Collaboration Will Provide World-Class AI Infrastructure, Research Funding, Internships and Joint Appointments to Advance Agentic AI Model Development for Korea

News Summary:

• NVIDIA and KAIST are launching a joint AI research lab at the KAIST Kim Jaechul Graduate School of AI in Seoul, dedicated to advancing agentic AI models and agent systems built for South Korea’s industries, language and future.
• The collaboration includes compute contributions, funding for at least 10 KAIST researchers annually with NVIDIA internships, plus full-time NVIDIA roles for top Korean researchers — creating new pathways for Korea’s AI talent.
• A core focus is developing models optimized for Korea, using NVIDIA Nemotron open models and local NVIDIA Cloud Partner infrastructure to build a pipeline from academic research to enterprise and national AI deployments.
   

NVIDIA and the Korea Advanced Institute of Science and Technology (KAIST) today announced the launch of a joint AI research laboratory at the KAIST Kim Jaechul Graduate School of AI in Seoul, dedicated to advancing agentic AI for South Korea.

The collaboration will establish a robust academic AI research program, bringing together NVIDIA full-stack AI expertise, NVIDIA Nemotron™ open models and NVIDIA AI Cloud partner computing with the world-class scientific talent at KAIST, one of Asia’s premier research universities.

“Korea is home to leading AI researchers and is one of the world’s most advanced technology ecosystems,” said Bill Dally, chief scientist and senior vice president of research at NVIDIA. “The joint NVIDIA-KAIST research lab will provide a foundation for the next frontier of AI research to accelerate AI models and agent systems built for Korea’s industries, language and future.”

“AI research is entering a new era — one that requires frontier talent, large-scale infrastructure and deep collaboration across academia and industry,” said Hyunwoo Kim, incoming faculty member at the KAIST Kim Jaechul Graduate School of AI, who will serve as head of the joint NVIDIA-KAIST lab upon joining KAIST. “Together, NVIDIA and KAIST Kim Jaechul Graduate School of AI will pursue ambitious work that helps Korea attract and retain top AI scientists while building lasting ties with NVIDIA’s global research organization.”

Full-Stack Infrastructure, Open Models and Collaboration Fuel Korea’s AI Future
The lab will be established at the KAIST Kim Jaechul Graduate School of AI in Seoul. KAIST, headquartered in the tech hub of Daejeon, has a strong focus on public research spanning engineering, AI, semiconductor technology, robotics and digital humanities.

The joint lab plans to fund at least 10 KAIST researchers annually and provide each with internship opportunities at NVIDIA. In addition, NVIDIA plans to hire exceptional Korean researchers for full-time positions. Together, these efforts will create stronger pathways for Korea’s top AI talent to pursue ambitious research, build long-term careers and deepen global collaboration between academia and industry.

The $300 million collaboration is expected to include $50-million-per-year compute contributions across an initial five-year period. Compute infrastructure from local NVIDIA Cloud Partners will provide researchers with direct access to the latest NVIDIA AI infrastructure.

Among the lab’s priorities will be developing models optimized for the Korean language and Korea-specific use cases, with NVIDIA Nemotron open models to advance the country’s AI capabilities, fostering a pipeline from academic discovery to enterprise and national AI deployments.

The post NVIDIA and KAIST Launch Joint AI Research Lab to Accelerate AI Innovation in Korea appeared first on Tech Scene ZA.

News Summary:

• NVIDIA Agent Toolkit now includes NVIDIA Omniverse libraries, giving AI agents tools and skills to help software developers integrate physical AI capabilities into their existing applications.
• New Omniverse libraries for NVIDIA RTX sensor simulation, GPU-accelerated physics simulation and simulation-ready asset validation are openly available on GitHub.
• SideFX and PTC are integrating Omniverse libraries into 3D applications for physical AI, with support for cloud and local AI systems, from NVIDIA RTX Spark to NVIDIA DGX Station.
• New NVIDIA blueprint for integrating Omniverse libraries in Blender.

NVIDIA today announced that NVIDIA Agent Toolkit now includes NVIDIA Omniverse™ libraries — a collection of software components that give AI agents tools and skills to add physical AI capabilities to existing applications and prepare 3D content for simulation.

Robots, factories and autonomous systems need to be designed, tested and trained in simulation before they operate in the real world. Preparing 3D content for simulation takes more than realistic visuals — assets need the right structure, materials, scale, labels, sensors and physical properties. With NVIDIA Omniverse libraries in NVIDIA Agent Toolkit, AI agents have the tools and skills to build workflows, inspect scenes, flag issues and prepare assets, helping developers move faster from 3D content to simulation-ready environments.

“The physical AI era will be built in simulation first,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA Agent Toolkit with Omniverse libraries brings AI agents into the 3D tools developers already use, helping build the simulation-ready worlds where robots, factories and autonomous systems are trained and tested long before they reach the real world.”

Software makers including SideFX and PTC are integrating Omniverse libraries for agent-ready sensor simulation, physics and asset validation, helping bring agentic AI into the applications and workflows developers and technical artists already use to prepare 3D content.

Omniverse Libraries Bring Physical AI Skills to NVIDIA Agent Toolkit
NVIDIA Agent Toolkit helps software makers build AI agents that connect tools, skills and data sources. Omniverse libraries extend those agents into 3D and physical AI workflows with callable tools for sensor simulation, GPU-accelerated physics and simulation-ready asset validation inside existing applications.

The new Omniverse libraries — including ovrtx, ovphysx and CAD-to-SimReady skills — are openly available on GitHub, giving AI agents tools to build workflows for inspecting scenes, testing changes and preparing 3D assets for simulation. A new blueprint for integrating Omniverse libraries in Blender is also now available on GitHub.

The libraries’ key capabilities include:

• NVIDIA RTX sensor simulation: ovrtx helps applications generate camera, lidar, radar and other sensor outputs from 3D scenes, so developers and AI agents can test how physical AI systems may perceive virtual environments.
• Physical behavior: ovphysx uses GPU-accelerated physics to bring realistic behavior to 3D scenes using properties such as collisions, mass, friction and motion, so teams can first test how objects and systems interact in simulation.
• Simulation-ready 3D objects: CAD-to-SimReady skills help convert computer-aided design (CAD) data to SimReady assets built on OpenUSD, giving 3D content the properties needed for physical AI simulation and virtual testing.

Software Makers Build With Omniverse Libraries
Software makers including SideFX and PTC, as well as startups ForgeCAD, Lightwheel, Moonlake AI and Palatial, are among the first to adopt and build with Omniverse libraries, now part of NVIDIA Agent Toolkit.

SideFX is using OpenUSD workflows, as well as ovrtx and ovphysx libraries, to explore how agents can help integrate Omniverse libraries into its Houdini procedural 3D content creation workflows, giving technical artists a path to generate, test physics and prepare content for simulation.

“Procedural 3D creation is essential to building the complex, controllable worlds needed for simulation, robotics and industrial AI,” said Kim Davidson, president and CEO of SideFX. “With NVIDIA Omniverse libraries and OpenUSD, SideFX is exploring how agent-ready tools can support Houdini workflows, helping technical artists review, test and prepare procedural content for simulation while staying in control of the creative process.”

The PTC Onshape CAD and product data management (PDM) platform is using OpenUSD and ovrtx to connect cloud-native design workflows with physical simulation, helping product design content stay connected with CAD, PDM, collaboration and simulation workflows.

“Engineering teams are seeking more connected ways to design, collaborate and simulate throughout the development process,” said Neil Barua, president and CEO of PTC. “PTC’s work with NVIDIA supports that broader vision, while NVIDIA Omniverse libraries help enable simulation-ready workflows that bring validation and testing closer to where products are designed.”

On display at SIGGRAPH, “SimReady” Blender is a sample workflow built in Blender with NVIDIA Omniverse libraries and NVIDIA NemoClaw™, showing how software makers can add agent-ready simulation capabilities — including NVIDIA RTX sensor simulation, physics and validation — into existing 3D applications while keeping creators in control. This is now openly available as a blueprint for integrating Omniverse libraries in Blender.

The demo also previews how these workflows, built with Omniverse libraries as part of NVIDIA Agent Toolkit, can run locally, from compact RTX-powered systems with NVIDIA RTX Spark™ to NVIDIA GB300-powered systems with NVIDIA DGX Station™. RTX Spark systems will be available this fall from ASUS, Dell Technologies, HP, Lenovo, Microsoft Surface and MSI, with models from Acer and GIGABYTE to follow. DGX Station systems are available to order from ASUS, Dell, GIGABYTE, HP, MSI, Supermicro and Exxact.

Startups, including those part of the NVIDIA Inception program, are also using Omniverse libraries and skills to add agent-assisted asset and scene preparation workflows. Palatial is using Omniverse CAD-to-SimReady skills to automate the creation and validation of SimReady assets at scale from CAD inputs. Lightwheel is using Omniverse Content Agents powered by OpenUSD in its SimReadyGen technology to generate physically accurate SimReady assets from text prompts.

ForgeCAD and Moonlake AI are exploring agent-driven 3D content workflows that use Omniverse capabilities to help generate, augment and prepare assets for physical AI simulation.

Watch the NVIDIA keynote at SIGGRAPH. Learn more about NVIDIA Omniverse libraries and explore available samples and documentation.

The post NVIDIA Agent Toolkit Expands With New Omniverse Libraries, Putting AI Agents to Work Building Simulation-Ready Worlds appeared first on Tech Scene ZA.

News Summary:

• Industry and research leaders including Dassault Systèmes, Databricks, Lilly, Schrödinger, Snowflake, the UW Medicine Institute for Protein Design and dozens others are adopting, and Anthropic and OpenAI are integrating, NVIDIA BioNeMo Agent Toolkit to bring agentic life sciences workflows to researchers and scientists.
• NVIDIA BioNeMo Agent Toolkit — including NVIDIA Nemotron, NemoClaw, OpenShell and BioNeMo — gives agents accelerated life sciences tools spanning biology, chemistry, genomics and drug discovery.
• New NVIDIA BioNeMo tools give agents the context and know-how to execute scientific computing — improving accuracy, task completion and token efficiency.

BIO—NVIDIA today announced NVIDIA BioNeMo Agent Toolkit, which provides domain-specific tools and skills for the agentic life sciences era.

Including more than a decade’s worth of NVIDIA life sciences libraries, tools and open models, the toolkit enables AI agents, scientists and labs to work together by gathering evidence, reasoning across findings, running computational experiments and recommending the next best steps to accelerate discovery.

It gives any agent or AI platform — from general-purpose assistants to specialized scientific agents, software platforms and in-house biopharma systems — the tools needed to synthesize and summarize scientific knowledge, call models, evaluate results, reason and execute next actions.

The toolkit includes NVIDIA BioNeMo™ and is powered by NVIDIA NIM™ microservices, NVIDIA Parabricks^®, NVIDIA NeMo™ and NVIDIA Nemotron™ technologies, along with accelerated computing and skills — providing an open and trusted foundation for agentic life sciences.

More than 50 leading companies are already using it to advance scientific discovery, tapping into agent-callable skills for tasks including protein structure prediction, molecular docking, generative chemistry, genomic analysis, protein design and biomarker discovery.

“Frontier models are the brains. BioNeMo is the scientific toolbox. Together, they give AI agents the skills of a PhD research assistant and the speed of a supercomputer,” said Jensen Huang, founder and CEO of NVIDIA. “For the first time, researchers can build AI agents that understand scientific knowledge, use scientific tools and execute scientific workflows. This is a new way to do science — one that can dramatically accelerate discovery across biology, chemistry, genomics and medicine.”

Open model and research organizations — including the Arc Institute, Open Molecular Software Foundation and the University of Washington’s Institute for Protein Design (IPD) — are working with NVIDIA to use BioNeMo to advance frontier models and make them more accessible through agent-ready workflows. The IPD collaboration has accelerated runtimes for state-of-the-art biodesign models like RosettaFold3, resulting in 2x faster performance than the prior-generation model, and many additional applications to accelerate protein design efforts are ongoing, giving researchers tools at a scale and cost not before possible.

“Every tool we’ve built for protein design is only as powerful as the scientists who can efficiently access it,” said David Baker, professor of biochemistry at the University of Washington School of Medicine and director of the Institute for Protein Design. “The next leap in science won’t come from a single discovery; it will come from the speed of iterative designs and agents that can repeatedly reason through the complexity of biology at a speed humans never could.”

Agent-Ready Tools and Skills for Life Sciences
Life sciences is one of the world’s most important scientific frontiers, with global scientific R&D reaching $3.8 trillion and annual pharmaceutical budgets approaching $300 billion.

Agentic workflows can help the industry iterate faster while reducing costs and maximizing the probability of success. With the toolkit allowing developers to transform general-purpose agents into life sciences agents in minutes, researchers can run experiments faster, continuously learn from results and close the loop between hypothesis and discovery, with some companies extending this iteration into physical labs.

A general-purpose agent can struggle to navigate scientific workflows efficiently, needing to infer the correct tools, inputs, outputs and biological meaning along the way. With BioNeMo Agent Toolkit, agents can call the right tools, interpret results more accurately and gain scientific insights faster and more reliably.

NVIDIA is optimizing the entire BioNeMo platform by turning libraries, models and frameworks into agent-callable tools.

This includes harnessing NVIDIA Agent Toolkit technologies such as NVIDIA Nemotron open models for the reasoning foundation, the NVIDIA NeMo RL library for reinforcement learning and NVIDIA NemoClaw™ blueprints for secure, private agents that can reason across tasks, call tools and interact with data continuously.

NVIDIA NIM microservices help agents call models and perform tasks. The NVIDIA OpenShell™ runtime provides a controlled executable environment.

The toolkit’s components enable agents to complete workflows such as:

• Virtual Screening: Agents can help researchers identify small-molecule drug candidates by generating and screening compounds, docking them to a target, predicting binding strength and filtering for drug-like properties. Then, the agent can output which candidates should be prioritized, compressing screening timelines from days to minutes.
• Genomic Analysis and Target Discovery: Agents can help researchers transform raw sequencing data into prioritized genetic insights and biological targets. NVIDIA Parabricks accelerates alignment and variant calling, while genomic foundation models score variant effects and the agent ranks the most disease-relevant candidates for further study.
• Protein Binder Design: Agents can help researchers design and validate candidates computationally before work begins, compressing traditionally labor-intensive design work.
• Deep Biomedical Research: Agents connect real-world data to reasoning models to improve the efficiency and accuracy of various scientific and clinical development processes, including literature review, protocol generation, clinical trial screening and pharmacovigilance with the NVIDIA Biomedical AI-Q Research Agent.
• Medical Imaging Analysis: Agents can help researchers process, segment, synthesize and reason over medical imaging data to support biomarker discovery, accelerating evidence generation across research workflows.

Life Sciences Ecosystem Builds With NVIDIA BioNeMo
Companies across the technology and life sciences ecosystem are using the toolkit to advance agentic workflows.

Frontier labs and scientific agent builders including Anthropic, Edison Scientific, Lila Sciences, OpenAI and Owkin are integrating with BioNeMo to help agents move from answering questions to completing scientific work. NVIDIA accelerated models and analysis libraries help shorten the time from hypothesis to insight.

Scientific data and workflow platforms from Benchling, Certara, Databricks, Snowflake and Seqera are using BioNeMo Agent Toolkit to connect data systems with AI-powered science. BioNeMo skills can help agents query biological and chemical datasets, prepare model-ready inputs, launch reproducible workflows, analyze outputs and return insights directly within the platforms scientists and data teams already use daily.

Diagnostics and pharmaceutical companies including Lilly and Natera are using BioNeMo Agent Toolkit to scale repeatable agentic workflows across discovery, translational research and clinical insight.

AI-native biology companies including Boltz, Basecamp Research, Chai Discovery, Dyno, PerturbAI and Proxima have collaborated with NVIDIA to develop tools to accelerate model-powered therapeutic design workflows.

Computer-aided drug discovery software providers including Dassault Systèmes, Cadence (OpenEye) and Schrödinger are integrating the toolkit’s capabilities into scientific applications used across discovery teams. Then, agents can help orchestrate molecular generation, docking and prediction, turning computer-aided design platforms into systems where researchers can ask questions, launch analyses and identify next-best actions faster.

Lab instruments and automation companies including Automata, HighRes, Tecan, Thermo Fisher and autonomous data generation platform Medra are connecting systems with computational discovery powered by BioNeMo skills.

AI clouds and AI infrastructure companies including Baseten, Modal and Nebius are using the toolkit to help developers build life sciences workflows as reliable hosted services. By supporting BioNeMo skills and tools through scalable application programming interfaces, managed compute and production inference environments, these companies can help move agentic biology workflows from prototypes into accessible services for researchers and enterprises.

Availability
BioNeMo Agent Toolkit and skills are available now through the NVIDIA developer resources page and GitHub.

The post NVIDIA Announces BioNeMo Agent Toolkit — Tools for Agents to Accelerate Scientific Discovery appeared first on Tech Scene ZA.

News Summary:

• NVIDIA Halos for Robotics is the industry’s only full-stack, open robotics safety system, extending NVIDIA Halos’ proven autonomous vehicle safety to robotics and physical AI to give machines that sense, decide and act in the real world a single common safety architecture.
• Safety is built in every layer, with NVIDIA IGX Thor and Holoscan Sensor Bridge for AI compute and sensor connectivity, the Halos OS software stack for safety functions and applications, and the NVIDIA Halos AI Systems Inspection Lab to help partners prepare for third-party certification with confidence.
• Humanoid robotics and physical AI innovator Agility is the first company to team with NVIDIA to incorporate elements of Halos for Robotics into its proprietary safety system, bringing a new standard of responsible automation to factories, warehouses and logistics operations.

NVIDIA today announced NVIDIA Halos for Robotics, the industry’s first full-stack, comprehensive safety system for robotics and physical AI that unifies AI compute and safety.

Agility, a leading humanoid robotics and physical AI company, is the first to use NVIDIA Halos for Robotics to build safety into its humanoids working in factories, warehouses and logistics operations for customers including Amazon, GXO, Schaeffler and Toyota Motor Manufacturing Canada.

The next generation of autonomous robots will operate in dynamic environments alongside humans, using AI foundation models, accelerated compute and distributed sensors. Scaling these systems requires a full-stack safety architecture.

NVIDIA Halos enables companies to rely on a standardized, unified safety architecture that connects AI compute, system software, sensor data, safety applications and inspection for robotic systems.

“Physical AI is transforming how factories, warehouses and logistics operations work, and robotics teams need a unified safety architecture to scale autonomous systems into these environments,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “With NVIDIA Halos for Robotics, developers and system builders can harness NVIDIA’s proven autonomous vehicle safety foundation to develop safer robots faster and bring them into industrial operations alongside workers with greater confidence.”

A Full-Stack Foundation for Robot Safety

Drawing on 18,600+ engineering years of autonomous vehicle safety development, NVIDIA Halos for Robotics provides developers with a common safety architecture for building, validating and deploying physical AI systems.

The system spans the key layers needed for robot safety:

• NVIDIA IGX Thor™ and NVIDIA Holoscan Sensor Bridge provide industrial-grade AI compute, built-in safety and sensor connectivity for real-time robotics and safety workloads.
• NVIDIA Halos OS provides the software stack for robotics safety, including Halos Core to support safety-related operating functions and safety applications built with the NVIDIA Halos Outside-In Safety Blueprint, which extends robot perception using external cameras and AI agents to dynamically control robot behavior in industrial settings.
• The NVIDIA Halos AI Systems Inspection Lab is the world’s first ANSI National Accreditation Board (ANAB)-accredited program for functional and AI safety for physical AI, helping partners prepare Halos integrations for third-party certification by leading certification bodies including TÜV Rheinland, UL Solutions, TÜV SÜD, exida, SGS and CertX.

“As AI-enabled robotics moves into industrial environments, the industry needs standardized, internationally recognized frameworks to assess safety across increasingly complex systems,” said Laurie E. Locascio, president and CEO of ANSI. “ANAB’s accreditation of the NVIDIA Halos AI Systems Inspection Lab confirms the program has the competence and impartiality to evaluate robotic AI systems against recognized safety requirements, giving companies a rigorous and internationally recognized foundation for their path to certification.”

Agility Incorporates Halos for Industrial Humanoids

Humanoid robots are designed to operate in dynamic environments alongside workers, equipment and other robots that are constantly in motion. That requires safety engineered for every layer of the stack.

Agility is extending its leadership in humanoid safety by teaming with NVIDIA to integrate NVIDIA IGX Thor and Halos Core into its proprietary safe human detection system for its humanoid robot Digit, which is designed for industrial work in logistics, manufacturing and warehouse operations. For Digit, NVIDIA IGX Thor delivers industrial-grade AI compute with built-in safety capabilities, while Halos Core supports the software layer for safety-related operating functions.

Agility will also participate in the NVIDIA Halos AI Systems Inspection Lab. Together, Agility and NVIDIA will use the lab to ensure Digit’s safety-related software, AI components and cybersecurity protections meet rigorous standards such as IEC 61508, ISO 13849 and ISO/IEC TR 5469 before final third-party certification.

“For humanoids to deliver value at scale, safety has to be built into the robot and validated across the entire system,” said Peggy Johnson, CEO of Agility. “Partnering with NVIDIA to implement and optimize the Halos for Robotics system extends our leadership in responsible automation, which is a nonnegotiable requirement for bringing humanoids safely into industrial workflows. This collaboration unlocks true human-robot teamwork, driving the long-term returns that will power next-generation manufacturing and logistics operations.”

A Robotics Safety Ecosystem Built for Scale

The NVIDIA Halos for Robotics ecosystem brings together partners across software, systems, sensors and silicon, industrial applications and certification bodies to support safety from development through deployment:

• Software: Acontis, FreeRTOS and QNX support the real-time operating environment, safety communications and embedded software layers needed for functional safety development.
• Embedded systems: Advantech and NexCobot deliver safety-designed NVIDIA IGX-based systems for robotics deployments.
• Sensors and silicon: Infineon, NXP Semiconductors, STMicroelectronics and Texas Instruments contribute sensor, safety microcontroller and other semiconductor technologies.
• Industrial applications: FORT Robotics, Inventec, KION Group, Lyte AI and Neurealm are developing functional safety agents using the NVIDIA Halos Outside-In Safety Blueprint.
• Assessment Agencies: TÜV Rheinland is inspecting NVIDIA IGX Thor, Halos OS and Holoscan Sensor Bridge for functional safety certification readiness, building on TÜV SÜD’s inspection of Thor SoC and Halos Core for ISO 26262.

The NVIDIA Halos AI Systems Inspection Lab includes more than 40 companies across manufacturers, certification bodies and safety vendors working to move safe physical AI systems from design to real-world deployment. TÜV Rheinland, TÜV SÜD, UL Solutions, exida, SGS and CertX all recognize the NVIDIA Halos AI Systems Inspection Lab as part of their certification process.

Availability

NVIDIA Halos Core for NVIDIA IGX™ is available in early access for registered developers in Linux and Linux plus QNX OS for Safety 8.0 configurations. The open source NVIDIA Halos Outside-In Safety Blueprint, part of the Halos Applications layer of Halos OS, is now available in early access on GitHu.

Learn more about NVIDIA Halos for Robotics in this technical blog and webpage. 

The post NVIDIA Announces Halos for Robotics, the Industry’s First Full-Stack Safety System for Physical AI appeared first on Tech Scene ZA.

Expanded Access to Next-Generation NVIDIA AI Infrastructure Equips Millions of Researchers to Advance AI HPC and Scientific Discovery

News Summary:

• Barcelona Supercomputing Center’s EuroHPC AI Factory, BavariaAI’s Blue Swan, IT4LIA, HLRS’s HammerHAI, NAISS’s Mimer EuroHPC AI Factory and more are building on next-generation NVIDIA AI infrastructure across 23 countries, accelerating the work of over 3 million researchers.
• NVIDIA AI infrastructure is powering over 90% of Europe’s AI factory buildout with 800 AI exaflops deployed or announced since last year.
• NVIDIA is supporting initiatives to accelerate AI-driven climate science, healthcare and clean-energy decarbonization, including work with Siemens Energy on hydrogen-capable gas turbine burners.
• Barcelona Supercomputing Center, CINECA, Fraunhofer and Jülich Supercomputing Centre are the latest institutes to use the CUDA-Q platform to integrate quantum processors, extending Europe’s leadership in quantum-GPU supercomputing.

ISC High Performance 2026 — NVIDIA today announced that a record 35 NVIDIA AI HPC supercomputers are in development across Europe — equipping more than 3 million researchers with next-generation infrastructure for continental AI, accelerated science and industrial innovation.

The systems represent Europe’s largest one-year expansion of supercomputers, spanning national supercomputing centers, AI factories and academic research institutions. Built on full-stack NVIDIA AI infrastructure, the systems will support research across climate science, healthcare, clean-energy decarbonization, quantum computing and fundamental science.

The NVIDIA Blackwell and NVIDIA Hopper™ platforms are powering the majority of Europe’s AI factory buildout, with 800 AI exaflops deployed or announced since last year. With NVIDIA Quantum InfiniBand networking, NVIDIA CUDA-X™ libraries, NVIDIA NIM™ microservices and NVIDIA AI Enterprise software, NVIDIA provides a full-stack platform for science, spanning model training, simulation, inference and agentic AI.

“AI is the new instrument of science, and Europe is building the infrastructure to put it in the hands of millions of researchers,” said Jensen Huang, founder and CEO of NVIDIA. “With NVIDIA accelerated computing, researchers can simulate more complex systems, train scientific AI models and build agentic AI workflows that turn Europe’s data and expertise into breakthroughs for the world.”

Supercomputers including Barcelona Supercomputing Center’s EuroHPC MareNostrum5 AI upgrade, BavariaAI’s Blue Swan, IT4LIA, HLRS’s HammerHAI and NAISS’s Mimer EuroHPC AI Factory are among those based on advanced NVIDIA AI infrastructure.

“BSC is committed to building AI infrastructure that advances science, industry and society,” said Mateo Valero Cortés, director of the Barcelona Supercomputing Center. “With the upgrade to MareNostrum5 and NVIDIA accelerated computing, the consortium composed of Spain, Portugal and Türkiye will make available to European researchers the tools to tackle some of the world’s most complex challenges, from climate modeling to biomedical discovery.”

“With the project ‘Blue Swan Platform,’ Bavaria is working on an innovative and independent, multimodal AI foundation model for important application areas like health and robotics,” said Bavarian Minister of Science Markus Blume. “This will allow us to provide a powerful AI tool for science and industry that fully meets European standards. For this ambitious goal, we are currently building a special computing infrastructure at Friedrich-Alexander University in Erlangen — the biggest GPU cluster you can find at any German university.”

“IT4LIA marks a strategic step in strengthening Europe’s AI and HPC ecosystem, providing a high-performance infrastructure to the research and innovation ecosystem,” said Gabriella Scipione, high-performance computing director of CINECA. “Through advanced accelerated computing, EuroHPC with CINECA, the Italian Ministry of University and Research, and the Italian Cybersecurity Agency are creating a trusted environment for open AI model development and applications across agritech, cybersecurity, meteorology, climate and manufacturing, strengthening Europe’s technological autonomy and reinforcing Italy’s role in the global AI landscape.”

“Germany has long been a leader in engineering, science and industrial innovation,” said Michael Resch, director of the High-Performance Computing Center Stuttgart. “With HammerHAI, Germany’s first AI factory, we are building on that foundation with secure, national AI infrastructure that will help researchers and industrial users accelerate simulation, inference and scientific discovery, strengthening Europe’s ability to turn advanced computing into real-world breakthroughs.”

Europe’s latest AI infrastructure expansion includes advancements at:

• Barcelona Supercomputing Center’s AI Factory, the first EuroHPC AI-specific installation: Will expand MareNostrum 5 with NVIDIA GB300 NVL72 and NVIDIA GB200 NVL4 systems, connected by the NVIDIA Quantum-X800 InfiniBand platform. Delivering up to approximately 20 exaflops of AI training and 33 exaflops of AI inference performance, the system will accelerate generative AI, climate modeling, health and biotech research, sustainable agriculture, energy systems and government AI services.
• BavariaAI’s Blue Swan: Brings 1,000 GPUs via NVIDIA GB200 NVL4 systems and NVIDIA Quantum-2 InfiniBand networking to FAU Erlangen and LRZ supercomputing centers. Delivering up to 11 exaflops of AI training and 22 exaflops of AI inference performance, the platform will support Bavaria’s foundation model initiative, advancing open multimodal models for science, public administration, health research, robotics and perception.
• IT4LIA: An AI factory with over 8,000 GPUs via NVIDIA GB200 NVL4 systems, NVIDIA Quantum-X800 InfiniBand networking and NVIDIA AI Enterprise software, delivering 82 exaflops of AI training and 164 exaflops of AI inference performance.
• HLRS’s HammerHAI: Will equip Germany’s first AI factory with over 850 GPUs via NVIDIA GB200 NVL4 systems connected with NVIDIA Quantum-X800 InfiniBand. Delivering up to approximately 8 exaflops of AI training and 15 exaflops of AI inference performance, HammerHAI will give researchers and industrial users secure AI infrastructure for engineering simulation, large language model inference and scientific discovery.
• NAISS’s Mimer AI Factory, owned by the EuroHPC Joint Undertaking: Hosted at Linköping University, this supercomputer will deploy 100 NVIDIA GB200 NVL4 systems, totaling 400 GPUs, with NVIDIA ConnectX^®-8 networking. Delivering up to 4 exaflops of AI training and about 7 exaflops of AI inference performance, Mimer AI Factory will advance Sweden’s AI science ecosystem across life sciences, materials research, autonomous systems, trustworthy AI and data-driven innovation.

AI for Climate and Decarbonization

NVIDIA is supporting initiatives that deploy AI infrastructure and software to help researchers apply AI to scientific challenges including climate and Earth systems modeling, biomedical research, and clean-energy technologies such as fusion, hydrogen and carbon capture.

Accelerated simulation and industrial engineering are already enabling breakthroughs in clean-energy research.

Siemens Energy is using the Siemens Xcelerator portfolio, accelerated by NVIDIA technologies, including NVIDIA Omniverse™ libraries, CUDA-X and AI infrastructure, to unify design, computational fluid dynamics simulation and manufacturing for gas turbines built to run on up to 100% hydrogen — a complex physics challenge involving extreme heat, fluid dynamics and combustion behavior.

The workflow supports rapid, simulation-driven design iterations for complex gas turbine burner configurations, followed by fast technology validation using additively manufactured combustors. This cuts simulation times by up to 77% to advance hydrogen-capable, low‑carbon gas turbines.

Quantum-GPU Supercomputing Advances in Europe

NVIDIA is enabling European supercomputing centers and institutions to develop and run useful hybrid quantum-classical applications using NVIDIA CUDA-Q™, an open, qubit-agnostic platform for hybrid computing, extending Europe’s leadership in quantum-GPU supercomputing.

CINECA, EuroHPC and Pasqal are integrating a neutral-atom QPU at the CINECA supercomputing center. The Pasqal hybrid environment is deploying the CUDA-Q platform through integration with Slurm. CUDA-Q provides Pasqal and CINECA with a platform for developing and running quantum applications including for optimization and materials science use cases.

Fraunhofer FOKUS is facilitating the integration of NVIDIA CUDA-Q with the quantum programming language Eclipse Qrisp. Qrisp, initiated at Fraunhofer FOKUS and being further developed by the Eclipse Foundation, enables researchers to more easily write complex quantum algorithms which can then be simulated, optimized and run with NVIDIA CUDA-Q.

The Barcelona Supercomputing Center has recently deployed a new analog quantum computer from QPU builder Qilimanjaro Quantum Tech, through the EuroHPC JU initiative. Qilimanjaro integrated NVIDIA CUDA-Q into its quantum software development kit, QiliSDK. Qilimanjaro is also working toward making its QPU available in the NVIDIA CUDA-Q platform for seamless control of quantum accelerated workflows at BSC.

Researchers at the Jülich Supercomputing Centre, working with a team from NVIDIA, set a world record by fully simulating a universal 50-qubit quantum computer. The simulation was run on JUPITER, powered by its NVIDIA GH200 Grace Hopper Superchips. Jülich’s JUQCS-50 (for 50 qubits) quantum simulator allows researchers to now test the largest possible quantum problems on supercomputers, to scale quantum computing.

The post Europe Unveils a Record 35 New NVIDIA AI Supercomputers appeared first on Tech Scene ZA.

RTX Spark — a 1-Petaflop Superchip, the Full CUDA and RTX Ecosystem, and Windows-Native Agents — a New Beginning for Personal Computers

News Summary:

• NVIDIA RTX Spark powers the world’s first Windows PCs purpose-built for personal agents, featuring 1 petaflop of AI performance, industry-leading power efficiency, full-stack NVIDIA AI and graphics technology, and up to 128GB of unified memory.
• NVIDIA and Microsoft collaborate to deliver a native Windows experience for personal agents, including new security primitives and NVIDIA OpenShell to run agents securely on primary devices.
• RTX Spark lets creators, AI developers and gamers render ultralarge 90GB+ 3D scenes, edit 12K 4:2:2 video, generate 4K AI videos, run 120B-parameter LLMs with up to 1 million tokens context using agents locally, and play AAA games at 1440p and over 100 frames per second.
• Adobe is rearchitecting Photoshop and Premiere from the ground up for RTX Spark to deliver 2x faster AI and graphics performance.
• RTX Spark-powered slim Windows laptops with all-day battery life and premium displays, as well as compact desktop PCs available this fall from ASUS, Dell, HP, Lenovo, Microsoft Surface and MSI, with models from Acer and GIGABYTE to follow.
   

NVIDIA GTC Taipei—NVIDIA today unveiled NVIDIA RTX Spark™, a new superchip that reinvents Windows PCs for the era of personal AI agents — offering a new class of computer that moves from tool to teammate.

Designed for AI, creating and gaming, RTX Spark brings together 30 years of NVIDIA innovation — including NVIDIA CUDA®, NVIDIA RTX™, DLSS, FP4, NVIDIA TensorRT™, NVIDIA OptiX™, Reflex and G-SYNC® — to slim Windows laptops with all-day battery life and small, ultraefficient desktop PCs.

“The PC is being reinvented,” said Jensen Huang, founder and CEO of NVIDIA. “For forty years, you launched apps. Click. Type. With RTX Spark and Microsoft Windows, you ask — and the PC does the work. RTX Spark brings everything NVIDIA has built — CUDA, RTX, our AI platform — into a single superchip. Local agents. Frontier models. Creative workflows. RTX games. All on a laptop. This is the new PC. The personal AI computer.”

The RTX Spark superchip features an NVIDIA Blackwell RTX GPU with 6,144 CUDA cores and fifth-generation Tensor Cores with FP4 precision, connected via the NVIDIA NVLink®-C2C chip-to-chip interconnect to a high-performance, 20-core NVIDIA Grace™ CPU.

MediaTek, a market leader in Arm-based system-on-a-chip designs, collaborated with NVIDIA on the custom CPU design, contributing to its best-in-class power efficiency, performance and connectivity.

Purpose-Built for Personal Agents
AI agents have reached an inflection point, with open source projects such as OpenClaw and Hermes Agent achieving record-breaking numbers on developer networks like GitHub and OpenRouter. Yet broad adoption has been limited by the inability to run agents securely and privately on users’ primary PCs.

NVIDIA and Microsoft are partnering to address this challenge by delivering a robust, secure Windows platform for on-device agents.

The collaboration begins with a strong foundation — new Windows security primitives and the NVIDIA OpenShell™ runtime — to ensure agents run safely and under full user control.

The new Windows primitives deliver identity, containment, policy and end-to-end security capabilities to build and run agents natively. NVIDIA OpenShell provides additional policy capabilities for the user to define what agents can and cannot do, the ability to intelligently route queries to local models based on the user’s privacy policies, and the ability to disguise personal information in queries sent to cloud models.

This robust security and privacy layer is being adopted by leading agent developers such as Hermes Agent and OpenClaw in their new Windows apps. These new apps will make it easy and secure for users to access powerful on-device agents that can execute tasks in Windows applications, reason through cross-app workflows, generate images and video, code plug-ins and apps, and semantically search local files.

“We are strong supporters of deploying agents like OpenClaw securely into the Windows ecosystem,” said Vincent Koc, chief architect at the OpenClaw Foundation. “Running solutions like OpenShell and the Microsoft security primitives on RTX Spark will enable users to leverage a fully integrated stack for private, personal agents running on device.”

Powering agents on local devices requires both robust security and performant hardware. RTX Spark features up to 1 petaflop of AI compute and 128GB of unified memory to meet the processing demands of on-device agents.

“At Nous, we expect tasks to increasingly run on device as personal agents like our Hermes Agent become more capable and ubiquitous,” said Dillon Rolnick, CEO of Nous Research. “RTX Spark and NVIDIA OpenShell give Hermes users a powerful and secure environment for agents to run and work alongside you. You realize you’re buying a full-fledged assistant, not a typical laptop.”

From this foundation, NVIDIA and Microsoft’s collaboration will expand to new RTX Spark-powered Windows agent experiences accessible from the Windows taskbar user interface.

“Our goal is to deliver unmetered intelligence to every home and every desk with Windows,” said Satya Nadella, chairman and CEO of Microsoft. “RTX Spark marks a real breakthrough towards that vision.”

Full-Stack RTX Creating and Gaming
RTX Spark delivers the full NVIDIA AI and graphics technology stack to creators, AI developers and gamers.

Users can render ultralarge 90GB 3D scenes with OptiX and DLSS, edit 12K 4:2:2 video with the NVIDIA Blackwell decoder, run 120-billion-parameter large language models with 1 million tokens context, and play AAA games at 1440p resolution and over 100 frames per second with ray tracing, DLSS and Reflex.

In addition to support for existing technologies, RTX Spark will power new RTX capabilities, including DLSS 4.5 Ray Reconstruction featuring a second-generation transformer model — coming to Blender 5.3 and dozens of games — and RTX Video with 4x Frame Generation, coming to ComfyUI.

RTX technology boosts performance, enhances image quality and adds powerful AI features in over 1,000 games and applications. Over 100 Windows software providers such as Adobe, Blackmagic Design, Blender, CapCut, ComfyUI and OTOY, and game developers such as KRAFTON, NetEase, Remedy Entertainment, Riot Games and XBOX are embracing the new RTX Spark platform.

• “Blackmagic Design and NVIDIA have accelerated video production for many years,” said Grant Petty, CEO of Blackmagic Design. “Portable, lightweight RTX Spark laptops with fantastic battery life are going to help our customers take the next leap in on-the-go production.”
• “Rendering is entering a new era where path tracing, AI and real-time workflows are converging into powerful new neural media artist tools,” said Jules Urbach, CEO of OTOY. “Our work with NVIDIA to bring OTOY Octane with Render Network support to RTX Spark will deliver a new class of portable systems for creators.”
• “The combination of RTX Spark’s processing capabilities and large unified memory will make it one of the best-performing laptops to run diffusion models,” said Yannik Marek, cofounder and creator of ComfyUI. “ComfyUI users can now run highly complex, multimodal workflows and generate ultra-high-resolution images and videos with unprecedented speed on a portable device.”
• “RTX Spark laptops change the game by multiplying the amount of context processing and putting it directly into a beautiful, portable chassis,” said Georgi Gerganov, founder of llama.cpp. “Highly optimized models running locally through llama.cpp with RTX Spark’s AI performance will unleash the next wave of personal, private agents.”
• “We worked closely with NVIDIA to support a great gaming experience and are excited to expand access to XBOX on RTX Spark devices, making it easy for players to discover and play with XBOX on PC,” said Jason Ronald, vice president of Next Generation at XBOX.
• “RTX Spark allows even more gamers to experience NetEase titles like ‘NARAKA: BLADEPOINT’ on ultrathin, high-performance laptops the way the developers intended,” said Long Cheng, senior vice president of Thunderfire BU at NetEase.
• “Remedy is looking forward to bringing its games together with NVIDIA to these stunning new RTX Spark laptops,” said Mika Vehkala, chief technology officer of Remedy Entertainment.
   

Delivering Powerful Creative Experiences
NVIDIA is partnering with Adobe to rearchitect Adobe Premiere and Photoshop for RTX Spark. Firefly-powered Generative Fill in Photoshop and Generative Extend in Premiere are among the hundreds of accelerated tools that deliver creative power, precision and control. RTX Spark takes these capabilities further, delivering up to 2x faster AI, editing, coloring and effects across creative workflows.

“The best creative work in the world happens in Adobe tools from Adobe Firefly to Photoshop and Premiere, and the expansion of our partnership with NVIDIA and Microsoft will make those experiences faster and more powerful than ever,” said Shantanu Narayen, chair and CEO of Adobe. “Together, we are building AI-native creative experiences for RTX Spark that deliver the performance, intelligence and responsiveness people need to create at the pace of their ambition.”

Adobe Premiere will feature a new video pipeline that taps into RTX Spark’s unified memory, Blackwell GPU and TensorRT software, delivering real-time performance for editing and color correction, GPU-accelerated AI performance and more efficient rendering of complex timelines. In addition, Adobe’s Substance 3D Painter and Stager will run natively on RTX Spark for smoother and more responsive 3D texturing and scene creation workflows.

Adobe’s next-generation Photoshop engine will be optimized for GPU-accelerated compositing, enabling live filters, high dynamic range and modern natural brushing. The AI-native pipeline is built to harness the full power of RTX Spark, including TensorRT.

Adobe will further extend Premiere and Photoshop to allow users to create, edit and design with Windows agents, providing creators with a collaborative teammate to accelerate their workflows.

Updates to Adobe’s creative apps like Premiere, Photoshop and Substance are expected to start rolling out alongside RTX Spark availability.

Premium Designs in All Sizes
Engineered to be as slim as 14 millimeters and as light as three pounds, RTX Spark laptops will be available in 14- to 16-inch sizes and feature precision-machined aluminum chassis that blends durability with a clean, modern design. Color-accurate tandem OLED displays with NVIDIA G-SYNC technology provide stunning visuals for creative work and immersive gaming.

Small, ultraefficient RTX Spark desktops are built for agents, creative workloads, gaming and everyday productivity. Major hardware makers are rallying around RTX Spark, with many designs already in development.

• “The next generation of PCs must be powerful, intelligent, mobile and beautifully designed,” said Jonney Shih, chairman of ASUS. “With RTX Spark, ASUS has the platform to build systems that define the future of personal computing.”
• “Creators shouldn’t have to choose between portability and performance,” said Michael Dell, chairman and CEO of Dell Technologies. “With RTX Spark, Dell is delivering RTX performance and massive unified memory in the XPS 16 Creator Edition, a laptop built for people who demand the most from their hardware.”
• “Developers and creators demand uncompromising performance wherever they work in the agentic AI era,” said Bruce Broussard, interim CEO of HP Inc. “Our upcoming HP OmniBooks powered by NVIDIA will be one of the thinnest RTX Spark laptops, combining NVIDIA’s RTX performance, the breadth of the Windows ecosystem and the efficiency of unified memory to deliver unprecedented portable power for agentic developers.”
• “The NVIDIA RTX Spark represents an exciting leap forward for AI-native computing,” said Yuanqing Yang, chairman and CEO of Lenovo. “Our long-standing partnership with NVIDIA continues to turn breakthrough innovation into real-world impact. With Lenovo’s engineering and design expertise, global scale and comprehensive AI device portfolio, we are delivering a whole new level of AI experiences to creators, gamers and AI developers together, offering more choices to customers to build smarter AI for all.”
• “For users who want AI acceleration, advanced content creation and strong gaming performance in a single device, RTX Spark is a compelling new platform,” said Jeans Huang, CEO of MSI. “It has enabled MSI to redefine what a compact, efficient PC can deliver.”
• “Surface has always exemplified the best of what a Windows PC can be. With Surface Laptop Ultra, we’re bringing that focus to creators, developers and engineers who need serious performance in a device that is thoughtfully designed, portable and deeply connected to the Windows tools and platform they count on,” said Brett Ostrum, corporate vice president of Surface at Microsoft. “Our work with NVIDIA will deliver a Surface built for the way ambitious work gets done.”
   

NVIDIA and Microsoft’s collaboration to deliver agents in the Windows experience extends from personal to frontier agents with NVIDIA DGX Station™ for Windows — scaling the Blackwell architecture to enterprise developers by putting an AI supercomputer for running agents deskside.

Availability
RTX Spark laptops and compact desktops will be available this fall from leading manufacturers including ASUS, Dell, HP, Lenovo, Microsoft Surface and MSI, with models from Acer and GIGABYTE to follow.

Tune in to the keynote at Microsoft Build, running June 2-3, to learn more about Windows agent capabilities for developers, including new Windows security and containment primitives and NVIDIA OpenShell.

Watch Huang’s keynote and learn more at NVIDIA GTC Taipei.

The post NVIDIA and Microsoft Reinvent Windows PCs for the Age of Personal AI appeared first on Tech Scene ZA.

Korea’s Leading Telco to Add NVIDIA-Powered AI Cloud Capacity Built on NVIDIA DSX AI Factory Architecture to Accelerate AI Startups, Robotics and Industrial Physical AI

• SK Telecom plans to build a gigawatt-scale AI Cloud in Korea using the NVIDIA DSX platform, with the first AI factory planned to come online in 2027.
• The AI Cloud will support sovereign, physical and agentic AI services for enterprises and industries across Korea, building on SK Telecom’s network, data center and enterprise infrastructure expertise.
• NVIDIA DSX will serve as the AI factory architecture blueprint, combining NVIDIA accelerated computing, systems, software and partner technologies to improve time to production and token performance per megawatt.
• NVIDIA and SK Group are planning to expand their collaboration from AI infrastructure deployments to joint research on next-generation AI factory architectures.
   

June 7, 2026 – NVIDIA and SK Telecom today announced that SK Telecom plans to build a gigawatt-scale AI Cloud in Korea using the NVIDIA DSX™ platform, with the first AI factory coming online in 2027.

An AI Cloud is large-scale AI infrastructure comprised of AI factories that manufacture tokens, building blocks of intelligence, from data. Unlike conventional large-scale providers offering general-purpose cloud services, AI Clouds specialize in GPU-based cloud computing tailored specifically for AI workloads across training, inference and agentic AI.

SK Telecom’s AI Cloud will be built on the NVIDIA DSX full-stack reference architecture of software, hardware and operations producing the lowest-cost tokens at maximum energy efficiency.

SK Telecom’s AI Cloud will power training, inference and agentic workloads including sovereign, physical and enterprise AI services for companies and industries across Korea, with the vision to expand to greater Asia regions.

The initiative reflects Korea’s role as one of the world’s most advanced pro-AI industrial economies. Korean companies lead in telecommunications, memory, semiconductors, manufacturing, robotics, mobility and consumer technology — industries where AI is moving from research labs and chatbots into secure, production-grade deployments.

“Telecom networks are becoming national AI infrastructure,” said Jensen Huang, founder and CEO of NVIDIA. “They connect people, companies, devices and machines — and now they can become the backbone of new AI clouds. With NVIDIA DSX, SK Telecom can build Korea’s AI cloud at scale and bring agents, enterprise and physical AI to the companies and industries that power Korea and the world.”

“Through our close partnership with NVIDIA, we have now secured full-stack AI infrastructure capabilities, from chips to data center operations,” said Chey Tae-won, Chairman of SK Group. “We will work with NVIDIA to tackle GPU, memory and energy challenges and become a leading AI factory player shaping Asia’s AI ecosystem.”

SK Telecom AI Cloud to Scale Agentic and Physical AI for Industries and Enterprises
The new SK Telecom AI Cloud is designed to serve rising demand for AI infrastructure, as accelerated AI computing growth continues to increase.

The new infrastructure builds on SK Telecom’s leadership in physical AI and agentic AI development. At GTC Taipei last week, SK Telecom announced its latest work in applying digital twins to SK hynix semiconductor fabs using NVIDIA Omniverse™ libraries, optimizing the technology for complex, large-scale manufacturing environments.

In April, SK Telecom revealed that it has adopted open source NVIDIA Nemotron™ datasets to train the A.X K1 model as part of the Korea government’s Sovereign AI Foundation Model Project.

Moreover, as part of this collaboration, SKT will become an NVIDIA Cloud Partner, joining a global program through which participants use NVIDIA’s latest AI infrastructure, software and developer ecosystem to deliver excellent AI performance and economics through AI cloud services.

NVIDIA DSX Platform Delivers Rapid Design, Ultraefficient Operations
The NVIDIA DSX platform is engineered from the ground up with extreme codesign for AI factories, built and operated to drive lowest token cost and accelerate time to first production across NVIDIA chips, systems, software, facilities and partner technologies.

NVIDIA DSX MaxLPS™ software delivers the lowest token cost by maximizing token performance per megawatt. NVIDIA DSX OS™ is the operating layer that helps providers increase revenue and improve margins with open source, modular software for lifecycle management, runtime consistency, health automation, resiliency and multi-tenant AI factory operations.

NVIDIA and SK Group to Pursue Joint Research for Next-Gen AI Infrastructure
NVIDIA and SK Group today announced plans to pursue joint research to codevelop next-generation AI factory architecture, extending their collaboration beyond infrastructure deployment.

The companies will focus on silicon-to-grid innovation across accelerated computing, memory technologies and data center operations. NVIDIA and SK Group companies including SKT will also explore projects for full-stack AI factory optimization to drive more efficient, scalable and resilient AI services.

The post SK Telecom and NVIDIA Build AI Infrastructure to Power Korea’s AI Innovation appeared first on Tech Scene ZA.

Taipei, Taiwan – Jun. 3, 2026 – MSI, a global leader in high-performance server solutions, returns to COMPUTEX 2026 (Booth #J0605a) with liquid-cooled AI platforms built on NVIDIA MGX and NVIDIA DGX Station architectures for large-scale AI infrastructure and deskside AI development. Designed for demanding AI workloads, the CG681-S6093 AI server and XpertStation WS300 based on NVIDIA DGX Station architecture, deliver high-performance AI computing from data centers to deskside AI workflows.

“As AI infrastructure continues scaling in performance and density, liquid cooling is becoming essential for modern AI data centers,” said Danny Hsu, General Manager of MSI’s Enterprise Platform Solutions. “MSI combines liquid-cooled system design with NVIDIA AI platforms to help customers deploy scalable AI infrastructure with greater performance and efficiency.”

CG681-S6093 6U Liquid-Cooled AI Server and NVIDIA MGX Rack-Scale Architecture

Built on NVIDIA MGX architecture, the CG681-S6093 6U liquid-cooled AI server supports dual AMD EPYC™ processors and up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs supporting up to 1200W TDP, delivering the compute density required for AI training and HPC workloads. Equipped with NVIDIA ConnectX-8 SuperNICs providing up to 8×400Gbps Ethernet connectivity, the platform enables high-bandwidth, low-latency communication for distributed AI environments, with a liquid-cooled architecture designed to sustain peak multi-GPU performance.

At the rack level, the liquid-cooled rack-scale system supports up to 4 CG681-S6093 GPU systems within a 48RU configuration, enabling scalable compute for multi-node AI workloads. NVIDIA Spectrum-4 SN5600 scale-out Ethernet and SN2201 out-of-band switches provide high-performance connectivity across AI clusters, while integrated power and thermal design help sustain performance and streamline deployment for large-scale AI training and inference.

XpertStation WS300 Desktop AI Supercomputer

The XpertStation WS300 based on NVIDIA DGX Station architecture, brings data-center-class AI computing to the desktop for AI development, fine-tuning, and inference workloads. Powered by NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip with up to 748GB coherent memory and 7.1TB/s HBM3e bandwidth, the system supports Windows-based AI development while enabling high-speed CPU-GPU data sharing for large AI models and data-intensive workflows. Dual 400GbE networking powered by NVIDIA ConnectX-8 SuperNIC supports high-bandwidth connectivity for multi-node AI workflows, while the liquid-cooled design helps sustain AI performance within a compact form factor. During COMPUTEX week, the XpertStation WS300 is also showcased in NVIDIA GTC Taipei, at Taipei International Convention Center, which brings together more applications and use cases.

The post MSI Brings Liquid-Cooled NVIDIA MGX and NVIDIA DGX Station to COMPUTEX 2026 appeared first on Tech Scene ZA.

At Microsoft Build, the companies showcased how developers can build, run and scale agentic and physical AI across Windows devices, Azure cloud and local deployments through a unified accelerated computing stack.

The agentic AI moment has arrived, but delivering on its promise requires more than good models. It also takes fast hardware, secure runtimes, a responsive data layer and models tuned for long-running reasoning. NVIDIA and Microsoft are bringing that full stack to developers across Windows devices, Azure cloud and local deployments.

At Microsoft Build, NVIDIA founder and CEO Jensen Huang joined Microsoft chairman and CEO Satya Nadella’s keynote via livestream from Taipei to discuss the expanded partnership: NVIDIA RTX Spark and DGX Station for Windows, NVIDIA GPU-accelerated Microsoft Fabric, NVIDIA open models on Microsoft Foundry, the NVIDIA OpenShell secure runtime in GitHub Copilot and the next generation of NVIDIA-powered AI factories.

Reinventing Windows for Agents: From RTX Spark to DGX Station for Windows

NVIDIA and Microsoft are reimagining Windows PCs for the age of AI agents. With RTX Spark laptops and small desktops, and DGX Station for Windows deskside AI supercomputers, developers can build, tune and run agents natively on Windows.

RTX Spark is a new beginning, powering the world’s first Windows PCs purpose-built for personal agents, with 1 petaflop of AI performance, up to 128GB of unified memory, all-day battery life, and full AI and graphics performance unplugged. Bringing over 30 years of NVIDIA innovation, including CUDA, RTX, DLSS and TensorRT, systems arrive this fall from Microsoft Surface, ASUS, Dell, HP, Lenovo and MSI.

DGX Station for Windows is the most powerful deskside AI supercomputer for building and running agents on Windows enterprise applications and workflows. Powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip with up to 748GB of coherent memory and 20 petaflops of FP4 performance, it runs frontier models of up to 1 trillion parameters for always-on enterprise agents. Systems are expected from ASUS, Dell, GIGABYTE, HP, MSI and Supermicro in Q4. Both products run NVIDIA OpenShell, a secure-by-design runtime for autonomous agents.

Read more in this Microsoft blog: “Introducing a powerful new chapter for Windows PCs, accelerated by NVIDIA RTX Spark”

Powering Agentic Workflows at Enterprise Scale With NVIDIA Open Models on Microsoft Foundry

Agentic AI runs on a system of models. With NVIDIA, Anthropic and OpenAI models —plus Hermes special agents — now on the hosted agents in Foundry Agent Service, enterprises can bring agentic systems to life on Azure with built-in identity and governance. Anthropic’s Claude models now run natively on NVIDIA GB300 Blackwell Ultra systems on Azure, with customer availability in the weeks ahead.

NVIDIA Nemotron 3 Ultra, a new open frontier reasoning model for long-running agents across coding, research and enterprise workflows, is available this month on Foundry managed compute, alongside Nemotron 3.5 ASR for speech recognition and Nemotron 3.5 Content Safety. Developers can compose Nemotron alongside frontier and local models, optimizing cost and quality for each workflow.

NVIDIA’s open model portfolio on Foundry now spans agentic, physical and scientific AI. NVIDIA Cosmos 3, the first fully open omnimodel for physical AI, brings vision reasoning, world simulation and action generation. NVIDIA Earth-2 AI weather models are available through Microsoft Planetary Computer Pro and Foundry for enterprise forecasting and risk analysis.

NVIDIA Agent Toolkit and NVIDIA NemoClaw blueprints give developers an open source platform to build production agents on Foundry. NVIDIA CUDA-X libraries including cuDF, cuOpt, AI-Q and NeMo are now accessible to agents as domain-specific skills.

Learn more in this Build breakout session: “Orchestrate Special Agents with NVIDIA Nemotron Models on Microsoft Foundry.”

Accelerating Enterprise Data Warehouses for the AI Era

Data fuels agentic AI, and fast access to it is critical. 

NVIDIA accelerated computing is now built into Microsoft Fabric Data Warehouse, with Microsoft’s internal benchmarking delivering SQL execution up to 6x faster than the CPU-powered baseline and up to 7x faster than three other leading cloud data warehouse providers for high-concurrency workloads. 

The enterprise data layer can now keep pace with AI agents that continuously query and reason over data, the result of years of deep engineering collaboration between NVIDIA and Microsoft, from research to production.

Read more in this Microsoft blog: “Microsoft Build 2026: Building agentic apps with Microsoft Fabric and Microsoft Databases”

Advancing Physical AI and Autonomous Systems

Physical AI is the next frontier for agents. 

Microsoft is integrating NVIDIA’s open source physical AI skills and tools with Azure and its Physical AI Toolchain. Developers get a unified platform, powered by Cosmos 3’s mixture-of-transformers architecture, to simulate, train and deploy autonomous systems, including robots, autonomous vehicles and industrial systems that can perceive, reason, plan and act in the physical world. Cosmos 3 ranks first among open models on key benchmarks for vision reasoning, world generation and action generation.

Enhancing Azure Local and Foundry Local With NVIDIA RTX PRO 6000 Blackwell Server Edition and Nemotron Models

Agentic AI is moving beyond the cloud. 

Microsoft is bringing Foundry Local on Azure Local to the NVIDIA RTX PRO 6000 Blackwell Server Edition platform. Paired with the NVIDIA Nemotron open model family, enterprises can run high-performance AI workloads where their data resides, whether in on-premises, hybrid or sovereign environments, without sacrificing performance or governance. 

Foundry Local on Azure Local now supports multinode deployments and the vLLM runtime, scaling inference for manufacturing, energy, sovereign data centers and other latency-sensitive scenarios.

Learn more in these Microsoft blogs: “Unlocking the possibilities of physical AI with Foundry Local and Azure Local,” “Scale On-Prem AI with Foundry Local on Azure Local” 

Bringing Secure Agent Development to GitHub Copilot With NVIDIA OpenShell

As agents move from coding assistance to autonomous execution, they need real capability without real credentials. 

NVIDIA OpenShell, now integrated into GitHub Copilot, solves this: Each agent runs isolated in its own sandboxed container, and every outbound call is evaluated against policy before it can reach files, networks or credentials. Policies are written as code, versioned in the repository and updatable on the fly. OpenShell is open source under Apache 2.0, model-agnostic and spans on-premises, hybrid and cloud environments.

Learn more in this Build lightning session: “Secure Agent Workflows with GitHub Copilot and NVIDIA OpenShell.”

Fairwater Wisconsin Goes Live, Validated for NVIDIA Vera Rubin

Microsoft’s Fairwater Wisconsin AI factory is now live, ahead of schedule, running hundreds of thousands of NVIDIA Grace Blackwell systems as a single AI factory, and connected with a similar AI factory in Georgia to deliver a scalable and distributed AI system for the most demanding frontier models. Through joint engineering on power, cooling, NVIDIA Spectrum-X Ethernet and the new Multipath Reliable Connection (MRC) transport protocol, Microsoft’s Fairwater AI data center designs are optimizing token economics.  

In addition, Microsoft has already validated the NVIDIA Vera Rubin platform, now in full production, for deployment across Azure data centers. 

Vera Rubin slots in alongside Blackwell with no retrofits, delivering up to 10x inference throughput per megawatt and reducing cost per agentic token by an order of magnitude. Built-in NVIDIA Confidential Computing protects models and data as agents reason at scale. The NVIDIA Dynamo inference framework extends those gains into software, accelerating model cold starts on AKS and bringing Kubernetes-native distributed inference orchestration via NVIDIA Grove.

Explore the full lineup of NVIDIA sessions, demos and hands-on labs at Microsoft Build.

The post NVIDIA Partners With Microsoft on Unified Stack for Agentic AI Deployment, From Windows Devices to Cloud to Local appeared first on Tech Scene ZA.