Records of hundreds of emergency calls from ICE detention centers obtained by WIRED—including audio recordings—show a system inundated by life-threatening incidents, delayed treatment, and overcrowding.

Although we might all fundamentally recognize that gaming consoles are just specialized computers, we generally treat them, culturally and physically, differently than we do desktops or laptops. But there was …read more

Most of what happens within the video games we play is invisible to us. Even the elements we're looking straight at work because of what's happening behind the scenes. If you've ever watched a behind-the-scenes video about game development, you might've seen these versions of flat, gray game worlds filled with lines and icons pointing every which way, with multiple grids and layers. These are the visual representations of all the systems that make the game work.Assassin's Creed ShadowsThis is an especially weird dichotomy to consider when it comes to lighting in any game with a 3D perspective, but especially so in high-fidelity games. We don't see light so much as we see everything it touches; it's invisible, but it gives us most of our information about game worlds. And it's a lot more complex than "turn on lamp, room light up." Reflection, absorption, diffusion, subsurface scattering--the movement of light is a complex thing that has been explored by physicists in the real world for literally centuries, and will likely be studied for centuries more. In the middle of all of that are game designers, applying the science of light to video games in practical ways, balanced with the limitations of even today's powerful GPUs, just to show all us nerds a good time.If you've wondered why many games seem to be like static amusement parks waiting for you to interact with a few specific things, lighting is often the reason. But it's also the reason more and more game worlds look vibrant and lifelike. Game developers have gotten good at simulating static lighting, but making it move is harder. Dynamic lighting has long been computationally expensive, potentially tanking game performance, and we're finally starting to see that change.Continue Reading at GameSpot

NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognition (CVPR) conference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop. This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR. The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehicle (AV) simulation framework. The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs. Generating Safe and Adaptive Driving Trajectories Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically. Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research. The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoring (GTRS) method, which generates a variety of trajectories and progressively filters out the best one. GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories. GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories. This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions. NVIDIA Automotive Research at CVPR  More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more. In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+. The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs: Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion Models (Read more in this blog.) FoundationStereo: Zero-Shot Stereo Matching (Best Paper nominee) Zero-Shot Monocular Scene Flow Estimation in the Wild (Best Paper nominee) Difix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models (Best Paper nominee) 3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models Zero-Shot 4D Lidar Panoptic Segmentation NVILA: Efficient Frontier Visual Language Models RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning Explore automotive workshops and tutorials at CVPR, including: Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone LatinX in CV Workshop, featuring Leal-Taixe Workshop on Exploring the Next Generation of Data, featuring Alvarez Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA Continuous Data Cycle via Foundation Models, led by NVIDIA Distillation of Foundation Models for Autonomous Driving, led by NVIDIA Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang. Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics. The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model.

In the face of growing labor shortages and need for sustainability, European manufacturers are racing to reinvent their processes to become software-defined and AI-driven. To achieve this, robot developers and industrial digitalization solution providers are working with NVIDIA to build safe, AI-driven robots and industrial technologies to drive modern, sustainable manufacturing. At NVIDIA GTC Paris at VivaTech, Europe’s leading robotics companies including Agile Robots, Extend Robotics, Humanoid, idealworks, Neura Robotics, SICK, Universal Robots, Vorwerk and Wandelbots are showcasing their latest AI-driven robots and automation breakthroughs, all accelerated by NVIDIA technologies. In addition, NVIDIA is releasing new models and tools to support the entire robotics ecosystem. NVIDIA Releases Tools for Accelerating Robot Development and Safety NVIDIA Isaac GR00T N1.5, an open foundation model for humanoid robot reasoning and skills, is now available for download on Hugging Face. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. The NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 open-source robotics simulation and learning frameworks, optimized for NVIDIA RTX PRO 6000 workstations, are available on GitHub for developer preview. In addition, NVIDIA announced that NVIDIA Halos — a full-stack, comprehensive safety system that unifies hardware architecture, AI models, software, tools and services — now expands to robotics, promoting safety across the entire development lifecycle of AI-driven robots. The NVIDIA Halos AI Systems Inspection Lab has earned accreditation from the ANSI National Accreditation Board (ANAB) to perform inspections across functional safety for robotics, in addition to automotive vehicles. “NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines — from automotive to robotics — can meet the highest benchmarks for functional safety,” said R. Douglas Leonard Jr., executive director of ANAB. Arcbest, Advantech, Bluewhite, Boston Dynamics, FORT, Inxpect, KION, NexCobot — a NEXCOM company, and Synapticon are among the first robotics companies to join the Halos Inspection Lab, ensuring their products meet NVIDIA safety and cybersecurity requirements. To support robotics leaders in strengthening safety across the entire development lifecycle of AI-driven robots, Halos will now provide: Safety extension packages for the NVIDIA IGX platform, enabling manufacturers to easily program safety functions into their robots, supported by TÜV Rheinland’s inspection of NVIDIA IGX. A robotic safety platform, which includes IGX and NVIDIA Holoscan Sensor Bridge for a unified approach to designing sensor-to-compute architecture with built-in AI safety. An outside-in safety AI inspector — an AI-powered agent for monitoring robot operations, helping improve worker safety. Europe’s Robotics Ecosystem Builds on NVIDIA’s Three Computers Europe’s leading robotics developers and solution providers are integrating the NVIDIA Isaac robotics platform to train, simulate and deploy robots across different embodiments. Agile Robots is post-training the GR00T N1 model in Isaac Lab to train its dual-arm manipulator robots, which run on NVIDIA Jetson hardware, to execute a variety of tasks in industrial environments. Meanwhile, idealworks has adopted the Mega NVIDIA Omniverse Blueprint for robotic fleet simulation to extend the blueprint’s capabilities to humanoids. Building on the VDA 5050 framework, idealworks contributes to the development of guidance that supports tasks uniquely enabled by humanoid robots, such as picking, moving and placing objects. Neura Robotics is integrating NVIDIA Isaac to further enhance its robot development workflows. The company is using GR00T-Mimic to post-train the Isaac GR00T N1 robot foundation model for its service robot MiPA. Neura is also collaborating with SAP and NVIDIA to integrate SAP’s Joule agents with its robots, using the Mega NVIDIA Omniverse Blueprint to simulate and refine robot behavior in complex, realistic operational scenarios before deployment. Vorwerk is using NVIDIA technologies to power its AI-driven collaborative robots. The company is post-training GR00T N1 models in Isaac Lab with its custom synthetic data pipeline, which is built on Isaac GR00T-Mimic and powered by the NVIDIA Omniverse platform. The enhanced models are then deployed on NVIDIA Jetson AGX, Jetson Orin or Jetson Thor modules for advanced, real-time home robotics. Humanoid is using NVIDIA’s full robotics stack, including Isaac Sim and Isaac Lab, to cut its prototyping time down by six weeks. The company is training its vision language action models on NVIDIA DGX B200 systems to boost the cognitive abilities of its robots, allowing them to operate autonomously in complex environments using Jetson Thor onboard computing. Universal Robots is introducing UR15, its fastest collaborative robot yet, to the European market. Using UR’s AI Accelerator — developed on NVIDIA Isaac’s CUDA-accelerated libraries and AI models, as well as NVIDIA Jetson AGX Orin — manufacturers can build AI applications to embed intelligence into the company’s new cobots. Wandelbots is showcasing its NOVA Operating System, now integrated with Omniverse, to simulate, validate and optimize robotic behaviors virtually before deploying them to physical robots. Wandelbots also announced a collaboration with EY and EDAG to offer manufacturers a scalable automation platform on Omniverse that speeds up the transition from proof of concept to full-scale deployment. Extend Robotics is using the Isaac GR00T platform to enable customers to control and train robots for industrial tasks like visual inspection and handling radioactive materials. The company’s Advanced Mechanics Assistance System lets users collect demonstration data and generate diverse synthetic datasets with NVIDIA GR00T-Mimic and GR00T-Gen to train the GR00T N1 foundation model. SICK is enhancing its autonomous perception solutions by integrating new certified sensor models — as well as 2D and 3D lidars, safety scanners and cameras — into NVIDIA Isaac Sim. This enables engineers to virtually design, test and validate machines using SICK’s sensing models within Omniverse, supporting processes spanning product development to large-scale robotic fleet management. Toyota Material Handling Europe is working with SoftServe to simulate its autonomous mobile robots working alongside human workers, using the Mega NVIDIA Omniverse Blueprint. Toyota Material Handling Europe is testing and simulating a multitude of traffic scenarios — allowing the company to refine its AI algorithms before real-world deployment. NVIDIA’s partner ecosystem is enabling European industries to tap into intelligent, AI-powered robotics. By harnessing advanced simulation, digital twins and generative AI, manufacturers are rapidly developing and deploying safe, adaptable robot fleets that address labor shortages, boost sustainability and drive operational efficiency. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. See notice regarding software product information.

These sparkling water makers will fizz up your life at a moment’s notice, and most don’t need a power outlet.

AI is packing and shipping efficiency for the retail and consumer packaged goods (CPG) industries, with a majority of surveyed companies in the space reporting the technology is increasing revenue and reducing operational costs. Global brands are reimagining every facet of their businesses with AI, from how products are designed and manufactured to how they’re marketed, shipped and experienced in-store and online. At NVIDIA GTC Paris at VivaTech, industry leaders including L’Oréal, LVMH and Nestlé shared how they’re using tools like AI agents and physical AI — powered by NVIDIA AI and simulation technologies — across every step of the product lifecycle to enhance operations and experiences for partners, customers and employees. 3D Digital Twins and AI Transform Marketing, Advertising and Product Design The meeting of generative AI and 3D product digital twins results in unlimited creative potential. Nestlé, the world’s largest food and beverage company, today announced a collaboration with NVIDIA and Accenture to launch a new, AI-powered in-house service that will create high-quality product content at scale for e-commerce and digital media channels. The new content service, based on digital twins powered by the NVIDIA Omniverse platform, creates exact 3D virtual replicas of physical products. Product packaging can be adjusted or localized digitally, enabling seamless integration into various environments, such as seasonal campaigns or channel-specific formats. This means that new creative content can be generated without having to constantly reshoot from scratch. Image courtesy of Nestlé The service is developed in partnership with Accenture Song, using Accenture AI Refinery built on NVIDIA Omniverse for advanced digital twin creation. It uses NVIDIA AI Enterprise for generative AI, hosted on Microsoft Azure for robust cloud infrastructure. Nestlé already has a baseline of 4,000 3D digital products — mainly for global brands — with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands. LVMH, the world’s leading luxury goods company, home to 75 distinguished maisons, is bringing 3D digital twins to its content production processes through its wine and spirits division, Moët Hennessy. The group partnered with content configuration engine Grip to develop a solution using the NVIDIA Omniverse platform, which enables the creation of 3D digital twins that power content variation production. With Grip’s solution, Moët Hennessy teams can quickly generate digital marketing assets and experiences to promote luxury products at scale. The initiative, led by Capucine Lafarge and Chloé Fournier, has been recognized by LVMH as a leading approach to scaling content creation. Image courtesy of Grip L’Oréal Gives Marketing and Online Shopping an AI Makeover Innovation starts at the drawing board. Today, that board is digital — and it’s powered by AI. L’Oréal Groupe, the world’s leading beauty player, announced its collaboration with NVIDIA today. Through this collaboration, L’Oréal and its partner ecosystem will leverage the NVIDIA AI Enterprise platform to transform its consumer beauty experiences, marketing and advertising content pipelines. “AI doesn’t think with the same constraints as a human being. That opens new avenues for creativity,” said Anne Machet, global head of content and entertainment at L’Oréal. “Generative AI enables our teams and partner agencies to explore creative possibilities.” CreAItech, L’Oréal’s generative AI content platform, is augmenting the creativity of marketing and content teams. Combining a modular ecosystem of models, expertise, technologies and partners — including NVIDIA — CreAltech empowers marketers to generate thousands of unique, on-brand images, videos and lines of text for diverse platforms and global audiences. The solution empowers L’Oréal’s marketing teams to quickly iterate on campaigns that improve consumer engagement across social media, e-commerce content and influencer marketing — driving higher conversion rates. Noli.com, the first AI-powered multi-brand marketplace startup founded and backed by the  L’Oréal Groupe, is reinventing how people discover and shop for beauty products. Noli’s AI Beauty Matchmaker experience uses L’Oréal Groupe’s century-long expertise in beauty, including its extensive knowledge of beauty science, beauty tech and consumer insights, built from over 1 million skin data points and analysis of thousands of product formulations. It gives users a BeautyDNA profile with expert-level guidance and personalized product recommendations for skincare and haircare. “Beauty shoppers are often overwhelmed by choice and struggling to find the products that are right for them,” said Amos Susskind, founder and CEO of Noli. “By applying the latest AI models accelerated by NVIDIA and Accenture to the unparalleled knowledge base and expertise of the L’Oréal Groupe, we can provide hyper-personalized, explainable recommendations to our users.”  https://blogs.nvidia.com/wp-content/uploads/2025/06/Noli_Demo.mp4 The Accenture AI Refinery, powered by NVIDIA AI Enterprise, will provide the platform for Noli to experiment and scale. Noli’s new agent models will use NVIDIA NIM and NVIDIA NeMo microservices, including NeMo Retriever, running on Microsoft Azure. Rapid Innovation With the NVIDIA Partner Ecosystem NVIDIA’s ecosystem of solution provider partners empowers retail and CPG companies to innovate faster, personalize customer experiences, and optimize operations with NVIDIA accelerated computing and AI. Global digital agency Monks is reshaping the landscape of AI-driven marketing, creative production and enterprise transformation. At the heart of their innovation lies the Monks.Flow platform that enhances both the speed and sophistication of creative workflows through NVIDIA Omniverse, NVIDIA NIM microservices and Triton Inference Server for lightning-fast inference. AI image solutions provider Bria is helping retail giants like Lidl and L’Oreal to enhance marketing asset creation. Bria AI transforms static product images into compelling, dynamic advertisements that can be quickly scaled for use across any marketing need. The company’s generative AI platform uses NVIDIA Triton Inference Server software and the NVIDIA TensorRT software development kit for accelerated inference, as well as NVIDIA NIM and NeMo microservices for quick image generation at scale. Physical AI Brings Acceleration to Supply Chain and Logistics AI’s impact extends far beyond the digital world. Physical AI-powered warehousing robots, for example, are helping maximize efficiency in retail supply chain operations. Four in five retail companies have reported that AI has helped reduce supply chain operational costs, with 25% reporting cost reductions of at least 10%. Technology providers Lyric, KoiReader Technologies and Exotec are tackling the challenges of integrating AI into complex warehouse environments. Lyric is using the NVIDIA cuOpt GPU-accelerated solver for warehouse network planning and route optimization, and is collaborating with NVIDIA to apply the technology to broader supply chain decision-making problems. KoiReader Technologies is tapping the NVIDIA Metropolis stack for its computer vision solutions within logistics, supply chain and manufacturing environments using the KoiVision Platform. And Exotec is using NVIDIA CUDA libraries and the NVIDIA JetPack software development kit for embedded robotic systems in warehouse and distribution centers. From real-time robotics orchestration to predictive maintenance, these solutions are delivering impact on uptime, throughput and cost savings for supply chain operations. Learn more by joining a follow-up discussion on digital twins and AI-powered creativity with Microsoft, Nestlé, Accenture and NVIDIA at Cannes Lions on Monday, June 16. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

Urban populations are expected to double by 2050, which means around 2.5 billion people could be added to urban areas by the middle of the century, driving the need for more sustainable urban planning and public services. Cities across the globe are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions. Building a digital twin of a city and testing smart city AI agents within it, however, is a complex and resource-intensive endeavor, fraught with technical and operational challenges. To address those challenges, NVIDIA today announced the NVIDIA Omniverse Blueprint for smart city AI, a reference framework that combines the NVIDIA Omniverse, Cosmos, NeMo and Metropolis platforms to bring the benefits of physical AI to entire cities and their critical infrastructure. Using the blueprint, developers can build simulation-ready, or SimReady, photorealistic digital twins of cities to build and test AI agents that can help monitor and optimize city operations. Leading companies including XXII, AVES Reality, Akila, Blyncsy, Bentley, Cesium, K2K, Linker Vision, Milestone Systems, Nebius, SNCF Gares&Connexions, Trimble and Younite AI are among the first to use the new blueprint. NVIDIA Omniverse Blueprint for Smart City AI  The NVIDIA Omniverse Blueprint for smart city AI provides the complete software stack needed to accelerate the development and testing of AI agents in physically accurate digital twins of cities. It includes: NVIDIA Omniverse to build physically accurate digital twins and run simulations at city scale. NVIDIA Cosmos to generate synthetic data at scale for post-training AI models. NVIDIA NeMo to curate high-quality data and use that data to train and fine-tune vision language models (VLMs) and large language models. NVIDIA Metropolis to build and deploy video analytics AI agents based on the NVIDIA AI Blueprint for video search and summarization (VSS), helping process vast amounts of video data and provide critical insights to optimize business processes. The blueprint workflow comprises three key steps. First, developers create a SimReady digital twin of locations and facilities using aerial, satellite or map data with Omniverse and Cosmos. Second, they can train and fine-tune AI models, like computer vision models and VLMs, using NVIDIA TAO and NeMo Curator to improve accuracy for vision AI use cases​. Finally, real-time AI agents powered by these customized models are deployed to alert, summarize and query camera and sensor data using the Metropolis VSS blueprint. NVIDIA Partner Ecosystem Powers Smart Cities Worldwide The blueprint for smart city AI enables a large ecosystem of partners to use a single workflow to build and activate digital twins for smart city use cases, tapping into a combination of NVIDIA’s technologies and their own. SNCF Gares&Connexions, which operates a network of 3,000 train stations across France and Monaco, has deployed a digital twin and AI agents to enable real-time operational monitoring, emergency response simulations and infrastructure upgrade planning. This helps each station analyze operational data such as energy and water use, and enables predictive maintenance capabilities, automated reporting and GDPR-compliant video analytics for incident detection and crowd management. Powered by Omniverse, Metropolis and solutions from ecosystem partners Akila and XXII, SNCF Gares&Connexions’ physical AI deployment at the Monaco-Monte-Carlo and Marseille stations has helped SNCF Gares&Connexions achieve a 100% on-time preventive maintenance completion rate, a 50% reduction in downtime and issue response time, and a 20% reduction in energy consumption. https://blogs.nvidia.com/wp-content/uploads/2025/06/01-Monaco-Akila.mp4 The city of Palermo in Sicily is using AI agents and digital twins from its partner K2K to improve public health and safety by helping city operators process and analyze footage from over 1,000 public video streams at a rate of nearly 50 billion pixels per second. Tapped by Sicily, K2K’s AI agents — built with the NVIDIA AI Blueprint for VSS and cloud solutions from Nebius — can interpret and act on video data to provide real-time alerts on public events. To accurately predict and resolve traffic incidents, K2K is generating synthetic data with Cosmos world foundation models to simulate different driving conditions. Then, K2K uses the data to fine-tune the VLMs powering the AI agents with NeMo Curator. These simulations enable K2K’s AI agents to create over 100,000 predictions per second. https://blogs.nvidia.com/wp-content/uploads/2025/06/02-K2K-Polermo-1600x900-1.mp4 Milestone Systems — in collaboration with NVIDIA and European cities — has launched Project Hafnia, an initiative to build an anonymized, ethically sourced video data platform for cities to develop and train AI models and applications while maintaining regulatory compliance. Using a combination of Cosmos and NeMo Curator on NVIDIA DGX Cloud and Nebius’ sovereign European cloud infrastructure, Project Hafnia scales up and enables European-compliant training and fine-tuning of video-centric AI models, including VLMs, for a variety of smart city use cases. The project’s initial rollout, taking place in Genoa, Italy, features one of the world’s first VLM models for intelligent transportation systems. https://blogs.nvidia.com/wp-content/uploads/2025/06/03-Milestone.mp4 Linker Vision was among the first to partner with NVIDIA to deploy smart city digital twins and AI agents for Kaohsiung City, Taiwan — powered by Omniverse, Cosmos and Metropolis. Linker Vision worked with AVES Reality, a digital twin company, to bring aerial imagery of cities and infrastructure into 3D geometry and ultimately into SimReady Omniverse digital twins. Linker Vision’s AI-powered application then built, trained and tested visual AI agents in a digital twin before deployment in the physical city. Now, it’s scaling to analyze 50,000 video streams in real time with generative AI to understand and narrate complex urban events like floods and traffic accidents. Linker Vision delivers timely insights to a dozen city departments through a single integrated AI-powered platform, breaking silos and reducing incident response times by up to 80%. https://blogs.nvidia.com/wp-content/uploads/2025/06/02-Linker-Vision-1280x680-1.mp4 Bentley Systems is joining the effort to bring physical AI to cities with the NVIDIA blueprint. Cesium, the open 3D geospatial platform, provides the foundation for visualizing, analyzing and managing infrastructure projects and ports digital twins to Omniverse. The company’s AI platform Blyncsy uses synthetic data generation and Metropolis to analyze road conditions and improve maintenance. Trimble, a global technology company that enables essential industries including construction, geospatial and transportation, is exploring ways to integrate components of the Omniverse blueprint into its reality capture workflows and Trimble Connect digital twin platform for surveying and mapping applications for smart cities. Younite AI, a developer of AI and 3D digital twin solutions, is adopting the blueprint to accelerate its development pipeline, enabling the company to quickly move from operational digital twins to large-scale urban simulations, improve synthetic data generation, integrate real-time IoT sensor data and deploy AI agents. Learn more about the NVIDIA Omniverse Blueprint for smart city AI by attending this GTC Paris session or watching the on-demand video after the event. Sign up to be notified when the blueprint is available. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

Esta semana el 3DExpress se centra en el sector aeroespacial. La empresa surcoreana de servicios de lanzamiento de satélites, INNOSPACE, ha inaugurado una nueva división para la fabricación de componentes clave mediante la impresión 3D. La compañía u

Telecom companies last year spent nearly $295 billion in capital expenditures and over $1 trillion in operating expenditures. These large expenses are due in part to laborious manual processes that telcos face when operating networks that require continuous optimizations. For example, telcos must constantly tune network parameters for tasks — such as transferring calls from one network to another or distributing network traffic across multiple servers — based on the time of day, user behavior, mobility and traffic type. These factors directly affect network performance, user experience and energy consumption. To automate these optimization processes and save costs for telcos across the globe, NVIDIA today unveiled at GTC Paris its first AI Blueprint for telco network configuration. At the blueprint’s core are customized large language models trained specifically on telco network data — as well as the full technical and operational architecture for turning the LLMs into an autonomous, goal-driven AI agent for telcos. Automate Network Configuration With the AI Blueprint NVIDIA AI Blueprints — available on build.nvidia.com — are customizable AI workflow examples. They include reference code, documentation and deployment tools that show enterprise developers how to deliver business value with NVIDIA NIM microservices. The AI Blueprint for telco network configuration — built with BubbleRAN 5G solutions and datasets — enables developers, network engineers and telecom providers to automatically optimize the configuration of network parameters using agentic AI. This can streamline operations, reduce costs and significantly improve service quality by embedding continuous learning and adaptability directly into network infrastructures. Traditionally, network configurations required manual intervention or followed rigid rules to adapt to dynamic network conditions. These approaches limited adaptability and increased operational complexities, costs and inefficiencies. The new blueprint helps shift telco operations from relying on static, rules-based systems to operations based on dynamic, AI-driven automation. It enables developers to build advanced, telco-specific AI agents that make real-time, intelligent decisions and autonomously balance trade-offs — such as network speed versus interference, or energy savings versus utilization — without human input. Powered and Deployed by Industry Leaders Trained on 5G data generated by BubbleRAN, and deployed on the BubbleRAN 5G O-RAN platform, the blueprint provides telcos with insight on how to set various parameters to reach performance goals, like achieving a certain bitrate while choosing an acceptable signal-to-noise ratio — a measure that impacts voice quality and thus user experience. With the new AI Blueprint, network engineers can confidently set initial parameter values and update them as demanded by continuous network changes. Norway-based Telenor Group, which serves over 200 million customers globally, is the first telco to integrate the AI Blueprint for telco network configuration as part of its initiative to deploy intelligent, autonomous networks that meet the performance and agility demands of 5G and beyond. “The blueprint is helping us address configuration challenges and enhance quality of service during network installation,” said Knut Fjellheim, chief technology innovation officer at Telenor Maritime. “Implementing it is part of our push toward network automation and follows the successful deployment of agentic AI for real-time network slicing in a private 5G maritime use case.” Industry Partners Deploy Other NVIDIA-Powered Autonomous Network Technologies The AI Blueprint for telco network configuration is just one of many announcements at NVIDIA GTC Paris showcasing how the telecom industry is using agentic AI to make autonomous networks a reality. Beyond the blueprint, leading telecom companies and solutions providers are tapping into NVIDIA accelerated computing, software and microservices to provide breakthrough innovations poised to vastly improve networks and communications services — accelerating the progress to autonomous networks and improving customer experiences. NTT DATA is powering its agentic platform for telcos with NVIDIA accelerated compute and the NVIDIA AI Enterprise software platform. Its first agentic use case is focused on network alarms management, where NVIDIA NIM microservices help automate and power observability, troubleshooting, anomaly detection and resolution with closed loop ticketing. Tata Consultancy Services is delivering agentic AI solutions for telcos built on NVIDIA DGX Cloud and using NVIDIA AI Enterprise to develop, fine-tune and integrate large telco models into AI agent workflows. These range from billing and revenue assurance, autonomous network management to hybrid edge-cloud distributed inference. For example, the company’s anomaly management agentic AI model includes real-time detection and resolution of network anomalies and service performance optimization. This increases business agility and improves operational efficiencies by up to 40% by eliminating human intensive toils, overheads and cross-departmental silos. Prodapt has introduced an autonomous operations workflow for networks, powered by NVIDIA AI Enterprise, that offers agentic AI capabilities to support autonomous telecom networks. AI agents can autonomously monitor networks, detect anomalies in real time, initiate diagnostics, analyze root causes of issues using historical data and correlation techniques, automatically execute corrective actions, and generate, enrich and assign incident tickets through integrated ticketing systems. Accenture announced its new portfolio of agentic AI solutions for telecommunications through its AI Refinery platform, built on NVIDIA AI Enterprise software and accelerated computing. The first available solution, the NOC Agentic App, boosts network operations center tasks by using a generative AI-driven, nonlinear agentic framework to automate processes such as incident and fault management, root cause analysis and configuration planning. Using the Llama 3.1 70B NVIDIA NIM microservice and the AI Refinery Distiller Framework, the NOC Agentic App orchestrates networks of intelligent agents for faster, more efficient decision-making. Infosys is announcing its agentic autonomous operations platform, called Infosys Smart Network Assurance (ISNA), designed to accelerate telecom operators’ journeys toward fully autonomous network operations. ISNA helps address long-standing operational challenges for telcos — such as limited automation and high average time to repair — with an integrated, AI-driven platform that reduces operational costs by up to 40% and shortens fault resolution times by up to 30%. NVIDIA NIM and NeMo microservices enhance the platform’s reasoning and hallucination-detection capabilities, reduce latency and increase accuracy. Get started with the new blueprint today. Learn more about the latest AI advancements for telecom and other industries at NVIDIA GTC Paris, running through Thursday, June 12, at VivaTech, including a keynote from NVIDIA founder and CEO Jensen Huang and a special address from Ronnie Vasishta, senior vice president of telecom at NVIDIA. Plus, hear from industry leaders in a panel session with Orange, Swisscom, Telenor and NVIDIA.