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.

NVIDIA today announced it is working with European nations, and technology and industry leaders, to build NVIDIA Blackwell AI infrastructure that will strengthen digital sovereignty, support economic growth and position the continent as a leader in the AI industrial revolution. France, Italy, Spain and the U.K. are among the nations building domestic AI infrastructure with an ecosystem of technology and cloud providers, including Domyn, Mistral AI, Nebius and Nscale, and telecommunications providers, including Orange, Swisscom, Telefónica and Telenor.

These deployments will deliver more than 3,000 exaflops of NVIDIA Blackwell compute resources for sovereign AI, enabling European enterprises, startups and public sector organizations to securely develop, train and deploy agentic and physical AI applications. NVIDIA is establishing and expanding AI technology centers in Germany, Sweden, Italy, Spain, the U.K. and Finland. These centers build on NVIDIA's history of collaborating with academic institutions and industry through the NVIDIA AI Technology Center program and NVIDIA Deep Learning Institute to develop the AI workforce and scientific discovery throughout the regions.

NVIDIA GTC Paris at VivaTech -- NVIDIA today announced that it is teaming with model builders and cloud providers across Europe and the Middle East to optimize sovereign large language models (LLMs), providing a springboard to accelerate enterprise AI adoption for the region's industries.

Model builders and AI consortiums Barcelona Supercomputing Center (BSC), Bielik.AI, Dicta, H Company, Domyn, LightOn, the National Academic Infrastructure for Supercomputing in Sweden (NAISS) together with KBLab at the National Library of Sweden, the Slovak Republic, the Technology Innovation Institute (TII), the University College of London, the University of Ljubljana and UTTER are teaming with NVIDIA to optimize their models with NVIDIA Nemotron techniques to maximize cost efficiency and accuracy for enterprise AI workloads, including agentic AI.

MSI, a leading global provider of high-performance server solutions, unveils its latest AI innovations using NVIDIA MGX and NVIDIA DGX Station reference architectures at COMPUTEX 2025, held from May 20-23 at booth J0506. Purpose-built to address the growing demands of AI, HPC, and accelerated computing workloads, MSI's AI solutions feature modular, scalable building blocks designed to deliver next-level AI performance for enterprises and cloud data center environments.

"AI adoption is transforming enterprise data centers as organizations move quickly to integrate advanced AI capabilities," said Danny Hsu, General Manager of Enterprise Platform Solutions at MSI. "With the explosive growth of generative AI and increasingly diverse workloads, traditional servers can no longer keep pace. MSI's AI solutions, built on the NVIDIA MGX and NVIDIA DGX Station reference architectures, deliver the scalability, flexibility, and performance enterprises need to future-proof their infrastructure and accelerate their AI innovation."

GIGABYTE at the 2025 Computex showed off the AI TOP Atom, a custom-design NVIDIA DGX Spark box. NVIDIA earlier today announced that it had opened up the DGX Spark compact AI supercomputer for custom designs, and the AI TOP Atom is one of many such custom designs. The box combines an NVIDIA GB10 "Grace Blackwell" GPU+CPU combo, with 128 GB of unified LPDDR5X memory, NVLink chip-to-chip interconnect for full memory/cache coherence, and a high bandwidth ConnectX-7 InfiniBand NIC letting you stack up additional DGX Spark boxes. The box offers up to 1,000 AI TOPS of compute power and is able to accelerate 70B and 200B parameter models. It's designed for AI-native localized software development.

Lenovo has announced the ThinkStation PGX, a compact, personal AI developer workstation. The ThinkStation PGX is ideal for AI researchers and developers, data scientists, practitioners, students, and application engineers who need a purpose-built, compact, and powerful AI desktop solution that works immediately out of the box. Built on the NVIDIA GB10 Grace Blackwell Superchip providing up to 1 PetaFlop (1000 TOPS) of AI performance, the ThinkStation PGX can tackle large generative AI models of up to 200 billion parameters. With 128 GB of coherent unified system memory, developers can experiment, fine-tune, or inference the latest generation of reasoning AI models. To double down on computing power, developers can connect two ThinkStation PGX systems together to work with even larger AI models up to 405 billion parameters.

The ThinkStation PGX comes preconfigured with the NVIDIA DGX OS, and the NVIDIA AI software stack, along with familiar tools and frameworks like PyTorch and Jupyter. Developers can instantly prototype, fine-tune, and inference large AI models from the desktop and seamlessly deploy to the data center or cloud. "By collaborating with NVIDIA to deliver a high-performance, yet compact device, Lenovo is empowering AI developers, researchers, data scientists, and students to accelerate their workloads and adoption of breakthrough innovation in generative AI."—Rob Herman, Vice President, Worldwide Workstation and Client AI Business at Lenovo.

MSI IPC, a global leader in industrial computing and AI-driven solutions, is set to unveil its latest innovations at COMPUTEX 2025, held from May 20 to 23 at the Taipei Nangang Exhibition Center. Visitors can explore MSI IPC's cutting-edge technologies at Booth J0506, Hall 1, 1F.

Introducing the EdgeXpert MS-C931: A Desktop AI Supercomputer
MSI IPC will unveil the EdgeXpert MS-C931, a desktop AI supercomputer built on the NVIDIA DGX Spark platform. Powered by the NVIDIA GB10 Grace Blackwell Superchip, the EdgeXpert MS-C931 delivers 1,000 AI TOPS FP4 performance, equipped with high-speed ConnectX 7 networking, 128 GB unified memory, and support for large language models. Designed for AI developers and researchers, it is ideal for applications in education, finance, and healthcare industries.

Around late April, MediaTek confirmed that their CEO—Dr. Rick Tsai—will be delivering a big keynote speech—on May 20—at this month's Computex 2025 trade show. The company's preamble focuses on their "driving of AI innovation—from edge to cloud," but industry moles propose a surprise new product introduction during proceedings. MediaTek and NVIDIA have collaborated on a number of projects; the most visible being automative solutions. Late last year, intriguing Arm-based rumors emerged online—with Team Green allegedly working on a first time attempt at breaking into the high-end CPU consumer market segment; perhaps with the leveraging of "Blackwell" GPU architecture. MediaTek was reportedly placed in the equation, due to expertise accumulated from their devising of modern Dimensity "big core" mobile processor designs. At the start of 2025, data miners presented evidence of Lenovo seeking new engineering talent. Their job description mentioned a mysterious NVIDIA "N1x" SoC.

Further conjecture painted a fanciful picture of forthcoming "high-end N1x and mid-tier N1 (non-X)" models—with potential flagship devices launching later on this year. According to ComputerBase.de, an unannounced "GB10" PC chip could be the result of NVIDIA and MediaTek's rumored "AI PC" joint venture. Yesterday's news article divulged: "currently (this) product (can be) found in NVIDIA DGX Spark (platforms), and similarly equipped partner solutions. The systems, available starting at $3000, are aimed at AI developers who can test LLMs locally before moving them to the data center. The chip combines a 'Blackwell' GPU with a 'Grace' Arm CPU (in order) to create an SoC with 128 GB LPDDR5X, and a 1 TB or 4 TB SSD. The 'GB10' offers a GPU with one petaflop of FP4 performance (with sparsity)." ComputerBase reckons that the integrated graphics solution makes use of familiar properties—namely "5th-generation Tensor Cores and 4th-generation RT Cores"—from GeForce RTX 50-series graphics cards. When discussing the design's "Grace CPU" setup, the publication's report outlined a total provision of: "20 Arm cores, including 10 Cortex-X925 and 10 Cortex-A725. The whole thing sits on a board measuring around 150 × 150 mm—for comparison: the classic NUC board format is 104 × 101 mm."

NVIDIA is collaborating with Google Cloud to bring agentic AI to enterprises seeking to locally harness the Google Gemini family of AI models using the NVIDIA Blackwell HGX and DGX platforms and NVIDIA Confidential Computing for data safety. With the NVIDIA Blackwell platform on Google Distributed Cloud, on-premises data centers can stay aligned with regulatory requirements and data sovereignty laws by locking down access to sensitive information, such as patient records, financial transactions and classified government information. NVIDIA Confidential Computing also secures sensitive code in the Gemini models from unauthorized access and data leaks.

"By bringing our Gemini models on premises with NVIDIA Blackwell's breakthrough performance and confidential computing capabilities, we're enabling enterprises to unlock the full potential of agentic AI," said Sachin Gupta, vice president and general manager of infrastructure and solutions at Google Cloud. "This collaboration helps ensure customers can innovate securely without compromising on performance or operational ease." Confidential computing with NVIDIA Blackwell provides enterprises with the technical assurance that their user prompts to the Gemini models' application programming interface—as well as the data they used for fine-tuning—remain secure and cannot be viewed or modified. At the same time, model owners can protect against unauthorized access or tampering, providing dual-layer protection that enables enterprises to innovate with Gemini models while maintaining data privacy.

In the latest MLPerf Inference V5.0 benchmarks, which reflect some of the most challenging inference scenarios, the NVIDIA Blackwell platform set records - and marked NVIDIA's first MLPerf submission using the NVIDIA GB200 NVL72 system, a rack-scale solution designed for AI reasoning. Delivering on the promise of cutting-edge AI takes a new kind of compute infrastructure, called AI factories. Unlike traditional data centers, AI factories do more than store and process data - they manufacture intelligence at scale by transforming raw data into real-time insights. The goal for AI factories is simple: deliver accurate answers to queries quickly, at the lowest cost and to as many users as possible.

The complexity of pulling this off is significant and takes place behind the scenes. As AI models grow to billions and trillions of parameters to deliver smarter replies, the compute required to generate each token increases. This requirement reduces the number of tokens that an AI factory can generate and increases cost per token. Keeping inference throughput high and cost per token low requires rapid innovation across every layer of the technology stack, spanning silicon, network systems and software.

NVIDIA today unveiled NVIDIA DGX personal AI supercomputers powered by the NVIDIA Grace Blackwell platform. DGX Spark—formerly Project DIGITS—and DGX Station, a new high-performance NVIDIA Grace Blackwell desktop supercomputer powered by the NVIDIA Blackwell Ultra platform, enable AI developers, researchers, data scientists and students to prototype, fine-tune and inference large models on desktops. Users can run these models locally or deploy them on NVIDIA DGX Cloud or any other accelerated cloud or data center infrastructure.

DGX Spark and DGX Station bring the power of the Grace Blackwell architecture, previously only available in the data center, to the desktop. Global system builders to develop DGX Spark and DGX Station include ASUS, Dell, HP Inc. and Lenovo.

Companies and organizations are increasingly using AI to protect their customers and thwart the efforts of fraudsters around the world. Voice security company Hiya found that 550 million scam calls were placed per week in 2023, with INTERPOL estimating that scammers stole $1 trillion from victims that same year. In the U.S., one of four noncontact-list calls were flagged as suspected spam, with fraudsters often luring people into Venmo-related or extended warranty scams.

Traditional methods of fraud detection include rules-based systems, statistical modeling and manual reviews. These methods have struggled to scale to the growing volume of fraud in the digital era without sacrificing speed and accuracy. For instance, rules-based systems often have high false-positive rates, statistical modeling can be time-consuming and resource-intensive, and manual reviews can't scale rapidly enough.

The 63rd edition of the TOP500 reveals that Frontier has once again claimed the top spot, despite no longer being the only exascale machine on the list. Additionally, a new system has found its way into the Top 10.

The Frontier system at Oak Ridge National Laboratory in Tennessee, USA remains the most powerful system on the list with an HPL score of 1.206 EFlop/s. The system has a total of 8,699,904 combined CPU and GPU cores, an HPE Cray EX architecture that combines 3rd Gen AMD EPYC CPUs optimized for HPC and AI with AMD Instinct MI250X accelerators, and it relies on Cray's Slingshot 11 network for data transfer. On top of that, this machine has an impressive power efficiency rating of 52.93 GFlops/Watt - putting Frontier at the No. 13 spot on the GREEN500.

Dell Technologies is strengthening its collaboration with NVIDIA to help enterprises adopt AI technologies. By expanding the Dell Generative AI Solutions portfolio, including with the new Dell AI Factory with NVIDIA, organizations can accelerate integration of their data, AI tools and on-premises infrastructure to maximize their generative AI (GenAI) investments. "Our enterprise customers are looking for an easy way to implement AI solutions—that is exactly what Dell Technologies and NVIDIA are delivering," said Michael Dell, founder and CEO, Dell Technologies. "Through our combined efforts, organizations can seamlessly integrate data with their own use cases and streamline the development of customized GenAI models."

"AI factories are central to creating intelligence on an industrial scale," said Jensen Huang, founder and CEO, NVIDIA. "Together, NVIDIA and Dell are helping enterprises create AI factories to turn their proprietary data into powerful insights."

NVIDIA today announced its next-generation AI supercomputer—the NVIDIA DGX SuperPOD powered by NVIDIA GB200 Grace Blackwell Superchips—for processing trillion-parameter models with constant uptime for superscale generative AI training and inference workloads.

Featuring a new, highly efficient, liquid-cooled rack-scale architecture, the new DGX SuperPOD is built with NVIDIA DGX GB200 systems and provides 11.5 exaflops of AI supercomputing at FP4 precision and 240 terabytes of fast memory—scaling to more with additional racks.

Powering a new era of computing, NVIDIA today announced that the NVIDIA Blackwell platform has arrived—enabling organizations everywhere to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor.

The Blackwell GPU architecture features six transformative technologies for accelerated computing, which will help unlock breakthroughs in data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing and generative AI—all emerging industry opportunities for NVIDIA.

During the 2024 SIEPR Economic Summit, NVIDIA CEO Jensen Huang acknowledged that the company's next-generation DGX systems, designed for AI and high-performance computing workloads, will require liquid cooling due to their immense power consumption. Huang also hinted that these new systems are set to be released in the near future. The revelation comes as no surprise, given the increasing power of GPUs needed to satisfy AI and machine learning applications. As computational requirements continue to grow, so does the need for more powerful hardware. However, with great power comes great heat generation, necessitating advanced cooling solutions to maintain optimal performance and system stability. Liquid cooling has long been a staple in high-end computing systems, offering superior thermal management compared to traditional air cooling methods.

By implementing liquid cooling in the upcoming DGX systems, NVIDIA aims to push the boundaries of performance while ensuring the hardware remains reliable and efficient. Although Huang did not provide a specific release date for the new DGX systems, his statement suggests that they are on the horizon. Whether the next generation of DGX systems uses the current NVIDIA H200 or the upcoming Blackwell B100 GPU as their primary accelerator, the performance will undoubtedly be delivered. As the AI and high-performance computing landscape continues to evolve, NVIDIA's position continues to strengthen, and liquid-cooled systems will certainly play a crucial role in shaping the future of these industries.

Nations have long invested in domestic infrastructure to advance their economies, control their own data and take advantage of technology opportunities in areas such as transportation, communications, commerce, entertainment and healthcare. AI, the most important technology of our time, is turbocharging innovation across every facet of society. It's expected to generate trillions of dollars in economic dividends and productivity gains. Countries are investing in sovereign AI to develop and harness such benefits on their own. Sovereign AI refers to a nation's capabilities to produce artificial intelligence using its own infrastructure, data, workforce and business networks.

Why Sovereign AI Is Important
The global imperative for nations to invest in sovereign AI capabilities has grown since the rise of generative AI, which is reshaping markets, challenging governance models, inspiring new industries and transforming others—from gaming to biopharma. It's also rewriting the nature of work, as people in many fields start using AI-powered "copilots." Sovereign AI encompasses both physical and data infrastructures. The latter includes sovereign foundation models, such as large language models, developed by local teams and trained on local datasets to promote inclusiveness with specific dialects, cultures and practices. For example, speech AI models can help preserve, promote and revitalize indigenous languages. And LLMs aren't just for teaching AIs human languages, but for writing software code, protecting consumers from financial fraud, teaching robots physical skills and much more.

NVIDIA (NASDAQ: NVDA) today reported revenue for the fourth quarter ended January 28, 2024, of $22.1 billion, up 22% from the previous quarter and up 265% from a year ago. For the quarter, GAAP earnings per diluted share was $4.93, up 33% from the previous quarter and up 765% from a year ago. Non-GAAP earnings per diluted share was $5.16, up 28% from the previous quarter and up 486% from a year ago.

For fiscal 2024, revenue was up 126% to $60.9 billion. GAAP earnings per diluted share was $11.93, up 586% from a year ago. Non-GAAP earnings per diluted share was $12.96, up 288% from a year ago. "Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations," said Jensen Huang, founder and CEO of NVIDIA.

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), and NVIDIA (NASDAQ: NVDA) today announced an expansion of their strategic collaboration to deliver the most-advanced infrastructure, software and services to power customers' generative artificial intelligence (AI) innovations. The companies will bring together the best of NVIDIA and AWS technologies—from NVIDIA's newest multi-node systems featuring next-generation GPUs, CPUs and AI software, to AWS Nitro System advanced virtualization and security, Elastic Fabric Adapter (EFA) interconnect, and UltraCluster scalability—that are ideal for training foundation models and building generative AI applications.

The expanded collaboration builds on a longstanding relationship that has fueled the generative AI era by offering early machine learning (ML) pioneers the compute performance required to advance the state-of-the-art in these technologies.

NVIDIA today introduced an AI foundry service to supercharge the development and tuning of custom generative AI applications for enterprises and startups deploying on Microsoft Azure.

The NVIDIA AI foundry service pulls together three elements—a collection of NVIDIA AI Foundation Models, NVIDIA NeMo framework and tools, and NVIDIA DGX Cloud AI supercomputing services—that give enterprises an end-to-end solution for creating custom generative AI models. Businesses can then deploy their customized models with NVIDIA AI Enterprise software to power generative AI applications, including intelligent search, summarization and content generation.

The 62nd edition of the TOP500 reveals that the Frontier system retains its top spot and is still the only exascale machine on the list. However, five new or upgraded systems have shaken up the Top 10.

Housed at the Oak Ridge National Laboratory (ORNL) in Tennessee, USA, Frontier leads the pack with an HPL score of 1.194 EFlop/s - unchanged from the June 2023 list. Frontier utilizes AMD EPYC 64C 2GHz processors and is based on the latest HPE Cray EX235a architecture. The system has a total of 8,699,904 combined CPU and GPU cores. Additionally, Frontier has an impressive power efficiency rating of 52.59 GFlops/watt and relies on HPE's Slingshot 11 network for data transfer.

Training generative AI models just got easier. NVIDIA DGX Cloud AI supercomputing platform and NVIDIA AI Enterprise software are now available in Oracle Cloud Marketplace, making it possible for Oracle Cloud Infrastructure customers to access high-performance accelerated computing and software to run secure, stable and supported production AI in just a few clicks. The addition - an industry first - brings new capabilities for end-to-end development and deployment on Oracle Cloud. Enterprises can get started from the Oracle Cloud Marketplace to train models on DGX Cloud, and then deploy their applications on OCI with NVIDIA AI Enterprise.

Oracle Cloud and NVIDIA Lift Industries Into Era of AI
Thousands of enterprises around the world rely on OCI to power the applications that drive their businesses. Its customers include leaders across industries such as healthcare, scientific research, financial services, telecommunications and more. Oracle Cloud Marketplace is a catalog of solutions that offers customers flexible consumption models and simple billing. Its addition of DGX Cloud and NVIDIA AI Enterprise lets OCI customers use their existing cloud credits to integrate NVIDIA's leading AI supercomputing platform and software into their development and deployment pipelines. With DGX Cloud, OCI customers can train models for generative AI applications like intelligent chatbots, search, summarization and content generation.