News Releases - NVIDIA Newsroom

Bringing the Spark to Europe: Local Intelligence Powers Next Wave of Agents

Gerardo Delgado — Wed, 21 Oct 2026 10:50:37 GMT

At GTC Berlin, NVIDIA is showcasing its full lineup of local AI hardware. RTX Spark, which launched last week, powers personal agents on Windows PCs; DGX Spark supports developers building and scaling applications on Linux; and DGX Station serves enterprise teams running frontier workloads on Linux, with a Windows version arriving in December. Announcements include: […]

Google Cloud and NVIDIA Announce General Availability of NVIDIA Vera Rubin Infrastructure

Uttara Kumar — Wed, 21 Oct 2026 10:45:17 GMT

General availability of the instances is coming next month, with planned expansion of availability to Europe — bringing an integrated platform for training, inference and large-scale reinforcement learning to cloud customers. A5X instances bring together NVIDIA Vera Rubin NVL72, NVIDIA ConnectX-9 SuperNICs, Google Cloud Virgo Network and Google Cloud’s fourth-generation advanced liquid-cooling technology for demanding […]

NVIDIA and Supply Chain Partners Expand Capacity to Accelerate AI Infrastructure Buildout

Wed, 21 Oct 2026 10:33:00 GMT

News Summary:

Substrate agreements with IBIDEN, Samsung Electro-Mechanics and Unimicron Technology Corporation will, in aggregate, drive a 2.5x increase in capacity over the next three years.
Amkor plans to increase its advanced packaging capacity by more than 300% by the end of 2028.
KYEC will build new facilities in the U.S., supported by a $1.1 billion capacity reservation advance from NVIDIA.
SPIL is targeting to increase its optical-engine capacity for co-packaged optics by 15x by mid-2027, with aims for another doubling by the end of 2028.

GTC Berlin—NVIDIA today announced plans with a group of supply chain partners to expand global manufacturing capacity to meet growing demand for its accelerated computing and full-stack AI factory platform.

Working with Amkor Technology, IBIDEN, King Yuan Electronics (KYEC), Samsung Electro-Mechanics, Siliconware Precision Industries (SPIL) and Unimicron Technology Corporation, NVIDIA is enabling new and existing suppliers to expand critical manufacturing capabilities across substrates, advanced packaging, testing and optical engines, strengthening the resiliency and redundancy of NVIDIA’s global supply chain.

“We are in the midst of the largest infrastructure buildout in human history. Demand is extraordinary. Capacity is the constraint,” said Jensen Huang, founder and CEO of NVIDIA. “Our supply chain partners are the world’s best manufacturers. I’m grateful they are expanding capacity around the globe to scale production and help us deliver the AI supercomputing systems powering this new industrial revolution.”

Expanding Substrate Capacity to Support Volume Growth
NVIDIA plans to increase substrate capacity for its products by 2.5x over the next three years. The agreements below will contribute to this capacity expansion, with more underway.

Under an agreement signed and announced earlier this year by IBIDEN, NVIDIA is providing a multibillion-dollar capacity reservation advance to support IBIDEN’s Ono Plant in Japan. The expansion targets capacity reaching 3x current levels at the plant, with additional capacity expected to begin ramping in the first quarter of 2028.

Samsung Electro-Mechanics is joining NVIDIA’s substrate supply chain, bringing immediate capacity from its existing operations in South Korea. The collaboration also supports facility upgrades and new factories in Sejong and Busan, South Korea. By 2028, production allocated to NVIDIA is projected to account for a significant portion of Samsung Electro-Mechanics’ total annual package substrate production capacity.

NVIDIA is supporting Unimicron’s KF substrate manufacturing expansion in Taiwan with a capacity reservation agreement. The expansion is expected to begin adding capacity in the second quarter of 2027 and reach full capacity by mid-2028.

Scaling Advanced Packaging for Next-Generation Platforms
NVIDIA and Amkor plan to expand advanced packaging capacity in South Korea, targeting a greater than 300% increase in interposer wafer capacity by the end of 2028. The planned capacity expansion, alongside Amkor’s development of new manufacturing facilities in South Korea, will support higher production volumes for NVIDIA’s current and next-generation platforms.

Expanding Semiconductor Testing and Strengthening US Manufacturing
NVIDIA expects its total semiconductor testing capacity to double from calendar 2026 to 2027, supported by buildouts in the U.S., Taiwan and Singapore.

NVIDIA’s $1.1 billion capacity reservation advance to KYEC will support new U.S. testing facilities and equipment, with high-volume production targeted for April 2027.

In Singapore, expanded testing operations are expected to begin high-volume production in February 2027.

Creating the Infrastructure for Co-Packaged Optics
NVIDIA and SPIL plan to expand manufacturing capacity in Taiwan for optical engines used in co-packaged optics, supporting the growing connectivity requirements of large-scale computing infrastructure. The expansion targets an increase of 15x by mid-2027, with aims for another doubling by the end of 2028.

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NVIDIA Cloud Partners Scale Across Europe — Sovereign, Open and Built for Safe AI Agents

Stuart Pitts — Wed, 21 Oct 2026 10:30:41 GMT

Demand from AI-natives is pulling the European AI cloud ecosystem forward faster than ever. Developers need compute closer to their data, open models they can customize and serve at scale, and full-stack infrastructure that is secure by design. NVIDIA Cloud Partners across Europe, the Nordics, Africa, and Central Asia are expanding regional compute capacity for […]

Europe’s Industrial Leaders Reinvent Engineering and Manufacturing With NVIDIA

James McKenna — Wed, 21 Oct 2026 10:30:40 GMT

To increase productivity, accelerate innovation and create new opportunities for economic growth, Europe’s industrial leaders are tapping NVIDIA CUDA-X and Omniverse libraries, as well as NVIDIA Cosmos and Nemotron open models, across the engineering and manufacturing lifecycle. Bringing those capabilities together on the factory floor, the NVIDIA Factory Operations Blueprint (FOX) is now available in […]

NVIDIA cuDSS Now Generally Available to Accelerate Engineering and Scientific Simulations

Timothy Costa — Wed, 21 Oct 2026 10:30:25 GMT

NVIDIA cuDSS, launched today in general availability, is an NVIDIA CUDA-X library that shifts a critical part of engineering and scientific simulations onto GPUs. Complex engineering feats — from advanced chips to aircraft to industrial systems —– depend on simulation to predict how designs will perform before they’re built. As designs become more complex, simulations […]

NVIDIA Confidential Computing Expands, Enabling Frontier Model Builders to Securely Scale Across Global Infrastructure

John Fanelli — Wed, 21 Oct 2026 10:30:02 GMT

NVIDIA builds tools to enable safe agents across the stack. The NVIDIA OpenShell Reference Architecture, announced today, is part of NVIDIA’s growing portfolio of technologies that enables organizations to safely deploy agents at scale. NVIDIA Confidential Computing is the infrastructure layer that protects the models and data those agents depend on while running. Today, NVIDIA […]

NVIDIA Advances Isaac Platform for General-Purpose Robotics With New Reference Humanoid, Frameworks, Simulation Pipelines and Data

Wed, 21 Oct 2026 10:20:00 GMT

News Summary:

Agile Robots announces Agile ONE SN, a humanoid reference platform built on NVIDIA Isaac GR00T and NVIDIA Jetson Thor with planned integration of the NVIDIA Halos safety stack, giving developers and researchers a complete platform for frontier humanoid development and validation.
NVIDIA Isaac platform adds new Isaac OS runtime, Isaac Lab 3.0 for robot learning and open source reference workflows that combine ChatGPT Astra with NVIDIA Isaac and Cosmos on NVIDIA DGX Station to accelerate robot data generation, training and evaluation.
Europe’s robotics ecosystem, including leaders like ABB Robotics, Flexion, Hexagon Robotics, Humanoid, KUKA, NEURA Robotics, Sereact and Universal Robots, is building on NVIDIA’s open robotics platform to advance autonomous robotic systems.

GTC Berlin—NVIDIA today announced a major expansion of the NVIDIA Isaac™ open robotics development platform, adding a reference humanoid, datasets and runtime, along with updates to its robot learning framework.

Together, these technologies give developers an integrated path from data to deployment to bring general-purpose robots to the real-world faster.

“General-purpose robotics is advancing at extraordinary speed — the ChatGPT moment for robotics is fast approaching,” said Jensen Huang, founder and CEO of NVIDIA. “With NVIDIA Isaac, our full-stack open robotics platform, we are giving developers the models, data, simulation tools and computing systems to bring physical AI to the world’s largest industries.”

Agile ONE SN — A Frontier Humanoid Reference Platform for Research
Agile Robots announced Agile ONE SN, a full-stack reference humanoid preconfigured with NVIDIA Isaac GR00T and powered by the NVIDIA Jetson Thor™ edge AI platform.

Robotics researchers and developers often struggle to integrate the separate simulation, training and deployment tools needed to take robot skills from development to the physical world. Agile ONE SN unifies these tools and workflows on a single platform, cutting setup time from weeks to days.

Agile ONE SN features:

Agile ONE S humanoid body, standing 1.40 meters (4.59 feet tall) and weighing 40 kilograms (88 pounds), with 31 degrees of freedom and a 3-kilogram payload per arm.
Dual WUJI Hand 2 five-finger hands, each offering 20 degrees of freedom, 1kHz force control and tactile sensing for dexterous manipulation
NVIDIA Jetson Thor onboard compute, delivering 2,070 FP4 teraflops of compute and 128GB of unified memory for onboard reasoning and real-time control.
Multimodal sensing, including head and wrist cameras, lidar sensors and inertial measurement units to help the robot perceive and interact with its surroundings.
NVIDIA Isaac GR00T platform, which comprises the GR00T foundation model, a full workflow from data capture to deployment and whole-body control for coordinated movement.
Safety capabilities, with planned integration of on-robot safety protocols with the NVIDIA Halos full-stack safety system for robotics.

“The breakthrough for humanoids is usefulness at scale: one adaptable machine that learns many skills and works across environments built for people,” said Zhaopeng Chen, founder and CEO of Agile Robots. “Today, Agile Robots introduced Agile ONE SN, a full-stack, open reference humanoid built on NVIDIA Isaac GR00T, powered by Jetson Thor, giving developers a ready system to create, train and validate the capabilities needed to put humanoids to work.”

Scheduled to be available in early 2027, Agile ONE SN is designed to advance frontier humanoid research and development, with interest from leading institutions such as Stanford University and ETH Zurich.

New NVIDIA Technology Accelerate Robot Learning — From Data to Deployment
New NVIDIA technologies help developers generate training data, scale robot learning, build simulation environments and deploy robot applications, reducing time to solution.

SimReady Central Library offers more than 2,000 simulation-ready robotics and factory assets, while the Human 1M Dataset includes diverse human activities, synchronized three-view video and 3D hand tracking. Both are available on Hugging Face, with the full Human 1M Dataset accessible to Cosmos Coalition partners.
NVIDIA Isaac Lab 3.0 is now generally available, providing an open source, agent-ready learning framework training and refining robot policies from desktop to data center using multi-GPU workflows and physics engines including Newton and NVIDIA PhysX™.
NVIDIA Isaac OS, an open source runtime framework built on NVIDIA Holoscan, connects AI, sensors, controls and robot hardware for deterministic, real-time performance from simulation to physical robots.
NVIDIA is releasing three open source reference workflows for NVIDIA DGX Station™ that help developers refine GR00T 1.7 models with reinforcement learning, train dexterous manipulation skills in NVIDIA Isaac Lab and post-train NVIDIA Cosmos™ world models for synthetic data generation using ChatGPT Astra.
NVIDIA Halos provides a full-stack safety platform built on NVIDIA IGX Thor™ to help move autonomous vehicles and robots from development to safer real-world deployment at scale.

SimReady Central Library on Hugging Face includes simulation-ready assets from Comau, FANUC, ForgeCAD, Franka Robotics, LG Electronics, Palatial, Robotiq, Standard Bots, Universal Robots and Vertiv.

NVIDIA’s open source robot learning reference workflows running on DGX Station will be supported by solutions from 1X, Agile Robots, Humanoid, Maven Robotics, Mentee, MicroAGI, Rhoda, Sereact and Skild AI.

Robotics partners are integrating NVIDIA Halos within their safety architectures, including Agile Robots, Agility, Dexory, FORT Robotics and KION for warehouse robot safety. SICK is evaluating Halos to advance dynamic safety for industrial robots, helping them respond to changing conditions beyond fixed zones.

Advantech and NexCOBOT are developing NVIDIA IGX-based industrial computing platforms, while Reynolds & Moore, Accenture and TÜV SÜD are accelerating the certification process for the safe deployment of industrial physical AI.

European Robotics Leaders Build on NVIDIA Open Technologies
ABB Robotics is integrating NVIDIA Omniverse™ libraries with RobotStudio HyperReality to simulate and virtually commission robotic systems before installation across a wide range of industries. KUKA Group is using Omniverse libraries in its Visual Components FactoryLens to add real-time rendering for factory simulation workflows. Sereact is using Isaac GR00T with Cosmos Transfer to train and post-train its Cortex platform for goods handling, running on Universal Robots industrial robot arms.

Using Jetson Thor, Holoscan Sensor Bridge, Halos and NVIDIA Isaac OS, Humanoid is developing and validating robot behaviors before industrial pilots, Hexagon Robotics is building AEON perception capabilities including teleoperation video, localization, mapping and object pose detection, and Bear Robotics is accelerating KR1 perception and model execution while post-training Isaac GR00T through Kino-2 for warehouse, returns and industrial workflows.

Toyota Material Handling Europe and SoftServe use Omniverse and the NVIDIA Isaac Sim™ framework to develop autonomous material-handling solutions, reducing deployment time by up to 50%. Idealworks is using NVIDIA open models and Jetson to develop memory capabilities for autonomous mobile robots in factories. Analog Devices Inc. (ADI) is using NVIDIA Jetson AGX Orin™ and the cuVSLAM library to build autonomous mobile robots.

Hugging Face and Pollen Robotics are using NVIDIA Isaac Lab, Isaac Sim and Newton to build Microduck, a small, open source robot designed to help developers and students train, modify and share new physical behaviors. Franka Robotics is using NVIDIA NIM™ microservices and Isaac Sim to turn natural-language requests into actions on its Franka FR3 Duo robot system. Bellboy is using Jetson and GR00T to power Billie, its first robot teammate built on Bellboy’s physical AI infrastructure, already deployed at hotels operated by Marriott, Hilton, IHG and OYO.

Flexion is using Isaac Lab and Newton to scale learning for Reflect, its unified robot intelligence model combining reasoning and whole-body movement for complex manipulation across robot bodies. Schaeffler is contributing its actuator technology as an exclusive foundational component for Newton, helping accelerate humanoid robot development with NVIDIA Isaac Lab and Isaac Sim.

NEURA Robotics is using Isaac Sim and Isaac Lab to generate synthetic training data and train robot skills in simulation for Neuron AI, its multimodal foundation model.

Watch the GTC Berlin keynote from Huang and explore sessions.

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European Mobility Leaders Build Safe Vehicles and Robotaxi Fleets on NVIDIA Hyperion

Wed, 21 Oct 2026 10:14:00 GMT

News Summary:

Bolt with Lucid, Mercedes-Benz, Volkswagen Commercial Vehicles and Einride are showcasing selected autonomous-mobility use cases on the NVIDIA Hyperion computing platform, demonstrating potential applications for level 3 and level 4 vehicles as well as future robotaxi fleets, with Volvo Cars adopting Hyperion and NVIDIA Alpamayo Stack for safe automated driving.
NVIDIA introduces Halos SAFE, a new framework within the NVIDIA Halos safety system, which combines simulation and physical testing to help developers generate measurable, traceable AV safety evidence.
NVIDIA announces Alpamayo 2 Edge, Alpamayo Agentic Factory and new Cosmos 3 Nano model variants to help developers build, customize and evaluate autonomous-driving for diverse vehicles, operating conditions and regions.

GTC Berlin—NVIDIA today announced that leading automakers in Europe and mobility providers, including Bolt with Lucid, Mercedes-Benz, Volkswagen Commercial Vehicles and Einride, are showcasing selected autonomous-mobility use cases on the NVIDIA Hyperion computing platform, demonstrating potential applications for level 3 and level 4 vehicles as well as future robotaxi fleets.

In addition, Volvo Cars is adopting Hyperion and NVIDIA Alpamayo Stack software for safe automated driving. NVIDIA also introduced new AI and safety technologies to help developers build, validate and deploy autonomous vehicles (AVs) at scale.

Autonomous transportation represents a multitrillion-dollar opportunity, with robotaxis leading the move to commercial level 4 deployment. NVIDIA Hyperion and the NVIDIA Halos full-stack safety system give automakers and mobility providers the computing performance, safety foundation and long-term support to bring AVs and robotaxi fleets to market at scale.

“Robotaxis are the first mass-market application of robotics and physical AI, reinventing how people and goods move,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA Hyperion, together with our Halos safety operating system, gives our partners a full-stack robotaxi platform designed to achieve full autonomy and the highest levels of safety, bringing us closer to a future where everything that moves is autonomous.”

Mobility Leaders in Europe Build on NVIDIA Hyperion
Automakers and mobility providers in Europe are pursuing various paths to autonomy, from passenger vehicles and robotaxi fleets to autonomous freight trucks. NVIDIA Hyperion’s modular architecture supports all of these programs, compatible with NVIDIA Alpamayo Stack autonomous driving software as well as partners’ own driving software.

Bolt has selected NVIDIA Alpamayo Stack for its European robotaxi program, beginning with future Lucid vehicles built on Hyperion. Bolt and NVIDIA will adapt the software for European roads and integrate it into vehicles from multiple manufacturers, combining NVIDIA’s driving and safety technologies with Bolt’s fleet-management systems, operations and local market expertise.

Bolt plans to begin gathering real-world driving data to support the development and validation of the autonomous driving technology — subject to regulatory approval — in Madrid in 2027, with Germany being a priority for future deployment as part of a planned European rollout of at least 25,000 level 4-capable future Lucid vehicles built on NVIDIA Hyperion.

At GTC Berlin, Volkswagen Commercial Vehicles is presenting its autonomous ID. Buzz AD vehicle platform with Hyperion to support multiple autonomous-driving systems. Hyperion provides a common computing and sensor architecture designed to simplify integration and validation, helping developers and mobility operators bring robotaxi and commercial transport services to market.

Volvo Cars is combining its industry-leading vehicle safety systems and engineering expertise with Hyperion, Halos OS and Alpamayo Stack to enable future Volvo cars to safely navigate complex real-world environments from door to door.

Mercedes-Benz is extending its partnership with NVIDIA on Hyperion and Alpamayo Stack to support the development of the automaker’s L3 and L4 capabilities. The company also announced that MB.DRIVE ASSIST PRO, developed in partnership with NVIDIA, will soon get approval for urban point-to-point urban driver assistance in Germany, helping drivers navigate journeys through complex city traffic.

Beyond passenger vehicles and robotaxis, Einride is building its next-generation Einride Driver on Hyperion for autonomous freight trucks, using Halos, Alpamayo and NVIDIA Cosmos™ open world models to develop and validate its driving system, while TIER IV and the Technical University of Munich plan to integrate Hyperion to develop and validate systems for autonomous public transportation in Germany.

NVIDIA technology and manufacturing partners are also helping expand the AV ecosystem, with Aptiv, Valeo and Schaeffler building Hyperion-based computing platforms that can be integrated by vehicle manufacturers for L4 AVs and robotaxis.

Scaling Safe Autonomy With NVIDIA Halos
Halos provides the safety foundation for NVIDIA’s AV platform, bringing together AI computing, safety software and validation from development through deployment.

To give developers repeatable ways to evaluate driving behavior and simulation accuracy, NVIDIA today introduced Halos SAFE — the Safety Assurance Framework for Evaluation — with dSPACE, IVEX and TÜV Rheinland collaborating on evaluation workflows. Halos SAFE connects simulation, software- and hardware-in-the-loop evaluation, on-road testing and fleet monitoring through defined scenarios, tests and measurable performance criteria to generate traceable safety evidence that supports deployment.

The Halos SAFE ecosystem also includes JLR, Mercedes-Benz, Volvo Cars, 51Sim, aiMotive, AVL, Deepen AI, Foretellix and Synopsys.

Accelerating AV Development
Developing AVs means teaching AI to handle the diversity of real-world driving, then bringing that intelligence into the vehicle. NVIDIA’s latest models, tools and blueprints help developers prepare driving data, improve models and evaluate performance:

Alpamayo 2 Edge, a 2-billion-parameter reasoning model built on NVIDIA Cosmos, is optimized for the NVIDIA DRIVE AGX Thor™ platform and designed to run at 10Hz for in-vehicle scene understanding and motion planning.
AlpaJudge, a human-calibrated evaluation and reward model, scores driving explanations to assess reasoning quality, filter weak annotations and reduce manual review of training data.
Foundation4D labels multicamera video without lidar input, supporting perception-model training and NVIDIA Omniverse™ NuRec scene reconstruction.
New Cosmos 3 Nano model variants expand synthetic data generation and closed-loop simulation for autonomous driving through synchronized multiview, multi-camera and lidar generation across diverse driving scenarios.
Cosmos Data Factory’s AV dataset-generation blueprint turns driving video and vehicle signals into curated, searchable, labeled data, using synthetic data to expand scenario coverage.
Alpamayo Agentic Factory, an open blueprint expected to become available in early 2027, uses AI agents to connect data preparation, model post-training and simulation evaluation, reducing integration work.
NVIDIA NIM™ microservices for Alpamayo 1.5 and NuRec Harmonizer deliver both models as optimized inference containers, giving AV reasoning and scene harmonization a simplified deployment path.

Uber and NVIDIA are developing a data factory powered by Cosmos to curate and process data for AV development. The effort is part of a broader partnership spanning AI development infrastructure, Hyperion-based vehicles and Uber’s global ride-hailing network.

Porsche is leading the development of a data flywheel workflow across Volkswagen Group brands through Voxel51, using NVIDIA Cosmos Data Factory and Omniverse NuRec on Microsoft Azure to turn fleet data into datasets and simulations for evaluating autonomous-driving models. This is expected to reduce repeated physical test drives by up to 90% and shorten development cycle duration by up to 85%.

Watch the GTC Berlin keynote from Huang and explore sessions.

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Healthcare and Life Sciences Leaders Build on NVIDIA to Advance Drug Discovery and Expand Patient Care

Wed, 21 Oct 2026 10:13:00 GMT

News Summary:

NVIDIA and the UW Medicine Institute for Protein Design debut RFD4-Proteina, a new open model that combines programmable protein design with search capabilities, unlocking new frontiers in biology.
Siemens Healthineers is advancing the next generation of adaptive radiotherapy, using NVIDIA intelligence to increase access to life-saving cancer care with agentic co-planning, patient-specific simulation and robotic control.
Automata, Benchling, Biolevate, Boltz, Danaher, Hologen and Therna Biosciences are using the NVIDIA BioNeMo open platform to develop scientific agents that connect drug design, autonomous laboratories and biological discovery, helping researchers move from hypothesis to experiments faster.

GTC Berlin—NVIDIA today announced collaborations with leading global healthcare and research organizations to advance protein design — including through a newly released open model, RFD4-Proteina — accelerate drug discovery and bring greater precision to cancer care.

Life sciences researchers must search vast biological design spaces and aim to shorten the cycle between computational design and laboratory testing to discover new medicines. Cancer care teams face a different challenge: translating complex imaging and treatment data into precise plans for each patient.

NVIDIA open models, accelerated computing and physical intelligence can help experts evaluate more possibilities faster, from designing new proteins to planning adaptive radiotherapy.

“Agentic and physical AI are opening new possibilities across medicine, from designing proteins and powering autonomous laboratories to improving personalized cancer care,” said Kimberly Powell, vice president of healthcare at NVIDIA. “Together with healthcare and life science leaders, we’re accelerating scientific discovery and advancing more precise, accessible care around the world.”

NVIDIA and the UW Institute for Protein Design Introduce RFD4-Proteina
Proteins are molecular tools that perform many of life’s essential tasks, and designing new versions could open paths to new medicines, diagnostics and industrial applications. But finding a protein capable of performing a designed function requires searching an immense range of possible designs.

NVIDIA and the UW Medicine Institute for Protein Design are debuting RFD4-Proteina, a new NVIDIA BioNeMo™ open model that combines programmable protein design with search capabilities.

The model generates targeted protein designs, enabling scientists and agents to search and refine designs using molecular inputs, constraints and scoring objectives. Potential applications include designing proteins to interrupt disease processes or detect signs of disease in diagnostic tests.

In testing reported in the research draft, RFD4-Proteina achieved higher computational design success rates and generation throughput than the evaluated baselines across four benchmark suites: protein binding, small-molecule binding, enzyme scaffolding and DNA binding. The model helps researchers explore and prioritize candidates for laboratory testing, where experiments establish how a design performs under tested conditions.

“We are moving from an era of discovering the proteins nature has made to one in which we can design entirely new ones,” said David Baker, 2024 Nobel Laureate in chemistry and director of the Institute for Protein Design at the University of Washington. “RFD4-Proteina expands what scientists can create, from proteins that could advance drug discovery to enzymes that break down pesticides. Making the model open will allow researchers around the world to build on these capabilities and pursue solutions once beyond the reach.”

RFD4-Proteina is available today through partners including Amazon Bio Discovery, Anthropic’s Claude Science, Benchling, Databricks, Google Cloud, Hugging Face, Nebius, OpenAI and Tamarind Bio, enabling researchers and developers to integrate the open protein design model into agent, cloud and scientific computing workflows.

Siemens Healthineers Advances Cancer Care With NVIDIA
Siemens Healthineers and NVIDIA are collaborating to develop the next generation of adaptive radiotherapy with agentic and robotic intelligence, combining imaging and oncology expertise with accelerated computing and simulation to simplify workflows and expand access to care.

By 2050, approximately 35 million people worldwide are projected to be diagnosed with cancer each year. Care teams face growing pressure to deliver precise, personalized treatment while managing limited specialist capacity. Greater efficiency can help expand access to care while maintaining the precision needed to deliver prescribed doses to tumors and protect surrounding healthy tissue.

Siemens Healthineers is working with NVIDIA to further develop adaptive radiotherapy through agentic co-planning, patient-specific simulation and real-time computing. NVIDIA Nemotron™ open foundation models are being explored to power agentic co-planning, with the aim of helping oncologists evaluate and refine personalized treatment strategies. The models could then be combined with NVIDIA CUDA^®-accelerated dose calculation for rapid patient-specific simulation and the NVIDIA Holoscan platform to connect live sensor data with AI and simulation to support adaptive treatment.

“Adaptive radiotherapy is built on a single principle: treatment should adapt to the patient, not the other way around,” said Arthur Kaindl, head of Varian, the Siemens Healthineers cancer-care business. “We’ve made important advances in precision and adaptation — most recently, with the launch of the Accela system. Our collaboration with NVIDIA builds on that progress, exploring how AI and real-time computing could give clinicians greater speed and insight to make informed decisions, adapt treatment with greater confidence and deliver personalized care to more patients.”

Scientific Agents Advance Drug Discovery and Development
Life sciences is one of the world’s most important scientific frontiers, with global scientific R&D reaching $3.8 trillion and annual pharmaceutical budgets approaching $300 billion.

Scientific agents and autonomous laboratories can help turn more of that investment into evidence, insight and, ultimately, new treatments by connecting design, experimentation and learning in a continuous cycle.

To accelerate discovery and free up scientists for work only they can do, research and laboratory technology companies are using NVIDIA BioNeMo — an open development platform that enables AI-driven biology and drug discovery — alongside Nemotron and other NVIDIA technologies to develop scientific agents and the specialized models and tools that connect drug design, scientific data and laboratory workflows:

Benchling is grounding agents in experimental data, research context and connected scientific workflows.
Biolevate is connecting biological data, specialized scientific tools and agentic reasoning across drug discovery and development.
Boltz is developing specialized models and tools that scientific agents can use to predict molecular structures and design and evaluate candidates. It is also previewing a scientific agent to plan workflows, apply the right models and interpret results to guide the next experiment.
Automata is connecting scientific agents with automated laboratory infrastructure so they can initiate experiments and capture structured, contextualized results through workflows.
Genedata’s AI co-scientist will coordinate protein design and testing in the protein design foundry within Danaher’s autonomous lab. The workflow will incorporate RFD4-Proteina, helping scientists use experimental results to guide the next round of designs.
Hologen is combining its large medicine models with NVIDIA Nemotron to build AI clinical scientists that help researchers turn imaging and clinical data into insights about patient outcomes to inform clinical trial design.
Therna Biosciences is using large language model reasoning to connect experimental evidence and RNA medicine design, helping scientists turn biological insights into therapeutic candidates.

NVIDIA Open Models Streamline Hospital Operations, Expand Access to Specialized Care
Healthcare systems across Europe are working to expand access to specialized care while reducing the administrative demands on already-stretched care teams.

Avelios, Corti, Dedalus, Dawn Health and Sword are also building on NVIDIA Nemotron, powering everything from AI scribes and AI-assisted clinical care to personalized patient support services.

PolyAI is building on NVIDIA Agent Toolkit to speed the path to care through its multilingual dialog deployment with medical software provider Corilus, which has a network spanning more than 70,000 healthcare professionals across Belgium and France.

Apian and VitVio are extending this into the physical world, using NVIDIA Cosmos™ world models and NVIDIA Omniverse™ libraries to build digital twins that monitor and improve hospital operations.

Watch the GTC Berlin keynote from NVIDIA founder and CEO Jensen Huang and explore sessions.

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NVIDIA, Nokia and Leading Telecom Operators Turn Networks Into Distributed Intelligence Platforms

Wed, 21 Oct 2026 10:11:00 GMT

News Summary:

Leading global telecom operators are expanding NVIDIA-powered computing across their networks to deliver advanced services closer to people and businesses, improve wireless experience and automate network operations.
T-Mobile completes the world’s first AI-RAN call on a commercial network, while BT, Deutsche Telekom and Elisa announce AI-RAN pilots on live networks using Nokia’s CUDA-accelerated anyRAN software on NVIDIA Aerial RAN Computer, and NVIDIA introduces new Aerial RAN Computer configurations for high-capacity sites.
Nine EMEA telecom operators are building and expanding NVIDIA-powered infrastructure across centralized and distributed locations.
Operators and software partners are adopting NVIDIA Nemotron open models to deliver agentic services and develop agents for autonomous network operations.

GTC Berlin—NVIDIA today announced that leading global telecom operators are turning their networks into distributed intelligence platforms, adding NVIDIA accelerated computing to centralized data centers, metro sites and cell sites so they can serve models and applications closer to the people, businesses and machines that use them.

T-Mobile has completed the world’s first AI-RAN call on a live network in Bellevue, Washington, with NVIDIA and Nokia. Deutsche Telekom is advancing physical AI for industries, and Orange is introducing new voice intelligence services for enterprises and emergency responders. Elisa has completed Europe’s first field trial of AI-RAN, running voice, mobile data and vision AI together on a single accelerated computing platform over 5G, and BT is preparing live AI-RAN trials in the U.K. Nokia is bringing its anyRAN software on NVIDIA Aerial RAN Computer (ARC) for trials at BT, Deutsche Telekom, Elisa and Orange.

Nine operators across Europe, the Middle East and Africa (EMEA) are building or expanding NVIDIA-powered infrastructure, while Nokia and Cisco are incorporating NVIDIA Nemotron™ open models into the software operators use to run autonomous networks.

“Telecom networks were built to carry the world’s conversations. Now, they will also carry the world’s intelligence,” said Jensen Huang, founder and CEO of NVIDIA. “Leading global operators are turning their land, power and connectivity into a distributed AI infrastructure — bringing intelligence closer to the industries, people and robots that use it. With Nokia, we’re extending accelerated computing into the radio network itself, creating the foundation for AI-native 5G.”

Intelligence is built in five layers: land, power and shell, chips, infrastructure, models and applications. Telecom operators already own sovereign infrastructure at the first layer, with data centers, regional sites and cell sites that have power, fiber and spectrum.

By adding NVIDIA accelerated computing, open models and applications on top, operators are building the full intelligence stack into their networks. At distributed sites, a common converged platform based on the AI-RAN architecture can serve open models, power robotics, voice and agentic applications, and run intelligent 5G software.

Europe’s Leading Telcos Build Distributed Infrastructure
Infrastructure sits at the foundation of telecom’s transition to distributed service platforms.

Deutsche Telekom plans to expand its NVIDIA-powered Industrial AI Cloud, which hosts open models — including NVIDIA Nemotron and Soofi — and serves robotics companies such as Agile Robots. At distributed sites, Deutsche Telekom is piloting AI-RAN trials with Nokia and NVIDIA, and demonstrating NVIDIA ARC to run inference between the device and the network edge.

A GTC Berlin demonstration with Agile Robots shows the approach: on-robot intelligence handles real-time perception and action, a model at the distributed edge supports fine-tuning and coordination across robots, and the central infrastructure provides capacity for larger training workloads.

Orange is hosting open models, including NVIDIA Nemotron, as a managed service on top of its Live Intelligence trusted AI platform, enabling new advanced services for enterprises. At distributed sites, Orange is deploying NVIDIA ARC for voice intelligence applications using Nemotron Speech, demonstrating new services to help emergency and field services teams translate across multiple languages in real time with low latency and reliability.

Elisa has deployed NVIDIA ARC at a distributed network location, running a voice intelligence application that serves as an enterprise assistant, and is using open models to build edge applications.

EMEA telcos are building or expanding NVIDIA-powered infrastructure:

New infrastructure: CRA in the Czech Republic, etisalat in the United Arab Emirates, Silknet in Georgia and TIM in Italy.
Expansions: Cassava in Africa, Deutsche Telekom in Germany, Fastweb + Vodafone in Italy, Kazakhtelecom in Central Asia and Orion Telecom in Serbia.

AI-RAN Brings Accelerated Computing Into the Radio Network
AI-RAN extends accelerated computing into the radio access network (RAN), turning it into an intelligence workload that runs on the same platform as advanced services, so operators can get more out of their spectrum while serving demand from sites close to users.

Globally, nearly 20 telecom operators have publicly announced AI-RAN collaborations using Nokia anyRAN software and NVIDIA ARC.

T-Mobile recently marked the world’s first AI-RAN call on its commercial network in Bellevue, Washington, running on commercial ARC servers, Nokia’s NVIDIA CUDA-accelerated RAN software and massive multiple-input multiple-output radios, and connected to an existing 5G Standalone core and a commercial smartphone.
BT is planning live AI-RAN trials in Birmingham, England, with Nokia and NVIDIA in 2027.
Deutsche Telekom has validated Nokia and NVIDIA’s commercial AI-RAN platform in Bonn and Oulu labs, including AI-enhanced uplink channel estimation to improve uplink user throughput, with plans to move to field trials in 2027.
Elisa simultaneously ran voice, mobile data and video analytics on the NVIDIA ARC platform, marking a European first in Elisa’s over-the-air field environment using 5G spectrum. The trial clears the way for distributed deployment and commercial AI-RAN services in 2027.
Orange is testing Nokia 5G software on NVIDIA ARC, focusing on AI-RAN spectral efficiency improvements and support for edge services in live networks.

NVIDIA is introducing two ARC configurations — MGX 2U and MGX 4U — designed for dense, high-capacity intelligence and radio workloads, typically deployed at centralized RAN sites. Powered by NVIDIA RTX PRO™ 6000 Blackwell Server Edition GPUs, the configurations will offer x86 and NVIDIA Vera CPU options. Dell Technologies, Quanta Cloud Technology and Supermicro will offer ARC-ready servers.

Open Models Power Autonomous Network Operations
Leading telcos are using open models and agents to speed progress toward fully autonomous network operations. NVIDIA Nemotron open models and NVIDIA Agent Toolkit software are now integrated into leading partners’ commercial software, powering specialized agents built for telecom network workflows.

Nokia is integrating NVIDIA Nemotron into its Autonomous Networks Suite and using NVIDIA Agent Toolkit software to build and deploy trusted agents that manage operations across fixed, radio, core and transport networks.

Cisco has fine-tuned NVIDIA Nemotron models and integrated them into Crosswork AI, creating a common agentic layer across its Crosswork Network Automation software to manage IP and optical transport networks. The company is also using NVIDIA Agent Toolkit to help telcos operate agents safely.

TCS is working with telcos to fine-tune NVIDIA Nemotron models and use NVIDIA Agent Toolkit to build specialized agents that validate radio-site builds, detect, diagnose and auto-remediate network issues, and deliver multilingual voice experiences. BT is adopting Nemotron to build agents that inspect field-installation photos, detect problems and help reduce repeat site visits.

NTT DATA is extending its NextGenOSS platform with fine-tuned NVIDIA Nemotron models and NVIDIA Agent Toolkit to build agents that detect early network degradation, identify likely root causes and recommend next actions.

Watch the GTC Berlin keynote from Huang and explore sessions.

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NVIDIA Agent Toolkit Expands, Grounding Enterprise Agents in Company Data

Erik Pounds — Wed, 21 Oct 2026 10:10:01 GMT

Agents are only as useful as what they know, and only as trustworthy as the boundaries they run within. Leading enterprises are using the open source NVIDIA Agent Toolkit — now expanded with new tools — to customize and control agents, use company data to inform their answers and actions, monitor what they do and […]

NVIDIA Open Models Advance Europe’s Sovereign Intelligence Across Industries

Kari Briski — Wed, 21 Oct 2026 10:00:07 GMT

NVIDIA is expanding its family of open models across language, robotics, biology, and quantum computing, giving developers, researchers and enterprises what they need to build applications tailored to local languages and industries The portfolio includes the new NVIDIA Nemotron 3.5 Super VL and Nemotron 3.5 Bolt models; new NVIDIA Nemotron Retriever models for embedding, reranking […]

NVIDIA Launches OpenShell Reference Architecture for Safe AI Agents

Wed, 21 Oct 2026 09:48:00 GMT

News Summary:

The NVIDIA OpenShell Reference Architecture delivers enterprise governance, isolation and security for building, containing, observing and enforcing safe agents across enterprise infrastructure and edge systems.
Built on the foundation of NVIDIA OpenShell secure runtime software, the architecture brings together NVIDIA Vera Rubin infrastructure for model inference, NVIDIA Vera CPUs for agent harnesses and tool use, and NVIDIA BlueField-4 DPUs running NVIDIA Sentry for in-silicon enforcement. The OpenShell Reference Architecture extends to the edge with NVIDIA RTX Spark, NVIDIA DGX Spark and NVIDIA DGX Station systems.
The OpenShell Reference Architecture runs on leading enterprise operating systems, including Canonical, Red Hat, and Microsoft Windows and Microsoft Execution Containers.
Anthropic, AWS, Cisco, CrowdStrike, Dassault Systèmes, Dell Technologies, Google Cloud, HPE, IBM, Meta, Microsoft, OpenAI, Palo Alto Networks, Perplexity, SAP, ServiceNow, Siemens, SpaceX Super Intelligence and others are among those working with the OpenShell Reference Architecture to enhance the security of agent deployments.

GTC Berlin—NVIDIA today announced the NVIDIA OpenShell Reference Architecture, which enables building, containing, observing and enforcing safe agents on enterprise infrastructure and edge systems.

The OpenShell Reference Architecture builds on the foundation of NVIDIA OpenShell™ secure runtime software, extending it into full-stack, industrial-scale infrastructure for agent development and operations.

It includes NVIDIA Vera Rubin infrastructure for running enterprise workloads, including closed and open models built with NVIDIA Nemotron™; NVIDIA Vera CPUs for operating agent harnesses; open source NVIDIA OpenShell software; and NVIDIA BlueField^® DPUs for running the NVIDIA Sentry unified security software framework that provides continuous out-of-band monitoring of agent behavior and in-silicon policy enforcement.

The OpenShell Reference Architecture is extensible to agents running at the edge across industries such as retail, healthcare, manufacturing, robotics, software development and telecommunications with NVIDIA RTX Spark™, NVIDIA DGX Spark™ and NVIDIA DGX Station™ systems.

“AI capability and safety must advance together,” said Jensen Huang, founder and CEO of NVIDIA. “As enterprises prepare to deploy billions of AI agents, safety and control must be built into the computing architecture. NVIDIA created OpenShell to give agents the freedom to do useful work within clearly defined boundaries — contained, monitored and under control. With the OpenShell Reference Architecture, agents can think on Rubin, act on Vera and be governed on BlueField.”

Full-Stack Infrastructure Built for Agents
The OpenShell Reference Architecture features NVIDIA accelerated computing paired with software for secure agent operations.

NVIDIA Vera Rubin, with NVIDIA Vera Rubin NVL72 infrastructure at its core, is fungible across pretraining, post-training and inference. For agentic workloads, NVIDIA Vera Rubin NVL72 systems deliver 30x higher throughput per megawatt.
NVIDIA Vera CPUs deliver 2x the performance of x86 processors with greater energy efficiency and run NVIDIA OpenShell, which provides a secure runtime boundary for autonomous agents.
NVIDIA BlueField-4 DPUs continuously monitor agent behavior with NVIDIA Sentry, built on NVIDIA DOCA™ software. BlueField and NVIDIA Sentry together provide in-silicon security enforcement — if an agent attempts to move outside its software boundary, NVIDIA Sentry quarantines and stops it in milliseconds. NVIDIA Sentry, powered by DOCA and running on BlueField-4, boosts agent capacity by up to 20%.

NVIDIA Partners Building Secure Agent Deployments With OpenShell
NVIDIA is working with industry leaders building infrastructure, models and software to enable industries to safely deploy agents in production.

The OpenShell Reference Architecture runs on leading enterprise operating systems and container orchestration layers, including Linux and Kubernetes infrastructure powered by Canonical, SUSE and Red Hat, as well as Microsoft Windows using Microsoft Execution Containers (MXC). It can run on cloud operating systems from Amazon Web Services, Google Cloud and Microsoft Azure.

Enterprises can run agents from model builders including Anthropic, Cohere, Google, Meta, OpenAI, Perplexity, Reflection and SpaceX Super Intelligence on OpenShell infrastructure. NVIDIA is also working with model builder partners on OpenShell deployments for advanced model research.

Cybersecurity leaders 1Password, Check Point, CrowdStrike, Cisco, F5, Fortinet, Microsoft, Okta, Palo Alto Networks, TrendAI and Zscaler are integrating support for the OpenShell Reference Architecture into their agent security solutions.

Leading banks — including Europe’s BBVA and Santander — are working with NVIDIA to explore the OpenShell Reference Architecture as a framework for strengthening agent safety, security and governance.

Enterprise software leaders Cadence, Dassault Systèmes, IBM, SAP, Siemens and Synopsys are working with OpenShell to build agent software platforms. Palantir and NVIDIA are working with customers to deploy secure agents in production.

SAP is integrating the NVIDIA OpenShell Reference Architecture with Joule Studio runtime, part of SAP Business AI Platform, connecting business governance with secure agent execution.

ServiceNow today announced the general availability of ServiceNow Arc, a personal long-running AI agent with actions governed at runtime by the ServiceNow Super Intelligence Control Tower and enforced by NVIDIA OpenShell. In addition, ServiceNow’s recently announced AI Passport authority layer carries those policies to NVIDIA OpenShell and NVIDIA Sentry, so enterprises can revoke an AI agent’s access across software and hardware within seconds.

NVIDIA system manufacturers Dell Technologies, Cisco, HPE, Lenovo and Supermicro are among those building infrastructure with the OpenShell Reference Architecture.

NVIDIA is also working with cloud service providers including CoreWeave, Crusoe, Firebird, Firmus, GMI Cloud, IREN, Lambda, Nebius, Nscale, Oracle Cloud Infrastructure and Vultr to deploy OpenShell-ready infrastructure.

Inference and post-training service providers including Baseten, Deepinfra, Fireworks and Together AI are building OpenShell Reference Architecture integrations into their model development pipelines.

Availability
The NVIDIA OpenShell Reference Architecture is now available.

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European Ecosystem Builds World’s Most Efficient AI Factories With NVIDIA DSX

Wed, 21 Oct 2026 09:35:00 GMT

News Summary:

NVIDIA DSX reference designs use closed-loop liquid cooling and dry coolers to enable near-zero facility cooling water consumption, with potential savings of 54 million liters a day for a 2-gigawatt deployment — equivalent to the daily water use of 180,000 households.
AI clouds in Europe are building and operating NVIDIA DSX-based AI factories, expanding access to accelerated computing for the continent’s enterprises, developers and governments.
NVIDIA DSX MaxLPS software helps operators use up to 30% less power to generate the same number of tokens, with CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale and Sharon AI planning to use the technology, while DSX Flex software turns AI factories into flexible power loads to support grid reliability and enable faster grid connection.
NVIDIA SimReady Central, a hub for simulation-ready digital models of physical equipment, launches on Hugging Face with validated power and cooling assets, helping operators build and simulate DSX AI factory digital twins faster.
New NVIDIA DSX OS open source software automates infrastructure lifecycle and improves health automation as well as resiliency capabilities to help operators run AI factories at scale.
An expanding ecosystem — including technology and industrial AI leaders AVEVA, Dassault Systèmes and Siemens, and energy and cooling providers ABB, Eaton, GE Vernova, Hitachi Energy, Schneider Electric, Siemens Energy, Trane Technologies and Vertiv — is connecting AI factory design, power, cooling and operations to support Europe’s accelerated computing buildout.

GTC Berlin—NVIDIA today announced that Europe’s leading ecosystem partners are adopting the NVIDIA DSX™ AI Factory Platform to build AI factories that minimize water consumption for cooling and use less power for the same AI output. The platform also helps partners bring new capacity online faster and adapt workload power consumption to support grid reliability.

NVIDIA DSX is a full-stack AI factory reference architecture, co-innovated with the world’s leading infrastructure companies. Compute, networking, storage, software, power and cooling are codesigned as one system — optimized from design to operation.

AI clouds and leading design, construction, energy and cooling providers are using DSX to build and operate infrastructure serving Europe’s enterprises, developers and governments.

“Europe’s technology leadership depends on how efficiently we turn power and infrastructure into intelligence,” said Warren Barkley, vice president of DSX product management at NVIDIA. “NVIDIA DSX brings together the technologies and ecosystem expertise operators need to build responsibly, operate efficiently at scale and bring intelligence to the market faster.”

The NVIDIA DSX platform includes DSX MaxLPS™ for dynamic power allocation, DSX Flex for coordinating workload power consumption with grid conditions, DSX Reference Design for validated infrastructure architectures, DSX Sim™ for simulation, DSX OS™ for infrastructure management and DSX Exchange™ for connecting computing and facility systems. These technologies help operators design, deploy and run AI factories that save valuable resources.

NVIDIA DSX Rethinks Cooling
Conventional cooling towers remove heat by evaporating water, requiring a continual supply of replacement water. NVIDIA DSX reference designs connect liquid-cooled computing with dry-cooler-based heat rejection that avoids evaporation: Cooling liquid absorbs heat from computing equipment and circulates in a closed loop, while outdoor dry coolers, similar to large radiators, release that heat into the air without evaporating water.

NVIDIA Vera Rubin infrastructure supports 100% liquid cooling with coolant temperatures of up to 45 degrees Celsius. With dry-cooler-based designs, this architecture can reduce facility cooling water consumption to near zero. At 2-gigawatt scale, NVIDIA DSX can save 54 million liters of water a day compared with conventional cooling-tower-based systems — equivalent to the daily water use of 180,000 households. Local climate determines whether supplemental mechanical cooling is needed during the hottest periods.

Delivering the Same AI Output With Less Power
Power availability defines how much capacity operators can bring online. DSX MaxLPS and DSX Flex address this constraint.

DSX MaxLPS dynamically allocates power within an AI factory’s provisioned budget, helping operators generate the same number of tokens with up to 30% less power. Operators can also use this efficiency to support more GPU capacity and higher throughput within existing power budgets. CoreWeave, Firmus, Google Cloud, IREN, Lambda, Nebius, Nscale and Sharon AI are exploring the software.

In a proof of concept across NVIDIA HGX™ B200 systems with DSX MaxLPS, Lambda demonstrated 24% more cluster token throughput and 19% more GPU capacity within a fixed power budget.

Coordinating AI Factory Power Demand With the Grid
DSX Flex helps AI factories become flexible assets for the power grid, enabling operators to adapt workload power consumption to utility needs, demand-response events and energy prices. It can also coordinate electricity from the grid, onsite renewables and energy storage, helping AI factories operate as flexible power loads that support grid reliability and enable faster grid connection.

In an early trial, Emerald AI, EPRI, Nebius, the U.K. National Grid and NVIDIA demonstrated reductions of up to 40% in the cluster’s power draw on an NVIDIA Blackwell Ultra GPU cluster in response to simulated grid events, while critical workloads continued running.

Nscale Advances AI Factory Efficiency With NVIDIA DSX
Using DSX MaxLPS, DSX Flex and DSX Sim, Nscale is demonstrating how the NVIDIA DSX platform connects power optimization, grid-responsive operations and design.

Based on an evaluation run in Nscale AI factory in Iceland, using DSX MaxLPS across four NVIDIA GB300 NVL72 racks, Nscale demonstrated 49% higher inference throughput and 37% more managed GPU capacity within the same 264-kilowatt provisioned power budget. The results demonstrate how dynamic power allocation can unlock additional capacity from existing infrastructure.

Nscale is also exploring DSX Flex to align workload power consumption with grid conditions.

“Europe’s AI ambitions demand that we make every megawatt count,” said Josh Payne, founder and CEO of Nscale. “With NVIDIA DSX, we’re building AI factories that deliver more compute from available power, respond to grid conditions and move faster from design to deployment.”

For its facilities in Portugal and Iceland, Nscale is using DSX Sim to create digital twins that help evaluate power, cooling and infrastructure configurations before deployment. By validating designs virtually, Nscale can identify potential issues earlier, reduce deployment risk and accelerate the path from planning to productive capacity.

Accelerating AI Factory Design With DSX Sim and SimReady Central Library
NVIDIA is launching SimReady Central Library with validated power and cooling equipment assets from partners like Vertiv, accelerating the creation of DSX AI factory digital twins.

Used with DSX Sim, ecosystem partners including PTC are helping create these simulation-ready assets with computer-aided design to enable SimReady workflows that let builders model infrastructure configurations and evaluate power and cooling decisions before equipment is installed. Operators can validate designs earlier, reduce deployment risk and move faster from planning to construction.

Driving Production Readiness With NVIDIA DSX OS
To help operators turn installed infrastructure into productive capacity, NVIDIA is expanding its modular, open source DSX OS portfolio with three components in developer preview:

NVIDIA Config Manager automates AI factory network configuration.
NVIDIA Rack Management Service provides rack-level power, inventory, firmware and switch management.
NVIDIA Cluster Readiness Engine runs distributed workloads to validate GPU clusters before production workloads arrive and isolate failures to specific nodes.

Together with NVIDIA Infrastructure Controller, NVIDIA AI Cluster Runtime and NVSentinel, these components help operators automate infrastructure lifecycle management, maintain consistent runtime environments and strengthen health validation, fault attribution and recovery.

Cloud partners including Aleria, Cassava, CoreWeave, Crusoe, Firmus, Firebird, G42, GMI Cloud, IREN, Lambda, Nebius, Nscale, Radiant, Sharon AI and Volta are exploring the latest components of NVIDIA DSX OS to automate infrastructure lifecycle management, and improve resiliency and reliability.

Connecting Design, Power and Cooling Across Europe’s AI Factory Ecosystem
NVIDIA’s industrial software, power and cooling partners are advancing Europe’s AI factory buildout with DSX reference designs, lifecycle digital twins and qualified equipment that connect facility infrastructure with accelerated computing.

Schneider Electric has developed power and cooling reference designs for NVIDIA Vera Rubin infrastructure and is working with AVEVA on digital twins spanning infrastructure design, construction and operations.
Procore is helping manage AI factory builds with its construction management platform, integrated with DSX Sim.
Siemens is using DSX Sim to simulate power, cooling and acoustics, while Dassault Systèmes and Vertiv are developing digital twin models of Vertiv’s OneCore infrastructure, enabling simulation and optimization through model-based systems engineering.
ABB is developing SimReady assets with NVIDIA DSX Sim, enabling engineers to evaluate source-to-rack architectures before construction while advancing 800 VDC development through its newly announced Infinitus Direct Current portfolio.

Partners are also delivering coordinated power and cooling infrastructure aligned with DSX reference designs. Trane Technologies and Eaton recently collaborated with NVIDIA to help boost data center efficiency and cut installation costs with an integrated design built for the NVIDIA Vera Rubin DSX AI Factory Reference Design, bringing together Eaton’s Beam platform and power infrastructure with Trane Continuum cooling and coordinated controls in a grid-to-chip architecture.

Trane Technologies has published seven thermal management system reference designs, including three 250-megawatt DSX-based cooling reference designs to support thermal infrastructure planning at scale.

Through the NVIDIA DSX Ready program, builders can select equipment qualified under applicable DSX categories. Trane Technologies’ LiquidStack GigaModular and Vertiv’s 2.3-megawatt CoolChip — both coolant distribution units — have qualified under their applicable categories, while Hitachi Energy’s battery energy storage system has earned NVIDIA DSX Ready BESS qualification.

For energy supply and grid integration, GE Vernova, Hitachi Energy and Siemens Energy are collaborating with NVIDIA on power infrastructure and digital twin initiatives that connect energy-system engineering and grid planning based on the facility’s requirements. Hitachi Energy is developing an integration between its energy management system and DSX Flex to optimize grid, generation and storage resources with workload demand.

Watch the GTC Berlin keynote from NVIDIA founder and CEO Jensen Huang and explore sessions.

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NVIDIA Introduces DSX POD AI Factories to Accelerate Europe’s Infrastructure Deployment

Wed, 21 Oct 2026 09:34:00 GMT

News Summary:

NVIDIA introduces DSX POD, a reference design for complete Vera Rubin AI factories built by partners in modular containers, integrated and validated before delivery.
Factory-built units reduce deployment time at a prepared site from six months to as little as 14 days, helping customers begin generating production tokens and earning revenue sooner.
A global ecosystem of computing and infrastructure partners are working with NVIDIA to deliver modular AI factories worldwide in early 2027.

GTC Berlin—NVIDIA today introduced DSX POD, a reference design for complete NVIDIA Vera Rubin AI factories built by partners inside modular containers, integrated and validated before delivery. The units arrive ready to connect out of the box to a prepared site’s power, cooling, networking and other supporting infrastructure, reducing deployment time from six months to as little as 14 days.

DSX POD moves the integration and installation of computing, networking, cabling, rack-level power and liquid cooling to the manufacturing facility, reducing the extensive planning, construction, specialized labor and logistics of a traditional onsite build. Factory-tested containers reduce exposure to component delays and costly, error-prone onsite work, creating a shorter path to model training and production inference so customers can begin generating tokens and earning revenue sooner.

“An AI factory creates value when it starts producing tokens — not when construction is complete,” said Jensen Huang, founder and CEO of NVIDIA. “With NVIDIA DSX POD, we’re bringing factory-built precision and speed to AI infrastructure construction — reducing deployment time from months to weeks so customers can scale capacity and bring revenue-generating production online faster.”

Factory-Built Infrastructure
NVIDIA DSX POD brings Vera Rubin systems together with the infrastructure needed to operate them in repeatable, factory-built, containerized designs that partners can manufacture and deliver at scale.

It carries forward the design philosophy of the broader NVIDIA DSX™ infrastructure platform, with a distinct architecture that integrates and validates systems in purpose-built containers before transport and deployment. Partners complete rack-to-rack cabling, wiring, piping and functional validation before shipment. This work takes place separately from site preparation, further shortening the time needed to bring new capacity online.

That earlier start to production is the link between deployment speed and economics. Time to first token marks when a new AI factory begins running models to serve production workloads, giving operators the opportunity to put their infrastructure to work for customers sooner.

Global Partner Ecosystem and Availability
NVIDIA is working with Anduril, Armada, Bull, Crusoe, DayOne, Dell Technologies, Delta, Eaton, Foxconn (Ingrasys), GIGABYTE, HPE, Lenovo, Pegatron, Quanta Cloud Technology (QCT), Schneider Electric, Vertiv and Wistron to deliver DSX POD AI factories worldwide in early 2027.

Watch the GTC Berlin keynote from Huang and explore sessions.

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GTC Berlin 2026: Live Updates From NVIDIA CEO Jensen Huang’s Keynote

Brian Caulfield — Wed, 21 Oct 2026 09:30:16 GMT

Founded in a tent near the Berlin Wall in 1980, the Tempodrom moved several times before settling near Anhalter Bahnhof in 2001. Its permanent home has since hosted concerts, galas and political events. Today, it hosts a different kind of spectacle. GTC Berlin runs three days, with more than 100 sessions on agentic AI, robotics, […]

European Leaders Turn to NVIDIA Vera CPUs to Build Local Infrastructure

Hannah Coutand — Tue, 20 Oct 2026 10:30:11 GMT

Nebius and Nscale are among global technology partners looking to NVIDIA Vera CPUs to build the next wave of infrastructure. Their momentum reflects rapid advancements in agentic computing. Agents do more than generate answers: they retrieve information, run software tools, execute code and evaluate results. Each step depends on fast CPU processing. Vera accelerates that […]

Spain-Based Startups Advance Regional Innovation With Barcelona Supercomputing Center

Tobias Halloran — Tue, 20 Oct 2026 05:00:00 GMT

The Barcelona Supercomputing Center (BSC)’s AI Factory Accelerator Programme, now in full operation following a pilot initiative, gives startups access to sovereign compute, technical support and training to support innovation across industries. Many of these companies are also members of the NVIDIA Inception program for cutting-edge startups — and as of today, access to some […]

Germany Wants to Lead the World in Industrial AI: How NVIDIA Will Help

NVIDIA Writers — Mon, 19 Oct 2026 19:27:08 GMT

In the cavernous hall of Kraftwerk, a former power station in Berlin, German Chancellor Friedrich Merz and NVIDIA founder and CEO Jensen Huang sat down to discuss Germany’s AI roadmap, and in particular, the industrial applications of AI. Huang opened by tracing NVIDIA’s longstanding relationship with German industry, beginning with gaming systems, workstations and automotive […]