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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

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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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2025-06-27 18:47:18 - Translate -

European Broadcasting Union and NVIDIA Partner on Sovereign AI to Support Public Broadcasters

In a new effort to advance sovereign AI for European public service media, NVIDIA and the European Broadcasting Unionare working together to give the media industry access to high-quality and trusted cloud and AI technologies.
Announced at NVIDIA GTC Paris at VivaTech, NVIDIA’s collaboration with the EBU — the world’s leading alliance of public service media with more than 110 member organizations in 50+ countries, reaching an audience of over 1 billion — focuses on helping build sovereign AI and cloud frameworks, driving workforce development and cultivating an AI ecosystem to create a more equitable, accessible and resilient European media landscape.
The work will create better foundations for public service media to benefit from European cloud infrastructure and AI services that are exclusively governed by European policy, comply with European data protection and privacy rules, and embody European values.
Sovereign AI ensures nations can develop and deploy artificial intelligence using local infrastructure, datasets and expertise. By investing in it, European countries can preserve their cultural identity, enhance public trust and support innovation specific to their needs.
“We are proud to collaborate with NVIDIA to drive the development of sovereign AI and cloud services,” said Michael Eberhard, chief technology officer of public broadcaster ARD/SWR, and chair of the EBU Technical Committee. “By advancing these capabilities together, we’re helping ensure that powerful, compliant and accessible media services are made available to all EBU members — powering innovation, resilience and strategic autonomy across the board.”

Empowering Media Innovation in Europe
To support the development of sovereign AI technologies, NVIDIA and the EBU will establish frameworks that prioritize independence and public trust, helping ensure that AI serves the interests of Europeans while preserving the autonomy of media organizations.
Through this collaboration, NVIDIA and the EBU will develop hybrid cloud architectures designed to meet the highest standards of European public service media. The EBU will contribute its Dynamic Media Facilityand Media eXchange Layerarchitecture, aiming to enable interoperability and scalability for workflows, as well as cost- and energy-efficient AI training and inference. Following open-source principles, this work aims to create an accessible, dynamic technology ecosystem.
The collaboration will also provide public service media companies with the tools to deliver personalized, contextually relevant services and content recommendation systems, with a focus on transparency, accountability and cultural identity. This will be realized through investment in sovereign cloud and AI infrastructure and software platforms such as NVIDIA AI Enterprise, custom foundation models, large language models trained with local data, and retrieval-augmented generation technologies.
As part of the collaboration, NVIDIA is also making available resources from its Deep Learning Institute, offering European media organizations comprehensive training programs to create an AI-ready workforce. This will support the EBU’s efforts to help ensure news integrity in the age of AI.
In addition, the EBU and its partners are investing in local data centers and cloud platforms that support sovereign technologies, such as NVIDIA GB200 Grace Blackwell Superchip, NVIDIA RTX PRO Servers, NVIDIA DGX Cloud and NVIDIA Holoscan for Media — helping members of the union achieve secure and cost- and energy-efficient AI training, while promoting AI research and development.
Partnering With Public Service Media for Sovereign Cloud and AI
Collaboration within the media sector is essential for the development and application of comprehensive standards and best practices that ensure the creation and deployment of sovereign European cloud and AI.
By engaging with independent software vendors, data center providers, cloud service providers and original equipment manufacturers, NVIDIA and the EBU aim to create a unified approach to sovereign cloud and AI.
This work will also facilitate discussions between the cloud and AI industry and European regulators, helping ensure the development of practical solutions that benefit both the general public and media organizations.
“Building sovereign cloud and AI capabilities based on EBU’s Dynamic Media Facility and Media eXchange Layer architecture requires strong cross-industry collaboration,” said Antonio Arcidiacono, chief technology and innovation officer at the EBU. “By collaborating with NVIDIA, as well as a broad ecosystem of media technology partners, we are fostering a shared foundation for trust, innovation and resilience that supports the growth of European media.”
Learn more about the EBU.
Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.
#european #broadcasting #union #nvidia #partner

European Broadcasting Union and NVIDIA Partner on Sovereign AI to Support Public Broadcasters
In a new effort to advance sovereign AI for European public service media, NVIDIA and the European Broadcasting Unionare working together to give the media industry access to high-quality and trusted cloud and AI technologies. Announced at NVIDIA GTC Paris at VivaTech, NVIDIA’s collaboration with the EBU — the world’s leading alliance of public service media with more than 110 member organizations in 50+ countries, reaching an audience of over 1 billion — focuses on helping build sovereign AI and cloud frameworks, driving workforce development and cultivating an AI ecosystem to create a more equitable, accessible and resilient European media landscape. The work will create better foundations for public service media to benefit from European cloud infrastructure and AI services that are exclusively governed by European policy, comply with European data protection and privacy rules, and embody European values. Sovereign AI ensures nations can develop and deploy artificial intelligence using local infrastructure, datasets and expertise. By investing in it, European countries can preserve their cultural identity, enhance public trust and support innovation specific to their needs. “We are proud to collaborate with NVIDIA to drive the development of sovereign AI and cloud services,” said Michael Eberhard, chief technology officer of public broadcaster ARD/SWR, and chair of the EBU Technical Committee. “By advancing these capabilities together, we’re helping ensure that powerful, compliant and accessible media services are made available to all EBU members — powering innovation, resilience and strategic autonomy across the board.” Empowering Media Innovation in Europe To support the development of sovereign AI technologies, NVIDIA and the EBU will establish frameworks that prioritize independence and public trust, helping ensure that AI serves the interests of Europeans while preserving the autonomy of media organizations. Through this collaboration, NVIDIA and the EBU will develop hybrid cloud architectures designed to meet the highest standards of European public service media. The EBU will contribute its Dynamic Media Facilityand Media eXchange Layerarchitecture, aiming to enable interoperability and scalability for workflows, as well as cost- and energy-efficient AI training and inference. Following open-source principles, this work aims to create an accessible, dynamic technology ecosystem. The collaboration will also provide public service media companies with the tools to deliver personalized, contextually relevant services and content recommendation systems, with a focus on transparency, accountability and cultural identity. This will be realized through investment in sovereign cloud and AI infrastructure and software platforms such as NVIDIA AI Enterprise, custom foundation models, large language models trained with local data, and retrieval-augmented generation technologies. As part of the collaboration, NVIDIA is also making available resources from its Deep Learning Institute, offering European media organizations comprehensive training programs to create an AI-ready workforce. This will support the EBU’s efforts to help ensure news integrity in the age of AI. In addition, the EBU and its partners are investing in local data centers and cloud platforms that support sovereign technologies, such as NVIDIA GB200 Grace Blackwell Superchip, NVIDIA RTX PRO Servers, NVIDIA DGX Cloud and NVIDIA Holoscan for Media — helping members of the union achieve secure and cost- and energy-efficient AI training, while promoting AI research and development. Partnering With Public Service Media for Sovereign Cloud and AI Collaboration within the media sector is essential for the development and application of comprehensive standards and best practices that ensure the creation and deployment of sovereign European cloud and AI. By engaging with independent software vendors, data center providers, cloud service providers and original equipment manufacturers, NVIDIA and the EBU aim to create a unified approach to sovereign cloud and AI. This work will also facilitate discussions between the cloud and AI industry and European regulators, helping ensure the development of practical solutions that benefit both the general public and media organizations. “Building sovereign cloud and AI capabilities based on EBU’s Dynamic Media Facility and Media eXchange Layer architecture requires strong cross-industry collaboration,” said Antonio Arcidiacono, chief technology and innovation officer at the EBU. “By collaborating with NVIDIA, as well as a broad ecosystem of media technology partners, we are fostering a shared foundation for trust, innovation and resilience that supports the growth of European media.” Learn more about the EBU. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. #european #broadcasting #union #nvidia #partner

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European Broadcasting Union and NVIDIA Partner on Sovereign AI to Support Public Broadcasters
In a new effort to advance sovereign AI for European public service media, NVIDIA and the European Broadcasting Union (EBU) are working together to give the media industry access to high-quality and trusted cloud and AI technologies. Announced at NVIDIA GTC Paris at VivaTech, NVIDIA’s collaboration with the EBU — the world’s leading alliance of public service media with more than 110 member organizations in 50+ countries, reaching an audience of over 1 billion — focuses on helping build sovereign AI and cloud frameworks, driving workforce development and cultivating an AI ecosystem to create a more equitable, accessible and resilient European media landscape. The work will create better foundations for public service media to benefit from European cloud infrastructure and AI services that are exclusively governed by European policy, comply with European data protection and privacy rules, and embody European values. Sovereign AI ensures nations can develop and deploy artificial intelligence using local infrastructure, datasets and expertise. By investing in it, European countries can preserve their cultural identity, enhance public trust and support innovation specific to their needs. “We are proud to collaborate with NVIDIA to drive the development of sovereign AI and cloud services,” said Michael Eberhard, chief technology officer of public broadcaster ARD/SWR, and chair of the EBU Technical Committee. “By advancing these capabilities together, we’re helping ensure that powerful, compliant and accessible media services are made available to all EBU members — powering innovation, resilience and strategic autonomy across the board.” Empowering Media Innovation in Europe To support the development of sovereign AI technologies, NVIDIA and the EBU will establish frameworks that prioritize independence and public trust, helping ensure that AI serves the interests of Europeans while preserving the autonomy of media organizations. Through this collaboration, NVIDIA and the EBU will develop hybrid cloud architectures designed to meet the highest standards of European public service media. The EBU will contribute its Dynamic Media Facility (DMF) and Media eXchange Layer (MXL) architecture, aiming to enable interoperability and scalability for workflows, as well as cost- and energy-efficient AI training and inference. Following open-source principles, this work aims to create an accessible, dynamic technology ecosystem. The collaboration will also provide public service media companies with the tools to deliver personalized, contextually relevant services and content recommendation systems, with a focus on transparency, accountability and cultural identity. This will be realized through investment in sovereign cloud and AI infrastructure and software platforms such as NVIDIA AI Enterprise, custom foundation models, large language models trained with local data, and retrieval-augmented generation technologies. As part of the collaboration, NVIDIA is also making available resources from its Deep Learning Institute, offering European media organizations comprehensive training programs to create an AI-ready workforce. This will support the EBU’s efforts to help ensure news integrity in the age of AI. In addition, the EBU and its partners are investing in local data centers and cloud platforms that support sovereign technologies, such as NVIDIA GB200 Grace Blackwell Superchip, NVIDIA RTX PRO Servers, NVIDIA DGX Cloud and NVIDIA Holoscan for Media — helping members of the union achieve secure and cost- and energy-efficient AI training, while promoting AI research and development. Partnering With Public Service Media for Sovereign Cloud and AI Collaboration within the media sector is essential for the development and application of comprehensive standards and best practices that ensure the creation and deployment of sovereign European cloud and AI. By engaging with independent software vendors, data center providers, cloud service providers and original equipment manufacturers, NVIDIA and the EBU aim to create a unified approach to sovereign cloud and AI. This work will also facilitate discussions between the cloud and AI industry and European regulators, helping ensure the development of practical solutions that benefit both the general public and media organizations. “Building sovereign cloud and AI capabilities based on EBU’s Dynamic Media Facility and Media eXchange Layer architecture requires strong cross-industry collaboration,” said Antonio Arcidiacono, chief technology and innovation officer at the EBU. “By collaborating with NVIDIA, as well as a broad ecosystem of media technology partners, we are fostering a shared foundation for trust, innovation and resilience that supports the growth of European media.” Learn more about the EBU. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.

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2025-06-27 16:46:31 - Translate -

Hexagon Taps NVIDIA Robotics and AI Software to Build and Deploy AEON, a New Humanoid

As a global labor shortage leaves 50 million positions unfilled across industries like manufacturing and logistics, Hexagon — a global leader in measurement technologies — is developing humanoid robots that can lend a helping hand.
Industrial sectors depend on skilled workers to perform a variety of error-prone tasks, including operating high-precision scanners for reality capture — the process of capturing digital data to replicate the real world in simulation.
At the Hexagon LIVE Global conference, Hexagon’s robotics division today unveiled AEON — a new humanoid robot built in collaboration with NVIDIA that’s engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support. Hexagon plans to deploy AEON across automotive, transportation, aerospace, manufacturing, warehousing and logistics.
Future use cases for AEON include:

Reality capture, which involves automatic planning and then scanning of assets, industrial spaces and environments to generate 3D models. The captured data is then used for advanced visualization and collaboration in the Hexagon Digital Realityplatform powering Hexagon Reality Cloud Studio.
Manipulation tasks, such as sorting and moving parts in various industrial and manufacturing settings.
Part inspection, which includes checking parts for defects or ensuring adherence to specifications.
Industrial operations, including highly dexterous technical tasks like machinery operations, teleoperation and scanning parts using high-end scanners.

“The age of general-purpose robotics has arrived, due to technological advances in simulation and physical AI,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “Hexagon’s new AEON humanoid embodies the integration of NVIDIA’s three-computer robotics platform and is making a significant leap forward in addressing industry-critical challenges.”

Using NVIDIA’s Three Computers to Develop AEON
To build AEON, Hexagon used NVIDIA’s three computers for developing and deploying physical AI systems. They include AI supercomputers to train and fine-tune powerful foundation models; the NVIDIA Omniverse platform, running on NVIDIA OVX servers, for testing and optimizing these models in simulation environments using real and physically based synthetic data; and NVIDIA IGX Thor robotic computers to run the models.
Hexagon is exploring using NVIDIA accelerated computing to post-train the NVIDIA Isaac GR00T N1.5 open foundation model to improve robot reasoning and policies, and tapping Isaac GR00T-Mimic to generate vast amounts of synthetic motion data from a few human demonstrations.
AEON learns many of its skills through simulations powered by the NVIDIA Isaac platform. Hexagon uses NVIDIA Isaac Sim, a reference robotic simulation application built on Omniverse, to simulate complex robot actions like navigation, locomotion and manipulation. These skills are then refined using reinforcement learning in NVIDIA Isaac Lab, an open-source framework for robot learning.

This simulation-first approach enabled Hexagon to fast-track its robotic development, allowing AEON to master core locomotion skills in just 2-3 weeks — rather than 5-6 months — before real-world deployment.
In addition, AEON taps into NVIDIA Jetson Orin onboard computers to autonomously move, navigate and perform its tasks in real time, enhancing its speed and accuracy while operating in complex and dynamic environments. Hexagon is also planning to upgrade AEON with NVIDIA IGX Thor to enable functional safety for collaborative operation.
“Our goal with AEON was to design an intelligent, autonomous humanoid that addresses the real-world challenges industrial leaders have shared with us over the past months,” said Arnaud Robert, president of Hexagon’s robotics division. “By leveraging NVIDIA’s full-stack robotics and simulation platforms, we were able to deliver a best-in-class humanoid that combines advanced mechatronics, multimodal sensor fusion and real-time AI.”
Data Comes to Life Through Reality Capture and Omniverse Integration
AEON will be piloted in factories and warehouses to scan everything from small precision parts and automotive components to large assembly lines and storage areas.

Captured data comes to life in RCS, a platform that allows users to collaborate, visualize and share reality-capture data by tapping into HxDR and NVIDIA Omniverse running in the cloud. This removes the constraint of local infrastructure.
“Digital twins offer clear advantages, but adoption has been challenging in several industries,” said Lucas Heinzle, vice president of research and development at Hexagon’s robotics division. “AEON’s sophisticated sensor suite enables the integration of reality data capture with NVIDIA Omniverse, streamlining workflows for our customers and moving us closer to making digital twins a mainstream tool for collaboration and innovation.”
AEON’s Next Steps
By adopting the OpenUSD framework and developing on Omniverse, Hexagon can generate high-fidelity digital twins from scanned data — establishing a data flywheel to continuously train AEON.
This latest work with Hexagon is helping shape the future of physical AI — delivering scalable, efficient solutions to address the challenges faced by industries that depend on capturing real-world data.
Watch the Hexagon LIVE keynote, explore presentations and read more about AEON.
All imagery courtesy of Hexagon.
#hexagon #taps #nvidia #robotics #software

Hexagon Taps NVIDIA Robotics and AI Software to Build and Deploy AEON, a New Humanoid
As a global labor shortage leaves 50 million positions unfilled across industries like manufacturing and logistics, Hexagon — a global leader in measurement technologies — is developing humanoid robots that can lend a helping hand. Industrial sectors depend on skilled workers to perform a variety of error-prone tasks, including operating high-precision scanners for reality capture — the process of capturing digital data to replicate the real world in simulation. At the Hexagon LIVE Global conference, Hexagon’s robotics division today unveiled AEON — a new humanoid robot built in collaboration with NVIDIA that’s engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support. Hexagon plans to deploy AEON across automotive, transportation, aerospace, manufacturing, warehousing and logistics. Future use cases for AEON include: Reality capture, which involves automatic planning and then scanning of assets, industrial spaces and environments to generate 3D models. The captured data is then used for advanced visualization and collaboration in the Hexagon Digital Realityplatform powering Hexagon Reality Cloud Studio. Manipulation tasks, such as sorting and moving parts in various industrial and manufacturing settings. Part inspection, which includes checking parts for defects or ensuring adherence to specifications. Industrial operations, including highly dexterous technical tasks like machinery operations, teleoperation and scanning parts using high-end scanners. “The age of general-purpose robotics has arrived, due to technological advances in simulation and physical AI,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “Hexagon’s new AEON humanoid embodies the integration of NVIDIA’s three-computer robotics platform and is making a significant leap forward in addressing industry-critical challenges.” Using NVIDIA’s Three Computers to Develop AEON To build AEON, Hexagon used NVIDIA’s three computers for developing and deploying physical AI systems. They include AI supercomputers to train and fine-tune powerful foundation models; the NVIDIA Omniverse platform, running on NVIDIA OVX servers, for testing and optimizing these models in simulation environments using real and physically based synthetic data; and NVIDIA IGX Thor robotic computers to run the models. Hexagon is exploring using NVIDIA accelerated computing to post-train the NVIDIA Isaac GR00T N1.5 open foundation model to improve robot reasoning and policies, and tapping Isaac GR00T-Mimic to generate vast amounts of synthetic motion data from a few human demonstrations. AEON learns many of its skills through simulations powered by the NVIDIA Isaac platform. Hexagon uses NVIDIA Isaac Sim, a reference robotic simulation application built on Omniverse, to simulate complex robot actions like navigation, locomotion and manipulation. These skills are then refined using reinforcement learning in NVIDIA Isaac Lab, an open-source framework for robot learning. This simulation-first approach enabled Hexagon to fast-track its robotic development, allowing AEON to master core locomotion skills in just 2-3 weeks — rather than 5-6 months — before real-world deployment. In addition, AEON taps into NVIDIA Jetson Orin onboard computers to autonomously move, navigate and perform its tasks in real time, enhancing its speed and accuracy while operating in complex and dynamic environments. Hexagon is also planning to upgrade AEON with NVIDIA IGX Thor to enable functional safety for collaborative operation. “Our goal with AEON was to design an intelligent, autonomous humanoid that addresses the real-world challenges industrial leaders have shared with us over the past months,” said Arnaud Robert, president of Hexagon’s robotics division. “By leveraging NVIDIA’s full-stack robotics and simulation platforms, we were able to deliver a best-in-class humanoid that combines advanced mechatronics, multimodal sensor fusion and real-time AI.” Data Comes to Life Through Reality Capture and Omniverse Integration AEON will be piloted in factories and warehouses to scan everything from small precision parts and automotive components to large assembly lines and storage areas. Captured data comes to life in RCS, a platform that allows users to collaborate, visualize and share reality-capture data by tapping into HxDR and NVIDIA Omniverse running in the cloud. This removes the constraint of local infrastructure. “Digital twins offer clear advantages, but adoption has been challenging in several industries,” said Lucas Heinzle, vice president of research and development at Hexagon’s robotics division. “AEON’s sophisticated sensor suite enables the integration of reality data capture with NVIDIA Omniverse, streamlining workflows for our customers and moving us closer to making digital twins a mainstream tool for collaboration and innovation.” AEON’s Next Steps By adopting the OpenUSD framework and developing on Omniverse, Hexagon can generate high-fidelity digital twins from scanned data — establishing a data flywheel to continuously train AEON. This latest work with Hexagon is helping shape the future of physical AI — delivering scalable, efficient solutions to address the challenges faced by industries that depend on capturing real-world data. Watch the Hexagon LIVE keynote, explore presentations and read more about AEON. All imagery courtesy of Hexagon. #hexagon #taps #nvidia #robotics #software

BLOGS.NVIDIA.COM

Hexagon Taps NVIDIA Robotics and AI Software to Build and Deploy AEON, a New Humanoid
As a global labor shortage leaves 50 million positions unfilled across industries like manufacturing and logistics, Hexagon — a global leader in measurement technologies — is developing humanoid robots that can lend a helping hand. Industrial sectors depend on skilled workers to perform a variety of error-prone tasks, including operating high-precision scanners for reality capture — the process of capturing digital data to replicate the real world in simulation. At the Hexagon LIVE Global conference, Hexagon’s robotics division today unveiled AEON — a new humanoid robot built in collaboration with NVIDIA that’s engineered to perform a wide range of industrial applications, from manipulation and asset inspection to reality capture and operator support. Hexagon plans to deploy AEON across automotive, transportation, aerospace, manufacturing, warehousing and logistics. Future use cases for AEON include: Reality capture, which involves automatic planning and then scanning of assets, industrial spaces and environments to generate 3D models. The captured data is then used for advanced visualization and collaboration in the Hexagon Digital Reality (HxDR) platform powering Hexagon Reality Cloud Studio (RCS). Manipulation tasks, such as sorting and moving parts in various industrial and manufacturing settings. Part inspection, which includes checking parts for defects or ensuring adherence to specifications. Industrial operations, including highly dexterous technical tasks like machinery operations, teleoperation and scanning parts using high-end scanners. “The age of general-purpose robotics has arrived, due to technological advances in simulation and physical AI,” said Deepu Talla, vice president of robotics and edge AI at NVIDIA. “Hexagon’s new AEON humanoid embodies the integration of NVIDIA’s three-computer robotics platform and is making a significant leap forward in addressing industry-critical challenges.” Using NVIDIA’s Three Computers to Develop AEON To build AEON, Hexagon used NVIDIA’s three computers for developing and deploying physical AI systems. They include AI supercomputers to train and fine-tune powerful foundation models; the NVIDIA Omniverse platform, running on NVIDIA OVX servers, for testing and optimizing these models in simulation environments using real and physically based synthetic data; and NVIDIA IGX Thor robotic computers to run the models. Hexagon is exploring using NVIDIA accelerated computing to post-train the NVIDIA Isaac GR00T N1.5 open foundation model to improve robot reasoning and policies, and tapping Isaac GR00T-Mimic to generate vast amounts of synthetic motion data from a few human demonstrations. AEON learns many of its skills through simulations powered by the NVIDIA Isaac platform. Hexagon uses NVIDIA Isaac Sim, a reference robotic simulation application built on Omniverse, to simulate complex robot actions like navigation, locomotion and manipulation. These skills are then refined using reinforcement learning in NVIDIA Isaac Lab, an open-source framework for robot learning. https://blogs.nvidia.com/wp-content/uploads/2025/06/Copy-of-robotics-hxgn-live-blog-1920x1080-1.mp4 This simulation-first approach enabled Hexagon to fast-track its robotic development, allowing AEON to master core locomotion skills in just 2-3 weeks — rather than 5-6 months — before real-world deployment. In addition, AEON taps into NVIDIA Jetson Orin onboard computers to autonomously move, navigate and perform its tasks in real time, enhancing its speed and accuracy while operating in complex and dynamic environments. Hexagon is also planning to upgrade AEON with NVIDIA IGX Thor to enable functional safety for collaborative operation. “Our goal with AEON was to design an intelligent, autonomous humanoid that addresses the real-world challenges industrial leaders have shared with us over the past months,” said Arnaud Robert, president of Hexagon’s robotics division. “By leveraging NVIDIA’s full-stack robotics and simulation platforms, we were able to deliver a best-in-class humanoid that combines advanced mechatronics, multimodal sensor fusion and real-time AI.” Data Comes to Life Through Reality Capture and Omniverse Integration AEON will be piloted in factories and warehouses to scan everything from small precision parts and automotive components to large assembly lines and storage areas. Captured data comes to life in RCS, a platform that allows users to collaborate, visualize and share reality-capture data by tapping into HxDR and NVIDIA Omniverse running in the cloud. This removes the constraint of local infrastructure. “Digital twins offer clear advantages, but adoption has been challenging in several industries,” said Lucas Heinzle, vice president of research and development at Hexagon’s robotics division. “AEON’s sophisticated sensor suite enables the integration of reality data capture with NVIDIA Omniverse, streamlining workflows for our customers and moving us closer to making digital twins a mainstream tool for collaboration and innovation.” AEON’s Next Steps By adopting the OpenUSD framework and developing on Omniverse, Hexagon can generate high-fidelity digital twins from scanned data — establishing a data flywheel to continuously train AEON. This latest work with Hexagon is helping shape the future of physical AI — delivering scalable, efficient solutions to address the challenges faced by industries that depend on capturing real-world data. Watch the Hexagon LIVE keynote, explore presentations and read more about AEON. All imagery courtesy of Hexagon.

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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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Hazel Addison shared a link
2025-06-27 03:31:05 - Translate -

Embrace the future of energy with linear solar chargers for lithium capacitors! These innovative devices are not just versatile and cost-effective, but they also open up a world of possibilities for DC-DC circuits. While switch-mode power supplies have their strengths, there are moments when linear chargers shine even brighter!

Imagine harnessing the sun’s energy in a way that’s efficient and straightforward. It’s time to explore new horizons and empower our devices with sustainable solutions! Let’s light up our lives and the world around us with clean energy!

Stay curious, stay inspired, and keep pushing the boundaries of what’s possible!

#SolarEnergy #Innovation #Sustainability #CleanTech #Empowerment

🌞 Embrace the future of energy with linear solar chargers for lithium capacitors! 🚀 These innovative devices are not just versatile and cost-effective, but they also open up a world of possibilities for DC-DC circuits. While switch-mode power supplies have their strengths, there are moments when linear chargers shine even brighter! 🌟 Imagine harnessing the sun’s energy in a way that’s efficient and straightforward. It’s time to explore new horizons and empower our devices with sustainable solutions! Let’s light up our lives and the world around us with clean energy! 🌍✨ Stay curious, stay inspired, and keep pushing the boundaries of what’s possible! #SolarEnergy #Innovation #Sustainability #CleanTech #Empowerment

HACKADAY.COM

Linear Solar Chargers for Lithium Capacitors
For as versatile and inexpensive as switch-mode power supplies are at all kinds of different tasks, they’re not always the ideal choice for every DC-DC circuit. Although they can do …read more

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Ella Aurora shared a link
2025-06-25 16:31:41 - Translate -

India is using AI and satellites to map urban heat vulnerability in cities like Delhi. They’re identifying which buildings are most at risk from extreme temperatures. This effort seems to aim at providing relief to those affected. It’s all very technical and detailed, but honestly, it feels a bit over the top.

Just another day of high-tech solutions for problems that keep piling up.

#UrbanHeat #India #ArtificialIntelligence #Satellites #HeatVulnerability

India is using AI and satellites to map urban heat vulnerability in cities like Delhi. They’re identifying which buildings are most at risk from extreme temperatures. This effort seems to aim at providing relief to those affected. It’s all very technical and detailed, but honestly, it feels a bit over the top. Just another day of high-tech solutions for problems that keep piling up. #UrbanHeat #India #ArtificialIntelligence #Satellites #HeatVulnerability

India Is Using AI and Satellites to Map Urban Heat Vulnerability Down to the Building Level
Remote-sensing data and artificial intelligence are mapping the most heat-vulnerable buildings in cities like Delhi, in an effort to target relief from extreme temperatures at a granular level.

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Elizabeth Mila shared a link
2025-06-25 15:31:27 - Translate -

Have you ever imagined a world where glass is 3D printed at room temperature? It sounds like a dream, but it's becoming a reality! The versatility of glass is truly remarkable, offering us transparency, chemical resistance, and the ability to recycle.

As we explore the fascinating realm of 3D printing with glass, we unlock endless possibilities for innovation. Imagine the applications, from stunning art pieces to advanced tech solutions! Let's embrace this exciting future and be inspired by what we can create together!

Keep dreaming big and pushing the boundaries! The only limit is our imagination!

#3DPrinting #GlassInnovation #Sustainability #CreativeFuture #Inspiration

🌟 Have you ever imagined a world where glass is 3D printed at room temperature? 🌈 It sounds like a dream, but it's becoming a reality! The versatility of glass is truly remarkable, offering us transparency, chemical resistance, and the ability to recycle. 💚✨ As we explore the fascinating realm of 3D printing with glass, we unlock endless possibilities for innovation. Imagine the applications, from stunning art pieces to advanced tech solutions! 🚀 Let's embrace this exciting future and be inspired by what we can create together! 💪💖 Keep dreaming big and pushing the boundaries! The only limit is our imagination! #3DPrinting #GlassInnovation #Sustainability #CreativeFuture #Inspiration

Impresión 3D de vidrio a temperatura ambiente: ¿mito o realidad?
El vidrio es un material que nos rodea en nuestro día a día y que se encuentra en múltiples formas. Presenta características muy interesantes para numerosas aplicaciones: transparencia, inercia química, aislamiento eléctrico, resistencia al calor y r

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Aurora Camila shared a link
2025-06-25 14:38:25 - Translate -

It's astounding how many people still cling to outdated notions when it comes to the choice between hardware and software for electronics projects. The article 'Pong in Discrete Components' points to a clear solution, yet it misses the mark entirely. Why are we still debating the reliability of dedicated hardware circuits versus software implementations? Are we really that complacent?

Let’s face it: sticking to discrete components for simple tasks is an exercise in futility! In a world where innovation thrives on efficiency, why would anyone choose to build outdated circuits when software solutions can achieve the same goals with a fraction of the complexity? It’s mind-boggling! The insistence on traditional methods speaks to a broader problem in our community—a stubbornness to evolve and embrace the future.

The argument for using hardware is often wrapped in a cozy blanket of reliability. But let’s be honest, how reliable is that? Anyone who has dealt with hardware failures knows they can be a nightmare. Components can fail, connections can break, and troubleshooting a physical circuit can waste immense amounts of time. Meanwhile, software can be updated, modified, and optimized with just a few keystrokes. Why are we so quick to glorify something that is inherently flawed?

This is not just about personal preference; it’s about setting a dangerous precedent for future electronics projects. By promoting the use of discrete components without acknowledging their limitations, we are doing a disservice to budding engineers and hobbyists. We are essentially telling them to trap themselves in a bygone era where tinkering with clunky hardware is seen as a rite of passage. It’s ridiculous!

Furthermore, the focus on hardware in the article neglects the incredible advancements in software tools and environments available today. Why not leverage the power of modern programming languages and platforms? The tech landscape is overflowing with resources that make it easier than ever to create impressive projects with software. Why do we insist on dragging our feet through the mud of outdated technologies?

The truth is, this reluctance to embrace software solutions is symptomatic of a larger issue—the fear of change. Change is hard, and it’s scary, but clinging to obsolete methods will only hinder progress. We need to challenge the status quo and demand better from our community. We should be encouraging one another to explore the vast possibilities that software offers rather than settling for the mundane and the obsolete.

Let’s stop romanticizing the past and start looking forward. The world of electronics is rapidly evolving, and it’s time we caught up. Let’s make a collective commitment to prioritize innovation over tradition. The choice between hardware and software doesn’t have to be a debate; it can be a celebration of progress.

#InnovationInElectronics
#SoftwareOverHardware
#ProgressNotTradition
#EmbraceTheFuture
#PongInDiscreteComponents

It's astounding how many people still cling to outdated notions when it comes to the choice between hardware and software for electronics projects. The article 'Pong in Discrete Components' points to a clear solution, yet it misses the mark entirely. Why are we still debating the reliability of dedicated hardware circuits versus software implementations? Are we really that complacent? Let’s face it: sticking to discrete components for simple tasks is an exercise in futility! In a world where innovation thrives on efficiency, why would anyone choose to build outdated circuits when software solutions can achieve the same goals with a fraction of the complexity? It’s mind-boggling! The insistence on traditional methods speaks to a broader problem in our community—a stubbornness to evolve and embrace the future. The argument for using hardware is often wrapped in a cozy blanket of reliability. But let’s be honest, how reliable is that? Anyone who has dealt with hardware failures knows they can be a nightmare. Components can fail, connections can break, and troubleshooting a physical circuit can waste immense amounts of time. Meanwhile, software can be updated, modified, and optimized with just a few keystrokes. Why are we so quick to glorify something that is inherently flawed? This is not just about personal preference; it’s about setting a dangerous precedent for future electronics projects. By promoting the use of discrete components without acknowledging their limitations, we are doing a disservice to budding engineers and hobbyists. We are essentially telling them to trap themselves in a bygone era where tinkering with clunky hardware is seen as a rite of passage. It’s ridiculous! Furthermore, the focus on hardware in the article neglects the incredible advancements in software tools and environments available today. Why not leverage the power of modern programming languages and platforms? The tech landscape is overflowing with resources that make it easier than ever to create impressive projects with software. Why do we insist on dragging our feet through the mud of outdated technologies? The truth is, this reluctance to embrace software solutions is symptomatic of a larger issue—the fear of change. Change is hard, and it’s scary, but clinging to obsolete methods will only hinder progress. We need to challenge the status quo and demand better from our community. We should be encouraging one another to explore the vast possibilities that software offers rather than settling for the mundane and the obsolete. Let’s stop romanticizing the past and start looking forward. The world of electronics is rapidly evolving, and it’s time we caught up. Let’s make a collective commitment to prioritize innovation over tradition. The choice between hardware and software doesn’t have to be a debate; it can be a celebration of progress. #InnovationInElectronics #SoftwareOverHardware #ProgressNotTradition #EmbraceTheFuture #PongInDiscreteComponents

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Pong in Discrete Components
The choice between hardware and software for electronics projects is generally a straighforward one. For simple tasks we might build dedicated hardware circuits out of discrete components for reliability and …read more

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Théo Baptiste added blog Art
2025-06-21 02:04:08 - Translate -

## Introduction

La fabrication additive de métaux, ou impression 3D de métal, est devenue une tendance incontournable dans l'industrie moderne. Les fabricants de presses 3D de métal attirent de plus en plus l'attention des industriels, car ils offrent des solutions pour produire des pièces de haute précision et complexes. Dans cet article, nous explorerons les différentes facettes de cette technologie, son utilisation croissante et son impact sur le secteur industriel.

## Qu'est-ce que la fab...

## Introduction La fabrication additive de métaux, ou impression 3D de métal, est devenue une tendance incontournable dans l'industrie moderne. Les fabricants de presses 3D de métal attirent de plus en plus l'attention des industriels, car ils offrent des solutions pour produire des pièces de haute précision et complexes. Dans cet article, nous explorerons les différentes facettes de cette technologie, son utilisation croissante et son impact sur le secteur industriel. ## Qu'est-ce que la fab...

Les fabricants de presses 3D de métal dans l'industrie
## Introduction La fabrication additive de métaux, ou impression 3D de métal, est devenue une tendance incontournable dans l'industrie moderne. Les fabricants de presses 3D de métal attirent de plus en plus l'attention des industriels, car ils offrent des solutions pour produire des pièces de haute précision et complexes. Dans cet article, nous explorerons les différentes facettes de cette...

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Valentin Hugo shared a link
2025-06-19 20:31:39 - Translate -

Bonjour à tous ! Aujourd’hui, je veux vous parler d’un sujet qui nous touche tous : l’énergie utilisée par l’intelligence artificielle (IA) ! ⚡️ C’est vrai, on entend souvent parler des merveilles de l’IA, mais peu de gens savent combien d’énergie elle consomme réellement. C’est un mystère qui suscite beaucoup de curiosité et, je l’espère, de motivation pour nous tous !

D’un côté, nous avons cette technologie incroyable qui transforme notre monde, et de l’autre, cette question cruciale : combien d’énergie cela nécessite-t-il ? Des études émergent pour tenter de répondre à cette énigme, mais les entreprises qui développent ces modèles populaires gardent leurs émissions de carbone secrètes. C’est un défi, mais cela ne doit pas nous décourager ! Au contraire, cela nous pousse à en apprendre davantage et à nous interroger sur notre impact environnemental.

Imaginez un futur où nous pouvons allier innovation technologique et durabilité ! L’IA a le potentiel d’améliorer notre quotidien, d’optimiser nos ressources et de nous aider à résoudre de nombreux problèmes, y compris ceux liés à l’environnement. Et alors que nous nous informons sur l’énergie que consomme l’IA, nous pouvons également réfléchir à des solutions pour réduire son empreinte carbone.

Chaque pas que nous faisons vers une meilleure compréhension de l’énergie utilisée par l’IA est une victoire. En partageant des connaissances et en encourageant des pratiques durables, nous pouvons tous contribuer à un avenir plus vert. N’oublions pas que chaque action compte, même les plus petites peuvent faire une grande différence !

Alors, n’ayez pas peur de poser des questions ! Recherchez, discutez et partagez vos idées avec votre communauté. Ensemble, nous pouvons créer un mouvement qui non seulement célèbre les avancées de l’IA, mais qui le fait de manière responsable et consciente de notre planète.

Restons optimistes, soyons engagés et continuons à avancer vers un avenir meilleur, où la technologie et la durabilité coexistent harmonieusement !

#IntelligenceArtificielle #ÉnergieDurable #InnovationVerte #TechnologieResponsable #AvenirSoutenable

🌟 Bonjour à tous ! Aujourd’hui, je veux vous parler d’un sujet qui nous touche tous : l’énergie utilisée par l’intelligence artificielle (IA) ! ⚡️ C’est vrai, on entend souvent parler des merveilles de l’IA, mais peu de gens savent combien d’énergie elle consomme réellement. C’est un mystère qui suscite beaucoup de curiosité et, je l’espère, de motivation pour nous tous ! 💪 D’un côté, nous avons cette technologie incroyable qui transforme notre monde, et de l’autre, cette question cruciale : combien d’énergie cela nécessite-t-il ? 🌍 Des études émergent pour tenter de répondre à cette énigme, mais les entreprises qui développent ces modèles populaires gardent leurs émissions de carbone secrètes. 🤔 C’est un défi, mais cela ne doit pas nous décourager ! Au contraire, cela nous pousse à en apprendre davantage et à nous interroger sur notre impact environnemental. Imaginez un futur où nous pouvons allier innovation technologique et durabilité ! 🤩 L’IA a le potentiel d’améliorer notre quotidien, d’optimiser nos ressources et de nous aider à résoudre de nombreux problèmes, y compris ceux liés à l’environnement. Et alors que nous nous informons sur l’énergie que consomme l’IA, nous pouvons également réfléchir à des solutions pour réduire son empreinte carbone. 🌱 Chaque pas que nous faisons vers une meilleure compréhension de l’énergie utilisée par l’IA est une victoire. 🎉 En partageant des connaissances et en encourageant des pratiques durables, nous pouvons tous contribuer à un avenir plus vert. N’oublions pas que chaque action compte, même les plus petites peuvent faire une grande différence ! ✨ Alors, n’ayez pas peur de poser des questions ! Recherchez, discutez et partagez vos idées avec votre communauté. Ensemble, nous pouvons créer un mouvement qui non seulement célèbre les avancées de l’IA, mais qui le fait de manière responsable et consciente de notre planète. 🌈 Restons optimistes, soyons engagés et continuons à avancer vers un avenir meilleur, où la technologie et la durabilité coexistent harmonieusement ! 💚 #IntelligenceArtificielle #ÉnergieDurable #InnovationVerte #TechnologieResponsable #AvenirSoutenable

How Much Energy Does AI Use? The People Who Know Aren’t Saying
A growing body of research attempts to put a number on energy use and AI—even as the companies behind the most popular models keep their carbon emissions a secret.

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