News Summary:<\/p>\n
\n\tT-Mobile pilots NVIDIA RTX PRO 6000 Blackwell Server Edition AI infrastructure to demonstrate physical AI applications at the edge, complementing the AI-RAN Innovation Center\u2019s distributed network\u00a0
\n\tPhysical AI developers including Fogsphere, LinkerVision, Levatas, Vaidio and Siemens Energy are building reasoning and vision AI agents to the edge using the NVIDIA Metropolis Blueprint for video search and summarization (VSS) to integrate into T-Mobile\u2019s distributed edge network, with the City of San Jose among first to assess the technology.\u00a0
\n\tThe new NVIDIA VSS blueprint version 3 accelerates the development of reasoning video analytics AI agents through a flexible modular architecture, advanced multimodal visual understanding and integrated agentic search capabilities.
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GTC\u2014NVIDIA and T-Mobile today announced they are working with Nokia and a growing ecosystem of developers to bring physical AI applications over distributed edge AI networks. This collaboration demonstrates how next generation AI-RAN infrastructure can transform the wireless network into a platform for distributed high-performance edge AI computing, creating a foundation for developers to deploy vision AI agents that understand the physical world across cities, utilities and industrial worksites using the\u202fNVIDIA Metropolis\u202fplatform.<\/p>\n
NVIDIA\u2019s AI-RAN portfolio encompasses NVIDIA ARC-Pro<\/a> built on NVIDIA RTX PRO\u2122 4500 Blackwell Server Edition<\/a> for power-constrained cell sites, and NVIDIA RTX PRO 6000 Blackwell Server Edition<\/a> for higher-capacity mobile switching offices.\u00a0<\/p>\n T-Mobile was the first in the U.S. to pilot NVIDIA\u2019s AI-RAN infrastructure with Nokia\u2019s anyRANsoftware and is now working with select NVIDIA physical AI partners, demonstrating how cell sites and mobile switching offices can support distributed edge AI workloads while continuing to deliver advanced 5G connectivity.<\/p>\n \u201cTelecommunication networks are evolving into the AI infrastructure enabling billions of devices \u2014 from vision AI agents to robots and autonomous vehicles \u2014 to see, hear and act in real time,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cBy turning the 5G network into a distributed AI computer with T-Mobile and Nokia, we\u2019re creating a scalable blueprint for the world\u2019s edge AI infrastructure.\u201d<\/p>\n \u201cTurning networks into distributed AI computing platforms to unlock the full potential of Physical AI will require ultra-low latency and space time coherency at the network edge for billions of endpoints, and that’s what we’ve built at T-Mobile,\u201d said Srini Gopalan, Chief Executive Officer of T-Mobile. \u201cWith the first nationwide 5G Standalone and 5G Advanced network, we are uniquely positioned to help power a future where intelligent systems don\u2019t wait on the cloud but rely on intelligent networks that allow them to act in real time.\u201d<\/p>\n The Mobile Network as the Nervous System for Physical AI<\/p>\n The transition to AI-RAN built on NVIDIA accelerated computing addresses a critical bottleneck in scaling physical AI: lack of low-latency, secure and ubiquitous connectivity. While Wi-Fi is limited by reach and security, T-Mobile\u2019s 5G standalone network provides the wide-area coverage and guaranteed quality of service required for complex AI agents to operate in busy city intersections, industrial facilities and rural areas.<\/p>\n This architecture enables physical AI to offload heavy computation from the device to the nearest edge location. Shifting heavy processing to the network edge allows developers to streamline hardware requirements for individual cameras and robots, making it possible to cost-effectively scale sophisticated AI models across billions of interconnected devices.<\/p>\n Leading Developers Bring Reasoning and Vision AI to the Edge<\/p>\n A growing ecosystem of developers is collaborating with NVIDIA and T-Mobile to integrate physical AI<\/a> agents that are driving real-time action, built with the NVIDIA Metropolis Blueprint for video search and summarization (VSS)<\/a> on T-Mobile\u2019s distributed edge network. Pilot use cases include:<\/p>\n
These initiatives reflect T-Mobile\u2019s broader strategy to test and enable edge AI capabilities in collaboration with NVIDIA, Nokia and a diverse ecosystem of software providers, manufacturers and enterprise innovators.\u00a0<\/p>\n Accelerating Vision AI Agents Development With the Metropolis VSS 3 Blueprint<\/p>\n While more than 1.5 billion cameras capture footage globally, less than 1% is ever reviewed by humans. NVIDIA is introducing the Metropolis VSS 3 Blueprint to enable agents to reason over video from the edge to the cloud.<\/p>\n Key features of the blueprint\u2019s latest iteration include:<\/p>\n
Partners using the VSS blueprint to optimize operations and enhance safety across industries include Caterpillar, KION, Hitachi, HCLTech, Siemens Energy, Tulip and Telit Cinterion.\u00a0<\/p>\n Learn more about the NVIDIA VSS blueprint<\/a> at build.nvidia.com<\/a>. Watch the GTC keynote<\/a> from Huang and explore vision AI sessions.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"News Summary:
T-Mobile pilots NVIDIA RTX PRO 6000 Blackwell Server Edition AI infrastructure to demonstrate physical AI…\n","protected":false},"author":2,"featured_media":349861,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[220,218,219,61,60,80],"class_list":["post-349860","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-ie","tag-ireland","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/349860","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=349860"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/349860\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/349861"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=349860"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=349860"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=349860"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n\tSmart City Operations: LinkerVision, Inchor and Voxelmaps are testing integrated computer vision-based \u201cCity Operations Agents\u201d and a digital twin that can perceive, simulate and optimize traffic light timing, targeting 5x faster incident response times for the City of San Jose.
\n\tAutomated Utility Inspection: Levatas and Skydio are automating the inspection of hundreds of thousands of miles of transmission lines over 5G with NVIDIA compute to detect and resolve anomalies such as leaning powerpoles, corrosion and thermal hotspots 5x faster. They are now evaluating AI-RAN infrastructure to further reduce costs, improve storm recovery time and accelerate the shift from reactive to predictive maintenance.
\n\tVision-Based Facility Management: Developers such as Vaidio are using the VSS blueprint to build facility management agents that move beyond simple sensors to perform threat detection and failure forecasting, triggering automated workflows to improve facility management.
\n\tReal-Time Industrial Safety: Fogsphere provides safety AI agents for SAIPEM to detect and respond in real-time to hazardous events \u2014 such as workers under suspended loads or hydrocarbon spills \u2014 in high-risk construction onshore, offshore and drilling environments. Fogsphere is now validating how AI-RAN infrastructure can enhance the capabilities and performance of these agents \u2014 already running 24\/7 without reliance on Wi-Fi \u2014 over secure and distributed network compute.\u00a0
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\n\tAgentic Information Retrieval: AI agents can decompose complex natural language queries and search across video footage to find specific events in under five seconds.
\n\tModular Architecture: A flexible framework allows teams to adapt VSS 3 to diverse environments \u2014 from retail stores to warehouses \u2014 without overhauling core infrastructure.
\n\t100x Efficiency: VSS can summarize long-form video up to 100x faster than manual reviews, drastically reducing repetitive tasks and review costs for global physical operations.
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