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  • NVIDIA Compartió un vínculo
    2025-06-27 19:47:09 - Translate -
    Calling on LLMs: New NVIDIA AI Blueprint Helps Automate Telco Network Configuration

    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
    Calling on LLMs: New NVIDIA AI Blueprint Helps Automate Telco Network Configuration
    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
    BLOGS.NVIDIA.COM
    Calling on LLMs: New NVIDIA AI Blueprint Helps Automate Telco Network Configuration
    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.
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  • NVIDIA Compartió un vínculo
    2025-06-27 15:46:25 - Translate -
    Plug and Play: Build a G-Assist Plug-In Today

    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
    Plug and Play: Build a G-Assist Plug-In Today
    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
    BLOGS.NVIDIA.COM
    Plug and Play: Build a G-Assist Plug-In Today
    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 (plugin.py), requirements.txt, manifest.json, config.json (if applicable), 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 (Intel Pentium G Series, Core i3, i5, i7 or higher; AMD FX, Ryzen 3, 5, 7, 9, Threadripper or higher), specific disk space requirements and a recent GeForce Game Ready Driver or NVIDIA Studio Driver. Plug-In(spiration) Explore 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(ance)  Join the NVIDIA Developer Discord channel to collaborate, share creations and gain support from fellow AI enthusiasts and NVIDIA staff. Save 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.
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  • NVIDIA Compartió un vínculo
    2025-06-27 13:46:30 - Translate -
    NVIDIA and Partners Highlight Next-Generation Robotics, Automation and AI Technologies at Automatica

    From the heart of Germany’s automotive sector to manufacturing hubs across France and Italy, Europe is embracing industrial AI and advanced AI-powered robotics to address labor shortages, boost productivity and fuel sustainable economic growth.
    Robotics companies are developing humanoid robots and collaborative systems that integrate AI into real-world manufacturing applications. Supported by a billion investment initiative and coordinated efforts from the European Commission, Europe is positioning itself at the forefront of the next wave of industrial automation, powered by AI.
    This momentum is on full display at Automatica — Europe’s premier conference on advancements in robotics, machine vision and intelligent manufacturing — taking place this week in Munich, Germany.
    NVIDIA and its ecosystem of partners and customers are showcasing next-generation robots, automation and AI technologies designed to accelerate the continent’s leadership in smart manufacturing and logistics.
    NVIDIA Technologies Boost Robotics Development 
    Central to advancing robotics development is Europe’s first industrial AI cloud, announced at NVIDIA GTC Paris at VivaTech earlier this month. The Germany-based AI factory, featuring 10,000 NVIDIA GPUs, provides European manufacturers with secure, sovereign and centralized AI infrastructure for industrial workloads. It will support applications ranging from design and engineering to factory digital twins and robotics.
    To help accelerate humanoid development, NVIDIA released NVIDIA Isaac GR00T N1.5 — an open foundation model for humanoid robot reasoning and skills. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks.
    To help post-train GR00T N1.5, NVIDIA has also released the Isaac GR00T-Dreams blueprint — a reference workflow for generating vast amounts of synthetic trajectory data from a small number of human demonstrations — enabling robots to generalize across behaviors and adapt to new environments with minimal human demonstration data.
    In addition, early developer previews of NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 — open-source robot simulation and learning frameworks optimized for NVIDIA RTX PRO 6000 workstations — are now available on GitHub.
    Image courtesy of Wandelbots.
    Robotics Leaders Tap NVIDIA Simulation Technology to Develop and Deploy Humanoids and More 
    Robotics developers and solutions providers across the globe are integrating NVIDIA’s three computers to train, simulate and deploy robots.
    NEURA Robotics, a German robotics company and pioneer for cognitive robots, unveiled the third generation of its humanoid, 4NE1, designed to assist humans in domestic and professional environments through advanced cognitive capabilities and humanlike interaction. 4NE1 is powered by GR00T N1 and was trained in Isaac Sim and Isaac Lab before real-world deployment.
    NEURA Robotics is also presenting Neuraverse, a digital twin and interconnected ecosystem for robot training, skills and applications, fully compatible with NVIDIA Omniverse technologies.
    Delta Electronics, a global leader in power management and smart green solutions, is debuting two next-generation collaborative robots: D-Bot Mar and D-Bot 2 in 1 — both trained using Omniverse and Isaac Sim technologies and libraries. These cobots are engineered to transform intralogistics and optimize production flows.
    Wandelbots, the creator of the Wandelbots NOVA software platform for industrial robotics, is partnering with SoftServe, a global IT consulting and digital services provider, to scale simulation-first automating using NVIDIA Isaac Sim, enabling virtual validation and real-world deployment with maximum impact.
    Cyngn, a pioneer in autonomous mobile robotics, is integrating its DriveMod technology into Isaac Sim to enable large-scale, high fidelity virtual testing of advanced autonomous operation. Purpose-built for industrial applications, DriveMod is already deployed on vehicles such as the Motrec MT-160 Tugger and BYD Forklift, delivering sophisticated automation to material handling operations.
    Doosan Robotics, a company specializing in AI robotic solutions, will showcase its “sim to real” solution, using NVIDIA Isaac Sim and cuRobo. Doosan will be showcasing how to seamlessly transfer tasks from simulation to real robots across a wide range of applications — from manufacturing to service industries.
    Franka Robotics has integrated Isaac GR00T N1.5 into a dual-arm Franka Research 3robot for robotic control. The integration of GR00T N1.5 allows the system to interpret visual input, understand task context and autonomously perform complex manipulation — without the need for task-specific programming or hardcoded logic.
    Image courtesy of Franka Robotics.
    Hexagon, the global leader in measurement technologies, launched its new humanoid, dubbed AEON. With its unique locomotion system and multimodal sensor fusion, and powered by NVIDIA’s three-computer solution, AEON is engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support.
    Intrinsic, a software and AI robotics company, is integrating Intrinsic Flowstate with  Omniverse and OpenUSD for advanced visualization and digital twins that can be used in many industrial use cases. The company is also using NVIDIA foundation models to enhance robot capabilities like grasp planning through AI and simulation technologies.
    SCHUNK, a global leader in gripping systems and automation technology, is showcasing its innovative grasping kit powered by the NVIDIA Jetson AGX Orin module. The kit intelligently detects objects and calculates optimal grasping points. Schunk is also demonstrating seamless simulation-to-reality transfer using IGS Virtuous software — built on Omniverse technologies — to control a real robot through simulation in a pick-and-place scenario.
    Universal Robots is showcasing UR15, its fastest cobot yet. Powered by the UR AI Accelerator — developed with NVIDIA and running on Jetson AGX Orin using CUDA-accelerated Isaac libraries — UR15 helps set a new standard for industrial automation.

    Vention, a full-stack software and hardware automation company, launched its Machine Motion AI, built on CUDA-accelerated Isaac libraries and powered by Jetson. Vention is also expanding its lineup of robotic offerings by adding the FR3 robot from Franka Robotics to its ecosystem, enhancing its solutions for academic and research applications.
    Image courtesy of Vention.
    Learn more about the latest robotics advancements by joining NVIDIA at Automatica, running through Friday, June 27. 
    #nvidia #partners #highlight #nextgeneration #robotics
    NVIDIA and Partners Highlight Next-Generation Robotics, Automation and AI Technologies at Automatica
    From the heart of Germany’s automotive sector to manufacturing hubs across France and Italy, Europe is embracing industrial AI and advanced AI-powered robotics to address labor shortages, boost productivity and fuel sustainable economic growth. Robotics companies are developing humanoid robots and collaborative systems that integrate AI into real-world manufacturing applications. Supported by a billion investment initiative and coordinated efforts from the European Commission, Europe is positioning itself at the forefront of the next wave of industrial automation, powered by AI. This momentum is on full display at Automatica — Europe’s premier conference on advancements in robotics, machine vision and intelligent manufacturing — taking place this week in Munich, Germany. NVIDIA and its ecosystem of partners and customers are showcasing next-generation robots, automation and AI technologies designed to accelerate the continent’s leadership in smart manufacturing and logistics. NVIDIA Technologies Boost Robotics Development  Central to advancing robotics development is Europe’s first industrial AI cloud, announced at NVIDIA GTC Paris at VivaTech earlier this month. The Germany-based AI factory, featuring 10,000 NVIDIA GPUs, provides European manufacturers with secure, sovereign and centralized AI infrastructure for industrial workloads. It will support applications ranging from design and engineering to factory digital twins and robotics. To help accelerate humanoid development, NVIDIA released NVIDIA Isaac GR00T N1.5 — an open foundation model for humanoid robot reasoning and skills. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. To help post-train GR00T N1.5, NVIDIA has also released the Isaac GR00T-Dreams blueprint — a reference workflow for generating vast amounts of synthetic trajectory data from a small number of human demonstrations — enabling robots to generalize across behaviors and adapt to new environments with minimal human demonstration data. In addition, early developer previews of NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 — open-source robot simulation and learning frameworks optimized for NVIDIA RTX PRO 6000 workstations — are now available on GitHub. Image courtesy of Wandelbots. Robotics Leaders Tap NVIDIA Simulation Technology to Develop and Deploy Humanoids and More  Robotics developers and solutions providers across the globe are integrating NVIDIA’s three computers to train, simulate and deploy robots. NEURA Robotics, a German robotics company and pioneer for cognitive robots, unveiled the third generation of its humanoid, 4NE1, designed to assist humans in domestic and professional environments through advanced cognitive capabilities and humanlike interaction. 4NE1 is powered by GR00T N1 and was trained in Isaac Sim and Isaac Lab before real-world deployment. NEURA Robotics is also presenting Neuraverse, a digital twin and interconnected ecosystem for robot training, skills and applications, fully compatible with NVIDIA Omniverse technologies. Delta Electronics, a global leader in power management and smart green solutions, is debuting two next-generation collaborative robots: D-Bot Mar and D-Bot 2 in 1 — both trained using Omniverse and Isaac Sim technologies and libraries. These cobots are engineered to transform intralogistics and optimize production flows. Wandelbots, the creator of the Wandelbots NOVA software platform for industrial robotics, is partnering with SoftServe, a global IT consulting and digital services provider, to scale simulation-first automating using NVIDIA Isaac Sim, enabling virtual validation and real-world deployment with maximum impact. Cyngn, a pioneer in autonomous mobile robotics, is integrating its DriveMod technology into Isaac Sim to enable large-scale, high fidelity virtual testing of advanced autonomous operation. Purpose-built for industrial applications, DriveMod is already deployed on vehicles such as the Motrec MT-160 Tugger and BYD Forklift, delivering sophisticated automation to material handling operations. Doosan Robotics, a company specializing in AI robotic solutions, will showcase its “sim to real” solution, using NVIDIA Isaac Sim and cuRobo. Doosan will be showcasing how to seamlessly transfer tasks from simulation to real robots across a wide range of applications — from manufacturing to service industries. Franka Robotics has integrated Isaac GR00T N1.5 into a dual-arm Franka Research 3robot for robotic control. The integration of GR00T N1.5 allows the system to interpret visual input, understand task context and autonomously perform complex manipulation — without the need for task-specific programming or hardcoded logic. Image courtesy of Franka Robotics. Hexagon, the global leader in measurement technologies, launched its new humanoid, dubbed AEON. With its unique locomotion system and multimodal sensor fusion, and powered by NVIDIA’s three-computer solution, AEON is engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support. Intrinsic, a software and AI robotics company, is integrating Intrinsic Flowstate with  Omniverse and OpenUSD for advanced visualization and digital twins that can be used in many industrial use cases. The company is also using NVIDIA foundation models to enhance robot capabilities like grasp planning through AI and simulation technologies. SCHUNK, a global leader in gripping systems and automation technology, is showcasing its innovative grasping kit powered by the NVIDIA Jetson AGX Orin module. The kit intelligently detects objects and calculates optimal grasping points. Schunk is also demonstrating seamless simulation-to-reality transfer using IGS Virtuous software — built on Omniverse technologies — to control a real robot through simulation in a pick-and-place scenario. Universal Robots is showcasing UR15, its fastest cobot yet. Powered by the UR AI Accelerator — developed with NVIDIA and running on Jetson AGX Orin using CUDA-accelerated Isaac libraries — UR15 helps set a new standard for industrial automation. Vention, a full-stack software and hardware automation company, launched its Machine Motion AI, built on CUDA-accelerated Isaac libraries and powered by Jetson. Vention is also expanding its lineup of robotic offerings by adding the FR3 robot from Franka Robotics to its ecosystem, enhancing its solutions for academic and research applications. Image courtesy of Vention. Learn more about the latest robotics advancements by joining NVIDIA at Automatica, running through Friday, June 27.  #nvidia #partners #highlight #nextgeneration #robotics
    BLOGS.NVIDIA.COM
    NVIDIA and Partners Highlight Next-Generation Robotics, Automation and AI Technologies at Automatica
    From the heart of Germany’s automotive sector to manufacturing hubs across France and Italy, Europe is embracing industrial AI and advanced AI-powered robotics to address labor shortages, boost productivity and fuel sustainable economic growth. Robotics companies are developing humanoid robots and collaborative systems that integrate AI into real-world manufacturing applications. Supported by a $200 billion investment initiative and coordinated efforts from the European Commission, Europe is positioning itself at the forefront of the next wave of industrial automation, powered by AI. This momentum is on full display at Automatica — Europe’s premier conference on advancements in robotics, machine vision and intelligent manufacturing — taking place this week in Munich, Germany. NVIDIA and its ecosystem of partners and customers are showcasing next-generation robots, automation and AI technologies designed to accelerate the continent’s leadership in smart manufacturing and logistics. NVIDIA Technologies Boost Robotics Development  Central to advancing robotics development is Europe’s first industrial AI cloud, announced at NVIDIA GTC Paris at VivaTech earlier this month. The Germany-based AI factory, featuring 10,000 NVIDIA GPUs, provides European manufacturers with secure, sovereign and centralized AI infrastructure for industrial workloads. It will support applications ranging from design and engineering to factory digital twins and robotics. To help accelerate humanoid development, NVIDIA released NVIDIA Isaac GR00T N1.5 — an open foundation model for humanoid robot reasoning and skills. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. To help post-train GR00T N1.5, NVIDIA has also released the Isaac GR00T-Dreams blueprint — a reference workflow for generating vast amounts of synthetic trajectory data from a small number of human demonstrations — enabling robots to generalize across behaviors and adapt to new environments with minimal human demonstration data. In addition, early developer previews of NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 — open-source robot simulation and learning frameworks optimized for NVIDIA RTX PRO 6000 workstations — are now available on GitHub. Image courtesy of Wandelbots. Robotics Leaders Tap NVIDIA Simulation Technology to Develop and Deploy Humanoids and More  Robotics developers and solutions providers across the globe are integrating NVIDIA’s three computers to train, simulate and deploy robots. NEURA Robotics, a German robotics company and pioneer for cognitive robots, unveiled the third generation of its humanoid, 4NE1, designed to assist humans in domestic and professional environments through advanced cognitive capabilities and humanlike interaction. 4NE1 is powered by GR00T N1 and was trained in Isaac Sim and Isaac Lab before real-world deployment. NEURA Robotics is also presenting Neuraverse, a digital twin and interconnected ecosystem for robot training, skills and applications, fully compatible with NVIDIA Omniverse technologies. Delta Electronics, a global leader in power management and smart green solutions, is debuting two next-generation collaborative robots: D-Bot Mar and D-Bot 2 in 1 — both trained using Omniverse and Isaac Sim technologies and libraries. These cobots are engineered to transform intralogistics and optimize production flows. Wandelbots, the creator of the Wandelbots NOVA software platform for industrial robotics, is partnering with SoftServe, a global IT consulting and digital services provider, to scale simulation-first automating using NVIDIA Isaac Sim, enabling virtual validation and real-world deployment with maximum impact. Cyngn, a pioneer in autonomous mobile robotics, is integrating its DriveMod technology into Isaac Sim to enable large-scale, high fidelity virtual testing of advanced autonomous operation. Purpose-built for industrial applications, DriveMod is already deployed on vehicles such as the Motrec MT-160 Tugger and BYD Forklift, delivering sophisticated automation to material handling operations. Doosan Robotics, a company specializing in AI robotic solutions, will showcase its “sim to real” solution, using NVIDIA Isaac Sim and cuRobo. Doosan will be showcasing how to seamlessly transfer tasks from simulation to real robots across a wide range of applications — from manufacturing to service industries. Franka Robotics has integrated Isaac GR00T N1.5 into a dual-arm Franka Research 3 (FR3) robot for robotic control. The integration of GR00T N1.5 allows the system to interpret visual input, understand task context and autonomously perform complex manipulation — without the need for task-specific programming or hardcoded logic. Image courtesy of Franka Robotics. Hexagon, the global leader in measurement technologies, launched its new humanoid, dubbed AEON. With its unique locomotion system and multimodal sensor fusion, and powered by NVIDIA’s three-computer solution, AEON is engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support. Intrinsic, a software and AI robotics company, is integrating Intrinsic Flowstate with  Omniverse and OpenUSD for advanced visualization and digital twins that can be used in many industrial use cases. The company is also using NVIDIA foundation models to enhance robot capabilities like grasp planning through AI and simulation technologies. SCHUNK, a global leader in gripping systems and automation technology, is showcasing its innovative grasping kit powered by the NVIDIA Jetson AGX Orin module. The kit intelligently detects objects and calculates optimal grasping points. Schunk is also demonstrating seamless simulation-to-reality transfer using IGS Virtuous software — built on Omniverse technologies — to control a real robot through simulation in a pick-and-place scenario. Universal Robots is showcasing UR15, its fastest cobot yet. Powered by the UR AI Accelerator — developed with NVIDIA and running on Jetson AGX Orin using CUDA-accelerated Isaac libraries — UR15 helps set a new standard for industrial automation. Vention, a full-stack software and hardware automation company, launched its Machine Motion AI, built on CUDA-accelerated Isaac libraries and powered by Jetson. Vention is also expanding its lineup of robotic offerings by adding the FR3 robot from Franka Robotics to its ecosystem, enhancing its solutions for academic and research applications. Image courtesy of Vention. Learn more about the latest robotics advancements by joining NVIDIA at Automatica, running through Friday, June 27. 
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  • NVIDIA Compartió un vínculo
    2025-06-27 11:32:07 - Translate -
    Into the Omniverse: World Foundation Models Advance Autonomous Vehicle Simulation and Safety

    Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse.
    Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehiclesacross countless real-world and edge-case scenarios without the risks and costs of physical testing.
    These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models— neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation.
    To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools.
    Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale.
    Universal Scene Description, a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale.
    NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale.
    Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models.

    Foundations for Scalable, Realistic Simulation
    Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots.

    In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools.
    Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos.
    Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing.
    The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases.
    Driving the Future of AV Safety
    To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety.
    The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems.
    These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks.

    At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance.
    Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay:

    Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks.
    Get Plugged Into the World of OpenUSD
    Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote.
    Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14.
    Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute.
    Explore the Alliance for OpenUSD forum and the AOUSD website.
    Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.
    #into #omniverse #world #foundation #models
    Into the Omniverse: World Foundation Models Advance Autonomous Vehicle Simulation and Safety
    Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehiclesacross countless real-world and edge-case scenarios without the risks and costs of physical testing. These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models— neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation. To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools. Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale. Universal Scene Description, a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale. NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale. Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models. Foundations for Scalable, Realistic Simulation Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots. In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools. Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos. Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing. The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases. Driving the Future of AV Safety To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety. The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems. These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks. At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance. Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay: Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks. Get Plugged Into the World of OpenUSD Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote. Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14. Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute. Explore the Alliance for OpenUSD forum and the AOUSD website. Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X. #into #omniverse #world #foundation #models
    BLOGS.NVIDIA.COM
    Into the Omniverse: World Foundation Models Advance Autonomous Vehicle Simulation and Safety
    Editor’s note: This blog is a part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Simulated driving environments enable engineers to safely and efficiently train, test and validate autonomous vehicles (AVs) across countless real-world and edge-case scenarios without the risks and costs of physical testing. These simulated environments can be created through neural reconstruction of real-world data from AV fleets or generated with world foundation models (WFMs) — neural networks that understand physics and real-world properties. WFMs can be used to generate synthetic datasets for enhanced AV simulation. To help physical AI developers build such simulated environments, NVIDIA unveiled major advances in WFMs at the GTC Paris and CVPR conferences earlier this month. These new capabilities enhance NVIDIA Cosmos — a platform of generative WFMs, advanced tokenizers, guardrails and accelerated data processing tools. Key innovations like Cosmos Predict-2, the Cosmos Transfer-1 NVIDIA preview NIM microservice and Cosmos Reason are improving how AV developers generate synthetic data, build realistic simulated environments and validate safety systems at unprecedented scale. Universal Scene Description (OpenUSD), a unified data framework and standard for physical AI applications, enables seamless integration and interoperability of simulation assets across the development pipeline. OpenUSD standardization plays a critical role in ensuring 3D pipelines are built to scale. NVIDIA Omniverse, a platform of application programming interfaces, software development kits and services for building OpenUSD-based physical AI applications, enables simulations from WFMs and neural reconstruction at world scale. Leading AV organizations — including Foretellix, Mcity, Oxa, Parallel Domain, Plus AI and Uber — are among the first to adopt Cosmos models. Foundations for Scalable, Realistic Simulation Cosmos Predict-2, NVIDIA’s latest WFM, generates high-quality synthetic data by predicting future world states from multimodal inputs like text, images and video. This capability is critical for creating temporally consistent, realistic scenarios that accelerate training and validation of AVs and robots. In addition, Cosmos Transfer, a control model that adds variations in weather, lighting and terrain to existing scenarios, will soon be available to 150,000 developers on CARLA, a leading open-source AV simulator. This greatly expands the broad AV developer community’s access to advanced AI-powered simulation tools. Developers can start integrating synthetic data into their own pipelines using the NVIDIA Physical AI Dataset. The latest release includes 40,000 clips generated using Cosmos. Building on these foundations, the Omniverse Blueprint for AV simulation provides a standardized, API-driven workflow for constructing rich digital twins, replaying real-world sensor data and generating new ground-truth data for closed-loop testing. The blueprint taps into OpenUSD’s layer-stacking and composition arcs, which enable developers to collaborate asynchronously and modify scenes nondestructively. This helps create modular, reusable scenario variants to efficiently generate different weather conditions, traffic patterns and edge cases. Driving the Future of AV Safety To bolster the operational safety of AV systems, NVIDIA earlier this year introduced NVIDIA Halos — a comprehensive safety platform that integrates the company’s full automotive hardware and software stack with AI research focused on AV safety. The new Cosmos models — Cosmos Predict- 2, Cosmos Transfer- 1 NIM and Cosmos Reason — deliver further safety enhancements to the Halos platform, enabling developers to create diverse, controllable and realistic scenarios for training and validating AV systems. These models, trained on massive multimodal datasets including driving data, amplify the breadth and depth of simulation, allowing for robust scenario coverage — including rare and safety-critical events — while supporting post-training customization for specialized AV tasks. At CVPR, NVIDIA was recognized as an Autonomous Grand Challenge winner, highlighting its leadership in advancing end-to-end AV workflows. The challenge used OpenUSD’s robust metadata and interoperability to simulate sensor inputs and vehicle trajectories in semi-reactive environments, achieving state-of-the-art results in safety and compliance. Learn more about how developers are leveraging tools like CARLA, Cosmos, and Omniverse to advance AV simulation in this livestream replay: Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks. Get Plugged Into the World of OpenUSD Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote. Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14. Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute. Explore the Alliance for OpenUSD forum and the AOUSD website. Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.
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  • NVIDIA Compartió un vínculo
    2025-06-27 11:30:14 - Translate -
    Startup Uses NVIDIA RTX-Powered Generative AI to Make Coolers, Cooler

    Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production.
    Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. about his workflow below.
    Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder.
    In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session.
    From Concept to Completion
    To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms.
    For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI.
    ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated.
    Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY.
    NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU.
    ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images.
    Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptationmodels — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost.
    LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY.
    “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY 

    Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models.
    Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch.
    To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x.
    Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started.
    Photorealistic renders. Image courtesy of FITY.
    Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time.
    Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY.
    “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY

    Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added.
    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.
    #startup #uses #nvidia #rtxpowered #generative
    Startup Uses NVIDIA RTX-Powered Generative AI to Make Coolers, Cooler
    Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptationmodels — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. 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. #startup #uses #nvidia #rtxpowered #generative
    BLOGS.NVIDIA.COM
    Startup Uses NVIDIA RTX-Powered Generative AI to Make Coolers, Cooler
    Mark Theriault founded the startup FITY envisioning a line of clever cooling products: cold drink holders that come with freezable pucks to keep beverages cold for longer without the mess of ice. The entrepreneur started with 3D prints of products in his basement, building one unit at a time, before eventually scaling to mass production. Founding a consumer product company from scratch was a tall order for a single person. Going from preliminary sketches to production-ready designs was a major challenge. To bring his creative vision to life, Theriault relied on AI and his NVIDIA GeForce RTX-equipped system. For him, AI isn’t just a tool — it’s an entire pipeline to help him accomplish his goals. Read more about his workflow below. Plus, GeForce RTX 5050 laptops start arriving today at retailers worldwide, from $999. GeForce RTX 5050 Laptop GPUs feature 2,560 NVIDIA Blackwell CUDA cores, fifth-generation AI Tensor Cores, fourth-generation RT Cores, a ninth-generation NVENC encoder and a sixth-generation NVDEC decoder. In addition, NVIDIA’s Plug and Play: Project G-Assist Plug-In Hackathon — running virtually through Wednesday, July 16 — invites developers to explore AI and build custom G-Assist plug-ins for a chance to win prizes. Save the date for the G-Assist Plug-In webinar on Wednesday, July 9, from 10-11 a.m. PT, to learn more about Project G-Assist capabilities and fundamentals, and to participate in a live Q&A session. From Concept to Completion To create his standout products, Theriault tinkers with potential FITY Flex cooler designs with traditional methods, from sketch to computer-aided design to rapid prototyping, until he finds the right vision. A unique aspect of the FITY Flex design is that it can be customized with fun, popular shoe charms. For packaging design inspiration, Theriault uses his preferred text-to-image generative AI model for prototyping, Stable Diffusion XL — which runs 60% faster with the NVIDIA TensorRT software development kit — using the modular, node-based interface ComfyUI. ComfyUI gives users granular control over every step of the generation process — prompting, sampling, model loading, image conditioning and post-processing. It’s ideal for advanced users like Theriault who want to customize how images are generated. Theriault’s uses of AI result in a complete computer graphics-based ad campaign. Image courtesy of FITY. NVIDIA and GeForce RTX GPUs based on the NVIDIA Blackwell architecture include fifth-generation Tensor Cores designed to accelerate AI and deep learning workloads. These GPUs work with CUDA optimizations in PyTorch to seamlessly accelerate ComfyUI, reducing generation time on FLUX.1-dev, an image generation model from Black Forest Labs, from two minutes per image on the Mac M3 Ultra to about four seconds on the GeForce RTX 5090 desktop GPU. ComfyUI can also add ControlNets — AI models that help control image generation — that Theriault uses for tasks like guiding human poses, setting compositions via depth mapping and converting scribbles to images. Theriault even creates his own fine-tuned models to keep his style consistent. He used low-rank adaptation (LoRA) models — small, efficient adapters into specific layers of the network — enabling hyper-customized generation with minimal compute cost. LoRA models allow Theriault to ideate on visuals quickly. Image courtesy of FITY. “Over the last few months, I’ve been shifting from AI-assisted computer graphics renders to fully AI-generated product imagery using a custom Flux LoRA I trained in house. My RTX 4080 SUPER GPU has been essential for getting the performance I need to train and iterate quickly.” – Mark Theriault, founder of FITY  Theriault also taps into generative AI to create marketing assets like FITY Flex product packaging. He uses FLUX.1, which excels at generating legible text within images, addressing a common challenge in text-to-image models. Though FLUX.1 models can typically consume over 23GB of VRAM, NVIDIA has collaborated with Black Forest Labs to help reduce the size of these models using quantization — a technique that reduces model size while maintaining quality. The models were then accelerated with TensorRT, which provides an up to 2x speedup over PyTorch. To simplify using these models in ComfyUI, NVIDIA created the FLUX.1 NIM microservice, a containerized version of FLUX.1 that can be loaded in ComfyUI and enables FP4 quantization and TensorRT support. Combined, the models come down to just over 11GB of VRAM, and performance improves by 2.5x. Theriault uses the Blender Cycles app to render out final files. For 3D workflows, NVIDIA offers the AI Blueprint for 3D-guided generative AI to ease the positioning and composition of 3D images, so anyone interested in this method can quickly get started. Photorealistic renders. Image courtesy of FITY. Finally, Theriault uses large language models to generate marketing copy — tailored for search engine optimization, tone and storytelling — as well as to complete his patent and provisional applications, work that usually costs thousands of dollars in legal fees and considerable time. Generative AI helps Theriault create promotional materials like the above. Image courtesy of FITY. “As a one-man band with a ton of content to generate, having on-the-fly generation capabilities for my product designs really helps speed things up.” – Mark Theriault, founder of FITY Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added. 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.
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  • Visual Effects Society Compartió un vínculo
    2025-06-27 11:25:48 - Translate -
    HOW DISGUISE BUILT OUT THE VIRTUAL ENVIRONMENTS FOR A MINECRAFT MOVIE

    By TREVOR HOGG

    Images courtesy of Warner Bros. Pictures.

    Rather than a world constructed around photorealistic pixels, a video game created by Markus Persson has taken the boxier 3D voxel route, which has become its signature aesthetic, and sparked an international phenomenon that finally gets adapted into a feature with the release of A Minecraft Movie. Brought onboard to help filmmaker Jared Hess in creating the environments that the cast of Jason Momoa, Jack Black, Sebastian Hansen, Emma Myers and Danielle Brooks find themselves inhabiting was Disguise under the direction of Production VFX Supervisor Dan Lemmon.

    “s the Senior Unreal Artist within the Virtual Art Departmenton Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.”
    —Talia Finlayson, Creative Technologist, Disguise

    Interior and exterior environments had to be created, such as the shop owned by Steve.

    “Prior to working on A Minecraft Movie, I held more technical roles, like serving as the Virtual Production LED Volume Operator on a project for Apple TV+ and Paramount Pictures,” notes Talia Finlayson, Creative Technologist for Disguise. “But as the Senior Unreal Artist within the Virtual Art Departmenton Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.” The project provided new opportunities. “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance,” notes Laura Bell, Creative Technologist for Disguise. “But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.”

    Set designs originally created by the art department in Rhinoceros 3D were transformed into fully navigable 3D environments within Unreal Engine. “These scenes were far more than visualizations,” Finlayson remarks. “They were interactive tools used throughout the production pipeline. We would ingest 3D models and concept art, clean and optimize geometry using tools like Blender, Cinema 4D or Maya, then build out the world in Unreal Engine. This included applying materials, lighting and extending environments. These Unreal scenes we created were vital tools across the production and were used for a variety of purposes such as enabling the director to explore shot compositions, block scenes and experiment with camera movement in a virtual space, as well as passing along Unreal Engine scenes to the visual effects vendors so they could align their digital environments and set extensions with the approved production layouts.”

    A virtual exploration of Steve’s shop in Midport Village.

    Certain elements have to be kept in mind when constructing virtual environments. “When building virtual environments, you need to consider what can actually be built, how actors and cameras will move through the space, and what’s safe and practical on set,” Bell observes. “Outside the areas where strict accuracy is required, you want the environments to blend naturally with the original designs from the art department and support the story, creating a space that feels right for the scene, guides the audience’s eye and sets the right tone. Things like composition, lighting and small environmental details can be really fun to work on, but also serve as beautiful additions to help enrich a story.”

    “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance. But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.”
    —Laura Bell, Creative Technologist, Disguise

    Among the buildings that had to be created for Midport Village was Steve’sLava Chicken Shack.

    Concept art was provided that served as visual touchstones. “We received concept art provided by the amazing team of concept artists,” Finlayson states. “Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging. Sometimes we would also help the storyboard artists by sending through images of the Unreal Engine worlds to help them geographically position themselves in the worlds and aid in their storyboarding.” At times, the video game assets came in handy. “Exteriors often involved large-scale landscapes and stylized architectural elements, which had to feel true to the Minecraft world,” Finlayson explains. “In some cases, we brought in geometry from the game itself to help quickly block out areas. For example, we did this for the Elytra Flight Chase sequence, which takes place through a large canyon.”

    Flexibility was critical. “A key technical challenge we faced was ensuring that the Unreal levels were built in a way that allowed for fast and flexible iteration,” Finlayson remarks. “Since our environments were constantly being reviewed by the director, production designer, DP and VFX supervisor, we needed to be able to respond quickly to feedback, sometimes live during a review session. To support this, we had to keep our scenes modular and well-organized; that meant breaking environments down into manageable components and maintaining clean naming conventions. By setting up the levels this way, we could make layout changes, swap assets or adjust lighting on the fly without breaking the scene or slowing down the process.” Production schedules influence the workflows, pipelines and techniques. “No two projects will ever feel exactly the same,” Bell notes. “For example, Pat Younisadapted his typical VR setup to allow scene reviews using a PS5 controller, which made it much more comfortable and accessible for the director. On a more technical side, because everything was cubes and voxels, my Blender workflow ended up being way heavier on the re-mesh modifier than usual, definitely not something I’ll run into again anytime soon!”

    A virtual study and final still of the cast members standing outside of the Lava Chicken Shack.

    “We received concept art provided by the amazing team of concept artists. Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging.”
    —Talia Finlayson, Creative Technologist, Disguise

    The design and composition of virtual environments tended to remain consistent throughout principal photography. “The only major design change I can recall was the removal of a second story from a building in Midport Village to allow the camera crane to get a clear shot of the chicken perched above Steve’s lava chicken shack,” Finlayson remarks. “I would agree that Midport Village likely went through the most iterations,” Bell responds. “The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled. I remember rebuilding the stairs leading up to the rampart five or six times, using different configurations based on the physically constructed stairs. This was because there were storyboarded sequences of the film’s characters, Henry, Steve and Garrett, being chased by piglins, and the action needed to match what could be achieved practically on set.”

    Virtually conceptualizing the layout of Midport Village.

    Complex virtual environments were constructed for the final battle and the various forest scenes throughout the movie. “What made these particularly challenging was the way physical set pieces were repurposed and repositioned to serve multiple scenes and locations within the story,” Finlayson reveals. “The same built elements had to appear in different parts of the world, so we had to carefully adjust the virtual environments to accommodate those different positions.” Bell is in agreement with her colleague. “The forest scenes were some of the more complex environments to manage. It could get tricky, particularly when the filming schedule shifted. There was one day on set where the order of shots changed unexpectedly, and because the physical sets looked so similar, I initially loaded a different perspective than planned. Fortunately, thanks to our workflow, Lindsay Georgeand I were able to quickly open the recorded sequence in Unreal Engine and swap out the correct virtual environment for the live composite without any disruption to the shoot.”

    An example of the virtual and final version of the Woodland Mansion.

    “Midport Village likely went through the most iterations. The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled.”
    —Laura Bell, Creative Technologist, Disguise

    Extensive detail was given to the center of the sets where the main action unfolds. “For these areas, we received prop layouts from the prop department to ensure accurate placement and alignment with the physical builds,” Finlayson explains. “These central environments were used heavily for storyboarding, blocking and department reviews, so precision was essential. As we moved further out from the practical set, the environments became more about blocking and spatial context rather than fine detail. We worked closely with Production Designer Grant Major to get approval on these extended environments, making sure they aligned with the overall visual direction. We also used creatures and crowd stand-ins provided by the visual effects team. These gave a great sense of scale and placement during early planning stages and allowed other departments to better understand how these elements would be integrated into the scenes.”

    Cast members Sebastian Hansen, Danielle Brooks and Emma Myers stand in front of the Earth Portal Plateau environment.

    Doing a virtual scale study of the Mountainside.

    Practical requirements like camera moves, stunt choreography and crane setups had an impact on the creation of virtual environments. “Sometimes we would adjust layouts slightly to open up areas for tracking shots or rework spaces to accommodate key action beats, all while keeping the environment feeling cohesive and true to the Minecraft world,” Bell states. “Simulcam bridged the physical and virtual worlds on set, overlaying Unreal Engine environments onto live-action scenes in real-time, giving the director, DP and other department heads a fully-realized preview of shots and enabling precise, informed decisions during production. It also recorded critical production data like camera movement paths, which was handed over to the post-production team to give them the exact tracks they needed, streamlining the visual effects pipeline.”

    Piglots cause mayhem during the Wingsuit Chase.

    Virtual versions of the exterior and interior of the Safe House located in the Enchanted Woods.

    “One of the biggest challenges for me was managing constant iteration while keeping our environments clean, organized and easy to update,” Finlayson notes. “Because the virtual sets were reviewed regularly by the director and other heads of departments, feedback was often implemented live in the room. This meant the environments had to be flexible. But overall, this was an amazing project to work on, and I am so grateful for the incredible VAD team I was a part of – Heide Nichols, Pat Younis, Jake Tuckand Laura. Everyone on this team worked so collaboratively, seamlessly and in such a supportive way that I never felt like I was out of my depth.” There was another challenge that is more to do with familiarity. “Having a VAD on a film is still a relatively new process in production,” Bell states. “There were moments where other departments were still learning what we did and how to best work with us. That said, the response was overwhelmingly positive. I remember being on set at the Simulcam station and seeing how excited people were to look at the virtual environments as they walked by, often stopping for a chat and a virtual tour. Instead of seeing just a huge blue curtain, they were stoked to see something Minecraft and could get a better sense of what they were actually shooting.”
    #how #disguise #built #out #virtual
    HOW DISGUISE BUILT OUT THE VIRTUAL ENVIRONMENTS FOR A MINECRAFT MOVIE
    By TREVOR HOGG Images courtesy of Warner Bros. Pictures. Rather than a world constructed around photorealistic pixels, a video game created by Markus Persson has taken the boxier 3D voxel route, which has become its signature aesthetic, and sparked an international phenomenon that finally gets adapted into a feature with the release of A Minecraft Movie. Brought onboard to help filmmaker Jared Hess in creating the environments that the cast of Jason Momoa, Jack Black, Sebastian Hansen, Emma Myers and Danielle Brooks find themselves inhabiting was Disguise under the direction of Production VFX Supervisor Dan Lemmon. “s the Senior Unreal Artist within the Virtual Art Departmenton Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.” —Talia Finlayson, Creative Technologist, Disguise Interior and exterior environments had to be created, such as the shop owned by Steve. “Prior to working on A Minecraft Movie, I held more technical roles, like serving as the Virtual Production LED Volume Operator on a project for Apple TV+ and Paramount Pictures,” notes Talia Finlayson, Creative Technologist for Disguise. “But as the Senior Unreal Artist within the Virtual Art Departmenton Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.” The project provided new opportunities. “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance,” notes Laura Bell, Creative Technologist for Disguise. “But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.” Set designs originally created by the art department in Rhinoceros 3D were transformed into fully navigable 3D environments within Unreal Engine. “These scenes were far more than visualizations,” Finlayson remarks. “They were interactive tools used throughout the production pipeline. We would ingest 3D models and concept art, clean and optimize geometry using tools like Blender, Cinema 4D or Maya, then build out the world in Unreal Engine. This included applying materials, lighting and extending environments. These Unreal scenes we created were vital tools across the production and were used for a variety of purposes such as enabling the director to explore shot compositions, block scenes and experiment with camera movement in a virtual space, as well as passing along Unreal Engine scenes to the visual effects vendors so they could align their digital environments and set extensions with the approved production layouts.” A virtual exploration of Steve’s shop in Midport Village. Certain elements have to be kept in mind when constructing virtual environments. “When building virtual environments, you need to consider what can actually be built, how actors and cameras will move through the space, and what’s safe and practical on set,” Bell observes. “Outside the areas where strict accuracy is required, you want the environments to blend naturally with the original designs from the art department and support the story, creating a space that feels right for the scene, guides the audience’s eye and sets the right tone. Things like composition, lighting and small environmental details can be really fun to work on, but also serve as beautiful additions to help enrich a story.” “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance. But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.” —Laura Bell, Creative Technologist, Disguise Among the buildings that had to be created for Midport Village was Steve’sLava Chicken Shack. Concept art was provided that served as visual touchstones. “We received concept art provided by the amazing team of concept artists,” Finlayson states. “Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging. Sometimes we would also help the storyboard artists by sending through images of the Unreal Engine worlds to help them geographically position themselves in the worlds and aid in their storyboarding.” At times, the video game assets came in handy. “Exteriors often involved large-scale landscapes and stylized architectural elements, which had to feel true to the Minecraft world,” Finlayson explains. “In some cases, we brought in geometry from the game itself to help quickly block out areas. For example, we did this for the Elytra Flight Chase sequence, which takes place through a large canyon.” Flexibility was critical. “A key technical challenge we faced was ensuring that the Unreal levels were built in a way that allowed for fast and flexible iteration,” Finlayson remarks. “Since our environments were constantly being reviewed by the director, production designer, DP and VFX supervisor, we needed to be able to respond quickly to feedback, sometimes live during a review session. To support this, we had to keep our scenes modular and well-organized; that meant breaking environments down into manageable components and maintaining clean naming conventions. By setting up the levels this way, we could make layout changes, swap assets or adjust lighting on the fly without breaking the scene or slowing down the process.” Production schedules influence the workflows, pipelines and techniques. “No two projects will ever feel exactly the same,” Bell notes. “For example, Pat Younisadapted his typical VR setup to allow scene reviews using a PS5 controller, which made it much more comfortable and accessible for the director. On a more technical side, because everything was cubes and voxels, my Blender workflow ended up being way heavier on the re-mesh modifier than usual, definitely not something I’ll run into again anytime soon!” A virtual study and final still of the cast members standing outside of the Lava Chicken Shack. “We received concept art provided by the amazing team of concept artists. Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging.” —Talia Finlayson, Creative Technologist, Disguise The design and composition of virtual environments tended to remain consistent throughout principal photography. “The only major design change I can recall was the removal of a second story from a building in Midport Village to allow the camera crane to get a clear shot of the chicken perched above Steve’s lava chicken shack,” Finlayson remarks. “I would agree that Midport Village likely went through the most iterations,” Bell responds. “The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled. I remember rebuilding the stairs leading up to the rampart five or six times, using different configurations based on the physically constructed stairs. This was because there were storyboarded sequences of the film’s characters, Henry, Steve and Garrett, being chased by piglins, and the action needed to match what could be achieved practically on set.” Virtually conceptualizing the layout of Midport Village. Complex virtual environments were constructed for the final battle and the various forest scenes throughout the movie. “What made these particularly challenging was the way physical set pieces were repurposed and repositioned to serve multiple scenes and locations within the story,” Finlayson reveals. “The same built elements had to appear in different parts of the world, so we had to carefully adjust the virtual environments to accommodate those different positions.” Bell is in agreement with her colleague. “The forest scenes were some of the more complex environments to manage. It could get tricky, particularly when the filming schedule shifted. There was one day on set where the order of shots changed unexpectedly, and because the physical sets looked so similar, I initially loaded a different perspective than planned. Fortunately, thanks to our workflow, Lindsay Georgeand I were able to quickly open the recorded sequence in Unreal Engine and swap out the correct virtual environment for the live composite without any disruption to the shoot.” An example of the virtual and final version of the Woodland Mansion. “Midport Village likely went through the most iterations. The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled.” —Laura Bell, Creative Technologist, Disguise Extensive detail was given to the center of the sets where the main action unfolds. “For these areas, we received prop layouts from the prop department to ensure accurate placement and alignment with the physical builds,” Finlayson explains. “These central environments were used heavily for storyboarding, blocking and department reviews, so precision was essential. As we moved further out from the practical set, the environments became more about blocking and spatial context rather than fine detail. We worked closely with Production Designer Grant Major to get approval on these extended environments, making sure they aligned with the overall visual direction. We also used creatures and crowd stand-ins provided by the visual effects team. These gave a great sense of scale and placement during early planning stages and allowed other departments to better understand how these elements would be integrated into the scenes.” Cast members Sebastian Hansen, Danielle Brooks and Emma Myers stand in front of the Earth Portal Plateau environment. Doing a virtual scale study of the Mountainside. Practical requirements like camera moves, stunt choreography and crane setups had an impact on the creation of virtual environments. “Sometimes we would adjust layouts slightly to open up areas for tracking shots or rework spaces to accommodate key action beats, all while keeping the environment feeling cohesive and true to the Minecraft world,” Bell states. “Simulcam bridged the physical and virtual worlds on set, overlaying Unreal Engine environments onto live-action scenes in real-time, giving the director, DP and other department heads a fully-realized preview of shots and enabling precise, informed decisions during production. It also recorded critical production data like camera movement paths, which was handed over to the post-production team to give them the exact tracks they needed, streamlining the visual effects pipeline.” Piglots cause mayhem during the Wingsuit Chase. Virtual versions of the exterior and interior of the Safe House located in the Enchanted Woods. “One of the biggest challenges for me was managing constant iteration while keeping our environments clean, organized and easy to update,” Finlayson notes. “Because the virtual sets were reviewed regularly by the director and other heads of departments, feedback was often implemented live in the room. This meant the environments had to be flexible. But overall, this was an amazing project to work on, and I am so grateful for the incredible VAD team I was a part of – Heide Nichols, Pat Younis, Jake Tuckand Laura. Everyone on this team worked so collaboratively, seamlessly and in such a supportive way that I never felt like I was out of my depth.” There was another challenge that is more to do with familiarity. “Having a VAD on a film is still a relatively new process in production,” Bell states. “There were moments where other departments were still learning what we did and how to best work with us. That said, the response was overwhelmingly positive. I remember being on set at the Simulcam station and seeing how excited people were to look at the virtual environments as they walked by, often stopping for a chat and a virtual tour. Instead of seeing just a huge blue curtain, they were stoked to see something Minecraft and could get a better sense of what they were actually shooting.” #how #disguise #built #out #virtual
    WWW.VFXVOICE.COM
    HOW DISGUISE BUILT OUT THE VIRTUAL ENVIRONMENTS FOR A MINECRAFT MOVIE
    By TREVOR HOGG Images courtesy of Warner Bros. Pictures. Rather than a world constructed around photorealistic pixels, a video game created by Markus Persson has taken the boxier 3D voxel route, which has become its signature aesthetic, and sparked an international phenomenon that finally gets adapted into a feature with the release of A Minecraft Movie. Brought onboard to help filmmaker Jared Hess in creating the environments that the cast of Jason Momoa, Jack Black, Sebastian Hansen, Emma Myers and Danielle Brooks find themselves inhabiting was Disguise under the direction of Production VFX Supervisor Dan Lemmon. “[A]s the Senior Unreal Artist within the Virtual Art Department (VAD) on Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.” —Talia Finlayson, Creative Technologist, Disguise Interior and exterior environments had to be created, such as the shop owned by Steve (Jack Black). “Prior to working on A Minecraft Movie, I held more technical roles, like serving as the Virtual Production LED Volume Operator on a project for Apple TV+ and Paramount Pictures,” notes Talia Finlayson, Creative Technologist for Disguise. “But as the Senior Unreal Artist within the Virtual Art Department (VAD) on Minecraft, I experienced the full creative workflow. What stood out most was how deeply the VAD was embedded across every stage of production. We weren’t working in isolation. From the production designer and director to the VFX supervisor and DP, the VAD became a hub for collaboration.” The project provided new opportunities. “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance,” notes Laura Bell, Creative Technologist for Disguise. “But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.” Set designs originally created by the art department in Rhinoceros 3D were transformed into fully navigable 3D environments within Unreal Engine. “These scenes were far more than visualizations,” Finlayson remarks. “They were interactive tools used throughout the production pipeline. We would ingest 3D models and concept art, clean and optimize geometry using tools like Blender, Cinema 4D or Maya, then build out the world in Unreal Engine. This included applying materials, lighting and extending environments. These Unreal scenes we created were vital tools across the production and were used for a variety of purposes such as enabling the director to explore shot compositions, block scenes and experiment with camera movement in a virtual space, as well as passing along Unreal Engine scenes to the visual effects vendors so they could align their digital environments and set extensions with the approved production layouts.” A virtual exploration of Steve’s shop in Midport Village. Certain elements have to be kept in mind when constructing virtual environments. “When building virtual environments, you need to consider what can actually be built, how actors and cameras will move through the space, and what’s safe and practical on set,” Bell observes. “Outside the areas where strict accuracy is required, you want the environments to blend naturally with the original designs from the art department and support the story, creating a space that feels right for the scene, guides the audience’s eye and sets the right tone. Things like composition, lighting and small environmental details can be really fun to work on, but also serve as beautiful additions to help enrich a story.” “I’ve always loved the physicality of working with an LED volume, both for the immersion it provides and the way that seeing the environment helps shape an actor’s performance. But for A Minecraft Movie, we used Simulcam instead, and it was an incredible experience to live-composite an entire Minecraft world in real-time, especially with nothing on set but blue curtains.” —Laura Bell, Creative Technologist, Disguise Among the buildings that had to be created for Midport Village was Steve’s (Jack Black) Lava Chicken Shack. Concept art was provided that served as visual touchstones. “We received concept art provided by the amazing team of concept artists,” Finlayson states. “Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging. Sometimes we would also help the storyboard artists by sending through images of the Unreal Engine worlds to help them geographically position themselves in the worlds and aid in their storyboarding.” At times, the video game assets came in handy. “Exteriors often involved large-scale landscapes and stylized architectural elements, which had to feel true to the Minecraft world,” Finlayson explains. “In some cases, we brought in geometry from the game itself to help quickly block out areas. For example, we did this for the Elytra Flight Chase sequence, which takes place through a large canyon.” Flexibility was critical. “A key technical challenge we faced was ensuring that the Unreal levels were built in a way that allowed for fast and flexible iteration,” Finlayson remarks. “Since our environments were constantly being reviewed by the director, production designer, DP and VFX supervisor, we needed to be able to respond quickly to feedback, sometimes live during a review session. To support this, we had to keep our scenes modular and well-organized; that meant breaking environments down into manageable components and maintaining clean naming conventions. By setting up the levels this way, we could make layout changes, swap assets or adjust lighting on the fly without breaking the scene or slowing down the process.” Production schedules influence the workflows, pipelines and techniques. “No two projects will ever feel exactly the same,” Bell notes. “For example, Pat Younis [VAD Art Director] adapted his typical VR setup to allow scene reviews using a PS5 controller, which made it much more comfortable and accessible for the director. On a more technical side, because everything was cubes and voxels, my Blender workflow ended up being way heavier on the re-mesh modifier than usual, definitely not something I’ll run into again anytime soon!” A virtual study and final still of the cast members standing outside of the Lava Chicken Shack. “We received concept art provided by the amazing team of concept artists. Not only did they send us 2D artwork, but they often shared the 3D models they used to create those visuals. These models were incredibly helpful as starting points when building out the virtual environments in Unreal Engine; they gave us a clear sense of composition and design intent. Storyboards were also a key part of the process and were constantly being updated as the project evolved. Having access to the latest versions allowed us to tailor the virtual environments to match camera angles, story beats and staging.” —Talia Finlayson, Creative Technologist, Disguise The design and composition of virtual environments tended to remain consistent throughout principal photography. “The only major design change I can recall was the removal of a second story from a building in Midport Village to allow the camera crane to get a clear shot of the chicken perched above Steve’s lava chicken shack,” Finlayson remarks. “I would agree that Midport Village likely went through the most iterations,” Bell responds. “The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled. I remember rebuilding the stairs leading up to the rampart five or six times, using different configurations based on the physically constructed stairs. This was because there were storyboarded sequences of the film’s characters, Henry, Steve and Garrett, being chased by piglins, and the action needed to match what could be achieved practically on set.” Virtually conceptualizing the layout of Midport Village. Complex virtual environments were constructed for the final battle and the various forest scenes throughout the movie. “What made these particularly challenging was the way physical set pieces were repurposed and repositioned to serve multiple scenes and locations within the story,” Finlayson reveals. “The same built elements had to appear in different parts of the world, so we had to carefully adjust the virtual environments to accommodate those different positions.” Bell is in agreement with her colleague. “The forest scenes were some of the more complex environments to manage. It could get tricky, particularly when the filming schedule shifted. There was one day on set where the order of shots changed unexpectedly, and because the physical sets looked so similar, I initially loaded a different perspective than planned. Fortunately, thanks to our workflow, Lindsay George [VP Tech] and I were able to quickly open the recorded sequence in Unreal Engine and swap out the correct virtual environment for the live composite without any disruption to the shoot.” An example of the virtual and final version of the Woodland Mansion. “Midport Village likely went through the most iterations. The archway, in particular, became a visual anchor across different levels. We often placed it off in the distance to help orient both ourselves and the audience and show how far the characters had traveled.” —Laura Bell, Creative Technologist, Disguise Extensive detail was given to the center of the sets where the main action unfolds. “For these areas, we received prop layouts from the prop department to ensure accurate placement and alignment with the physical builds,” Finlayson explains. “These central environments were used heavily for storyboarding, blocking and department reviews, so precision was essential. As we moved further out from the practical set, the environments became more about blocking and spatial context rather than fine detail. We worked closely with Production Designer Grant Major to get approval on these extended environments, making sure they aligned with the overall visual direction. We also used creatures and crowd stand-ins provided by the visual effects team. These gave a great sense of scale and placement during early planning stages and allowed other departments to better understand how these elements would be integrated into the scenes.” Cast members Sebastian Hansen, Danielle Brooks and Emma Myers stand in front of the Earth Portal Plateau environment. Doing a virtual scale study of the Mountainside. Practical requirements like camera moves, stunt choreography and crane setups had an impact on the creation of virtual environments. “Sometimes we would adjust layouts slightly to open up areas for tracking shots or rework spaces to accommodate key action beats, all while keeping the environment feeling cohesive and true to the Minecraft world,” Bell states. “Simulcam bridged the physical and virtual worlds on set, overlaying Unreal Engine environments onto live-action scenes in real-time, giving the director, DP and other department heads a fully-realized preview of shots and enabling precise, informed decisions during production. It also recorded critical production data like camera movement paths, which was handed over to the post-production team to give them the exact tracks they needed, streamlining the visual effects pipeline.” Piglots cause mayhem during the Wingsuit Chase. Virtual versions of the exterior and interior of the Safe House located in the Enchanted Woods. “One of the biggest challenges for me was managing constant iteration while keeping our environments clean, organized and easy to update,” Finlayson notes. “Because the virtual sets were reviewed regularly by the director and other heads of departments, feedback was often implemented live in the room. This meant the environments had to be flexible. But overall, this was an amazing project to work on, and I am so grateful for the incredible VAD team I was a part of – Heide Nichols [VAD Supervisor], Pat Younis, Jake Tuck [Unreal Artist] and Laura. Everyone on this team worked so collaboratively, seamlessly and in such a supportive way that I never felt like I was out of my depth.” There was another challenge that is more to do with familiarity. “Having a VAD on a film is still a relatively new process in production,” Bell states. “There were moments where other departments were still learning what we did and how to best work with us. That said, the response was overwhelmingly positive. I remember being on set at the Simulcam station and seeing how excited people were to look at the virtual environments as they walked by, often stopping for a chat and a virtual tour. Instead of seeing just a huge blue curtain, they were stoked to see something Minecraft and could get a better sense of what they were actually shooting.”
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  • Alexander Michael Compartió un vínculo
    2025-06-17 18:31:04 - Translate -
    Hey there, fabulous friends!

    Are you ready to take your market research game to the next level? Today, I want to share with you something that can truly transform how you see competition! In this fast-paced world, every entrepreneur and marketer needs to be equipped with the right tools to uncover hidden gems in the market. And guess what? The answer lies in the **14 Best Competitive Intelligence Tools for Market Research**!

    Imagine having the power to peek behind the curtain of your competitors and discover their strategies and tactics! With these amazing tools, you can gather insights that will not only help you understand your market better but also give you the edge you need to soar higher than ever before!

    One standout tool that I absolutely adore is the **Semrush Traffic & Market Toolkit**. It’s like having a secret weapon in your back pocket! This toolkit provides invaluable data about traffic sources, keyword strategies, and much more! Say goodbye to guesswork and hello to informed decisions! Each piece of information you gather brings you one step closer to your goals.

    But that’s not all! Each of the 14 tools has its own unique features that cater to different aspects of competitive intelligence. Whether it's analyzing social media performance, tracking keywords, or monitoring brand mentions, there’s something for everyone! It’s time to embrace the power of knowledge and turn it into your competitive advantage!

    I know that diving into market research might seem daunting, but let me tell you, it’s a thrilling adventure! Every insight you uncover is like finding a treasure map leading you to success! So, don’t shy away from exploring these tools. Embrace them with open arms and watch your business flourish!

    Remember, the only limit to your success is the extent of your imagination and the determination to use the right resources. So gear up, equip yourself with these 14 best competitive intelligence tools, and let’s conquer the market together!

    Let’s lift each other up and share our discoveries! What tools are you excited to try? Drop your thoughts in the comments below! Let’s inspire one another to reach new heights!

    #MarketResearch #CompetitiveIntelligence #BusinessGrowth #Semrush #Inspiration
    🌟 Hey there, fabulous friends! 🌟 Are you ready to take your market research game to the next level? 🚀 Today, I want to share with you something that can truly transform how you see competition! In this fast-paced world, every entrepreneur and marketer needs to be equipped with the right tools to uncover hidden gems in the market. And guess what? The answer lies in the **14 Best Competitive Intelligence Tools for Market Research**! 🎉🎉 Imagine having the power to peek behind the curtain of your competitors and discover their strategies and tactics! With these amazing tools, you can gather insights that will not only help you understand your market better but also give you the edge you need to soar higher than ever before! 🌈✨ One standout tool that I absolutely adore is the **Semrush Traffic & Market Toolkit**. It’s like having a secret weapon in your back pocket! 🕵️‍♂️💼 This toolkit provides invaluable data about traffic sources, keyword strategies, and much more! Say goodbye to guesswork and hello to informed decisions! Each piece of information you gather brings you one step closer to your goals. 🌟 But that’s not all! Each of the 14 tools has its own unique features that cater to different aspects of competitive intelligence. Whether it's analyzing social media performance, tracking keywords, or monitoring brand mentions, there’s something for everyone! It’s time to embrace the power of knowledge and turn it into your competitive advantage! 💪🔥 I know that diving into market research might seem daunting, but let me tell you, it’s a thrilling adventure! Every insight you uncover is like finding a treasure map leading you to success! 🗺️💖 So, don’t shy away from exploring these tools. Embrace them with open arms and watch your business flourish! 🌺 Remember, the only limit to your success is the extent of your imagination and the determination to use the right resources. So gear up, equip yourself with these 14 best competitive intelligence tools, and let’s conquer the market together! 🌍💫 Let’s lift each other up and share our discoveries! What tools are you excited to try? Drop your thoughts in the comments below! 👇💬 Let’s inspire one another to reach new heights! #MarketResearch #CompetitiveIntelligence #BusinessGrowth #Semrush #Inspiration
    The 14 Best Competitive Intelligence Tools for Market Research
    Discover the competition and reveal strategies and tactics of any industry player with these top 14 competitive intelligence tools, including the Semrush Traffic & Market Toolkit.
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  • Ava Aria Compartió un vínculo
    2025-06-16 17:32:00 - Translate -
    Why is it so hard for people to grasp the absolute necessity of setting up 301 redirects in an .htaccess file? Honestly, it’s infuriating! We’re in a digital age where every click counts, and yet, so many website owners continue to neglect this vital aspect of web management. Why? Because they’re either too lazy to learn or they just don’t care about preserving their ranking authority!

    Let’s get one thing straight: if you think you can just change URLs and your content magically stays relevant, you’re living in a fantasy world! When you fail to implement 301 redirects properly, you’re not just risking your SEO; you’re throwing away all the hard work you’ve put into building your online presence. It’s like setting fire to a pile of money because you couldn’t be bothered to use a fire extinguisher. Ridiculous!

    The process of adding 301 redirects in .htaccess files is straightforward. It’s not rocket science, people! You have two methods at your disposal, and yet countless websites are still losing traffic and authority daily because their owners can’t figure it out. You would think that in a realm where every detail matters, folks would prioritize understanding how to maintain their site’s integrity. But no! Instead, they leave their sites vulnerable, confused visitors, and plunging search rankings in their wake.

    If you’re still scratching your head over how to set up 301 redirects in an .htaccess file, wake up! The first method is simply to use the `RedirectPermanent` directive. It’s right there for you, and it’s as easy as pie. You just need to specify the old URL and the new URL, and boom! You’re done. Or, if you’re feeling fancy, the second method involves using the `RewriteRule` directive. Again, it’s not complicated! Just a few lines of code, and you’re on your way to preserving that precious ranking authority.

    What’s more infuriating is when people rush into updating their websites without even considering the fallout of their actions. Do you think Google is going to give you a free pass for being reckless? No! It will punish you for not taking the necessary precautions. Imagine losing all that traffic you worked so hard to get, just because you couldn’t be bothered to set up a simple redirect. Pathetic!

    Let’s not even begin to talk about the customer experience. When users click on a link and end up on a 404 error page because you didn’t implement a 301 redirect, that’s a surefire way to lose their trust and business. Do you really want to be known as the website that provides a dead-end for visitors? Absolutely not! So, for the love of all that is holy in the digital world, get your act together and learn how to set up those redirects!

    In conclusion, if you’re still ignoring the importance of 301 redirects in your .htaccess file, you’re not just being negligent; you’re actively sabotaging your own success. Stop making excuses, roll up your sleeves, and do what needs to be done. Your website deserves better!

    #301Redirects #SEO #WebManagement #DigitalMarketing #htaccess
    Why is it so hard for people to grasp the absolute necessity of setting up 301 redirects in an .htaccess file? Honestly, it’s infuriating! We’re in a digital age where every click counts, and yet, so many website owners continue to neglect this vital aspect of web management. Why? Because they’re either too lazy to learn or they just don’t care about preserving their ranking authority! Let’s get one thing straight: if you think you can just change URLs and your content magically stays relevant, you’re living in a fantasy world! When you fail to implement 301 redirects properly, you’re not just risking your SEO; you’re throwing away all the hard work you’ve put into building your online presence. It’s like setting fire to a pile of money because you couldn’t be bothered to use a fire extinguisher. Ridiculous! The process of adding 301 redirects in .htaccess files is straightforward. It’s not rocket science, people! You have two methods at your disposal, and yet countless websites are still losing traffic and authority daily because their owners can’t figure it out. You would think that in a realm where every detail matters, folks would prioritize understanding how to maintain their site’s integrity. But no! Instead, they leave their sites vulnerable, confused visitors, and plunging search rankings in their wake. If you’re still scratching your head over how to set up 301 redirects in an .htaccess file, wake up! The first method is simply to use the `RedirectPermanent` directive. It’s right there for you, and it’s as easy as pie. You just need to specify the old URL and the new URL, and boom! You’re done. Or, if you’re feeling fancy, the second method involves using the `RewriteRule` directive. Again, it’s not complicated! Just a few lines of code, and you’re on your way to preserving that precious ranking authority. What’s more infuriating is when people rush into updating their websites without even considering the fallout of their actions. Do you think Google is going to give you a free pass for being reckless? No! It will punish you for not taking the necessary precautions. Imagine losing all that traffic you worked so hard to get, just because you couldn’t be bothered to set up a simple redirect. Pathetic! Let’s not even begin to talk about the customer experience. When users click on a link and end up on a 404 error page because you didn’t implement a 301 redirect, that’s a surefire way to lose their trust and business. Do you really want to be known as the website that provides a dead-end for visitors? Absolutely not! So, for the love of all that is holy in the digital world, get your act together and learn how to set up those redirects! In conclusion, if you’re still ignoring the importance of 301 redirects in your .htaccess file, you’re not just being negligent; you’re actively sabotaging your own success. Stop making excuses, roll up your sleeves, and do what needs to be done. Your website deserves better! #301Redirects #SEO #WebManagement #DigitalMarketing #htaccess
    How to Set Up 301 Redirects in an .htaccess File
    Adding 301 redirects in .htaccess files is useful to preserve ranking authority. Here are two methods.
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  • NeowinFeed Compartió un vínculo
    2025-06-16 08:39:28 - Translate -
    Microsoft 365 security in the spotlight after Washington Post hack

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    Microsoft 365 security in the spotlight after Washington Post hack

    Paul Hill

    Neowin
    @ziks_99 ·

    Jun 16, 2025 03:36 EDT

    The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access.
    The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers.
    Microsoft's enterprise security offerings and challenges

    As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe.
    One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post.
    Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used.
    While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security.
    Lessons for organizations using Microsoft 365
    The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authenticationfor all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner.
    Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time.

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    #microsoft #security #spotlight #after #washington
    Microsoft 365 security in the spotlight after Washington Post hack
    When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Microsoft 365 security in the spotlight after Washington Post hack Paul Hill Neowin @ziks_99 · Jun 16, 2025 03:36 EDT The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access. The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers. Microsoft's enterprise security offerings and challenges As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe. One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post. Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used. While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security. Lessons for organizations using Microsoft 365 The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authenticationfor all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner. Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time. Tags Report a problem with article Follow @NeowinFeed #microsoft #security #spotlight #after #washington
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    Microsoft 365 security in the spotlight after Washington Post hack
    When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Microsoft 365 security in the spotlight after Washington Post hack Paul Hill Neowin @ziks_99 · Jun 16, 2025 03:36 EDT The Washington Post has come under cyberattack which saw Microsoft email accounts of several journalists get compromised. The attack, which was discovered last Thursday, is believed to have been conducted by a foreign government due to the topics the journalists cover, including national security, economic policy, and China. Following the hack, the passwords on the affected accounts were reset to prevent access. The fact that a Microsoft work email account was potentially hacked strongly suggests The Washington Post utilizes Microsoft 365, which makes us question the security of Microsoft’s widely used enterprise services. Given that Microsoft 365 is very popular, it is a hot target for attackers. Microsoft's enterprise security offerings and challenges As the investigation into the cyberattack is still ongoing, just how attackers gained access to the accounts of the journalists is unknown, however, Microsoft 365 does have multiple layers of protection that ought to keep journalists safe. One of the security tools is Microsoft Defender for Office 365. If the hackers tried to gain access with malicious links, Defender provides protection against any malicious attachments, links, or email-based phishing attempts with the Advanced Threat Protection feature. Defender also helps to protect against malware that could be used to target journalists at The Washington Post. Another security measure in place is Entra ID which helps enterprises defend against identity-based attacks. Some key features of Entra ID include multi-factor authentication which protects accounts even if a password is compromised, and there are granular access policies that help to limit logins from outside certain locations, unknown devices, or limit which apps can be used. While Microsoft does offer plenty of security technologies with M365, hacks can still take place due to misconfiguration, user-error, or through the exploitation of zero-day vulnerabilities. Essentially, it requires efforts from both Microsoft and the customer to maintain security. Lessons for organizations using Microsoft 365 The incident over at The Washington Post serves as a stark reminder that all organizations, not just news organizations, should audit and strengthen their security setups. Some of the most important security measures you can put in place include mandatory multi-factor authentication (MFA) for all users, especially for privileged accounts; strong password rules such as using letters, numbers, and symbols; regular security awareness training; and installing any security updates in a timely manner. Many of the cyberattacks that we learn about from companies like Microsoft involve hackers taking advantage of the human in the equation, such as being tricked into sharing passwords or sharing sensitive information due to trickery on behalf of the hackers. This highlights that employee training is crucial in protecting systems and that Microsoft’s technologies, as advanced as they are, can’t mitigate all attacks 100 percent of the time. Tags Report a problem with article Follow @NeowinFeed
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  • Mashable Compartió un vínculo
    2025-06-16 08:37:05 - Translate -
    NYT Connections Sports Edition today: Hints and answers for June 16, 2025

    Credit: Image Credit: Ian Moore / James Martin / Viva Tung / Mashable Composite

    Connections: Sports Edition is a new version of the popular New York Times word game that seeks to test the knowledge of sports fans. Like the original Connections, the game is all about finding the "common threads between words." And just like Wordle, Connections resets after midnight and each new set of words gets trickier and trickier—so we've served up some hints and tips to get you over the hurdle.If you just want to be told today's puzzle, you can jump to the end of this article for the latest Connections solution. But if you'd rather solve it yourself, keep reading for some clues, tips, and strategies to assist you.What is Connections Sports Edition?The NYT's latest daily word game has launched in association with The Athletic, the New York Times property that provides the publication's sports coverage. Connections can be played on both web browsers and mobile devices and require players to group four words that share something in common.Each puzzle features 16 words and each grouping of words is split into four categories. These sets could comprise of anything from book titles, software, country names, etc. Even though multiple words will seem like they fit together, there's only one correct answer.If a player gets all four words in a set correct, those words are removed from the board. Guess wrong and it counts as a mistake—players get up to four mistakes until the game ends.Players can also rearrange and shuffle the board to make spotting connections easier. Additionally, each group is color-coded with yellow being the easiest, followed by green, blue, and purple. Like Wordle, you can share the results with your friends on social media.

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    Here's a hint for today's Connections Sports Edition categoriesWant a hint about the categories without being told the categories? Then give these a try:Yellow: ScorelessGreen: Midwest college townsBlue: GolfPurple: Major names behind the plate

    Featured Video For You

    Connections: How to play and how to win

    Here are today's Connections Sports Edition categoriesNeed a little extra help? Today's connections fall into the following categories:Yellow: Slang for ZeroGreen: Big Ten CitiesBlue: Sites of This Year's Men's Golf MajorsPurple: MLB CatchersLooking for Wordle today? Here's the answer to today's Wordle.Ready for the answers? This is your last chance to turn back and solve today's puzzle before we reveal the solutions.Drumroll, please!The solution to today's Connections Sports Edition #266 is...What is the answer to Connections Sports Edition todaySlang for Zero - BAGEL, DONUT, GOOSE EGG, NILBig Ten Cities - COLLEGE PARK, COLUMBUS, EAST LANSING, MADISONSites of This Year's Men's Golf Majors - AUGUSTA, OAKMONT, QUAIL HOLLOW, ROYAL PORTRUSHMLB Catchers - PEREZ, RALEIGH, REALMUTO, RUTSCHMANDon't feel down if you didn't manage to guess it this time. There will be new Connections for you to stretch your brain with tomorrow, and we'll be back again to guide you with more helpful hints.Are you also playing NYT Strands? See hints and answers for today's Strands.If you're looking for more puzzles, Mashable's got games now! Check out our games hub for Mahjong, Sudoku, free crossword, and more.Not the day you're after? Here's the solution to yesterday's Connections.

    Topics
    Connections
    #nyt #connections #sports #edition #today
    NYT Connections Sports Edition today: Hints and answers for June 16, 2025
    Credit: Image Credit: Ian Moore / James Martin / Viva Tung / Mashable Composite Connections: Sports Edition is a new version of the popular New York Times word game that seeks to test the knowledge of sports fans. Like the original Connections, the game is all about finding the "common threads between words." And just like Wordle, Connections resets after midnight and each new set of words gets trickier and trickier—so we've served up some hints and tips to get you over the hurdle.If you just want to be told today's puzzle, you can jump to the end of this article for the latest Connections solution. But if you'd rather solve it yourself, keep reading for some clues, tips, and strategies to assist you.What is Connections Sports Edition?The NYT's latest daily word game has launched in association with The Athletic, the New York Times property that provides the publication's sports coverage. Connections can be played on both web browsers and mobile devices and require players to group four words that share something in common.Each puzzle features 16 words and each grouping of words is split into four categories. These sets could comprise of anything from book titles, software, country names, etc. Even though multiple words will seem like they fit together, there's only one correct answer.If a player gets all four words in a set correct, those words are removed from the board. Guess wrong and it counts as a mistake—players get up to four mistakes until the game ends.Players can also rearrange and shuffle the board to make spotting connections easier. Additionally, each group is color-coded with yellow being the easiest, followed by green, blue, and purple. Like Wordle, you can share the results with your friends on social media. Mashable Top Stories Stay connected with the hottest stories of the day and the latest entertainment news. Sign up for Mashable's Top Stories newsletter By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy. Thanks for signing up! Here's a hint for today's Connections Sports Edition categoriesWant a hint about the categories without being told the categories? Then give these a try:Yellow: ScorelessGreen: Midwest college townsBlue: GolfPurple: Major names behind the plate Featured Video For You Connections: How to play and how to win Here are today's Connections Sports Edition categoriesNeed a little extra help? Today's connections fall into the following categories:Yellow: Slang for ZeroGreen: Big Ten CitiesBlue: Sites of This Year's Men's Golf MajorsPurple: MLB CatchersLooking for Wordle today? Here's the answer to today's Wordle.Ready for the answers? This is your last chance to turn back and solve today's puzzle before we reveal the solutions.Drumroll, please!The solution to today's Connections Sports Edition #266 is...What is the answer to Connections Sports Edition todaySlang for Zero - BAGEL, DONUT, GOOSE EGG, NILBig Ten Cities - COLLEGE PARK, COLUMBUS, EAST LANSING, MADISONSites of This Year's Men's Golf Majors - AUGUSTA, OAKMONT, QUAIL HOLLOW, ROYAL PORTRUSHMLB Catchers - PEREZ, RALEIGH, REALMUTO, RUTSCHMANDon't feel down if you didn't manage to guess it this time. There will be new Connections for you to stretch your brain with tomorrow, and we'll be back again to guide you with more helpful hints.Are you also playing NYT Strands? See hints and answers for today's Strands.If you're looking for more puzzles, Mashable's got games now! Check out our games hub for Mahjong, Sudoku, free crossword, and more.Not the day you're after? Here's the solution to yesterday's Connections. Topics Connections #nyt #connections #sports #edition #today
    MASHABLE.COM
    NYT Connections Sports Edition today: Hints and answers for June 16, 2025
    Credit: Image Credit: Ian Moore / James Martin / Viva Tung / Mashable Composite Connections: Sports Edition is a new version of the popular New York Times word game that seeks to test the knowledge of sports fans. Like the original Connections, the game is all about finding the "common threads between words." And just like Wordle, Connections resets after midnight and each new set of words gets trickier and trickier—so we've served up some hints and tips to get you over the hurdle.If you just want to be told today's puzzle, you can jump to the end of this article for the latest Connections solution. But if you'd rather solve it yourself, keep reading for some clues, tips, and strategies to assist you.What is Connections Sports Edition?The NYT's latest daily word game has launched in association with The Athletic, the New York Times property that provides the publication's sports coverage. Connections can be played on both web browsers and mobile devices and require players to group four words that share something in common.Each puzzle features 16 words and each grouping of words is split into four categories. These sets could comprise of anything from book titles, software, country names, etc. Even though multiple words will seem like they fit together, there's only one correct answer.If a player gets all four words in a set correct, those words are removed from the board. Guess wrong and it counts as a mistake—players get up to four mistakes until the game ends.Players can also rearrange and shuffle the board to make spotting connections easier. Additionally, each group is color-coded with yellow being the easiest, followed by green, blue, and purple. Like Wordle, you can share the results with your friends on social media. Mashable Top Stories Stay connected with the hottest stories of the day and the latest entertainment news. Sign up for Mashable's Top Stories newsletter By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy. Thanks for signing up! Here's a hint for today's Connections Sports Edition categoriesWant a hint about the categories without being told the categories? Then give these a try:Yellow: ScorelessGreen: Midwest college townsBlue: GolfPurple: Major names behind the plate Featured Video For You Connections: How to play and how to win Here are today's Connections Sports Edition categoriesNeed a little extra help? Today's connections fall into the following categories:Yellow: Slang for ZeroGreen: Big Ten CitiesBlue: Sites of This Year's Men's Golf MajorsPurple: MLB CatchersLooking for Wordle today? Here's the answer to today's Wordle.Ready for the answers? This is your last chance to turn back and solve today's puzzle before we reveal the solutions.Drumroll, please!The solution to today's Connections Sports Edition #266 is...What is the answer to Connections Sports Edition todaySlang for Zero - BAGEL, DONUT, GOOSE EGG, NILBig Ten Cities - COLLEGE PARK, COLUMBUS, EAST LANSING, MADISONSites of This Year's Men's Golf Majors - AUGUSTA, OAKMONT, QUAIL HOLLOW, ROYAL PORTRUSHMLB Catchers - PEREZ, RALEIGH, REALMUTO, RUTSCHMANDon't feel down if you didn't manage to guess it this time. There will be new Connections for you to stretch your brain with tomorrow, and we'll be back again to guide you with more helpful hints.Are you also playing NYT Strands? See hints and answers for today's Strands.If you're looking for more puzzles, Mashable's got games now! Check out our games hub for Mahjong, Sudoku, free crossword, and more.Not the day you're after? Here's the solution to yesterday's Connections. Topics Connections
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