AI News Archive: June 1, 2026 — Part 18
Sourced from 500+ daily AI sources, scored by relevance.
- US tightens controls on AI chip sales to China
The move aims to close a loophole that may have allowed Chinese firms’ subsidiaries in places such as Malaysia to obtain Nvidia Blackwell processors.
- US takes step to halt Nvidia AI chip shipments to Chinese firms outside China
UPDATE 1-US takes step to halt Nvidia AI chip shipments to Chinese firms outside China
- OpenAI wants you to have a personal robot; starts hiring for robotics division
The robotics division grew out of OpenAI's world simulation research program, led by Aditya Ramesh, the researcher also known for his work on DALL-E.
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
A robot is helping an ailing couple stay in their home. Are more to come for an aging population? The Boston Globe
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
The decades-long quest to build home robots that are both helpful and lifelike — spurred on by fictional machines like The Jetsons’ humanoid maid Rosie —- is still mostly a pipe dream, but some developers are getting closer.
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
A robot is helping an ailing couple stay in their home. Are more to come for an aging population? Houston Chronicle
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
A robot is helping an ailing couple stay in their home. Are more to come for an aging population? AP News
- A robot is helping an ailing couple stay in their home
The decades-long quest to build home robots that are both helpful and lifelike — spurred on by fictional machines like The Jetsons’ humanoid maid Rosie —- is still mostly a pipe dream, but some developers are getting closer
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
The decades-long quest to build home robots that are both helpful and lifelike — spurred on by fictional machines like The Jetsons’ humanoid maid Rosie —- is still mostly a pipe dream, but some developers are getting closer
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
A robot is helping an ailing couple stay in their home. Are more to come for an aging population? Boston Herald
- A robot is helping an ailing couple stay in their home. Are more to come for an aging population?
After outliving Booker T. Bones, their second service dog, Brenda and Brian Marquis still needed help with some of the more difficult parts of daily life.
- A virtual tomato training arena for harvesting robots
A virtual tomato training arena for harvesting robots EurekAlert!
- Microsoft Surface Laptop Ultra Announced With Blackwell RTX GPU, Nvidia RTX Spark Superchip
Microsoft Surface Laptop Ultra was announced on Sunday as the company’s most powerful Surface laptop ever built. Developed in collaboration with Nvidia, the Redmond-based tech giant says its new laptop is aimed at creators, developers, AI researchers, and professionals. The Surface Laptop Ultra features Nvidia's latest Blackwell RTX graphics architecture with up to ...
- Microsoft Surface Ultra is a portable AI supercomputer powered by Nvidias RTX Spark chip
Microsoft's Surface Ultra is the most powerful Surface yet, and it comes with an Nvidia RTX Spark inside.
- MSI Claw 8 EX AI+ to bring Intel Arc G3 Extreme to gaming handhelds
MSI's upcoming Claw 8 EX AI+ handheld gaming console is set to debut with Intel's Arc G3 Extreme chip, an 8-inch 120Hz display, Xbox Mode and up to 32GB RAM
- Is the MSI Claw 8 EX AI+ the New Gaming Handheld to Beat? video
The MSI Claw 8 EX AI+ and Acer Predator Atlas 8 are running Intel's new Arc G3 Extreme processor, while Asus unveiled an ROG Xbox Ally X20. Which one is right for you?
- Apple’s much-awaited AI smart glasses delayed until 2027: Report
Apple’s much-awaited AI smart glasses delayed until 2027: Report
- NVIDIA announces Isaac GR00T reference humanoid robot for academic research
NVIDIA announced the NVIDIA Isaac GR00T Reference Humanoid Robot, the first open humanoid robot reference design built on NVIDIA Jetson Thor and the NVIDIA Isaac GR00T open development platform. The reference design helps democratize frontier humanoid robotics research by providing access to advanced hardware and an open software stack without requiring proprietary platforms. As demand for general-purpose humanoids accelerates, researchers still face a fragmented process spanning hardware integration, data collection, simulation, training, evaluation and deployment. The NVIDIA Isaac GR00T Reference Humanoid Robot unifies development by bringing a Unitree H2 Plus humanoid robot and Sharpa Wave tactile five-finger hands (the “body”), with NVIDIA Jetson Thor-powered onboard compute and Isaac GR00T software and workflows (the “brain”) into a single integrated reference design, helping research teams move faster from robot bring-up to skill development and real-world validation. With NVIDIA’s compute and open software stack at the center, the reference design gives research teams a more unified, secure foundation for advancing humanoid robotics. “Humanoid robots will bring physical AI to the world’s largest industries, opening a multitrillion-dollar economic opportunity,” said Jensen Huang, founder and CEO of NVIDIA. “The NVIDIA Isaac GR00T Reference Humanoid Robot gives researchers a single, open platform to make breakthrough discoveries toward general-purpose physical intelligence.” State-of-the-art humanoid robot for physical AI development The NVIDIA Isaac GR00T Reference Humanoid Robot is a state-of-the-art platform that brings the key building blocks for frontier humanoid research into one system, pairing a human-scale robot body with dexterous manipulation, sensing, control and onboard AI compute. The reference design features: Unitree H2 humanoid chassis, standing nearly 6 feet tall and weighing 150 pounds, with 31 degrees of freedom across the body for human-scale testing. Dual Sharpa Wave tactile five-finger hands, enabling dexterous manipulation with 22 degrees of freedom and bringing the robot to 75 degrees of freedom across the body and hands. Multi-view sensing, including a head-mounted stereo camera with wide field of view (140 degrees horizontal, 102 degrees vertical), wrist cameras for close-range manipulation and an inertia measurement unit for motion tracking. Whole-body control, with arm torque of up to 120 Newton-meters, leg torque of up to 360 Newton-meters, a rated arm payload of 7 kilograms and peak payload of 15 kilograms, unlocking more capable lifting and reach. NVIDIA Jetson AGX Thor T5000 onboard compute, featuring an NVIDIA Blackwell GPU with 2,070 FP4 teraflops of AI performance, a 14-core Arm CPU, 128GB of unified memory and a configurable 40- to 130-watt power range for real-time sensor processing and robot inference. Connectivity across Ethernet, Wi-Fi 6, Bluetooth 5.2, USB and an array of microphones and speakers for voice interaction. Battery for extended operation, with a 15Ah, 0.972kWh capacity and about three hours of life. On-remote emergency stop function for quickly disengaging the robot safely. Isaac GR00T provides full-stack platform for humanoid development The NVIDIA software stack provides the development environment for simulation, training, evaluation and deployment, while researchers retain control of their robot data, training data, telemetry and logs. The Isaac GR00T platform includes: NVIDIA Isaac Teleop to capture high-quality robot demonstration data for training and policy development. NVIDIA Isaac GR00T open foundation models to support humanoid reasoning, learning and multitask behavior. NVIDIA Isaac Sim and Isaac Lab to simulate, train, test and evaluate robot policies before real-world deployment. Accelerated NVIDIA Isaac ROS middleware to move trained policies onto robots. NVIDIA Jetson Thor to run real-time, on-robot inference and control. Its modular design lets robotics teams use the full platform or integrate selected capabilities into existing development pipelines, helping them scale humanoid development without rebuilding the same infrastructure for each robot or task. The NVIDIA Isaac GR00T developer platform will also support the Unitree G1 humanoid robot, extending the same development approach to a robot widely used by researchers and humanoid developers across leading institutions. Accelerating the robotics research ecosystem Leading research institutions, including Ai2, ETH Zurich, Stanford Robotics Center and UC San Diego’s Advanced Robotics and Controls Laboratory will use this humanoid robot reference design to advance frontier humanoid robotics research. “Robotics moves fastest when researchers can build on open platforms, share code and test ideas on real machines,” said Steve Cousins, Executive Director of the Stanford Robotics Center. “The NVIDIA Isaac GR00T Reference Robot gives our students and collaborators an open humanoid reference design with dexterous hands, onboard AI compute and the NVIDIA Isaac GR00T development platform for creating, comparing and sharing robot behaviors on physical hardware.” “ETH Zurich’s robotics research aims to advance machines that can move, perceive and manipulate reliably in the real world,” said Marco Hutter, Prof., ETH Zurich’s Robotic Systems Lab. “The NVIDIA Isaac GR00T reference design gives our teams a state-of-the-art humanoid platform for collecting data, testing algorithms and validating robot behaviors with the NVIDIA Isaac GR00T development platform.” “To make progress toward general-purpose robots, researchers need platforms that are both capable and broadly accessible,” said Deepak Pathak, Co-founder and CEO of Skild AI. “A reference design lets more researchers participate in frontier humanoid research and move from ideas to experiments faster. This helps push the whole robotics research ecosystem forward.” “At Ai2, our mission is to accelerate robotics through open science,” said Dieter Fox, Senior Research Director at Ai2 and Prof., University of Washington. “The NVIDIA Isaac GR00T Reference Robot, built on NVIDIA’s open technologies, provides our researchers with the hardware and software components necessary to continue our work in broadly competent robotics.” “Advancing robotics research for real-world problems requires humanoids that can move, interact and manipulate with precision in dynamic environments,” said Michael Yip, Prof., UC San Diego, and Director of the Advanced Robotics and Controls Laboratory. “An integrated platform that connects robot hardware, data capture, policy learning and physical evaluation can help researchers accelerate loco-manipulation research and develop more useful real-world systems.” NVIDIA Research will also use this reference design to advance Isaac GR00T open models, frameworks and hardware. The NVIDIA Isaac GR00T Reference Humanoid Robot will be available from Unitree in late 2026. The NVIDIA Isaac GR00T reference workflow for Unitree G1 is expected to be available soon on GitHub and Hugging Face for robot developers.
- NVIDIA unveils Vera, the CPU for agents
NVIDIA has announced that the world’s technology leaders are planning to adopt NVIDIA Vera, the first CPU built for AI agents. Now in full production, NVIDIA Vera is a new class of processor enabling 1.8x faster task completion compared with x86 CPUs to drive diverse workloads across industries — including agentic AI, reinforcement learning and data processing — generating more data center token revenue. Building on the success of NVIDIA Grace CPUs, which have nearly 2.5 million shipments to date, Vera takes CPU performance and energy efficiency to new levels for the most demanding AI workloads in modern data centers — where agents move from answering basic questions to taking actions, running code, using tools and evaluating results. Customers exploring the Vera CPU include finance leader NYSE, global AI labs Anthropic, OpenAI and SpaceXAI, and hyperscalers ByteDance, CoreWeave, Lambda, Nebius, Nscale and Oracle Cloud Infrastructure (OCI). Vera is also being integrated into AI infrastructure from world-leading system manufacturers such as Dell Technologies, HPE, Lenovo and Supermicro, along with Taiwan system builders. “AI agents will be the largest users of computing,” said Jensen Huang, founder and CEO of NVIDIA. “Vera is the first CPU designed for that future — built to run agentic AI at hyperscale with extraordinary performance, efficiency and programmability.” “At the NYSE, our focus is to optimize the latency, throughput and reliability of the systems underpinning our unrivaled infrastructure,” said Lynn Martin, President of NYSE Group. “The NYSE processes more than 1.1 trillion messages per day, and in collaboration with Redpanda and HPE, using NVIDIA Vera CPUs, we will be scaling our capacity while further optimizing latency to power a high-performance, resilient and AI-ready market infrastructure.” Anthropic, the AI innovator behind Claude, is evaluating adding Vera to scale CPU-intensive agentic workloads. “Scaling compute is an important accelerant for the growth of models,” said James Bradbury, Head of Compute at Anthropic. “We’re excited to see Vera emerge as a promising part of the ecosystem when solving for agentic workloads.” OCI Supercluster powered by NVIDIA Vera represents the next frontier in hyperscale AI supercomputing. “Oracle Cloud Infrastructure is rapidly scaling AI infrastructure to meet surging demand for training, inference and agentic AI,” said Mahesh Thiagarajan, Executive VP of Oracle Cloud Infrastructure. “By deploying NVIDIA Vera CPUs, OCI will support high-throughput reasoning and data processing workloads across next-generation AI environments.” According to Phoronix, which offers a comprehensive, open source benchmarking suite, NVIDIA Vera delivered the fastest overall performance across agentic workloads including code compilation, Python, Java and database processing. These workloads sit on the critical path of modern AI factories, including for agent tool use and sandbox execution, where faster CPU performance delivers higher agent throughput and interactivity. Custom CPU for agentic era AI factory economics are shifting from cores per dollar to tokens per dollar, requiring CPUs that complete agentic, data-processing and orchestration work faster and more efficiently. Vera is powered by Olympus, a custom NVIDIA CPU core engineered for the CPU work behind that shift, from Python runtimes and sandboxed code execution to orchestration logic and analytics pipelines. Vera is built to process more instructions, anticipate application behavior and move data across large numbers of concurrent environments, queries and data processing tasks — featuring 88 Olympus cores, Spatial Multithreading, and a LPDDR5X memory subsystem that delivers up to 1.2TB/s of bandwidth. This helps agents spend less time waiting on CPU-bound steps and lets AI factories keep accelerators moving. The Vera CPU can also be deployed across the full AI factory — from the standalone CPU infrastructure to tightly coupled accelerated systems. Vera helps AI factories deliver higher end-to-end throughput and faster time to solution for users, improving responsiveness and efficiency across training, inference and agentic execution. Vera serves as the host CPU for NVIDIA Vera Rubin platforms through second-generation NVIDIA NVLink-C2C interconnect technology, which provides up to 1.8TB/s of coherent bandwidth between CPU and GPU. It extends NVIDIA Confidential Computing at rack scale, protecting agentic workloads. The NVIDIA Vera BlueField-4 STX processor integrates Vera with high-performance networking, storage acceleration and in-silicon security to create secure-by-design AI-native data platforms. Extensive ecosystem support Vera CPUs are available in dense, liquid-cooled racks for large-scale agentic AI and reinforcement learning environments, as well as flexible two-socket air-cooled systems for enterprise, cloud, data processing and AI factory deployments. Leading infrastructure providers offering Vera CPU-based systems include Aivres, ASRock Rack, ASUS, Compal, Dell, Foxconn, GIGABYTE, HPE, Hyve Solutions, Inventec, Lenovo, MiTAC Computing, MSI, Pegatron, Quanta Cloud Technology (QCT), Supermicro, Wistron and Wiwynn. Major original equipment manufacturers — Dell, HPE, Lenovo and Supermicro — will be offering Vera in standalone CPU server configurations, the first standard CPU option beyond x86. Leading cloud service providers planning to deploy Vera CPUs include Akamai, ByteDance, Cloudflare, CoreWeave, Crusoe, Lambda, Nebius, Nscale, Oracle Cloud Infrastructure, Redpanda, Starburst, Together AI and Vultr. Vera systems will be available from system builders and cloud partners starting this fall.
- NVIDIA Vera Rubin ramps into full production to power agentic AI factories
NVIDIA has announced the NVIDIA Vera Rubin platform is ramping into full production to power agentic AI factories worldwide. Taiwan’s top server makers and global supply chain leaders are manufacturing Vera Rubin-based systems at scale — fueling AI labs, cloud providers and hyperscalers to build tomorrow’s intelligence. Vera Rubin delivers NVIDIA’s most extensive POD-scale platform — five purpose-built racks operating as one massive AI supercomputer for agentic workloads. The platform unifies NVIDIA Vera Rubin NVL72 systems, NVIDIA Vera CPU, NVIDIA Groq 3 LPX, NVIDIA Vera BlueField-4 STX storage and NVIDIA Spectrum-6 SPX Ethernet racks into a fully integrated system. Vera Rubin delivers 10x agent throughput at scale compared with the previous-generation NVIDIA Grace Blackwell platform. “Agentic AI is a new kind of workload. One prompt can launch a thousand-step journey of reasoning, retrieval, tool use and response generation,” said Jensen Huang, founder and CEO of NVIDIA. “Vera Rubin was built for this moment — an AI factory engine that delivers intelligence at scale, with the performance, efficiency and security needed to power the next industrial revolution.” Vera Rubin ramp Vera Rubin marks the third generation of NVIDIA MGX rack-scale systems. With a proven, open source MGX design, hundreds of NVIDIA supply chain ecosystem partners — 150 in Taiwan alone — across 350+ factories and 30 countries are ramping Vera Rubin. Top system builders, infrastructure software and storage partners are in full-scale production of Vera Rubin. This includes Dell Technologies, HPE, Lenovo and Supermicro, as well as AIC, Aivres, ASRock Rack, ASUS, Cloudian, Compal, DDN, Everpure, Foxconn, GIGABYTE, Hitachi Vantara, Hyve Solutions, IBM, Inventec, MinIO, MiTAC Computing, MSI, NetApp, Nutanix, Pegatron, Quanta Cloud Technology (QCT), VAST Data, WEKA, Wistron and Wiwynn. Building fabric for million-GPU AI factories To support scale-out and scale-across AI factory deployments, the Vera Rubin platform introduced the NVIDIA Spectrum-X Ethernet Photonics, the world’s first co-packaged-optics (CPO)-based switches with 200Gb/s SerDes — now in production. Spectrum-X Ethernet Photonics, a new generation of switching technology built on CPO, delivers 5x better power efficiency, 5x longer AI uptime and 1.3x faster time to deployment than networks using traditional transceivers. By simplifying design and freeing more power for compute, NVIDIA co-packaged optics networking provides the foundational fabric for million-GPU AI factories, with CoreWeave, Lambda and Oracle Cloud Infrastructure among the first ecosystem partners and adopters. The NVIDIA Vera Rubin platform also integrates NVIDIA BlueField®-4 DPUs, featuring software-defined networking at speeds of up to 800Gb/s and built-in multi-tenant isolation. With the NVIDIA BlueField-4 Advanced Secure Trusted Resource Architecture, customers can simplify network operations, improve tenant isolation and gain greater control across million GPU AI clusters. Secure AI for AI factories AI factories are increasingly processing proprietary data, regulated content and mission-critical models in agentic workflows. This requires advanced infrastructure security tailored to autonomous agents in shared or cloud environments where infrastructure cannot be implicitly trusted. The Vera Rubin platform was designed with full-stack NVIDIA Confidential Computing for a trusted execution environment at rack scale. Vera Rubin NVL72 combines Vera CPUs, Rubin GPUs, NVIDIA NVLink™ networking and security features into a unified platform, encrypting data across high-speed interconnects. This provides hardware-level attestation to ensure the system is tamper-proof. Cloud providers CoreWeave, Firmus, GMI Cloud, IBM Cloud, IREN, Lambda, Microsoft Azure, Nebius, Nscale, SpaceXAI, and Vultr are adopting NVIDIA Confidential Computing. Delivering this level of protection at POD scale also requires a programmable software layer capable of enforcing, orchestrating and adapting security policies across the entire system. The NVIDIA DOCA™ software platform delivers advanced security across every Vera Rubin platform rack and layer of the AI factory — protecting data, agents, context memory and AI inference through capabilities enforced directly in BlueField-4 silicon. DOCA enables multi-tenant network isolation, zero-trust policy enforcement, runtime threat detection and end-to-end encryption at speeds of up to 800Gb/s, all without taxing host CPU resources, so enterprises can scale AI factories with confidence. Accelerating buildout of AI factories The NVIDIA DSX platform provides the complete design and operational foundation for Vera Rubin AI factories — unifying reference designs, simulation, infrastructure software, facilities and ecosystem technologies to help build and operate energy-efficient AI factories optimized for lowest token cost. Built for the Vera Rubin POD architecture, DSX aligns every layer of the stack — from silicon and systems to lifecycle management and multi-tenant operations — dramatically accelerating deployment and setting a new bar for operational reliability and resiliency at scale. Dell Technologies, HPE, Lenovo and Supermicro together with ASUS, Foxconn, GIGABYTE, Pegatron, Quanta Cloud Technology (QCT), Wistron and Wiwynn are adopting NVIDIA DSX to accelerate AI factory ramp with Vera Rubin. Production shipments of Vera Rubin are set to begin starting this fall.
- Nvidia ramps up production of Vera Rubin, the foundation of the next generation of AI factories
Nvidia Corp. said early Monday at the Computex conference in Taipei that it’s gearing up the production of its forthcoming Vera Rubin platform, which is set to become the foundation of a new generation of artificial intelligence factories that will dominate the enterprise infrastructure story for years to come. The company unveiled Vera Rubin for […] The post Nvidia ramps up production of Vera Rubin, the foundation of the next generation of AI factories appeared first on SiliconANGLE .
- Taiwan’s industry titans turbocharge world’s AI infrastructure buildout with NVIDIA
Semiconductor and electronics manufacturing leaders are using NVIDIA AI to speed manufacturing from fabs to factory floors as they ramp up the production of NVIDIA Vera Rubin NVL72 infrastructure for agentic AI factories. Taiwan is home to more than 500 NVIDIA ecosystem partners. More than 1 million NVIDIA MGX rack components for NVIDIA Vera Rubin infrastructure come together in Taiwan, from across 25 factory sites. As Vera Rubin ramps into full production to power agentic AI factories worldwide, that ecosystem spans the full supply chain — from key wafer and chip partners such as TSMC, SPIL, Kinsus, KYEC and UMTC, to manufacturing and systems leaders including Foxconn, Pegatron, Quanta Cloud Technology (QCT), Wistron and Inventec. But, these partners are doing more than building AI factories. They are applying accelerated computing, simulation, AI agents and physical AI to their own operations, creating a model for how AI can make advanced manufacturing faster, more efficient and adaptive. Taiwan’s manufacturing leaders build future of AI, with NVIDIA AI Across chipmaking, server assembly and factory operations, Taiwan’s manufacturing leaders are applying NVIDIA technologies to reshape how AI infrastructure is designed, built, tested and scaled. TSMC is applying NVIDIA CUDA-X libraries and AI models across computational lithography, transistor and process simulation, advanced process control, yield analysis, fab operations and inspection. NVIDIA cuLitho improves cost-effectiveness or cycle time by 20-50% over CPU-based computational lithography at the same cost of ownership, while the NVIDIA cuEST library improves semiconductor material simulation by 50x on average, cuML library, Metropolis platform and TAO Toolkit help accelerate material simulations, improve process control and strengthen rare-defect inspection. Foxconn is using the new NVIDIA Factory Operations Blueprint and NemoClaw blueprints to build MoMClaw, its manufacturing operations management agent, connecting sensor and machine signals with specialized agents that give plant managers and operators real-time answers and action plans through a natural language interface with NVIDIA OpenShell privacy controls and safety guardrails. Foxconn estimates an 80% speed up in root-cause analysis time, a 15% increase in labor productivity and a 10% decrease in machine failure rates. Foxconn also uses DeepHow’s SOP Verification vision AI system using NVIDIA Cosmos and the NVIDIA Metropolis Blueprint for video search and summarization (VSS) to gain greater visibility into complex manufacturing processes, resulting in improved manufacturing efficiency and boosting first pass yield by 3%. The company is also applying NVIDIA Isaac Teleop, Isaac Sim, Isaac Lab and ROS 2 to wheeled humanoid robots operating in its factories, supporting precision assembly tasks such as pick and place, dual-arm collaboration and force-controlled screw fastening. Foxconn’s $1.4 billion AI cloud supercomputing center in Taiwan — powered by 10,000 NVIDIA GPUs — is being built with the NVIDIA GB300 NVL72 hybrid cooling architecture. Quanta Cloud Technology (QCT) is using NVIDIA Omniverse-based digital twins to accelerate factory planning, giving engineering, operations and logistics teams shared access to design data for faster layout feedback, optimized workflows and improved space utilization. QCT is also working with its subsidiary Techman Robot on a physical AI developer kit that uses QuantaGrid systems for data generation and model training. Techman Robot is using NVIDIA Jetson Thor and the Isaac GR00T platform to support the development of its next-generation robots, including the TM Xplore I humanoid, for advanced industrial tasks such as server fan assembly. Wistron is using the NVIDIA Omniverse DSX Blueprint, the NVIDIA PhysicsNeMo framework and Cadence Reality DC Design to simulate burn-in environments for stress-testing across global manufacturing sites and to optimize AI server manufacturing. Running on Wistron’s NVIDIA AI infrastructure with NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, NVIDIA Omniverse and NVIDIA Metropolis libraries, these workflows speed layout analysis by as much as 70% and cut facility power demand by 20% through dynamic rack optimization. Pegatron is adopting the NVIDIA Omniverse DSX Blueprint, developing simulation-ready assets, and connecting design data, thermal simulation, digital twins and physical qualification — accelerating the design and deployment of AI factories. Pegatron is also using NVIDIA’s Defect Image Generation physical AI agent skill with NVIDIA Cosmos world foundation models and Isaac Sim to generate synthetic defect data, reducing AI visual inspection deployment time by 67% and operational effort by 10%. Inventec is using the Defect Image Generation agent skill in its Observation Agent to generate synthetic defect data for automated optical inspection. In notebook cosmetic inspection, internal validation produced more than 10,000 synthetic defect images and showed the potential to reduce real-world data collection and manual labeling by about 30%, shorten AI deployment time by about 25% and improve anomaly detection by about 10%. As NVIDIA Vera Rubin ramps into full production, Taiwan’s manufacturing leaders are showing how AI infrastructure becomes part of its own manufacturing engine — using accelerated computing, simulation, agents and physical AI to build the next generation of AI systems.
- NVIDIA factory operations blueprint gives factories a new AI brain
At GTC Taipei, and at COMPUTEX, NVIDIA announced the NVIDIA Factory Operations Blueprint (FOX) — a reference design for building an autonomous factory manager agent that continuously monitors and reasons across the real-time data and orchestrates a fleet of speciality agents and machines to quickly resolve issues at scale. FOX helps developers build secure, centralized factory manager agents for orchestrating and optimizing specialized industrial AI agents for quality control, material transport and worker safety. Built with NVIDIA NemoClaw, AI-Q Blueprint and NVIDIA Nemotron open models, the blueprint provides a customizable foundation for connecting factory systems, automating model development and running intelligent operations at scale. The blueprint is optimized to run on NVIDIA DGX Station, the ultimate deskside AI supercomputer companion for factory managers. DGX Station is powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip, featuring 20 petaflops of FP4 performance and 748GB of coherent memory, and is capable of running large AI models up to 1 trillion parameters, making it ideal for developing and running powerful AI agents locally. The superchip features the NVIDIA Blackwell Ultra GPU connected to a high-performance NVIDIA Grace CPU using the NVIDIA NVLink-C2C interconnect to deliver best-in-class system communication and performance, ideal for lightning-fast interactions between NemoClaw and AI models. Key capabilities of the FOX blueprint include: Connecting factory systems and agents: FOX integrates with industrial data sources, machines, applications and robot fleets, and can connect to specialized agents from leading software developers through standard application programming interfaces and agent skills. Automating AI model training: Using NVIDIA TAO skills, factory manager agents can automate the full model-training lifecycle — identifying accuracy gaps, sourcing or synthetically generating training data, fine-tuning models and redeploying them into production. Operating intelligent factory workflows: Visual inspection, process compliance and material transport agents can be managed with NVIDIA open models and blueprints, including the NVIDIA Metropolis Blueprint for video search and summarization (VSS). Real-time factory data can also be visualized in an operational twin built with NVIDIA Omniverse libraries. Taiwan manufacturers Advantech, Foxconn, Pegatron and Wistron are the first to deploy autonomous factory manager agents using the NVIDIA FOX blueprint and NemoClaw. Foxconn, the world’s largest electronics manufacturer, is using the FOX blueprint and NemoClaw to build MoMClaw, a manufacturing operations multi-agent system. Running alongside a live production work, MoMClaw connects sensors, machine signals and other digital systems with hundreds of specialized agents in a single agentic layer — giving plant managers and operators real-time answers and action plans through a natural language interface with NVIDIA OpenShell privacy controls and safety guardrails. With MoMClaw, Foxconn projects an 80% improvement in root cause analysis time, a 15% increase in labor productivity and a 10% decrease in machine failure rates. Pegatron is using the FOX blueprint and NemoClaw to build a factory manager agent that orchestrates specialized agents for material transport, AI inspection, standard operating procedure guidance and machine-to-machine coordination. With the factory manager agent, Pegatron can orchestrate robot utilization more efficiently, eliminating the need for expensive standby equipment, with an estimated 15% reduction in asset redundancy costs. Advantech has introduced the AI Factory Brain, an intelligent multi-agent system led by a factory manager agent built with the FOX blueprint and NemoClaw. Advantech has deployed the factory manager agent in its own factories to autonomously manage energy across HVAC and lighting specialized agents and projects to cut energy consumption by 10%. Wistron is adopting the FOX blueprint and using NVIDIA Cosmos, NVIDIA Nemotron open models and the NVIDIA Metropolis VSS blueprint to build surface-mount technology agents that analyze and orchestrate production-line operations, enabling real-time root-cause analysis and quality control. To monitor manufacturing operations, improve quality, verify standard operating procedures and improve worker safety, companies including DeepHow, Overview AI, Roboflow and Spingence are building specialized agents powered by NVIDIA AI and the NVIDIA VSS blueprint: * DeepHow is using the Metropolis VSS Blueprint and Cosmos 3 to develop a standard operating procedure agent for Foxconn that supports assembly of Bianca boards for NVIDIA GB300 servers. Running on NVIDIA RTX PRO Servers, the agent accurately understands complex assembly motions to help improve first-pass yield by 3%, minimizing rework and production waste. * Spingence is using the NVIDIA Defect Image Generation skill, NVIDIA Cosmos open vision language model and NVIDIA TAO Toolkit for fine-tuning to develop a factory manager agent for Cooler Master that connects automated optical inspection and model-building agents, achieving 99.6% defect recall, reducing defect escapes by 78% and increasing inspection capacity by 3x. * Overview AI is using an NVIDIA agent skill for defect image generation and NVIDIA Cosmos to help Amphenol improve manufacturing efficiency with its Advanced GenAI Toolkit. The toolkit generates synthetic defect data and deploys visual inspection AI models 12x faster, reducing time to first inference to under 30 minutes across more than 300 products. * Roboflow is using NVIDIA Cosmos to develop a model-building agent for Corning Fiber Optics that generates synthetic defect images when training data is limited, delivering near-perfect detection rates and demonstrates the potential to reduce daily manual image review.
- NVIDIA DSX gives infrastructure builders playbook for AI Factories
NVIDIA has announced the NVIDIA DSX platform, which gives infrastructure builders a complete playbook to create AI factories. NVIDIA DSX brings together open source, modular software libraries, application programming interfaces, reference designs, NVIDIA accelerated computing platforms and partner technologies into a common, codesigned platform for AI factory design, deployment and operations. NVIDIA is the only company that builds the full AI factory. By aligning every layer of the stack across compute, software, facilities and partner technologies, DSX provides infrastructure builders with a proven framework to design, deploy, and operate AI factories at scale. The integrated platform accelerates deployment, improves operational reliability and resiliency at scale and enables a broad ecosystem of solutions designed to turn every megawatt into more intelligence at the lowest token cost. “We’re not just shipping chips — we’re giving every infrastructure builder a complete playbook to build AI factories,” said Jensen Huang, founder and CEO of NVIDIA. “With the DSX platform, you can simulate the entire factory before you spend a dollar, validate performance before a single rack is installed and operate with the kind of reliability that production AI demands.” DSX platform elements DSX now spans the full stack, from silicon and systems to infrastructure software, facilities and partner technologies. The latest additions to the platform include new open source software: DSX MaxLPS: A suite of technologies to maximize token performance per megawatt within a fixed power budget, enabling lowest token cost for AI factories. Combining 45-degrees-Celsius liquid cooling with in-rack technologies that optimize performance per watt, DSX MaxLPS lets operators run up to 40% more GPUs at their most energy-efficient operating point with minimal impact on workload performance. DSX OS: Open source, modular software purpose-built for AI factory operations, providing lifecycle management, intelligence scheduling, runtime consistency, health automation, resiliency, multi-tenant operations and platform services. DSX MaxLPS and DSX OS join an existing set of features under the DSX platform: DSX Reference Design: Generation-specific, validated AI factory architectures covering compute, networking, storage, hardware cluster design and facilities infrastructure — including power, cooling and controls, as well as civil, structural and architectural design. DSX Sim: High-fidelity simulation layer for the AI factory lifecycle, helping NVIDIA, partners and customers to model, validate and optimize infrastructure decisions from planning and design through deployment and operations. DSX Flex: Connects AI factories to power-grid services, enabling dynamic workload adaptation to grid signals such as load shedding, demand response and pricing events, and orchestrating renewable and hybrid power across utility, onsite renewables and storage. DSX Exchange: Enables scalable, secure integration of compute, network, energy, power and cooling plant signals between IT, operational technology and operations agents. Growing DSX ecosystem NVIDIA is partnering with industry-leading Taiwan system manufacturers to expand the DSX ecosystem, supporting the buildout of AI factories with extreme codesign at their core. NVIDIA cloud partners CoreWeave, Crusoe, Firmus, IREN, Lambda, Nebius, Nscale and Yotta Data Services are deploying core components of the DSX platform stack — DSX Sim, DSX MaxLPS and DSX OS — to reduce risk, improve GPU utilization and bring AI cloud capacity online faster. Dell Technologies, HPE, Lenovo and Supermicro together with ASUS, Foxconn, GIGABYTE, Pegatron, Quanta Cloud Technology (QCT), Wistron and Wiwynn are building NVIDIA DSX-ready systems and contributing simulation-ready assets that enable customers to deploy complete, full-stack AI factory solutions at global scale. Within the ecosystem, model-based systems engineering serves as the bridge between rack design to facility deployment, for an AI infrastructure optimized for token performance per megawatt. Quanta Cloud Technology (QCT) and Pegatron are working with Dassault Systèmes to create a live AI factory digital twin configurator to automate rack-to-facility design with increased quality and reduced workload. The adoption of DSX Sim by system manufacturers expands the NVIDIA Omniverse DSX Blueprint ecosystem, deepening integration with software partners Cadence, PTC and Siemens. DSX Flex is powering a commercial, multi-megawatt pilot with Emerald AI and Silicon Valley Power to demonstrate grid-responsive AI factories that can dynamically adjust power consumption in response to utility signals while protecting AI workload performance, helping safeguard grid reliability and affordability for customers while unlocking additional power capacity to support AI growth. Partners are adopting various DSX OS software components for lifecycle management, multi-tenancy, security, health automation, resilience and platform services. Ecosystem partners adopting DSX OS components include Aible, BeyondAI, Bhashini, DCAI, Mirantis, OpenNebula Systems, Rafay, Red Hat, Sarvam, Simplismart, Spectro Cloud, Supermicro, vCluster and Vultr.
- Nemotron 3 Ultra announced: high-speed, leading US open weights intelligence
NVIDIA announces Nemotron 3 Ultra, a high-speed open weights model.
- Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
- Develop Physical AI Reasoning, World, and Action Models with NVIDIA Cosmos 3
Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what's...
- How Cosmos 3 Helps Physical AI Think Before It Acts
How Cosmos 3 Helps Physical AI Think Before It Acts
- NVIDIA DGX Station for Windows Puts a Trillion-Parameter AI Supercomputer on Every Enterprise Desk
NVIDIA today announced NVIDIA DGX Station™ for Windows, the world’s most powerful deskside AI supercomputer designed to build, run and connect always-on AI agents to Windows applications and workflows, capable of running frontier AI models of up to 1 trillion parameters locally.
- NYT: Senator Sanders Proposes Gov't Take 50% Ownership of AI Labs
Quoting from Senator Bernie Sanders Op-Ed in the New York Times today : (...) I will soon be introducing the American A.I. Sovereign Wealth Fund Act. This legislation would give the public a direct ownership stake in the largest A.I. companies in our country. How? It would create a sovereign wealth fund through a one-time 50 percent tax — not on the profits of OpenAI, Anthropic, xAI and other companies, but paid with something far more valuable than that: the stock. If passed, this legislation would do two crucial things. First, it would give the public a direct role in determining the future of this technology. No longer would the future of A.I. and the transformation of human life that it will bring be dictated by a handful of Big Tech oligarchs. The federal government would have the power, through its voting shares and an equal representation on each company’s board, to block decisions that hurt our citizens and to push for policies that help them. Second, this legislation would guarantee that the trillions of dollars potentially generated by A.I. are used to improve the lives of all of us — not simply to make the richest people in the world even richer. If the big A.I. companies continue to grow as rapidly as many analysts expect, then the value of the sovereign wealth fund will grow as well — and the benefits to the American people will grow along with it. As you may know, Senator Bernie Sanders has recently started taking the idea of AGI/ASI much more seriously . Now he's proposing partial nationalization on the premise that AI is a uniquely valuable and important technology. [1] While this particular upcoming bill of his is rather unlikely to pass, I like that ideas are being proposed which are at least somewhat commensurate to the problem. ^ Quote from article: "Artificial intelligence will almost certainly be the most transformational technology in the history of the world." Discuss
- Intel puts agentic AI to work with Xeon 6+, networking, and AI systems
Intel expands its AI‑ready platform across data center, network, and edge—showing why the CPU is at the heart of agentic AI orchestration, scale and data movement
- Japan stations, facilities using AI system to prevent suicide by jumping
KYODO — About 40 stations and commercial buildings in Japan have introduced an artificial intelligence (AI) system to prevent suicide that has helped to save the lives of at least 2 people, according to its developer.
- New York Times Publisher Slams AI Companies' 'Brazen Theft' From News Outlets
New York Times Publisher Slams AI Companies' 'Brazen Theft' From News Outlets Barron's
- New York Times publisher slams AI companies' 'brazen theft' from news outlets
The New York Times publisher on Monday slammed artificial intelligence companies for "brazen theft of intellectual property," warning they threaten the future of journalism during a speech at the World News Media Congress in the French city of Marseille.
- What are AI PCs and what can they do that your computer can’t?
What are AI PCs and what can they do that your computer can’t? The Straits Times
- ASUS Unveils Revolutionary ProArt PCs Powered by NVIDIA RTX Spark at COMPUTEX 2026
ASUS Unveils Revolutionary ProArt PCs Powered by NVIDIA RTX Spark at COMPUTEX 2026 The Straits Times
- Connected vehicle data ‘can have intelligence value’ to adversaries: federal document
Connected vehicle data ‘can have intelligence value’ to adversaries: federal document Automotive News
- This AI Kidnapping Scam Is Every Parent's Worst Nightmare
This AI Kidnapping Scam Is Every Parent's Worst Nightmare PCMag UK
- Cruise giant says six million customers’ personal information was exposed in breach
Cruise giant says six million customers’ personal information was exposed in breach
- Young and unemployed? Remote work, not AI, may be the problem, study finds
Young and unemployed? Remote work, not AI, may be the problem, study finds Austin American-Statesman
- Young and unemployed? Remote work, not AI, may be the problem, study finds
Young and unemployed? Remote work, not AI, may be the problem, study finds Boston Herald
- As the Pentagon pushes for battlefield AI, some military leaders urge caution
As the Pentagon pushes for battlefield AI, some military leaders urge caution The Boston Globe
- As the Pentagon pushes for battlefield AI, some military leaders urge caution
As the Pentagon pushes for battlefield AI, some military leaders urge caution Dallas News
- As the Pentagon pushes for battlefield AI, some military leaders urge caution
As the Pentagon pushes for battlefield AI, some military leaders urge caution Boston Herald
- As the Pentagon Pushes for Battlefield AI, Some Military Leaders Urge Caution
AI’s use in the military is part of the administration’s larger push to grow the capability it sees as a unique American advantage. The post As the Pentagon Pushes for Battlefield AI, Some Military Leaders Urge Caution appeared first on SecurityWeek .
- Around 1 in 5 young people use AI chatbots for mental health advice, survey finds
Nearly 1 in 5 adolescents and young adults are turning to AI chatbots for advice when they’re sad, angry, nervous or stressed, according to a new study.
- AI chatbot use and disclosure for mental health among US adolescents and young adults
AI chatbot use and disclosure for mental health among US adolescents and young adults EurekAlert!
- OpenAI’s next legal battle is against states who claim its models are dangerous
OpenAI’s next legal battle is against states who claim its models are dangerous
- Your phone screen doesn't have the same color range as the human eye, and AI widens the gap
A peacock feather in sunlight shifts from blue to green to bronze as you turn it. Photograph it, and this shimmer collapses into one angle, one exposure, one compromise.