Industrial AI isn’t slowing down. Germany is ready.

Following London Tech Week and GTC Paris at VivaTech, NVIDIA founder and CEO Jensen Huang’s European tour continued with a stop in Germany to discuss with Chancellor Friedrich Merz — pictured above — new partnerships poised to bring breakthrough innovations on the world’s first industrial AI cloud.

This AI factory, to be located in Germany and operated by Deutsche Telekom, will enable Europe’s industrial leaders to accelerate manufacturing applications including design, engineering, simulation, digital twins and robotics.

“In the era of AI, every manufacturer needs two factories: one for making things, and one for creating the intelligence that powers them,” said Jensen Huang, founder and CEO of NVIDIA. “By building Europe’s first industrial AI infrastructure, we’re enabling the region’s leading industrial companies to advance simulation-first, AI-driven manufacturing.”

“Europe’s technological future needs a sprint, not a stroll,” said Timotheus Höttges, CEO of Deutsche Telekom AG. “We must seize the opportunities of artificial intelligence now, revolutionize our industry and secure a leading position in the global technology competition. Our economic success depends on quick decisions and collaborative innovations.”

This AI infrastructure — Germany’s single largest AI deployment — is an important leap for the nation in establishing its own sovereign AI infrastructure and providing a launchpad to accelerate AI development and adoption across industries. In its first phase, it’ll feature 10,000 NVIDIA Blackwell GPUs — spanning NVIDIA DGX B200 systems and NVIDIA RTX PRO Servers — as well as NVIDIA networking and AI software.

NEURA Robotics, a Germany-based global pioneer in physical AI and cognitive robotics, will use the computing resources to power its state-of-the-art training centers for cognitive robots — a tangible example of how physical AI can evolve through powerful, connected infrastructure.

At this work’s core is the Neuraverse, a seamlessly networked robot ecosystem that allows robots to learn from each other across a wide range of industrial and domestic applications. This platform creates an app-store-like hub for robotic intelligence — for tasks like welding and ironing — enabling continuous development and deployment of robotic skills in real-world environments.

“Physical AI is the electricity of the future — it will power every machine on the planet,” said David Reger, founder and CEO of NEURA Robotics. “Through this initiative, we’re helping build the sovereign infrastructure Europe needs to lead in intelligent robotics and stay in control of its future.”

Critical to Germany’s competitiveness is AI technology development, including the expansion of data center capacity, according to a Deloitte study. This is strategically important because demand for data center capacity is expected to triple over the next five years to 5 gigawatts.

Driving Germany’s Industrial Ecosystem

Deutsche Telekom will operate the AI factory and provide AI cloud computing resources to Europe’s industrial ecosystem.

Customers will be able to run NVIDIA CUDA-X libraries, as well as NVIDIA RTX- and Omniverse-accelerated workloads from leading software providers such as Siemens, Ansys, Cadence and Rescale.

Many more stand to benefit. From the country’s robust small- and medium-sized businesses, known as the Mittelstand, to academia, research and major enterprises — the AI factory offers strategic technology leaps.

A Speedboat Toward AI Gigafactories

The industrial AI cloud will accelerate AI development and adoption from European manufacturers, driving simulation-first, AI-driven manufacturing practices and helping prepare for the country’s transition to AI gigafactories, the next step in Germany’s sovereign AI infrastructure journey.

The AI gigafactory initiative is a 100,000 GPU-powered program backed by the European Union, Germany and partners.

Poised to go online in 2027, it’ll provide state-of-the-art AI infrastructure that gives enterprises, startups, researchers and universities access to accelerated computing through the establishment and expansion of high-performance computing centers.

As of March, there are about 900 Germany-based members of the NVIDIA Inception program for cutting-edge startups, all of which will be eligible to access the AI resources.

NVIDIA offers learning courses through its Deep Learning Institute to promote education and certification in AI across the globe, and those resources are broadly available across Germany’s computing ecosystem to offer upskilling opportunities.

Additional European telcos are building AI infrastructure for regional enterprises to build and deploy agentic AI applications.

Learn more about the latest AI advancements by watching Huang’s GTC Paris keynote in replay.

Level up GeForce NOW experiences this summer with 40% off Performance Day Passes. Enjoy 24 hours of premium cloud gaming with RTX ON, delivering low latency and shorter wait times.

The hot deal comes just in time for the cloud’s highly anticipated launch of Dune: Awakening — a multiplayer survival game on a massive scale set on the unforgiving sands of Arrakis.

It’s perfect to pair with the nine games available this week, including the Frosthaven demo announced at Steam Next Fest.

Try Before You Buy

Level up to the cloud, no commitment required. For a limited time, grab a Performance Day Pass at a price that’s less than an ice cream sundae and experience premium GeForce NOW gaming for 24 hours.

With RTX ON, enjoy shorter wait times and lower latency for supported games, all powered by the cloud. Dive into popular games with upgraded visuals and smoother gameplay over free users, whether exploring vast open worlds or battling in fast-paced arenas.

Take the experience even further by applying the value of the Day Pass toward a six-month Performance membership during the limited-time summer sale. It’s the perfect way to try out premium cloud gaming before jumping into a longer-term membership.

Survive and Thrive

Dune: Awakening, a multiplayer survival game on a massive scale from Funcom, is set on an ever-changing desert planet called Arrakis. Whether braving colossal sandworms, battling for spice or forging alliances, gamers can experience the spectacle of Arrakis with all the benefits of GeForce NOW.

Manage hydration, temperature and exposure while contending with deadly sandworms, sandstorms and rival factions. Blend skills-based third-person action combat — featuring ranged and melee weapons, gadgets and abilities — with deep crafting, base building and resource management. Explore and engage in large-scale player vs. player and player vs. environment battles while vying for control over territory and the precious spice.

The spice is flowing — and so is the power of the cloud. Stream it on GeForce NOW without waiting for lengthy downloads or worrying about hardware requirements. Dune: Awakening is available for members to stream from anywhere with the power of NVIDIA RTX for ultra-smooth gameplay and stunning visuals, even on low-powered devices.

Chill Out

Experience the highly anticipated Frosthaven demo in the cloud during Steam Next Fest with GeForce NOW. For a limited time, dive into a preview of the game directly from the cloud — no high-end PC required.

Frosthaven — a dark fantasy tactical role-playing game from Snapshot Games and X-COM creator Julian Gollop — brings to life the board game of the same name. It features deep, turn-based combat, unique character classes, and single-player and online co-op modes.

Play the Frosthaven demo on virtually any device with GeForce NOW and experience the magic of gathering around a board game — now in the cloud. Enter the frozen north of Frosthaven, strategize with friends and dive into epic battles without the hassle of setup or cleanup. With GeForce NOW, game night is just a click away, wherever members are playing from.

Seize New Games

Rainbow Six Siege X, the biggest evolution in the game’s history, is now available with free access for new players. It introduces a new 6v6 “Dual Front” game mode, where teams attack and defend simultaneously with respawns and new strategic objectives. R6 Siege X also brings new and improved gameplay features — such as modernized maps with enhanced visuals and lighting, new destructible environmental elements, advanced rappel, smoother movement, an audio overhaul and a communication wheel for precise strategic plays, as well as weapon inspections to showcase gamers’ favorite cosmetics.

Look for the following games available to stream in the cloud this week:

• Frosthaven Demo (New release on Steam, June 9)
• Dune: Awakening (New release on Steam, June 10)
• MindsEye (New release on Steam, June 10)
• Kingdom Two Crowns (New release on Xbox, available on PC Game Pass, June 11)
• The Alters (New release on Steam and Xbox, available on PC Game Pass, June 13)
• Lost in Random: The Eternal Die (New release on Steam and Xbox, June 13, available on PC Game Pass, June 17)
• Firefighting Simulator – The Squad (Xbox, available on PC Game Pass)
• JDM: Japanese Drift Master (Steam)
• Hellslave (Steam)

What are you planning to play this weekend? Let us know on X or in the comments below.

Generative AI has reshaped how people create, imagine and interact with digital content.

As AI models continue to grow in capability and complexity, they require more VRAM, or video random access memory. The base Stable Diffusion 3.5 Large model, for example, uses over 18GB of VRAM — limiting the number of systems that can run it well.

By applying quantization to the model, noncritical layers can be removed or run with lower precision. NVIDIA GeForce RTX 40 Series and the Ada Lovelace generation of NVIDIA RTX PRO GPUs support FP8 quantization to help run these quantized models, and the latest-generation NVIDIA Blackwell GPUs also add support for FP4.

NVIDIA collaborated with Stability AI to quantize its latest model, Stable Diffusion (SD) 3.5 Large, to FP8 — reducing VRAM consumption by 40%. Further optimizations to SD3.5 Large and Medium with the NVIDIA TensorRT software development kit (SDK) double performance.

In addition, TensorRT has been reimagined for RTX AI PCs, combining its industry-leading performance with just-in-time (JIT), on-device engine building and an 8x smaller package size for seamless AI deployment to more than 100 million RTX AI PCs. TensorRT for RTX is now available as a standalone SDK for developers.

RTX-Accelerated AI

NVIDIA and Stability AI are boosting the performance and reducing the VRAM requirements of Stable Diffusion 3.5, one of the world’s most popular AI image models. With NVIDIA TensorRT acceleration and quantization, users can now generate and edit images faster and more efficiently on NVIDIA RTX GPUs.

To address the VRAM limitations of SD3.5 Large, the model was quantized with TensorRT to FP8, reducing the VRAM requirement by 40% to 11GB. This means five GeForce RTX 50 Series GPUs can run the model from memory instead of just one.

SD3.5 Large and Medium models were also optimized with TensorRT, an AI backend for taking full advantage of Tensor Cores. TensorRT optimizes a model’s weights and graph — the instructions on how to run a model — specifically for RTX GPUs.

Combined, FP8 TensorRT delivers a 2.3x performance boost on SD3.5 Large compared with running the original models in BF16 PyTorch, while using 40% less memory. And in SD3.5 Medium, BF16 TensorRT provides a 1.7x performance increase compared with BF16 PyTorch.

The optimized models are now available on Stability AI’s Hugging Face page.

NVIDIA and Stability AI are also collaborating to release SD3.5 as an NVIDIA NIM microservice, making it easier for creators and developers to access and deploy the model for a wide range of applications. The NIM microservice is expected to be released in July.

TensorRT for RTX SDK Released

Announced at Microsoft Build — and already available as part of the new Windows ML framework in preview — TensorRT for RTX is now available as a standalone SDK for developers.

Previously, developers needed to pre-generate and package TensorRT engines for each class of GPU — a process that would yield GPU-specific optimizations but required significant time.

With the new version of TensorRT, developers can create a generic TensorRT engine that’s optimized on device in seconds. This JIT compilation approach can be done in the background during installation or when they first use the feature.

The easy-to-integrate SDK is now 8x smaller and can be invoked through Windows ML — Microsoft’s new AI inference backend in Windows. Developers can download the new standalone SDK from the NVIDIA Developer page or test it in the Windows ML preview.

For more details, read this NVIDIA technical blog and this Microsoft Build recap.

Join NVIDIA at GTC Paris

At NVIDIA GTC Paris at VivaTech — Europe’s biggest startup and tech event — NVIDIA founder and CEO Jensen Huang yesterday delivered a keynote address on the latest breakthroughs in cloud AI infrastructure, agentic AI and physical AI. Watch a replay.

GTC Paris runs through Thursday, June 12, with hands-on demos and sessions led by industry leaders. Whether attending in person or joining online, there’s still plenty to explore at the event.

Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations. 

Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter.

Follow NVIDIA Workstation on LinkedIn and X. 

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At GTC Paris — held alongside VivaTech, Europe’s largest tech event — NVIDIA founder and CEO Jensen Huang delivered a clear message: Europe isn’t just adopting AI — it’s building it.

“We now have a new industry, an AI industry, and it’s now part of the new infrastructure, called intelligence infrastructure, that will be used by every country, every society,” Huang said, addressing an audience gathered online and at the iconic Dôme de Paris.

From exponential inference growth to quantum breakthroughs, and from infrastructure to industry, agentic AI to robotics, Huang outlined how the region is laying the groundwork for an AI-powered future.

A New Industrial Revolution

At the heart of this transformation, Huang explained, are systems like GB200 NVL72 — “one giant GPU” and NVIDIA’s most powerful AI platform yet — now in full production and powering everything from sovereign models to quantum computing.

“This machine was designed to be a thinking machine, a thinking machine, in the sense that it reasons, it plans, it spends a lot of time talking to itself,” Huang said, walking the audience through the size and scale of these machines and their performance.

There’s more coming, with Huang saying NVIDIA’s partners are now producing 1,000 GB200 systems a week, “and this is just the beginning.” He walked the audience through a range of available systems ranging from the tiny NVIDIA DGX Spark to rack-mounted RTX PRO Servers.

Huang explained that NVIDIA is working to help countries use technologies like these to build both AI infrastructure — services built for third parties to use and innovate on — and AI factories, which companies build for their own use, to generate revenue.

NVIDIA is partnering with European governments, telcos and cloud providers to deploy NVIDIA technologies across the region. NVIDIA is also expanding its network of technology centers across Europe — including new hubs in Finland, Germany, Spain, Italy and the U.K. — to accelerate skills development and quantum growth.

Quantum Meets Classical

Europe’s quantum ambitions just got a boost.

The NVIDIA CUDA-Q platform is live on Denmark’s Gefion supercomputer, opening new possibilities for hybrid AI and quantum engineering. In addition, Huang announced that CUDA-Q is now available on NVIDIA Grace Blackwell systems.

Across the continent, NVIDIA is partnering with supercomputing centers and quantum hardware builders to advance hybrid quantum-AI research and accelerate quantum error correction.

“Quantum computing is reaching an inflection point,” Huang said. “We are within reach of being able to apply quantum computing, quantum classical computing, in areas that can solve some interesting problems in the coming years.”

Sovereign Models, Smarter Agents

European developers want more control over their models. Enter NVIDIA Nemotron, designed to help build large language models tuned to local needs.

“And so now you know that you have access to an enhanced open model that is still open, that is top of the leader chart,” Huang said.

These models will be coming to Perplexity, a reasoning search engine, enabling secure, multilingual AI deployment across Europe.

“You can now ask and get questions answered in the language, in the culture, in the sensibility of your country,” Huang said.

Every company will build its own agents, Huang said. To help create those agents, Huang introduced a suite of agentic AI blueprints, including an Agentic AI Safety blueprint for enterprises and governments.

The new NVIDIA NeMo Agent toolkit and NVIDIA AI Blueprint for building data flywheels further accelerate the development of safe, high-performing AI agents.

To help deploy these agents, NVIDIA is partnering with European governments, telcos and cloud providers to deploy the DGX Cloud Lepton platform across the region, providing instant access to accelerated computing capacity.

“One model architecture, one deployment, and you can run it anywhere,” Huang said, adding that Lepton is now integrated with Hugging Face, giving developers direct access to global compute.

The Industrial Cloud Goes Live

AI isn’t just virtual. It’s powering physical systems, too, sparking a new industrial revolution.

“We’re working on industrial AI with one company after another,” Huang said, describing work to build digital twins based on the NVIDIA Omniverse platform with companies across the continent.

To further this work, Huang announced NVIDIA is launching the world’s first industrial AI cloud — to be built in Germany — to help Europe’s manufacturers simulate, automate and optimize at scale.

“Soon, everything that moves will be robotic,” Huang said. “And the car is the next one.”

NVIDIA DRIVE, NVIDIA’s full-stack AV platform, is now in production to accelerate the large-scale deployment of safe, intelligent transportation.

And to show what’s coming next, Huang was joined on stage by Grek, a pint-sized robot, as Huang talked about how NVIDIA partnered with DeepMind and Disney to build Newton, the world’s most advanced physics training engine for robotics.

The Next Wave

The next wave of AI has begun — and it’s exponential, Huang explained.

“We have physical robots, and we have information robots. We call them agents,” Huang said. “The technology necessary to teach a robot to manipulate, to simulate — and of course, the manifestation of an incredible robot — is now right in front of us.”

This new era of AI is being driven by a surge in inference workloads. “The number of people using inference has gone from 8 million to 800 million — 100x in just a couple of years,” Huang said.

To meet this demand, Huang emphasized the need for a new kind of computer: “We need a special computer designed for thinking, designed for reasoning. And that’s what Blackwell is — a thinking machine.”

These Blackwell-powered systems will live in a new class of data centers — AI factories — built to generate tokens, the raw material of modern intelligence.

“These AI factories are going to generate tokens,” Huang said, turning to Grek with a smile. “And these tokens are going to become your food, little Grek.”

With that, the keynote closed on a bold vision: a future powered by sovereign infrastructure, agentic AI, robotics — and exponential inference — all built in partnership with Europe.

Watch the NVIDIA GTC Paris keynote from Huang at VivaTech and explore GTC Paris sessions.

In a new effort to advance sovereign AI for European public service media, NVIDIA and the European Broadcasting Union (EBU) are working together to give the media industry access to high-quality and trusted cloud and AI technologies.

Announced at NVIDIA GTC Paris at VivaTech, NVIDIA’s collaboration with the EBU — the world’s leading alliance of public service media with more than 110 member organizations in 50+ countries, reaching an audience of over 1 billion — focuses on helping build sovereign AI and cloud frameworks, driving workforce development and cultivating an AI ecosystem to create a more equitable, accessible and resilient European media landscape.

The work will create better foundations for public service media to benefit from European cloud infrastructure and AI services that are exclusively governed by European policy, comply with European data protection and privacy rules, and embody European values.

Sovereign AI ensures nations can develop and deploy artificial intelligence using local infrastructure, datasets and expertise. By investing in it, European countries can preserve their cultural identity, enhance public trust and support innovation specific to their needs.

“We are proud to collaborate with NVIDIA to drive the development of sovereign AI and cloud services,” said Michael Eberhard, chief technology officer of public broadcaster ARD/SWR, and chair of the EBU Technical Committee. “By advancing these capabilities together, we’re helping ensure that powerful, compliant and accessible media services are made available to all EBU members — powering innovation, resilience and strategic autonomy across the board.”

Empowering Media Innovation in Europe

To support the development of sovereign AI technologies, NVIDIA and the EBU will establish frameworks that prioritize independence and public trust, helping ensure that AI serves the interests of Europeans while preserving the autonomy of media organizations.

Through this collaboration, NVIDIA and the EBU will develop hybrid cloud architectures designed to meet the highest standards of European public service media. The EBU will contribute its Dynamic Media Facility (DMF) and Media eXchange Layer (MXL) architecture, aiming to enable interoperability and scalability for workflows, as well as cost- and energy-efficient AI training and inference. Following open-source principles, this work aims to create an accessible, dynamic technology ecosystem.

The collaboration will also provide public service media companies with the tools to deliver personalized, contextually relevant services and content recommendation systems, with a focus on transparency, accountability and cultural identity. This will be realized through investment in sovereign cloud and AI infrastructure and software platforms such as NVIDIA AI Enterprise, custom foundation models, large language models trained with local data, and retrieval-augmented generation technologies.

As part of the collaboration, NVIDIA is also making available resources from its Deep Learning Institute, offering European media organizations comprehensive training programs to create an AI-ready workforce. This will support the EBU’s efforts to help ensure news integrity in the age of AI.

In addition, the EBU and its partners are investing in local data centers and cloud platforms that support sovereign technologies, such as NVIDIA GB200 Grace Blackwell Superchip, NVIDIA RTX PRO Servers, NVIDIA DGX Cloud and NVIDIA Holoscan for Media — helping members of the union achieve secure and cost- and energy-efficient AI training, while promoting AI research and development.

Partnering With Public Service Media for Sovereign Cloud and AI

Collaboration within the media sector is essential for the development and application of comprehensive standards and best practices that ensure the creation and deployment of sovereign European cloud and AI.

By engaging with independent software vendors, data center providers, cloud service providers and original equipment manufacturers, NVIDIA and the EBU aim to create a unified approach to sovereign cloud and AI.

This work will also facilitate discussions between the cloud and AI industry and European regulators, helping ensure the development of practical solutions that benefit both the general public and media organizations.

“Building sovereign cloud and AI capabilities based on EBU’s Dynamic Media Facility and Media eXchange Layer architecture requires strong cross-industry collaboration,” said Antonio Arcidiacono, chief technology and innovation officer at the EBU. “By collaborating with NVIDIA, as well as a broad ecosystem of media technology partners, we are fostering a shared foundation for trust, innovation and resilience that supports the growth of European media.”

Learn more about the EBU.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. 

Telecom companies last year spent nearly $295 billion in capital expenditures and over $1 trillion in operating expenditures.

These large expenses are due in part to laborious manual processes that telcos face when operating networks that require continuous optimizations.

For example, telcos must constantly tune network parameters for tasks — such as transferring calls from one network to another or distributing network traffic across multiple servers — based on the time of day, user behavior, mobility and traffic type.

These factors directly affect network performance, user experience and energy consumption.

To automate these optimization processes and save costs for telcos across the globe, NVIDIA today unveiled at GTC Paris its first AI Blueprint for telco network configuration.

At the blueprint’s core are customized large language models trained specifically on telco network data — as well as the full technical and operational architecture for turning the LLMs into an autonomous, goal-driven AI agent for telcos.

Automate Network Configuration With the AI Blueprint

NVIDIA AI Blueprints — available on build.nvidia.com — are customizable AI workflow examples. They include reference code, documentation and deployment tools that show enterprise developers how to deliver business value with NVIDIA NIM microservices.

The AI Blueprint for telco network configuration — built with BubbleRAN 5G solutions and datasets — enables developers, network engineers and telecom providers to automatically optimize the configuration of network parameters using agentic AI.

This can streamline operations, reduce costs and significantly improve service quality by embedding continuous learning and adaptability directly into network infrastructures.

Traditionally, network configurations required manual intervention or followed rigid rules to adapt to dynamic network conditions. These approaches limited adaptability and increased operational complexities, costs and inefficiencies.

The new blueprint helps shift telco operations from relying on static, rules-based systems to operations based on dynamic, AI-driven automation. It enables developers to build advanced, telco-specific AI agents that make real-time, intelligent decisions and autonomously balance trade-offs — such as network speed versus interference, or energy savings versus utilization — without human input.

Powered and Deployed by Industry Leaders

Trained on 5G data generated by BubbleRAN, and deployed on the BubbleRAN 5G O-RAN platform, the blueprint provides telcos with insight on how to set various parameters to reach performance goals, like achieving a certain bitrate while choosing an acceptable signal-to-noise ratio — a measure that impacts voice quality and thus user experience.

With the new AI Blueprint, network engineers can confidently set initial parameter values and update them as demanded by continuous network changes.

Norway-based Telenor Group, which serves over 200 million customers globally, is the first telco to integrate the AI Blueprint for telco network configuration as part of its initiative to deploy intelligent, autonomous networks that meet the performance and agility demands of 5G and beyond.

“The blueprint is helping us address configuration challenges and enhance quality of service during network installation,” said Knut Fjellheim, chief technology innovation officer at Telenor Maritime. “Implementing it is part of our push toward network automation and follows the successful deployment of agentic AI for real-time network slicing in a private 5G maritime use case.”

Industry Partners Deploy Other NVIDIA-Powered Autonomous Network Technologies

The AI Blueprint for telco network configuration is just one of many announcements at NVIDIA GTC Paris showcasing how the telecom industry is using agentic AI to make autonomous networks a reality.

Beyond the blueprint, leading telecom companies and solutions providers are tapping into NVIDIA accelerated computing, software and microservices to provide breakthrough innovations poised to vastly improve networks and communications services — accelerating the progress to autonomous networks and improving customer experiences.

NTT DATA is powering its agentic platform for telcos with NVIDIA accelerated compute and the NVIDIA AI Enterprise software platform. Its first agentic use case is focused on network alarms management, where NVIDIA NIM microservices help automate and power observability, troubleshooting, anomaly detection and resolution with closed loop ticketing.

Tata Consultancy Services is delivering agentic AI solutions for telcos built on NVIDIA DGX Cloud and using NVIDIA AI Enterprise to develop, fine-tune and integrate large telco models into AI agent workflows. These range from billing and revenue assurance, autonomous network management to hybrid edge-cloud distributed inference.

For example, the company’s anomaly management agentic AI model includes real-time detection and resolution of network anomalies and service performance optimization. This increases business agility and improves operational efficiencies by up to 40% by eliminating human intensive toils, overheads and cross-departmental silos.

Prodapt has introduced an autonomous operations workflow for networks, powered by NVIDIA AI Enterprise, that offers agentic AI capabilities to support autonomous telecom networks. AI agents can autonomously monitor networks, detect anomalies in real time, initiate diagnostics, analyze root causes of issues using historical data and correlation techniques, automatically execute corrective actions, and generate, enrich and assign incident tickets through integrated ticketing systems.

Accenture announced its new portfolio of agentic AI solutions for telecommunications through its AI Refinery platform, built on NVIDIA AI Enterprise software and accelerated computing.

The first available solution, the NOC Agentic App, boosts network operations center tasks by using a generative AI-driven, nonlinear agentic framework to automate processes such as incident and fault management, root cause analysis and configuration planning. Using the Llama 3.1 70B NVIDIA NIM microservice and the AI Refinery Distiller Framework, the NOC Agentic App orchestrates networks of intelligent agents for faster, more efficient decision-making.

Infosys is announcing its agentic autonomous operations platform, called Infosys Smart Network Assurance (ISNA), designed to accelerate telecom operators’ journeys toward fully autonomous network operations.

ISNA helps address long-standing operational challenges for telcos — such as limited automation and high average time to repair — with an integrated, AI-driven platform that reduces operational costs by up to 40% and shortens fault resolution times by up to 30%. NVIDIA NIM and NeMo microservices enhance the platform’s reasoning and hallucination-detection capabilities, reduce latency and increase accuracy.

Get started with the new blueprint today.

Learn more about the latest AI advancements for telecom and other industries at NVIDIA GTC Paris, running through Thursday, June 12, at VivaTech, including a keynote from NVIDIA founder and CEO Jensen Huang and a special address from Ronnie Vasishta, senior vice president of telecom at NVIDIA. Plus, hear from industry leaders in a panel session with Orange, Swisscom, Telenor and NVIDIA.

Urban populations are expected to double by 2050, which means around 2.5 billion people could be added to urban areas by the middle of the century, driving the need for more sustainable urban planning and public services. Cities across the globe are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions.

Building a digital twin of a city and testing smart city AI agents within it, however, is a complex and resource-intensive endeavor, fraught with technical and operational challenges.

To address those challenges, NVIDIA today announced the NVIDIA Omniverse Blueprint for smart city AI, a reference framework that combines the NVIDIA Omniverse, Cosmos, NeMo and Metropolis platforms to bring the benefits of physical AI to entire cities and their critical infrastructure.

Using the blueprint, developers can build simulation-ready, or SimReady, photorealistic digital twins of cities to build and test AI agents that can help monitor and optimize city operations.

Leading companies including XXII, AVES Reality, Akila, Blyncsy, Bentley, Cesium, K2K, Linker Vision, Milestone Systems, Nebius, SNCF Gares&Connexions, Trimble and Younite AI are among the first to use the new blueprint.

NVIDIA Omniverse Blueprint for Smart City AI 

The NVIDIA Omniverse Blueprint for smart city AI provides the complete software stack needed to accelerate the development and testing of AI agents in physically accurate digital twins of cities. It includes:

• NVIDIA Omniverse to build physically accurate digital twins and run simulations at city scale.
• NVIDIA Cosmos to generate synthetic data at scale for post-training AI models.
• NVIDIA NeMo to curate high-quality data and use that data to train and fine-tune vision language models (VLMs) and large language models.
• NVIDIA Metropolis to build and deploy video analytics AI agents based on the NVIDIA AI Blueprint for video search and summarization (VSS), helping process vast amounts of video data and provide critical insights to optimize business processes.

The blueprint workflow comprises three key steps. First, developers create a SimReady digital twin of locations and facilities using aerial, satellite or map data with Omniverse and Cosmos. Second, they can train and fine-tune AI models, like computer vision models and VLMs, using NVIDIA TAO and NeMo Curator to improve accuracy for vision AI use cases​. Finally, real-time AI agents powered by these customized models are deployed to alert, summarize and query camera and sensor data using the Metropolis VSS blueprint.

NVIDIA Partner Ecosystem Powers Smart Cities Worldwide

The blueprint for smart city AI enables a large ecosystem of partners to use a single workflow to build and activate digital twins for smart city use cases, tapping into a combination of NVIDIA’s technologies and their own.

SNCF Gares&Connexions, which operates a network of 3,000 train stations across France and Monaco, has deployed a digital twin and AI agents to enable real-time operational monitoring, emergency response simulations and infrastructure upgrade planning.

This helps each station analyze operational data such as energy and water use, and enables predictive maintenance capabilities, automated reporting and GDPR-compliant video analytics for incident detection and crowd management.

Powered by Omniverse, Metropolis and solutions from ecosystem partners Akila and XXII, SNCF Gares&Connexions’ physical AI deployment at the Monaco-Monte-Carlo and Marseille stations has helped SNCF Gares&Connexions achieve a 100% on-time preventive maintenance completion rate, a 50% reduction in downtime and issue response time, and a 20% reduction in energy consumption.

The city of Palermo in Sicily is using AI agents and digital twins from its partner K2K to improve public health and safety by helping city operators process and analyze footage from over 1,000 public video streams at a rate of nearly 50 billion pixels per second.

Tapped by Sicily, K2K’s AI agents — built with the NVIDIA AI Blueprint for VSS and cloud solutions from Nebius — can interpret and act on video data to provide real-time alerts on public events.

To accurately predict and resolve traffic incidents, K2K is generating synthetic data with Cosmos world foundation models to simulate different driving conditions. Then, K2K uses the data to fine-tune the VLMs powering the AI agents with NeMo Curator. These simulations enable K2K’s AI agents to create over 100,000 predictions per second.

Milestone Systems — in collaboration with NVIDIA and European cities — has launched Project Hafnia, an initiative to build an anonymized, ethically sourced video data platform for cities to develop and train AI models and applications while maintaining regulatory compliance.

Using a combination of Cosmos and NeMo Curator on NVIDIA DGX Cloud and Nebius’ sovereign European cloud infrastructure, Project Hafnia scales up and enables European-compliant training and fine-tuning of video-centric AI models, including VLMs, for a variety of smart city use cases.

The project’s initial rollout, taking place in Genoa, Italy, features one of the world’s first VLM models for intelligent transportation systems.

Linker Vision was among the first to partner with NVIDIA to deploy smart city digital twins and AI agents for Kaohsiung City, Taiwan — powered by Omniverse, Cosmos and Metropolis. Linker Vision worked with AVES Reality, a digital twin company, to bring aerial imagery of cities and infrastructure into 3D geometry and ultimately into SimReady Omniverse digital twins.

Linker Vision’s AI-powered application then built, trained and tested visual AI agents in a digital twin before deployment in the physical city. Now, it’s scaling to analyze 50,000 video streams in real time with generative AI to understand and narrate complex urban events like floods and traffic accidents. Linker Vision delivers timely insights to a dozen city departments through a single integrated AI-powered platform, breaking silos and reducing incident response times by up to 80%.

Bentley Systems is joining the effort to bring physical AI to cities with the NVIDIA blueprint. Cesium, the open 3D geospatial platform, provides the foundation for visualizing, analyzing and managing infrastructure projects and ports digital twins to Omniverse. The company’s AI platform Blyncsy uses synthetic data generation and Metropolis to analyze road conditions and improve maintenance.

Trimble, a global technology company that enables essential industries including construction, geospatial and transportation, is exploring ways to integrate components of the Omniverse blueprint into its reality capture workflows and Trimble Connect digital twin platform for surveying and mapping applications for smart cities.

Younite AI, a developer of AI and 3D digital twin solutions, is adopting the blueprint to accelerate its development pipeline, enabling the company to quickly move from operational digital twins to large-scale urban simulations, improve synthetic data generation, integrate real-time IoT sensor data and deploy AI agents.

Learn more about the NVIDIA Omniverse Blueprint for smart city AI by attending this GTC Paris session or watching the on-demand video after the event. Sign up to be notified when the blueprint is available.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

AI is packing and shipping efficiency for the retail and consumer packaged goods (CPG) industries, with a majority of surveyed companies in the space reporting the technology is increasing revenue and reducing operational costs.

Global brands are reimagining every facet of their businesses with AI, from how products are designed and manufactured to how they’re marketed, shipped and experienced in-store and online.

At NVIDIA GTC Paris at VivaTech, industry leaders including L’Oréal, LVMH and Nestlé shared how they’re using tools like AI agents and physical AI — powered by NVIDIA AI and simulation technologies — across every step of the product lifecycle to enhance operations and experiences for partners, customers and employees.

3D Digital Twins and AI Transform Marketing, Advertising and Product Design

The meeting of generative AI and 3D product digital twins results in unlimited creative potential.

Nestlé, the world’s largest food and beverage company, today announced a collaboration with NVIDIA and Accenture to launch a new, AI-powered in-house service that will create high-quality product content at scale for e-commerce and digital media channels.

The new content service, based on digital twins powered by the NVIDIA Omniverse platform, creates exact 3D virtual replicas of physical products. Product packaging can be adjusted or localized digitally, enabling seamless integration into various environments, such as seasonal campaigns or channel-specific formats. This means that new creative content can be generated without having to constantly reshoot from scratch.

The service is developed in partnership with Accenture Song, using Accenture AI Refinery built on NVIDIA Omniverse for advanced digital twin creation. It uses NVIDIA AI Enterprise for generative AI, hosted on Microsoft Azure for robust cloud infrastructure.

Nestlé already has a baseline of 4,000 3D digital products — mainly for global brands — with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands.

LVMH, the world’s leading luxury goods company, home to 75 distinguished maisons, is bringing 3D digital twins to its content production processes through its wine and spirits division, Moët Hennessy.

The group partnered with content configuration engine Grip to develop a solution using the NVIDIA Omniverse platform, which enables the creation of 3D digital twins that power content variation production. With Grip’s solution, Moët Hennessy teams can quickly generate digital marketing assets and experiences to promote luxury products at scale.

The initiative, led by Capucine Lafarge and Chloé Fournier, has been recognized by LVMH as a leading approach to scaling content creation.

L’Oréal Gives Marketing and Online Shopping an AI Makeover

Innovation starts at the drawing board. Today, that board is digital — and it’s powered by AI.

L’Oréal Groupe, the world’s leading beauty player, announced its collaboration with NVIDIA today. Through this collaboration, L’Oréal and its partner ecosystem will leverage the NVIDIA AI Enterprise platform to transform its consumer beauty experiences, marketing and advertising content pipelines.

“AI doesn’t think with the same constraints as a human being. That opens new avenues for creativity,” said Anne Machet, global head of content and entertainment at L’Oréal. “Generative AI enables our teams and partner agencies to explore creative possibilities.”

CreAItech, L’Oréal’s generative AI content platform, is augmenting the creativity of marketing and content teams. Combining a modular ecosystem of models, expertise, technologies and partners — including NVIDIA — CreAltech empowers marketers to generate thousands of unique, on-brand images, videos and lines of text for diverse platforms and global audiences.

The solution empowers L’Oréal’s marketing teams to quickly iterate on campaigns that improve consumer engagement across social media, e-commerce content and influencer marketing — driving higher conversion rates.

Noli.com, the first AI-powered multi-brand marketplace startup founded and backed by the  L’Oréal Groupe, is reinventing how people discover and shop for beauty products.

Noli’s AI Beauty Matchmaker experience uses L’Oréal Groupe’s century-long expertise in beauty, including its extensive knowledge of beauty science, beauty tech and consumer insights, built from over 1 million skin data points and analysis of thousands of product formulations. It gives users a BeautyDNA profile with expert-level guidance and personalized product recommendations for skincare and haircare.

“Beauty shoppers are often overwhelmed by choice and struggling to find the products that are right for them,” said Amos Susskind, founder and CEO of Noli. “By applying the latest AI models accelerated by NVIDIA and Accenture to the unparalleled knowledge base and expertise of the L’Oréal Groupe, we can provide hyper-personalized, explainable recommendations to our users.” 

The Accenture AI Refinery, powered by NVIDIA AI Enterprise, will provide the platform for Noli to experiment and scale. Noli’s new agent models will use NVIDIA NIM and NVIDIA NeMo microservices, including NeMo Retriever, running on Microsoft Azure.

Rapid Innovation With the NVIDIA Partner Ecosystem

NVIDIA’s ecosystem of solution provider partners empowers retail and CPG companies to innovate faster, personalize customer experiences, and optimize operations with NVIDIA accelerated computing and AI.

Global digital agency Monks is reshaping the landscape of AI-driven marketing, creative production and enterprise transformation. At the heart of their innovation lies the Monks.Flow platform that enhances both the speed and sophistication of creative workflows through NVIDIA Omniverse, NVIDIA NIM microservices and Triton Inference Server for lightning-fast inference.

AI image solutions provider Bria is helping retail giants like Lidl and L’Oreal to enhance marketing asset creation. Bria AI transforms static product images into compelling, dynamic advertisements that can be quickly scaled for use across any marketing need.

The company’s generative AI platform uses NVIDIA Triton Inference Server software and the NVIDIA TensorRT software development kit for accelerated inference, as well as NVIDIA NIM and NeMo microservices for quick image generation at scale.

Physical AI Brings Acceleration to Supply Chain and Logistics

AI’s impact extends far beyond the digital world. Physical AI-powered warehousing robots, for example, are helping maximize efficiency in retail supply chain operations. Four in five retail companies have reported that AI has helped reduce supply chain operational costs, with 25% reporting cost reductions of at least 10%.

Technology providers Lyric, KoiReader Technologies and Exotec are tackling the challenges of integrating AI into complex warehouse environments.

Lyric is using the NVIDIA cuOpt GPU-accelerated solver for warehouse network planning and route optimization, and is collaborating with NVIDIA to apply the technology to broader supply chain decision-making problems. KoiReader Technologies is tapping the NVIDIA Metropolis stack for its computer vision solutions within logistics, supply chain and manufacturing environments using the KoiVision Platform. And Exotec is using NVIDIA CUDA libraries and the NVIDIA JetPack software development kit for embedded robotic systems in warehouse and distribution centers.

From real-time robotics orchestration to predictive maintenance, these solutions are delivering impact on uptime, throughput and cost savings for supply chain operations.

Learn more by joining a follow-up discussion on digital twins and AI-powered creativity with Microsoft, Nestlé, Accenture and NVIDIA at Cannes Lions on Monday, June 16.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

In the face of growing labor shortages and need for sustainability, European manufacturers are racing to reinvent their processes to become software-defined and AI-driven.

To achieve this, robot developers and industrial digitalization solution providers are working with NVIDIA to build safe, AI-driven robots and industrial technologies to drive modern, sustainable manufacturing.

At NVIDIA GTC Paris at VivaTech, Europe’s leading robotics companies including Agile Robots, Extend Robotics, Humanoid, idealworks, Neura Robotics, SICK, Universal Robots, Vorwerk and Wandelbots are showcasing their latest AI-driven robots and automation breakthroughs, all accelerated by NVIDIA technologies. In addition, NVIDIA is releasing new models and tools to support the entire robotics ecosystem.

NVIDIA Releases Tools for Accelerating Robot Development and Safety

NVIDIA Isaac GR00T N1.5, an open foundation model for humanoid robot reasoning and skills, is now available for download on Hugging Face. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. The NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 open-source robotics simulation and learning frameworks, optimized for NVIDIA RTX PRO 6000 workstations, are available on GitHub for developer preview.

In addition, NVIDIA announced that NVIDIA Halos — a full-stack, comprehensive safety system that unifies hardware architecture, AI models, software, tools and services — now expands to robotics, promoting safety across the entire development lifecycle of AI-driven robots.

The NVIDIA Halos AI Systems Inspection Lab has earned accreditation from the ANSI National Accreditation Board (ANAB) to perform inspections across functional safety for robotics, in addition to automotive vehicles.

“NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines — from automotive to robotics — can meet the highest benchmarks for functional safety,” said R. Douglas Leonard Jr., executive director of ANAB.

Arcbest, Advantech, Bluewhite, Boston Dynamics, FORT, Inxpect, KION, NexCobot — a NEXCOM company, and Synapticon are among the first robotics companies to join the Halos Inspection Lab, ensuring their products meet NVIDIA safety and cybersecurity requirements.

To support robotics leaders in strengthening safety across the entire development lifecycle of AI-driven robots, Halos will now provide:

• Safety extension packages for the NVIDIA IGX platform, enabling manufacturers to easily program safety functions into their robots, supported by TÜV Rheinland’s inspection of NVIDIA IGX.
• A robotic safety platform, which includes IGX and NVIDIA Holoscan Sensor Bridge for a unified approach to designing sensor-to-compute architecture with built-in AI safety.
• An outside-in safety AI inspector — an AI-powered agent for monitoring robot operations, helping improve worker safety.

Europe’s Robotics Ecosystem Builds on NVIDIA’s Three Computers

Europe’s leading robotics developers and solution providers are integrating the NVIDIA Isaac robotics platform to train, simulate and deploy robots across different embodiments.

Agile Robots is post-training the GR00T N1 model in Isaac Lab to train its dual-arm manipulator robots, which run on NVIDIA Jetson hardware, to execute a variety of tasks in industrial environments.

Meanwhile, idealworks has adopted the Mega NVIDIA Omniverse Blueprint for robotic fleet simulation to extend the blueprint’s capabilities to humanoids. Building on the VDA 5050 framework, idealworks contributes to the development of guidance that supports tasks uniquely enabled by humanoid robots, such as picking, moving and placing objects.

Neura Robotics is integrating NVIDIA Isaac to further enhance its robot development workflows. The company is using GR00T-Mimic to post-train the Isaac GR00T N1 robot foundation model for its service robot MiPA. Neura is also collaborating with SAP and NVIDIA to integrate SAP’s Joule agents with its robots, using the Mega NVIDIA Omniverse Blueprint to simulate and refine robot behavior in complex, realistic operational scenarios before deployment.

Vorwerk is using NVIDIA technologies to power its AI-driven collaborative robots. The company is post-training GR00T N1 models in Isaac Lab with its custom synthetic data pipeline, which is built on Isaac GR00T-Mimic and powered by the NVIDIA Omniverse platform. The enhanced models are then deployed on NVIDIA Jetson AGX, Jetson Orin or Jetson Thor modules for advanced, real-time home robotics.

Humanoid is using NVIDIA’s full robotics stack, including Isaac Sim and Isaac Lab, to cut its prototyping time down by six weeks. The company is training its vision language action models on NVIDIA DGX B200 systems to boost the cognitive abilities of its robots, allowing them to operate autonomously in complex environments using Jetson Thor onboard computing.

Universal Robots is introducing UR15, its fastest collaborative robot yet, to the European market. Using UR’s AI Accelerator — developed on NVIDIA Isaac’s CUDA-accelerated libraries and AI models, as well as NVIDIA Jetson AGX Orin — manufacturers can build AI applications to embed intelligence into the company’s new cobots.

Wandelbots is showcasing its NOVA Operating System, now integrated with Omniverse, to simulate, validate and optimize robotic behaviors virtually before deploying them to physical robots. Wandelbots also announced a collaboration with EY and EDAG to offer manufacturers a scalable automation platform on Omniverse that speeds up the transition from proof of concept to full-scale deployment.

Extend Robotics is using the Isaac GR00T platform to enable customers to control and train robots for industrial tasks like visual inspection and handling radioactive materials. The company’s Advanced Mechanics Assistance System lets users collect demonstration data and generate diverse synthetic datasets with NVIDIA GR00T-Mimic and GR00T-Gen to train the GR00T N1 foundation model.

SICK is enhancing its autonomous perception solutions by integrating new certified sensor models — as well as 2D and 3D lidars, safety scanners and cameras — into NVIDIA Isaac Sim. This enables engineers to virtually design, test and validate machines using SICK’s sensing models within Omniverse, supporting processes spanning product development to large-scale robotic fleet management.

Toyota Material Handling Europe is working with SoftServe to simulate its autonomous mobile robots working alongside human workers, using the Mega NVIDIA Omniverse Blueprint. Toyota Material Handling Europe is testing and simulating a multitude of traffic scenarios — allowing the company to refine its AI algorithms before real-world deployment.

NVIDIA’s partner ecosystem is enabling European industries to tap into intelligent, AI-powered robotics. By harnessing advanced simulation, digital twins and generative AI, manufacturers are rapidly developing and deploying safe, adaptable robot fleets that address labor shortages, boost sustainability and drive operational efficiency.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

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NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognition (CVPR) conference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop.

This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR.

The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehicle (AV) simulation framework.

The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs.

Generating Safe and Adaptive Driving Trajectories

Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically.

Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research.

The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoring (GTRS) method, which generates a variety of trajectories and progressively filters out the best one.

GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories.

This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions.

NVIDIA Automotive Research at CVPR 

More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more.

In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+.

The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs:

• Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion Models (Read more in this blog.)
• FoundationStereo: Zero-Shot Stereo Matching (Best Paper nominee)
• Zero-Shot Monocular Scene Flow Estimation in the Wild (Best Paper nominee)
• Difix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models (Best Paper nominee)
• 3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
• Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
• Zero-Shot 4D Lidar Panoptic Segmentation
• NVILA: Efficient Frontier Visual Language Models
• RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models
• OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning

Explore automotive workshops and tutorials at CVPR, including:

• Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA
• Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA
• Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe
• Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA
• Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe
• Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone
• LatinX in CV Workshop, featuring Leal-Taixe
• Workshop on Exploring the Next Generation of Data, featuring Alvarez
• Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA
• Continuous Data Cycle via Foundation Models, led by NVIDIA
• Distillation of Foundation Models for Autonomous Driving, led by NVIDIA

Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang.

Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics.

The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model.

Using NVIDIA platforms, tools and libraries, European telecommunications institutions are accelerating efforts to develop 6G — the next generation of cellular technology, with AI woven in from the start.

6G will be an AI-native platform that fosters innovation, enables new services, enhances customer experiences and promotes sustainability. Since the launch of the NVIDIA 6G Developer Program last year, over 200 telecommunications organizations across 30+ European countries have used NVIDIA technologies to accelerate their work.

In the U.K., the Department for Science, Innovation and Technology announced a collaboration with NVIDIA to promote the nation’s goals for AI development in telecom. Leading U.K. universities will gain access to a suite of powerful AI tools, 6G research platforms and training resources — including NVIDIA AI Aerial and Sionna — to bolster research and development on AI-native wireless networks.

“This collaboration between the U.K. government and NVIDIA marks a pivotal step in our ambition to make the U.K. a global leader in the development of advanced connectivity technologies,” said Sir Chris Bryant, minister of state for data protection and telecoms of the U.K.“The use of AI in telecoms will make our networks more intelligent, efficient and reliable, and by equipping our world leading academia and researchers with cutting-edge AI tools and training, we will accelerate innovation that improves the everyday digital experience for people across the country.”

In Finland, the University of Oulu is conducting research for wireless channel estimation with a real-time network digital twin that taps into synthetic lidar data, using the NVIDIA Isaac Sim reference application for robotics simulation.

The project enables advanced development of AI and machine learning features for integrated sensing and communications, or ISAC, a capability that allows the network itself to act as a sensor of the physical world to enhance operations. The project also enables modeling of the 6G access system.

France-based OpenAirInterface (OAI) and NVIDIA are collaborating to advance AI-native wireless networks by integrating OAI’s open-source virtualized and open RAN stack with the GPU-accelerated NVIDIA AI Aerial– and NVIDIA Sionna-based systems. OAI provides the layer 2+ software for Aerial Commercial Testbed and full-stack O-RAN software for Sionna Research Kit, enabling researchers to innovate in 5G and 6G radio access networks using AI and machine learning at every layer.

In Germany, Fraunhofer HHI is conducting groundbreaking research on neuromorphic wireless cognition for robotic control using the NVIDIA AI Aerial suite of accelerated computing platforms and software for designing, simulating and operating wireless networks.

The research involves an event-based camera that senses and captures robotic movements, and forwards the information to a neuromorphic processor. Then, neural network models are used for decoding and gesture recognition to boost transmission over the base station, enhancing the quality of the connection.

Rohde & Schwarz, also based in Germany, is helping set new benchmarks in AI-powered wireless communication research with its latest milestone in neural receiver design and testing.

Showcased in March at Mobile World Congress in Barcelona, Rohde & Schwarz’s innovative proof of concept — developed in collaboration with NVIDIA — integrates advanced digital twin technology and high-fidelity ray tracing to create a robust framework for testing 5G-Advanced and 6G neural receivers under real-world radio environments. Tapping into simulations built with the NVIDIA Sionna library, this initiative paves the way for more efficient, accurate and reliable testing of next-generation receiver architectures.

ETH Zurich and NVIDIA are working on 6G projects related to the performance of AI-native 6G networks. This includes a new machine learning-based architecture, called DUIDD (Deep Unfolded Iterative Detector Decoder), which was developed using NVIDIA Sionna to improve the amount of data a base station can transmit or receive using information learned from its local environment. DUIDD is expected to be implemented on the real-time, over-the-air NVIDIA AI Aerial commercial testbed, dubbed ARC-OTA.

Other projects include a new approach to machine learning-assisted model training, machine learning approaches for positioning mobile devices using channel charting, and device identification based on their radio frequency signature, developed with NVIDIA 6G research tools.

The University of Leeds is developing an agentic architecture for integrating large language models into RAN operations to realize scalable, intelligent orchestration. The research involves creating standardized frameworks for deploying agent-based architectures, establishing key performance indicators for benchmarking performance and building templates for new agents to enhance performance and reduce operational costs.

Europe Key to Developing AI-Native 6G

Europe’s role in wireless networks dates back to the 1987 development of the Global System for Mobile Communications, or GSM, a widely used standard for digital cellular communication.

Today, the European Union continues to drive innovation through substantial governmental support and flagship initiatives such as the Smart Networks and Services Joint Undertaking, 6G SNS and the 6G Flagship project. These programs unite universities, research institutions and industry to create next-generation AI-native networks, pioneering work in AI integration, sustainability and security while educating future industry experts.

Major European telecommunications vendors play a vital role in shaping the vision and standards for 6G through their leadership and participation in major research consortia.

NVIDIA Technologies for AI-Native 6G Research and Development

For these European 6G researchers, the NVIDIA 6G research portfolio provides a three-computer solution for 1) developing and training AI algorithms, 2) simulating them and 3) deploying them into wireless stacks for AI-native 6G.

The portfolio includes accelerated compute infrastructure, as well as software libraries, including NVIDIA AI Aerial, Sionna and NVIDIA CUDA-X for accelerating workloads. NVIDIA provides the world’s only 6G research portfolio with open-source and source-code offerings, cloud and on-premises options, and full-stack systems or components-level options for researchers to choose the best tool for their mission.

In addition, the NVIDIA Deep Learning Institute provides training on skills essential to 6G development, such as simulating physical environments.

The NVIDIA 6G Developer Program offers early access to advanced tools, technical support and a global community of innovators. So far, more than 2,000 researchers across 85 countries have joined the program, leading to over 190,000 downloads of NVIDIA tools and 350+ citations in technical papers and journals.

Learn more about the latest AI advancements for telecom and other industries at NVIDIA GTC Paris, running June 11-14 at VivaTech, including a special address from Ronnie Vasishta, senior vice president of telecom at NVIDIA.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech 2025, and explore GTC Paris sessions.

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NVIDIA Research has developed an AI light switch for videos that can turn daytime scenes into nightscapes, transform sunny afternoons to cloudy days and tone down harsh fluorescent lighting into soft, natural illumination.

Called DiffusionRenderer, it’s a new technique for neural rendering — a process that uses AI to approximate how light behaves in the real world. It brings together two traditionally distinct processes — inverse rendering and forward rendering — in a unified neural rendering engine that outperforms state-of-the-art methods.

DiffusionRenderer provides a framework for video lighting control, editing and synthetic data augmentation, making it a powerful tool for creative industries and physical AI development.

Creators in advertising, film and game development could use applications based on DiffusionRenderer to add, remove and edit lighting in real-world or AI-generated videos. Physical AI developers could use it to augment synthetic datasets with a greater diversity of lighting conditions to train models for robotics and autonomous vehicles (AVs).

DiffusionRenderer is one of over 60 NVIDIA papers accepted to the Computer Vision and Pattern Recognition (CVPR) conference, taking place June 11-15 in Nashville, Tennessee.

Creating AI That Delights

DiffusionRenderer tackles the challenge of de-lighting and relighting a scene from only 2D video data.

De-lighting is a process that takes an image and removes its lighting effects, so that only the underlying object geometry and material properties remain. Relighting does the opposite, adding or editing light in a scene while maintaining the realism of complex properties like object transparency and specularity — how a surface reflects light.

Classic, physically based rendering pipelines need 3D geometry data to calculate light in a scene for de-lighting and relighting. DiffusionRenderer instead uses AI to estimate properties including normals, metallicity and roughness from a single 2D video.

With these calculations, DiffusionRenderer can generate new shadows and reflections, change light sources, edit materials and insert new objects into a scene — all while maintaining realistic lighting conditions.

Using an application powered by DiffusionRenderer, AV developers could take a dataset of mostly daytime driving footage and randomize the lighting of every video clip to create more clips representing cloudy or rainy days, evenings with harsh lighting and shadows, and nighttime scenes. With this augmented data, developers can boost their development pipelines to train, test and validate AV models that are better equipped to handle challenging lighting conditions.

Creators who capture content for digital character creation or special effects could use DiffusionRenderer to power a tool for early ideation and mockups — enabling them to explore and iterate through various lighting options before moving to expensive, specialized light stage systems to capture production-quality footage.

Enhancing DiffusionRenderer With NVIDIA Cosmos

Since completing the original paper, the research team behind DiffusionRenderer has integrated their method with Cosmos Predict-1, a suite of world foundation models for generating realistic, physics-aware future world states.

By doing so, the researchers observed a scaling effect, where applying Cosmos Predict’s larger, more powerful video diffusion model boosted the quality of DiffusionRenderer’s de-lighting and relighting correspondingly — enabling sharper, more accurate and temporally consistent results.

Cosmos Predict is part of NVIDIA Cosmos, a platform of world foundation models, tokenizers, guardrails and an accelerated data processing and curation pipeline to accelerate synthetic data generation for physical AI development. Read about the new Cosmos Predict-2 model on the NVIDIA Technical Blog.

NVIDIA Research at CVPR 

At CVPR, NVIDIA researchers are presenting dozens of papers on topics spanning automotive, healthcare, robotics and more. Three NVIDIA papers are nominated for this year’s Best Paper Award:

• FoundationStereo: This foundation model reconstructs 3D information from 2D images by matching pixels in stereo images. Trained on a dataset of over 1 million images, the model works out-of-the-box on real-world data, outperforming existing methods and generalizing across domains.
• Zero-Shot Monocular Scene Flow Estimation in the Wild: A collaboration between researchers at NVIDIA and Brown University, this paper introduces a generalizable model for predicting scene flow — the motion field of points in a 3D environment.
• Difix3D+: This paper, by researchers from the NVIDIA Spatial Intelligence Lab, introduces an image diffusion model that removes artifacts from novel viewpoints in reconstructed 3D scenes, enhancing the overall quality of 3D representations.

NVIDIA was also named an Autonomous Grand Challenge winner at CVPR, marking the second consecutive year NVIDIA topped the leaderboard in the end-to-end category — and the third consecutive year winning an Autonomous Grand Challenge award at the conference.

Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics.

Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang.

NVIDIA is launching a comprehensive, industry-defining autonomous vehicle (AV) software platform to accelerate large-scale deployment of safe, intelligent transportation innovations for automakers, truck manufacturers, robotaxi companies and startups worldwide.

Announced today at NVIDIA GTC Paris at VivaTech, the full-stack NVIDIA DRIVE AV software platform is now in full production. Combined with NVIDIA accelerated compute, this provides the automotive industry with a robust foundation for AI-powered mobility — unlocking a multitrillion-dollar global opportunity in autonomous and highly automated vehicles. For consumers, this means safer journeys and enjoyable hands-free driving experiences.

Safety First: A Unified, Full-Stack Software Approach

NVIDIA DRIVE’s modular, flexible approach empowers customers to scale based on their specific needs — whether that means adopting the entire stack or a subset. NVIDIA’s robust, safety-certified AV software architecture supports real-time sensor fusion and continuous improvement through over-the-air updates.

Its scalability allows automakers to deploy a subset of advanced driver-assistance features — such as surround perception, automated lane changes, parking and active safety — for level 2++ and level 3 vehicles, with a seamless path to higher levels of automation as technologies and regulations evolve.

Augmenting NVIDIA’s full-stack, end-to-end AV software is NVIDIA’s three-computer solution, which spans the entire AV development pipeline and is designed to tackle the challenges associated with the safe deployment of autonomous vehicles at scale. The three computers include:

• NVIDIA DGX systems and GPUs for training AI models and developing AV software.
• The NVIDIA Omniverse and NVIDIA Cosmos platforms running on NVIDIA OVX systems for simulation and synthetic data generation, enabling the testing and validation of autonomous driving scenarios and optimization of smart factory operations.
• The automotive-grade NVIDIA DRIVE AGX in-vehicle computer for processing real-time sensor data for safe, highly automated and autonomous driving capabilities.

Embracing Generative AI and an End-to-End Model Approach

Most traffic accidents are linked to human factors such as distraction or misjudgment, meaning there’s tremendous potential to make our roads safer. As such, the automotive industry is racing to develop AI-driven systems that improve road safety. But building an autonomous system that can safely navigate the complex physical world is extremely challenging.

AV software development has traditionally been based on a modular approach, with separate components for perception, prediction, planning and control. While there are benefits to this approach, it also opens up potential inefficiencies and errors that can hinder development at scale.

NVIDIA DRIVE AV software unifies these functions, using deep learning and foundation models trained on large datasets of human driving behavior to process sensor data and directly control vehicle actions, eliminating the need for predefined rules or traditional modular pipelines. As a result, vehicles can learn from vast amounts of real and synthetic driving behavior data to safely navigate complex environments and scenarios with human-like decision-making.

The NVIDIA Omniverse Blueprint for AV simulation can be used to further enhance the development pipeline, enabling physically accurate sensor simulation for AV training, testing and validation. By combining the blueprint with NVIDIA’s three-computer solution, developers can convert thousands of human-driven miles into billions of virtually driven miles, amplifying data quality and enabling efficient, scalable and continuously improving AV systems.

Bolstering End-to-End Safety With NVIDIA Halos

Safety is the most important component of all AVs. That’s why NVIDIA earlier this year launched NVIDIA Halos, a comprehensive end-to-end safety system integrating hardware, software, AI models and tools to ensure safe AV development and deployment from cloud to car. Halos provides guardrails for AV safety across simulation, training and deployment — and is backed by 15,000 engineering years of expertise.

A key part of this safety framework is the NVIDIA DriveOS safety-certified ASIL B/D operating system for autonomous driving, which provides a robust, reliable foundation for safe vehicle operation and meets stringent automotive safety standards.

The Future of Transportation, Here Today

With Halos and support for intelligent, adaptive sensors, NVIDIA’s AV stack delivers the tools, compute power and foundational AI models needed to accelerate safe, intelligent mobility — today.

NVIDIA has worked with the European auto industry for over a dozen years to drive automotive innovation, partnering with leading manufacturers, suppliers and mobility startups across the continent and the globe.

The work is transforming vehicle cockpits, along with automotive vehicle design, engineering and manufacturing, and enabling highly automated and self-driving vehicles with physical AI and accelerated computing.

At GTC Paris, NVIDIA also showcased how the transportation industry is using NVIDIA Omniverse and Cosmos for factory planning, vehicle design and simulation.

Plus, NVIDIA announced today at the Computer Vision and Pattern Recognition conference that it won the End-to-End Autonomous Driving Grand Challenge, recognized for creating technologies that allow the development of safer, smarter AVs using real-world and synthetic data — enabling these vehicles to handle even unexpected driving situations. This marks NVIDIA’s second consecutive year topping the leaderboard in the end-to-end category and its third straight Autonomous Grand Challenge award at CVPR.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

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At NVIDIA GTC Paris, Europe-based healthcare and life sciences companies are showcasing themselves as leaders in global healthcare innovation, demonstrating their ability to deliver transformative, AI-driven impact at a time when the continent needs it most.

Aimed at addressing staffing shortages, aging populations and rising costs, their diverse efforts across biopharma, population health and digital medicine are supported by the NVIDIA Inception program for startups, which provides cutting-edge startups with benefits including access to the latest developer tools, technical training and exposure to venture capital firms.

Whether building the world’s largest biodiversity database or deploying intelligent agents and AI factories that accelerate discovery and patient care, here’s how European companies are tapping the NVIDIA BioNeMo platform, NVIDIA DGX Cloud and the NVIDIA Cloud Partner network to drive better health outcomes for the region and beyond.

Basecamp Research’s AI-Ready Genomics Database Breaks the Data Wall

London-based Inception startup Basecamp Research has unveiled BaseData, the world’s largest and most diverse biological dataset for generative AI in life sciences.

Built from samples collected at over 125 locations in 26 countries, BaseData contains more than 9.8 billion new biological sequences and over a million previously unknown species — making it 30x faster, and growing up to 1000x faster — than UniRef 50, a public database that’s been used to train more than 80% of all biological sequence models.

This resource is now being used to train next-generation foundation models using NVIDIA BioNeMo Framework on the NVIDIA DGX Cloud Lepton platform.

By collaborating with NVIDIA, Basecamp has overcome the bottlenecks of scale, diversity and data governance that have traditionally held back commercial biopharma research. Its approach — combining a new data supply chain, global partnerships and GPU-accelerated workflows — enables the retraining of new classes of biological foundation models with the goal of unlocking generalizable biological design and accelerating drug discovery.

With this milestone, Basecamp is setting a new industry benchmark for data-driven AI in biosciences and laying the groundwork for generative biology breakthroughs.

“Data-optimal scaling is the key to overcoming the real-world limitations of current biological models,” said Phil Lorenz, chief technology officer at Basecamp Research. “Combined with NVIDIA’s compute and AI stack, we’re training models that can understand and generate biology like never before.”

Intelligent Agents Transform Healthcare Delivery in UK

Guy’s and St. Thomas’ NHS Foundation Trust — the largest NHS Trust in the U.K., with over 2.8 million patient contacts a year — is launching the Proactive and Accessible Transformation of Healthcare initiative, aka PATH, in collaboration with global investment company General Catalyst and Inception startups Hippocratic AI and Sword Health.

PATH seeks to transform care delivery by integrating advanced AI agents, helping to reduce specialty care waitlists, improve pain management and streamline triage.

“PATH aims to deliver better, faster and fairer healthcare for all,” said Ian Abbs, CEO of Guy’s and St. Thomas’. “By combining cutting-edge technology, including AI, with clinical care, we can build a more proactive NHS.”

This initiative brings together Hippocratic AI’s conversational agents that automate tasks like patient outreach, history-taking and referral validation with Sword Health’s AI Care platform, which has treated over 500,000 patients globally across physical pain, pelvic health and other clinical areas, delivering 6.5 million AI sessions to date.

“Our safety-focused generative AI agents can enable healthcare abundance in the U.K.,” said Munjal Shah, founder and CEO of Hippocratic AI. “With more personalized care, patients can feel more supported and heard, improving outcomes.”

“Our AI Care platform transforms the way care is delivered, turning waiting lists into recovery journeys,” said Virgílio Bento, founder and CEO of Sword Health. “Together, we can reduce waste in healthcare and materially improve clinical outcomes.”

PATH will explore solutions to address the U.K.’s elective care crisis, with more than 53,000 patients waiting for a first appointment at Guy’s and St. Thomas’ alone. By prioritizing cases based on clinical need and enabling timely intervention, PATH aims to design a blueprint for national-scale, AI-driven healthcare transformation.

“The goal of PATH is to enable the NHS to work better for everyone,” said Chris Bischoff, managing director at General Catalyst. “By deploying applied AI to increase access, improve care, optimize resources and empower staff, we believe we can build an NHS fit for the future.”

Pangaea Data’s AI Platform Closes Care Gaps Across Hard-to-Diagnose Diseases

Pangaea Data, an Inception company based in London and San Francisco, is helping close care gaps by discovering patients who are untreated and under-treated despite available intelligence in their existing medical records.

Pangaea’s platform is powered by the NVIDIA NeMo Agent toolkit, an open-source library for profiling and optimizing connected teams of AI agents. Pangaea is also adopting NVIDIA NIM microservices to harness large language models  that can help identify patients with rare and prevalent hard-to-diagnose diseases.

These tools help calculate clinical scores required to discover patients with such diseases — involving non-specific features such as fever, nausea and headache — in a manner which emulates a clinician’s manual review process for higher accuracy.

“The NeMo Agent toolkit and NVIDIA NIM microservices enable us to reduce the time taken to configure our platform for each disease condition from weeks to a single day, helping accelerate our mission of improving patient outcomes globally,” said Vibhor Gupta, founder and CEO of Pangaea Data.

Pangaea helps global pharmaceutical providers, health systems and policymakers transform care for better outcomes and increased health equity.

Its platform is now being deployed across health systems in the U.S., U.K., Spain and Barbados as a key part of a population health initiative led by the Prime Minister of Barbados.

Sofinnova, Cure51 and Next-Generation Startups Tap NVIDIA DGX Cloud

Through NVIDIA DGX Cloud Lepton, top European healthcare and life sciences venture capital firms like Sofinnova are bolstering AI-native startups.

As part of this initiative, selected VCs can offer their top portfolio companies early access to DGX Cloud Lepton — including access to 25 NVIDIA H100 GPU nodes for three months, plus white-glove support — to help them scale into new markets requiring sovereign, localized compute.

DGX Cloud is already used by startups like Paris-based Cure51, U.K.-based Sensible Biotechnologies and U.K.-based Molecular Glue Labs (MGL) through an Inception program benefit.

Cure51, a Sofinnova portfolio company, achieved a 17x speedup in genomic analysis and 2x cost savings by shifting workloads to NVIDIA BioNeMo running on DGX Cloud.

Using NVIDIA’s sovereign AI infrastructure through the NVIDIA Cloud Partner network, Sensible reduced its optimization cycles for cell-based mRNA therapeutics design from 15 days to just one, while MGL validated new protein engineering approaches. This program demonstrates how regional innovation labs and cloud partners can empower early-stage biotech.

Learn more about NVIDIA Inception startups advancing AI for healthcare and life sciences in Europe at NVIDIA GTC Paris, taking place June 10-12 at VivaTech. 

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

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Autonomous vehicle (AV) stacks are evolving from many distinct models to a unified, end-to-end architecture that executes driving actions directly from sensor data. This transition to using larger models is drastically increasing the demand for high-quality, physically based sensor data for training, testing and validation.

To help accelerate the development of next-generation AV architectures, NVIDIA today released NVIDIA Cosmos Predict-2 — a new world foundation model with improved future world state prediction capabilities for high-quality synthetic data generation — as well as new developers tools.

Cosmos Predict-2 is part of the NVIDIA Cosmos platform, which equips developers with technologies to tackle the most complex challenges in end-to-end AV development. Industry leaders such as Oxa, Plus and Uber are using Cosmos models to rapidly scale synthetic data generation for AV development.

Cosmos Predict-2 Accelerates AV Training

Building on Cosmos Predict-1 — which was designed to predict and generate future world states using text, image and video prompts — Cosmos Predict-2 better understands context from text and visual inputs, leading to fewer hallucinations and richer details in generated videos.

By using the latest optimization techniques, Cosmos Predict-2 significantly speeds up synthetic data generation on NVIDIA GB200 NVL72 systems and NVIDIA DGX Cloud.

Post-Training Cosmos Unlocks New Training Data Sources

By post-training Cosmos models on AV data, developers can generate videos that accurately match existing physical environments and vehicle trajectories, as well as generate multi-view videos from a single-view video, such as dashcam footage. The ability to turn widely available dashcam data into multi-camera data gives developers access to new troves of data for AV training. These multi-view videos can also be used to replace real camera data from broken or occluded sensors.

Post-trained Cosmos models generate multi-view videos to significantly augment AV training datasets.

The NVIDIA Research team post-trained Cosmos models on 20,000 hours of real-world driving data. Using the AV-specific models to generate multi-view video data, the team improved model performance in challenging conditions such as fog and rain.

AV Ecosystem Drives Advancements Using Cosmos Predict

AV companies have already integrated Cosmos Predict to scale and accelerate vehicle development.

Autonomous trucking leader Plus, which is building its solution with the NVIDIA DRIVE AGX platform, is post-training Cosmos Predict on trucking data to generate highly realistic synthetic driving scenarios to accelerate commercialization of their autonomous solutions at scale. AV software company Oxa is also using Cosmos Predict to support the generation of multi-camera videos with high fidelity and temporal consistency.

New NVIDIA Models and NIM Microservices Empower AV Developers

In addition to Cosmos Predict-2, NVIDIA today also announced Cosmos Transfer as an NVIDIA NIM microservice preview for easy deployment on data center GPUs.

The Cosmos Transfer NIM microservice preview augments datasets and generates photorealistic videos using structured input or ground-truth simulations from the NVIDIA Omniverse platform. And the NuRec Fixer model helps inpaint and resolve gaps in reconstructed AV data.

NuRec Fixer fills in gaps in driving data to improve neural reconstructions.

CARLA, the world’s leading open-source AV simulator, will be integrating Cosmos Transfer and NVIDIA NuRec — a set of application programming interfaces and tools for neural reconstruction and rendering — into its latest release. This will enable CARLA’s user base of over 150,000 AV developers to render synthetic simulation scenes and viewpoints with high fidelity and to generate endless variations of lighting, weather and terrain using simple prompts.

Developers can try out this pipeline using open-source data available on the NVIDIA Physical AI Dataset. The latest dataset release includes 40,000 clips generated using Cosmos, as well as sample reconstructed scenes for neural rendering. With this latest version of CARLA, developers can author new trajectories, reposition sensors and simulate drives.

Such scalable data generation pipelines unlock the development of end-to-end AV model architectures, as recently demonstrated by NVIDIA Research’s second consecutive win at the End-to-End Autonomous Grand Challenge at CVPR.

The challenge offered researchers the opportunity to explore new ways to handle unexpected situations — beyond using only real-world human driving data — to accelerate the development of smarter AVs.

NVIDIA Halos Advances End-to-End AV Safety

To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software safety stack with state-of-the-art AI research focused on AV safety.

Bosch, Easyrain and Nuro are the latest automotive leaders to join the NVIDIA Halos AI Systems Inspection Lab to verify the safe integration of their products with NVIDIA technologies and advance AV safety. Lab members announced earlier this year include Continental, Ficosa, OMNIVISION, onsemi and Sony Semiconductor Solutions.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

AI supercomputing is accelerating the development of new quantum applications, driving breakthroughs in critical industries such as aerospace, automotive and manufacturing.

Underscoring that opportunity, Ansys announced today it is using the NVIDIA CUDA-Q quantum computing platform running on the Gefion supercomputer to advance quantum algorithms for fluid dynamics applications.

Gefion is Denmark’s first AI supercomputer, consisting of an NVIDIA DGX SuperPOD interconnected with NVIDIA Quantum-2 InfiniBand networking. Using the open-source NVIDIA CUDA-Q software platform, Ansys drew on the power of the supercomputer to perform GPU-accelerated simulations of quantum algorithms applicable to fluid dynamics applications.

“To discover tomorrow’s practical quantum applications, researchers need to be able to run meaningfully large simulations of them today,” said Tim Costa, senior director of quantum and CUDA-X at NVIDIA. “NVIDIA is enabling collaborators like Ansys and the DCAI by providing the supercomputing platforms researchers need to increase quantum computing’s impact.”

Gefion is based in Copenhagen and operated by DCAI. It was established by the Novo Nordisk Foundation and the Export and Investment Fund of Denmark.

CUDA-Q taps into GPU-accelerated libraries, enabling Gefion to run complex simulations of a class of algorithms known as Quantum Lattice Boltzmann Methods. By simulating how these algorithms would perform on a 39-qubit quantum computer, Ansys could rapidly and cost-effectively investigate how they impact fluid dynamics applications.

“We’re seeing how CUDA-Q can unlock hybrid quantum-classical computing for researchers using Gefion,” said Nadia Carlsten, CEO of DCAI. “Partnering with NVIDIA and Ansys has allowed us to drive the convergence of quantum technologies and AI supercomputing.”

“CUDA-Q’s GPU-accelerated simulations have allowed us to study quantum applications in the regimes where we can really begin to see their effects,” said Prith Banerjee, chief technology officer of Ansys. “Working with NVIDIA and DCAI, we’re expanding the role of quantum computing in engineering disciplines like computational fluid dynamics.”

This latest work builds on NVIDIA’s recent announcements on using accelerated computing to propel quantum computing research — including the opening of Japan’s ABCI-Q, the world’s largest quantum research supercomputer, and a new NVIDIA-powered supercomputer at the National Center for High-Performance Computing in Taiwan.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

AI is already driving revenue increases for financial institutions — and with new investments in AI infrastructure and development across Europe, the region’s financial services industry is poised to mint even greater value from the technology.

With sovereign AI models and agents built using AI factories, financial institutions and digital payment companies can extract powerful insights from their vast data sources to protect investments, detect fraud and offer personalized services to customers.

At the NVIDIA GTC Paris at VivaTech, one of Europe’s largest finance companies announced that it’s building an NVIDIA-powered AI factory to deploy sovereign AI for wide-ranging financial services.

Banks and online payment companies operating across the continent are harnessing NVIDIA AI and data science libraries to speed up data analysis for fraud detection and other applications. And the region’s AI platforms and service providers are helping banks and fintech companies accelerate their workflows with AI agents and models built on NVIDIA software libraries, models and blueprints.

European Bank Builds AI Factory to Develop and Scale Financial Services Applications

Across Europe, banks are building regional AI factories to enable the deployment of AI models for customer service, fraud detection, risk modeling and the automation of regulatory compliance.

In Germany, Finanz Informatik, the digital technology provider of the Savings Banks Finance Group, is scaling its on-premises AI factory and using NVIDIA AI Enterprise software for applications including an AI assistant to help its employees automate routine tasks and efficiently process the institution’s banking data.

Financial Services Companies Speed Data Science and Processing

Leading online payment and banking providers in Europe are tapping NVIDIA CUDA-X AI and data science libraries to accelerate financial data processing and analysis.

Amsterdam-based neobank bunq, which serves over 17 million users in the European Union, uses NVIDIA-accelerated XGBoost to boost fraud detection workflows.

The company’s AI-powered monitoring system is used to flag suspicious transactions that present risk of fraud or money laundering. Using NVIDIA GPUs running XGBoost and NVIDIA cuDF, bunq accelerated its model training by 100x and data processing by 5x.

The company is also using NVIDIA NIM microservices to implement and scale large language model-powered applications like its personal AI assistant, dubbed Finn. The bank uses NVIDIA NeMo Retriever, a collection of NIM microservices for extracting, embedding and reranking enterprise data so it can be semantically searched, which can help further improve Finn’s accuracy.

The recently launched NVIDIA AI Blueprint for financial fraud detection also includes XGBoost to support anomaly detection from financial data. The NVIDIA AI Blueprint is available for customers to run on Amazon Web Services and Hewlett Packard Enterprise, with availability coming soon on Dell Technologies. Customers can also adopt the blueprint through NVIDIA partners including Cloudera, EXL, Infosys and SHI International.

Checkout.com is a London-based fintech company providing digital payment solutions to enterprises around the world. The company, which operates in more than 55 countries and supports over 180 currencies, is speeding up data analysis pipelines from minutes to under 10 seconds using the NVIDIA cuDF accelerator for pandas — the go-to Python library for data handling and analysis.

Checkout.com is also exploring the use of NVIDIA cuML and the RAPIDS Accelerator for Apache Spark to further boost analysis of the company’s terabyte-scale data lake.

PayPal, based in the U.S., is another popular digital payment platform for European customers. The company used the RAPIDS Accelerator for Apache Spark to achieve a 70% cost reduction for Spark-based data pipelines running on NVIDIA accelerated computing.

Investment management firms are adopting GPU-accelerated optimization for capital allocation in dynamic markets. The NVIDIA cuFOLIO module, built on the NVIDIA cuOpt optimization engine, enables rapid portfolio adjustments that balance risk, return and investor preferences — turning time-consuming, CPU-bound workflows into scalable, real-time simulation engines.

AI Platforms, Solution Providers Offer NVIDIA-Accelerated Financial Services

European software companies and solution providers are integrating NVIDIA AI software to accelerate financial services workflows for their customers.

Dataiku, an AI platform company founded in Paris and based in New York City, announced at GTC Paris a new blueprint to help banking and insurance institutions deploy agentic AI systems at scale. The company is also integrating the NVIDIA Enterprise AI Factory validated design to accelerate AI development, and offers native integration of its LLM Mesh platform with NVIDIA NIM microservices.

KX, a global data and analytics software company based in the U.K., launched an AI Banker Agent Blueprint at GTC Paris. Built with NVIDIA AI tools including the NVIDIA NeMo platform, Nemotron family of models and NIM microservices, the blueprint can be deployed by banks as an AI-powered research assistant, client relationship manager or personalized customer portfolio manager.

Temenos, a global provider of banking technology, uses NIM microservices to deploy its generative AI models to banks. The company’s generative AI solutions can be applied to use cases including credit scoring, fraud detection and customer service.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

The integration of quantum processors into tomorrow’s supercomputers promises to dramatically expand the problems that can be addressed with compute — revolutionizing industries including drug and materials development.

In addition to being part of the vision for tomorrow’s hybrid quantum-classical supercomputers, accelerated computing is dramatically advancing the work quantum researchers and developers are already doing to achieve that vision. And in today’s development of tomorrow’s quantum technology, NVIDIA GB200 NVL72 systems and their fifth-generation multinode NVIDIA NVLink interconnect capabilities have emerged as the leading architecture.

Here are five key quantum computing workloads in development, powered by NVIDIA Blackwell architecture.

1. Developing Better Quantum Algorithms

Simulating how candidate algorithms will run on quantum computers allows researchers to discover and refine performant quantum applications. For example, large-scale simulations performed with Ansys on DCAI’s Gefion supercomputer are being used to develop new quantum algorithms for computational fluid dynamics.

But such simulations are extremely computationally intensive. GB200 NVL72’s high-bandwidth interconnect with all-to-all GPU connectivity is an important factor in allowing NVIDIA cuQuantum libraries to execute state-of-the-art simulation techniques on feasible time scales — with an 800x speedup compared with the best CPU implementations.

2. Designing Low-Noise Qubits

Conventional chip manufacturing relies heavily on detailed physics simulations to rapidly iterate toward performant processor designs. Quantum hardware designers must tap into these same simulation tools to discover low-noise qubit designs, which are crucial for quantum computing.

Simulations capable of emulating noise in potential qubit designs need to crunch through complex quantum mechanical calculations. GB200 NVL72, paired with cuQuantum’s dynamics library, provides a 1,200x speedup for these workloads — providing a valuable new tool that accelerates the design process for quantum hardware builders like Alice & Bob.

3. Generating Quantum Training Data

AI models show increasing promise for challenges in quantum computing, including performing the control operations needed to keep quantum computers running.

But in many cases, a key stumbling block for these models is obtaining the volumes of data needed to effectively train them. The necessary data would ideally come from actual quantum hardware, but this proves either expensive or simply unavailable.

Output from simulated quantum processors offers a solution. GB200 NVL72 can output quantum training data 4,000x faster than with CPU-based techniques, helping bring the latest AI advancements to quantum computing.

4. Exploring Hybrid Applications

Effective future quantum applications will lean on both quantum and classical hardware, seamlessly distributing algorithm subroutines to whichever hardware type is most appropriate.

Exploring hybrid algorithms suited to this environment requires a platform that can combine simulations of quantum hardware with access to state-of-the-art AI supercomputing, such as the capabilities offered by GB200 NVL72. NVIDIA CUDA-Q is such a platform. It can draw on GB200 NVL72 to provide an ideal hybrid computing environment for researchers to explore hybrid quantum-classical applications, speeding development by 1,300x.

5. Unlocking Quantum Error Correction

Future quantum-GPU supercomputers will rely on quantum error correction — a control process that continually processes qubit data through demanding decoding algorithms — in order to continually correct errors.

The decoding algorithms required by quantum error correction run on conventional computing hardware and must process terabytes of data every second to stay on top of qubit errors. This requires the power of accelerated computing. GB200 NVL72 demonstrates a 500x speedup in running a commonly used class of decoding algorithms — making quantum error correction a feasible prospect for the future of quantum computing.

These breakthroughs are allowing the quantum computing industry to perform the quantum-GPU integrations needed for large-scale useful quantum computing.

For example, qubit-builder Diraq announced at NVIDIA GTC Paris that it is using the NVIDIA DGX Quantum reference architecture to connect spins-in-silicon qubits to NVIDIA GPUs. Plus, the NVIDIA CUDA-Q Academic program is onboarding researchers to use GB200 NVL72 and other advanced technologies.

NVIDIA is working toward a future where all supercomputers integrate quantum hardware to solve commercially relevant problems. NVIDIA GB200 NVL72 is the platform for building this future.

Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.