Create physical AI apps with Omniverse real-time simulation.
Cadence, Dassault Systèmes, PTC, Siemens, and Synopsys are bringing NVIDIA-accelerated industrial software and tools to major cloud providers and original equipment manufacturers. NVIDIA is partnering with the global robotics ecosystem — including leading robot brain developers, industrial robot giants and humanoid pioneers — to power production-scale physical AI. Sensor simulation and physically-based, real-time rendering libraries built on NVIDIA RTX™ for generating datasets at scale. GPU-accelerated physics library built on NVIDIA PhysX® delivers highly-performant, USD-native physics for complex simulation, robotics, and industrial digital twins. Optimized data architecture and runtime for faster development, performance, and collaboration. Leverage Omniverse libraries to develop advanced virtual factory solutions and bring data interoperability, physically based visualization, generative AI, and real-time collaboration to your software. Physical AI-powered robots and robot fleets must autonomously sense, plan, and execute complex tasks in the physical world. These include safely and efficiently transporting and manipulating objects in dynamic, unpredictable environments. With NVIDIA Cosmos, conditioned on Omniverse physics libraries, simulation developers can enhance their AV simulation workflows with high-fidelity, diverse sensor data and realistic behavior to train perception models and validate the AV software stack. Preprogrammed robots struggle with unexpected changes, while AI-driven robots use simulation-based learning to adapt to dynamic environments. This enables them to refine capabilities such as navigation and manipulation, improving performance in a wide range of scenarios. Agility, Apptronik, Fourier Intelligence, Unitree Integrate Omniverse libraries into physical AI applications. Jump-start building physical AI solutions with NVIDIA Blueprints. Gain foundational knowledge, explore essential concepts, and harness the full potential of USD today with our Learn OpenUSD curriculum for developers and 3D practitioners. Learn the basics of building intelligent factories, warehouses, and industrial facilities with 3D integration, simulation, and real-time visualization for the era of physical AI. Explore core robotics concepts such as simulation, ROS, and AI training, and how they enable robots to navigate, adapt, and perform tasks in real-world environments. NVIDIA Omniverse™ is a collection of libraries and microservices for developing physical AI applications such as industrial digital twins and robotics simulation. Leveraging NVIDIA’s deep expertise in accelerated computing and AI, Omniverse libraries enable software makers to integrate pre-built functionality into their solutions. These libraries include developer tools, GPU-accelerated libraries, and technologies packaged as microservices and cloud APIs for streamlined development and deployment. There are two ways to start developing with NVIDIA Omniverse librar
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During his #NVIDIAGTC keynote, our CEO Jensen Huang announced that the world’s first CPO Spectrum-X switch ASIC is now in full production. This breakthrough marks a new era in AI networking—deliverin
During his #NVIDIAGTC keynote, our CEO Jensen Huang announced that the world’s first CPO Spectrum-X switch ASIC is now in full production. This breakthrough marks a new era in AI networking—delivering the performance, efficiency, and scale required to power next-generation AI factories. 🎥 Watch the full keynote: https://t.co/AEppi2Qod4
View originalThe next leap in AI networking is here. At #NVIDIAGTC, our CEO Jensen Huang announced that the world’s first Spectrum-X switch ASIC with co-packaged optics (CPO) is now in full production. By integr
The next leap in AI networking is here. At #NVIDIAGTC, our CEO Jensen Huang announced that the world’s first Spectrum-X switch ASIC with co-packaged optics (CPO) is now in full production. By integrating optics directly with the switch silicon, Spectrum-X CPO delivers higher bandwidth, improved power efficiency, and the scalability required to support massive AI factories.
View originalAgentic AI is pushing memory and storage to new limits. A single 100K-token context can require up to 50GB of KV cache. To keep GPUs fully utilized, that data must be efficiently shared and reused at
Agentic AI is pushing memory and storage to new limits. A single 100K-token context can require up to 50GB of KV cache. To keep GPUs fully utilized, that data must be efficiently shared and reused at scale. NVIDIA DOCA Memos and CMX storage on NVIDIA BlueField DPUs create an AI-native storage tier for inference, delivering up to 99.8% cache hit rates and 96%+ GPU utilization by reducing recompute and accelerating data access. Watch this #NVIDIAGTC session to see how it works ▶️ https://t.co/8sGARdypcX
View originalAI factories need AI-native security. @CheckPointSW + NVIDIA are transforming data center protection: ✅ NVIDIA BlueField DPUs ✅ NVIDIA DOCA software framework ✅ NVIDIA DSX Air simulation Security th
AI factories need AI-native security. @CheckPointSW + NVIDIA are transforming data center protection: ✅ NVIDIA BlueField DPUs ✅ NVIDIA DOCA software framework ✅ NVIDIA DSX Air simulation Security that scales from $236B to $934B market 📈 Learn more ⤵️
View original⚡ Long-context inference is pushing KV cache beyond traditional memory and storage tiers. NVIDIA CMX introduces a dedicated context memory tier powered by NVIDIA BlueField-4 to extend effective GPU m
⚡ Long-context inference is pushing KV cache beyond traditional memory and storage tiers. NVIDIA CMX introduces a dedicated context memory tier powered by NVIDIA BlueField-4 to extend effective GPU memory, boost tokens per second, and improve power efficiency for agentic AI. Learn more about CMX and how it rearchitects storage for the next frontier of AI ➡️ https://t.co/VrTGP9yxaI
View original☁️ The AI factory era demands a new kind of cloud infrastructure. At #NVIDIAGTC, Gady Rosenfeld (NVIDIA) and Pradeep Vincent (@Oracle) revealed how OCI is architecting for giga-scale AI, combining t
☁️ The AI factory era demands a new kind of cloud infrastructure. At #NVIDIAGTC, Gady Rosenfeld (NVIDIA) and Pradeep Vincent (@Oracle) revealed how OCI is architecting for giga-scale AI, combining the Oracle Acceleron fabric with NVIDIA BlueField technology to deliver performance, resilience, and zero-trust security for production-grade workloads. From multi-planar network architecture to BlueField-4 DPUs, this is the infrastructure powering the world's most demanding AI deployments. 🎬 Watch the full session here: https://t.co/5OwRbERCR4
View originalAI factories are now built in simulation first. With NVIDIA DSX Air, teams validate full-stack AI infrastructure before deployment—faster time to AI, lower risk, better scale. 📖 Learn more: https:/
AI factories are now built in simulation first. With NVIDIA DSX Air, teams validate full-stack AI infrastructure before deployment—faster time to AI, lower risk, better scale. 📖 Learn more: https://t.co/XlWUk5fLBj https://t.co/dhn3Ebpt2d
View original🧠 How simulation-first AI factories accelerate deployment. With NVIDIA DSX Air, teams can move from months to days, bringing AI capacity online faster and with greater confidence. At #NVIDIAGTC, Am
🧠 How simulation-first AI factories accelerate deployment. With NVIDIA DSX Air, teams can move from months to days, bringing AI capacity online faster and with greater confidence. At #NVIDIAGTC, Amit Katz (NVIDIA) and Harshdeep Banwait (CoreWeave) shared how DSX Air enables @CoreWeave to validate AI infrastructure before hardware arrives. Key benefits CoreWeave highlighted: 🚀 Early hardware testing at scale 📊 Maximized concurrency 🛠️ Accelerated debugging Watch the full session here ▶️ https://t.co/LcpRJNKZ0r
View original💡 What does it really take to scale AI infrastructure? Go beyond the hype and hear from NVIDIA experts and industry leaders as they share real-world lessons from designing, deploying, and operating
💡 What does it really take to scale AI infrastructure? Go beyond the hype and hear from NVIDIA experts and industry leaders as they share real-world lessons from designing, deploying, and operating massive AI environments. You’ll learn: ✔️ How hyperscale AI infrastructure is architected and optimized ✔️ Strategies to scale network performance across clusters ✔️ What’s next for AI networking and data center architecture 🎥 Watch this panel from #NVIDIAGTC, now available on demand: https://t.co/Kk9qkilABB
View original“By embedding Cisco’s Hybrid Mesh Firewall policy into NVIDIA BlueField DPUs on AI servers, our joint customers achieve high-performance, multi-tenant, intent-driven enforcement and hardware-accelerat
“By embedding Cisco’s Hybrid Mesh Firewall policy into NVIDIA BlueField DPUs on AI servers, our joint customers achieve high-performance, multi-tenant, intent-driven enforcement and hardware-accelerated protection, seamlessly connected via Cisco Nexus One AI front-end fabrics.” — Kevin Deierling, SVP of Networking, NVIDIA
View originalWatch our CEO Jensen Huang’s #NVIDIAGTC 2026 keynote to see how we’re building the next generation of intelligent networks for agentic AI, AI factories, and physical AI. ▶️ https://t.co/ktVKrcL8VR ht
Watch our CEO Jensen Huang’s #NVIDIAGTC 2026 keynote to see how we’re building the next generation of intelligent networks for agentic AI, AI factories, and physical AI. ▶️ https://t.co/ktVKrcL8VR https://t.co/G4WYbH5fVp
View originalBuilding the next generation of AI infrastructure with DOCA? Catch all four DOCA Developer Day sessions from #NVIDIAGTC and see how experts use NVIDIA DOCA to accelerate AI networking, storage, and s
Building the next generation of AI infrastructure with DOCA? Catch all four DOCA Developer Day sessions from #NVIDIAGTC and see how experts use NVIDIA DOCA to accelerate AI networking, storage, and security end to end. Explore the DOCA Developer Day playlist here ➡️ https://t.co/9124M1ENuo
View original🌐 Missed #NVIDIAGTC or want to dive deeper into the networking side of AI factories? Our featured GTC26 networking sessions are now available to watch on NVIDIA On‑Demand! Hear directly from NVIDIA
🌐 Missed #NVIDIAGTC or want to dive deeper into the networking side of AI factories? Our featured GTC26 networking sessions are now available to watch on NVIDIA On‑Demand! Hear directly from NVIDIA experts and partners on scaling multi‑gigawatt AI factories, building secure enterprise AI networking, accelerating cloud platforms and DOCA‑powered data paths, and transforming content delivery with AI at the edge. 🎥 Dive into the networking playlist here: https://t.co/q4bFOfx5ys
View original📣 Announced last week at #NVIDIAGTC, the NVIDIA Vera Rubin POD is a next-gen AI supercomputer built from seven co-designed chips across compute, networking, and storage to power agentic AI at rack an
📣 Announced last week at #NVIDIAGTC, the NVIDIA Vera Rubin POD is a next-gen AI supercomputer built from seven co-designed chips across compute, networking, and storage to power agentic AI at rack and POD scale. In this technical blog, you’ll see how Spectrum-6 SPX networking racks, BlueField-4 STX AI-native storage, and third-gen NVIDIA MGX architecture come together to deliver 60 exaflops, 10 PB/s bandwidth, and ultra-efficient token throughput. Read it here 👉 https://t.co/n6T6NTGWjz
View originalBehold the power of NVIDIA BlueField-4 in the hands of our storage partners. Don’t miss Jensen’s #NVIDIAGTC keynote announcement on the new co-designed NVIDIA BlueField-4 STX storage architecture—an
Behold the power of NVIDIA BlueField-4 in the hands of our storage partners. Don’t miss Jensen’s #NVIDIAGTC keynote announcement on the new co-designed NVIDIA BlueField-4 STX storage architecture—and the NVIDIA CMX context memory storage configuration that extends long-context AI at scale. Learn more below ⤵️
View original🏭 AI factories are moving from build-first to simulate-first. With NVIDIA DSX Air, organizations can design and validate AI infrastructure across compute, networking, storage, and security together
🏭 AI factories are moving from build-first to simulate-first. With NVIDIA DSX Air, organizations can design and validate AI infrastructure across compute, networking, storage, and security together with ecosystem partners—before deployment. The impact: ⏱️ Infrastructure validation from months → days ✅ Deployment timelines from weeks → day one Simulation-first is how modern AI factories are designed, scaled, and operated with confidence. Learn more ➡️ https://t.co/kMtch4etfZ
View originalNVIDIA Omniverse uses a tiered pricing model. Visit their website for current pricing details.
Key features include: OpenUSD, Physics, Runtime, Robot Simulation, Robot Learning, Libraries, Blueprints, Skild AI: Pioneering Omni-Bodied Intelligence Through Simulation.
NVIDIA Omniverse is commonly used for: How Omniverse Libraries Are Being Used.
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