Telecom companies last year spent nearly billion in capital expenditures and over 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, 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. #calling #llms #new #nvidia #blueprint

Magic: the Gathering has officially announced an exciting new crossover coming to the beloved card game, teaming up with Sega for an exclusive set of Sonic the Hedgehog cards. The massively popular trading card game developed by Wizards of the Coast has looked to break bold new grounds with its crossover content in recent years. Magic: the Gathering ramped up its "Universes Beyond" initiative this year with multiple new crossover sets, debuting Final Fantasy in June with Spider-Man and Avatar the Last Airbender expansions to come. Now, another iconic franchise is set to make the jump to Magic. #magic #gathering #announces #collab #with

At GTC Paris — held alongside VivaTech, Europe’s largest tech event — NVIDIA founder and CEO Jensen Huang delivered a clear message: Europe isn’t just adopting AI — it’s building it. “We now have a new industry, an AI industry, and it’s now part of the new infrastructure, called intelligence infrastructure, that will be used by every country, every society,” Huang said, addressing an audience gathered online and at the iconic Dôme de Paris. From exponential inference growth to quantum breakthroughs, and from infrastructure to industry, agentic AI to robotics, Huang outlined how the region is laying the groundwork for an AI-powered future. A New Industrial Revolution At the heart of this transformation, Huang explained, are systems like GB200 NVL72 — “one giant GPU” and NVIDIA’s most powerful AI platform yet — now in full production and powering everything from sovereign models to quantum computing. “This machine was designed to be a thinking machine, a thinking machine, in the sense that it reasons, it plans, it spends a lot of time talking to itself,” Huang said, walking the audience through the size and scale of these machines and their performance. At GTC Paris, Huang showed audience members the innards of some of NVIDIA’s latest hardware. There’s more coming, with Huang saying NVIDIA’s partners are now producing 1,000 GB200 systems a week, “and this is just the beginning.” He walked the audience through a range of available systems ranging from the tiny NVIDIA DGX Spark to rack-mounted RTX PRO Servers. Huang explained that NVIDIA is working to help countries use technologies like these to build both AI infrastructure — services built for third parties to use and innovate on — and AI factories, which companies build for their own use, to generate revenue. NVIDIA is partnering with European governments, telcos and cloud providers to deploy NVIDIA technologies across the region. NVIDIA is also expanding its network of technology centers across Europe — including new hubs in Finland, Germany, Spain, Italy and the U.K. — to accelerate skills development and quantum growth. Quantum Meets Classical Europe’s quantum ambitions just got a boost. The NVIDIA CUDA-Q platform is live on Denmark’s Gefion supercomputer, opening new possibilities for hybrid AI and quantum engineering. In addition, Huang announced that CUDA-Q is now available on NVIDIA Grace Blackwell systems. Across the continent, NVIDIA is partnering with supercomputing centers and quantum hardware builders to advance hybrid quantum-AI research and accelerate quantum error correction. “Quantum computing is reaching an inflection point,” Huang said. “We are within reach of being able to apply quantum computing, quantum classical computing, in areas that can solve some interesting problems in the coming years.” Sovereign Models, Smarter Agents European developers want more control over their models. Enter NVIDIA Nemotron, designed to help build large language models tuned to local needs. “And so now you know that you have access to an enhanced open model that is still open, that is top of the leader chart,” Huang said. These models will be coming to Perplexity, a reasoning search engine, enabling secure, multilingual AI deployment across Europe. “You can now ask and get questions answered in the language, in the culture, in the sensibility of your country,” Huang said. Huang explained how NVIDIA is helping countries across Europe build AI infrastructure. Every company will build its own agents, Huang said. To help create those agents, Huang introduced a suite of agentic AI blueprints, including an Agentic AI Safety blueprint for enterprises and governments. The new NVIDIA NeMo Agent toolkit and NVIDIA AI Blueprint for building data flywheels further accelerate the development of safe, high-performing AI agents. To help deploy these agents, NVIDIA is partnering with European governments, telcos and cloud providers to deploy the DGX Cloud Lepton platform across the region, providing instant access to accelerated computing capacity. “One model architecture, one deployment, and you can run it anywhere,” Huang said, adding that Lepton is now integrated with Hugging Face, giving developers direct access to global compute. The Industrial Cloud Goes Live AI isn’t just virtual. It’s powering physical systems, too, sparking a new industrial revolution. “We’re working on industrial AI with one company after another,” Huang said, describing work to build digital twins based on the NVIDIA Omniverse platform with companies across the continent. Huang explained that everything he showed during his keynote was “computer simulation, not animation” and that it looks beautiful because “it turns out the world is beautiful, and it turns out math is beautiful.” To further this work, Huang announced NVIDIA is launching the world’s first industrial AI cloud — to be built in Germany — to help Europe’s manufacturers simulate, automate and optimize at scale. “Soon, everything that moves will be robotic,” Huang said. “And the car is the next one.” NVIDIA DRIVE, NVIDIA’s full-stack AV platform, is now in production to accelerate the large-scale deployment of safe, intelligent transportation. And to show what’s coming next, Huang was joined on stage by Grek, a pint-sized robot, as Huang talked about how NVIDIA partnered with DeepMind and Disney to build Newton, the world’s most advanced physics training engine for robotics. The Next Wave The next wave of AI has begun — and it’s exponential, Huang explained. “We have physical robots, and we have information robots. We call them agents,” Huang said. “The technology necessary to teach a robot to manipulate, to simulate — and of course, the manifestation of an incredible robot — is now right in front of us.” This new era of AI is being driven by a surge in inference workloads. “The number of people using inference has gone from 8 million to 800 million — 100x in just a couple of years,” Huang said. To meet this demand, Huang emphasized the need for a new kind of computer: “We need a special computer designed for thinking, designed for reasoning. And that’s what Blackwell is — a thinking machine.” Huang and Grek, as he explained how AI is driving advancements in robotics. These Blackwell-powered systems will live in a new class of data centers — AI factories — built to generate tokens, the raw material of modern intelligence. “These AI factories are going to generate tokens,” Huang said, turning to Grek with a smile. “And these tokens are going to become your food, little Grek.” With that, the keynote closed on a bold vision: a future powered by sovereign infrastructure, agentic AI, robotics — and exponential inference — all built in partnership with Europe. Watch the NVIDIA GTC Paris keynote from Huang at VivaTech and explore GTC Paris sessions. #nvidia #ceo #drops #blueprint #europes

A few months after the first major patch for Monster Hunter Wilds, it is now time for Title Update 2 to arrive for the game from Capcom, bringing new monsters for players to hunt, items, and other gear to enhance character effectiveness. Additionally, the update will include gameplay improvements, support for new PC technologies, and seasonal events with exclusive rewards. #what #time #does #update #come

Dandadan follows two eccentric teenagers as they explore the bizarre secrets and myths of the world they inhabit. In their misadventures, Momo and Okarun learn more about one another and become close friends in the process. Their bond is unique, as no one else truly understands or relates to the unorthodox beliefs and interests they have. #dandadan #there #anyone #who #can

Project G-Assist — available through the NVIDIA App — is an experimental AI assistant that helps tune, control and optimize NVIDIA GeForce RTX systems. NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites the community to explore AI and build custom G-Assist plug-ins for a chance to win prizes and be featured on NVIDIA social media channels. G-Assist allows users to control their RTX GPU and other system settings using natural language, thanks to a small language model that runs on device. It can be used from the NVIDIA Overlay in the NVIDIA App without needing to tab out or switch programs. Users can expand its capabilities via plug-ins and even connect it to agentic frameworks such as Langflow. Below, find popular G-Assist plug-ins, hackathon details and tips to get started. Plug-In and Win Join the hackathon by registering and checking out the curated technical resources. G-Assist plug-ins can be built in several ways, including with Python for rapid development, with C++ for performance-critical apps and with custom system interactions for hardware and operating system automation. For those that prefer vibe coding, the G-Assist Plug-In Builder — a ChatGPT-based app that allows no-code or low-code development with natural language commands — makes it easy for enthusiasts to start creating plug-ins. To submit an entry, participants must provide a GitHub repository, including source code file, requirements.txt, manifest.json, config.json, a plug-in executable file and READme code. Then, submit a video — between 30 seconds and two minutes — showcasing the plug-in in action. Finally, hackathoners must promote their plug-in using #AIonRTXHackathon on a social media channel: Instagram, TikTok or X. Submit projects via this form by Wednesday, July 16. Judges will assess plug-ins based on three main criteria: 1) innovation and creativity, 2) technical execution and integration, reviewing technical depth, G-Assist integration and scalability, and 3) usability and community impact, aka how easy it is to use the plug-in. Winners will be selected on Wednesday, Aug. 20. First place will receive a GeForce RTX 5090 laptop, second place a GeForce RTX 5080 GPU and third a GeForce RTX 5070 GPU. These top three will also be featured on NVIDIA’s social media channels, get the opportunity to meet the NVIDIA G-Assist team and earn an NVIDIA Deep Learning Institute self-paced course credit. Project G-Assist requires a GeForce RTX 50, 40 or 30 Series Desktop GPU with at least 12GB of VRAM, Windows 11 or 10 operating system, a compatible CPU, specific disk space requirements and a recent GeForce Game Ready Driver or NVIDIA Studio Driver. Plug-InExplore open-source plug-in samples available on GitHub, which showcase the diverse ways on-device AI can enhance PC and gaming workflows. Popular plug-ins include: Google Gemini: Enables search-based queries using Google Search integration and large language model-based queries using Gemini capabilities in real time without needing to switch programs from the convenience of the NVIDIA App Overlay. Discord: Enables users to easily share game highlights or messages directly to Discord servers without disrupting gameplay. IFTTT: Lets users create automations across hundreds of compatible endpoints to trigger IoT routines — such as adjusting room lights and smart shades, or pushing the latest gaming news to a mobile device. Spotify: Lets users control Spotify using simple voice commands or the G-Assist interface to play favorite tracks and manage playlists. Twitch: Checks if any Twitch streamer is currently live and can access detailed stream information such as titles, games, view counts and more. Get G-Assist  Join the NVIDIA Developer Discord channel to collaborate, share creations and gain support from fellow AI enthusiasts and NVIDIA staff. the date for NVIDIA’s How to Build a G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities, discover the fundamentals of building, testing and deploying Project G-Assist plug-ins, and participate in a live Q&A session. Explore NVIDIA’s GitHub repository, which provides everything needed to get started developing with G-Assist, including sample plug-ins, step-by-step instructions and documentation for building custom functionalities. Learn more about the ChatGPT Plug-In Builder to transform ideas into functional G-Assist plug-ins with minimal coding. The tool uses OpenAI’s custom GPT builder to generate plug-in code and streamline the development process. NVIDIA’s technical blog walks through the architecture of a G-Assist plug-in, using a Twitch integration as an example. Discover how plug-ins work, how they communicate with G-Assist and how to build them from scratch. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information. #plug #play #build #gassist #plugin

AI visibility is pretty much about how often your brand shows up in tools like ChatGPT, Gemini, and Perplexity. If you're into tracking or growing your brand's presence, there's this guide that covers it. It's supposed to be expert-backed and all, but honestly, who knows? Just another thing to think about. If you want to dive into it, go ahead. If not, whatever. #AIVisibility #BrandPresence #LLMs #DigitalMarketing #ContentStrategy

Adventure Gamers, the once beloved site for point-and-click adventure gaming, has wiped its forums and relaunched as a gambling affiliate. It's just another cash-grab, really. What used to be a hub for enthusiasts now feels like a hollow echo of its former self. After years of supporting the adventure genre, it's sad to see it turn into something so... uninspiring. Not much else to say. Guess that's how it goes. #AdventureGamers #GamingNews #GamblingAffiliate #PointAndClick #SadChange

There’s no stopping Boruto: Two Blue Vortex from releasing new and intense chapters one after another in the God Tree arc. With Boruto facing Jura, fans know that Ikemoto is going to insert Kawaki into the fight sooner or later. True enough, Kawaki makes a dramatic entrance in Boruto: Two Blue Vortex chapter 23, sporting a new look that fans instantly noticed. #boruto #kawaki #officially #leaf #ninja

Halo Studios has decided to give their blessing for a fan-made Halo game called "survivors." Apparently, it’s supposed to be made by the community, with the community, and for the community. Sounds fine, I guess. But, you know, it’s just another game in an endless stream of fan projects. Not really sure if it’ll be anything special. Anyway, if you’re into Halo, maybe check it out. Or don’t. Whatever. #HaloSurvivors #FanMade #HaloCommunity #GamingNews #NoExcitement