caterpillar Robotics | Blog How Caterpillar Is Bringing Edge AI to the Jobsite Caterpillar is integrating NVIDIA technologies, from NVIDIA Jetson Thor to speech models, to transform the world’s heavy industries. Previous Next Short Description NVIDIA and Global Robotics post 1 From Model to Machine post 2 NVIDIA and Telecom Leaders NVIDIA IGX Thor™ GTC26 1 As Open Models Spark AI Physical AI Days at GTC Explore Robotics Sessions at GTC How Caterpillar Data Center and Cloud Computing From the cloud to the office to the data center to the edge, NVIDIA provides solutions that deliver breakthrough performance on enterprise AI and HPC workloads at any scale, driving business decisions in real time and resulting in faster time to value. Quick Links Data Center Cloud Computing Edge Computing NVIDIA LaunchPad NVIDIA AI Enterprise DGX Systems NVIDIA-Certified Systems Data Center | Announcement NVIDIA and Emerald AI Accelerate Power-Flexible AI Deployment New AI factories built with NVIDIA Vera Rubin DSX are set to strengthen the U.S. power grid. Data Center | Announcement NVIDIA Launches Vera CPU, Purpose-Built for Agentic AI Delivering high performance and energy for AI training and agentic inference at scale. Data Center | Announcement Storage Industry Adopts NVIDIA BlueField®-4 STX Reference architecture to enable storage providers to build next-gen infrastructure for agentic AI. Data Center | Blog Introducing NVIDIA RTX PRO™ 4500 Blackwell Server Edition This compact GPU delivers power-efficient performance for every enterprise. Networking | Blog NVIDIA DSX Air Boosts Time to Token With AI Factory Simulation Simulate complex deployments for compute and networking—before a single server is unboxed. Data Center | Announcement NVIDIA Launches New Era of Space Computing Explore edge AI for geospatial intelligence with the NVIDIA Space-1 Vera Rubin module, IGX Thor™, and Jetson Orin™. Data Center | Product NVIDIA AI Enterprise Adds Expanded Capabilities for Production AI NVIDIA Run:ai and Omniverse now included to optimize GPU utilization and advance physical AI. Data Center | Blog Supercharging Drug Discovery with LillyPod Lilly’s NVIDIA-powered AI factory to advance science at the speed of 9 quintillion calculations per second. Previous Next Short Description NVIDIA and Emerald AI NVIDIA Launches Vera CPU GTC26 1 Storage Industry Adopts GTC26 2 Introducing NVIDIA RTX PRO™ GTC26 3 NVIDIA DSX Air Boosts GTC26 4 NVIDIA Launches New Era GTC26 5 NVIDIA AI Enterprise Adds Supercharging Drug Discovery About NVIDIA NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society. Quick Links About NVIDIA NVIDIA GTC Careers Newsroom NVIDIA On-Demand Leaders NVIDIA In Brief NVIDIA GTC | Event Watch NVIDIA CEO Jensen Huang’s Keynote See Jensen take the stage with breakthroughs and announcements that will redefine the next generation of AI. NVIDIA GTC | Event NVIDIA GTC Live Keynote Pregame Join the pregame to hear the latest on accelerated computing beyond AI, including history’s largest infrastructure buildouts. Corporate | Blog AI is a Five-Layer Cake AI is one of the most powerful forces shaping the world today. It isn't a clever app or a single model; it's essential infrastructure, like electricity and the internet. Artificial Intelligence | Event NVIDIA Live at CES 2026 with Founder and CEO Jensen Huang Catch up on the latest news and announcements on AI Infrastructure, robotics, automotive, gaming, and more. Artificial Intelligence | Video Building Blocks of AI. See how tokens transform data into intelligence, power AI models, scale inference, and drive next-gen systems that predict, generate, and adapt. Corporate | Blog Our Story NVIDIA is the result of the decades-long pursuit of a vision and the life’s work of our employees. Discover our company’s story. Accuray Company | About Learn the NVIDIA Story Our work is truly unique. Part science. Part art. Every breakthrough helps shape what’s next. Artificial Intelligence | Blog Sustainable Strides: AI and Accelerated Computing Drive Energy Efficiency Learn how companies, from finance to manufacturing and beyond, are on the way to sustainable AI with NVIDIA technologies. Artificial Intelligence | Blog Self-Paced Career Development Courses in AI and Data Science Industry experts share advice on starting a career in AI with technical training and certifications. Previous Next Short Description GTC26 Keynote GTC26 pregame AI is a Five-Layer Cake NVIDIA Live at CES 2026 Building Blocks of AI Our Story Learn the NVIDIA Story Sustainable Strides: AI and Accelerated Computing Drive Energy Efficiency Self-Paced Career Development Courses in AI and Data Science SMS is Now a Part of NVIDIA SMS was acquired by NVIDIA Corporation of Santa Clara, CA in May 2022 and was dissolved as a separate corporate entity. NVIDIA is incorporating SMS technology into its Omniverse platform and OpenUSD. For legacy support content please refer to the following: SMLib and NLib. Close Deci is Now a Part of NVIDIA Deci was acquired by NVIDIA Corporation of Santa Clara, CA in May 2024 and was dissolved as a separate corporate entity. 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Download the State of AI Report NVIDIA Guide to Healthcare and Life Sciences Platforms NVIDIA AI Infrastructure Programs Success Stories Partners Newsroom Get Started Platforms Platforms NVIDIA AI Infrastructure Programs Success Stories Partners Newsroom Get Started Platforms NVIDIA AI Infrastructure Programs Success Stories Partners Newsroom Get Started Stay Informed Platforms NVIDIA AI Platforms for Healthcare and Life Sciences Explore open-source tools, APIs, frameworks, and SDKs designed for healthcare and life sciences developers, as well as documentation and community support. Python | PyTorch | CUDA® | NVIDIA Dynamo | JAX | DeepSpeed BioNeMo NVIDIA BioNeMo™ is the development platform for AI-driven biology and drug discovery. The platform includes open models, libraries, datasets, and NVIDIA NIM™ microservices for the entire AI lifecycle, enabling researchers and developers to build, customize, and deploy AI applications that drive the next experiment. Use Cases: biofoundation model building, molecular design, virtual screening, protein structure prediction, protein binder design 2x faster biofoundation model training 6x faster model inference Three model acceleration recipes Models & Libraries Recipes & Toolkits NIM Microservices NVIDIA NeMo™ | NVIDIA® TensorRT™ LLM | NVIDIA Dynamo Nemotron NVIDIA Nemotron™ is the foundation for digital health AI. Nemotron offers optimized open models with open weights, training data, and recipes for advanced reasoning, coding, visual understanding, agentic tasks, safety, speech, and information retrieval, delivering leading efficiency and accuracy for building specialized AI agents. Use Cases: ambient healthcare agents, deep clinical research agents Open models for visual understanding, information retrieval, speech, and safety Five use case examples 16 cookbooks on how to deploy and use the models Explore Models Tutorials Forums NVIDIA Omniverse™ | TensorRT | NVIDIA Holoscan Isaac for Healthcare NVIDIA Isaac™ is a robotics and simulation platform. This healthcare robotics developer platform is centered on simulation and synthetic data, enabling design, validation, and runtime deployment. Based on NVIDIA’s training–simulation–runtime architecture, it connects AI development directly to deployment on edge robotic systems. Use Cases: hospital automation, teleoperation, autonomous ultrasound, surgical autonomy Synthetic data generation pipelines for anatomy, procedural variation, hospital environments, and patient interaction Sensor simulation pipelines for endoscopy, ultrasound, CT imaging, and multimodal sensor fusion GitHub Workflows Documentation Python | PyTorch | NumPy MONAI MONAI is the open medical imaging AI framework. This open-source, PyTorch-based medical imaging AI framework brings together domain-optimized data loaders, rich transformers, and 50+ high-quality pretrained models to streamline everything from 2D and 3D segmentation and registration to reporting and multimodal workflows. Use Cases: medical imaging model training, medical imaging segmentation and annotation Over 8 million downloads and over 4,000 projects Multimodal, integrating imaging, text, and agentic AI for radiology, surgery, and pathology workflows across images and clinical documentation 20 medical imaging challenges won GitHub Website C++ | Python | GXF | TensorRT Holoscan SDK The NVIDIA Holoscan SDK is a runtime for physical AI and sensor processing. Holoscan is a real-time runtime for building GPU-accelerated systems that ingest high-bandwidth, multimodal, multi-rate sensor data, perform AI reasoning, and drive deterministic real-world actions. With a graph-based execution engine and accelerated input and output (IO), Holoscan scales from NVIDIA Jetson Nano™ to DGX™. Use Cases: real-time robotics and autonomous machines, AI raw-data-to-insights for medical devices, deterministic edge AI deployment Scale to tens or hundreds of gigabits per second (Gb/s) without extensive system optimizations Accelerated IO directly into GPU memory with ready-to-use, advanced network operators, NVIDIA Rivermax®, and Holoscan Sensor Bridge 10 minutes to inference with domain accelerator examples Download Examples Documentation CUDA | Docker Parabricks NVIDIA Parabricks® enables GPU-accelerated genomics. This scalable genomics software suite for secondary analysis offers GPU-accelerated implementations of BWA-MEM, GATK, and DeepVariant for whole-genome and exome workflows. Use Cases: cancer and rare diseases, NICU and critical care, population studies, research Over 100x faster analysis of whole genome sequencing (WGS) 50 percent lower compute cost for WGS 23 accelerated tools and six pipelines Download Documentation NVIDIA AI Infrastructure Tools for Every Stage of AI Development and Deployment Integrated, domain-specific platforms combine AI models, tools, and infrastructure to accelerate healthcare and life sciences workloads, from data ingestion to deployment. Explore NVIDIA AI Infrastructure Datasets Curated, domain-specific, open source datasets to kickstart model development. Libraries Prebuilt CUDA-X™ libraries for math, deep learning, data processing, image, video, and more. Training Hardware-optimized libraries, training recipes, frameworks, and orchestration platforms. AI Models Open source AI models for biomedical research across omics, protein and molecule structures, medical imaging, 3D anatomy, surgical robotics, and digital twins for physics-informed simulation. Deployment Tools for optimizing performance, scaling inference workloads, and deploying across cloud, on-prem, and edge environments. NVIDIA Blackwell Architecture The engine behind AI factories for the age of AI reasoning. The architecture centers on a dual-die design that packs 208 billion transistors into a unified package capable of 10 terabytes per second (TB/s) of GPU bandwidth. Its Transformer Engine supports FP4 precision, effectively doubling performance and capacity for generative AI workloads. Massive-scale deployments are handled through NVIDIA NVLink™ and NVSwitch™, delivering 1.8 TB/s per GPU and 130 TB/s of aggregate bandwidth for trillion-parameter models. A dedicated Decompression Engine offloads data-intensive analytics tasks from the CPU, while AI-driven remote access service (RAS) monitoring and a first-of-its-kind trusted execution environment (TEE)-capable GPU round out the platform with enterprise-grade reliability and confidential computing support. View NVIDIA Blackwell Products NVIDIA Programs Learn and Grow Your Business With NVIDIA Programs Join our ecosystem of startups, partners, and developers building healthcare and life sciences platforms and applications. NVIDIA Inception Inception is a free program that guides AI startups through the diverse NVIDIA platforms and ecosystems. From prototype to production, Inception meets each startup where they are, with member benefits to help them discover new AI opportunities, build with world-class technologies, and grow their business. 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