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NVIDIA شارك رابطًا
2025-06-28 03:48:18 -

NVIDIA Scores Consecutive Win for End-to-End Autonomous Driving Grand Challenge at CVPR

NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognitionconference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop.
This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR.
The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehiclesimulation framework.
The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs.
Generating Safe and Adaptive Driving Trajectories
Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically.
Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research.
The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoringmethod, which generates a variety of trajectories and progressively filters out the best one.
GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories.
GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories.
This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions.

NVIDIA Automotive Research at CVPR
More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more.
In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+.
The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs:

Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion ModelsFoundationStereo: Zero-Shot Stereo MatchingZero-Shot Monocular Scene Flow Estimation in the WildDifix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting
Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
Zero-Shot 4D Lidar Panoptic Segmentation
NVILA: Efficient Frontier Visual Language Models
RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models
OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning

Explore automotive workshops and tutorials at CVPR, including:

Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA
Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA
Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe
Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA
Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe
Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone
LatinX in CV Workshop, featuring Leal-Taixe
Workshop on Exploring the Next Generation of Data, featuring Alvarez
Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA
Continuous Data Cycle via Foundation Models, led by NVIDIA
Distillation of Foundation Models for Autonomous Driving, led by NVIDIA

Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang.
Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics.
The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model.
#nvidia #scores #consecutive #win #endtoend

NVIDIA Scores Consecutive Win for End-to-End Autonomous Driving Grand Challenge at CVPR
NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognitionconference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop. This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Scale category and the third year in a row winning an Autonomous Grand Challenge award at CVPR. The theme of this year’s challenge was “Towards Generalizable Embodied Systems” — based on NAVSIM v2, a data-driven, nonreactive autonomous vehiclesimulation framework. The challenge offered researchers the opportunity to explore ways to handle unexpected situations, beyond using only real-world human driving data, to accelerate the development of smarter, safer AVs. Generating Safe and Adaptive Driving Trajectories Participants of the challenge were tasked with generating driving trajectories from multi-sensor data in a semi-reactive simulation, where the ego vehicle’s plan is fixed at the start, but background traffic changes dynamically. Submissions were evaluated using the Extended Predictive Driver Model Score, which measures safety, comfort, compliance and generalization across real-world and synthetic scenarios — pushing the boundaries of robust and generalizable autonomous driving research. The NVIDIA AV Applied Research Team’s key innovation was the Generalized Trajectory Scoringmethod, which generates a variety of trajectories and progressively filters out the best one. GTRS model architecture showing a unified system for generating and scoring diverse driving trajectories using diffusion- and vocabulary-based trajectories. GTRS introduces a combination of coarse sets of trajectories covering a wide range of situations and fine-grained trajectories for safety-critical situations, created using a diffusion policy conditioned on the environment. GTRS then uses a transformer decoder distilled from perception-dependent metrics, focusing on safety, comfort and traffic rule compliance. This decoder progressively filters out the most promising trajectory candidates by capturing subtle but critical differences between similar trajectories. This system has proved to generalize well to a wide range of scenarios, achieving state-of-the-art results on challenging benchmarks and enabling robust, adaptive trajectory selection in diverse and challenging driving conditions. NVIDIA Automotive Research at CVPR More than 60 NVIDIA papers were accepted for CVPR 2025, spanning automotive, healthcare, robotics and more. In automotive, NVIDIA researchers are advancing physical AI with innovation in perception, planning and data generation. This year, three NVIDIA papers were nominated for the Best Paper Award: FoundationStereo, Zero-Shot Monocular Scene Flow and Difix3D+. The NVIDIA papers listed below showcase breakthroughs in stereo depth estimation, monocular motion understanding, 3D reconstruction, closed-loop planning, vision-language modeling and generative simulation — all critical to building safer, more generalizable AVs: Diffusion Renderer: Neural Inverse and Forward Rendering With Video Diffusion ModelsFoundationStereo: Zero-Shot Stereo MatchingZero-Shot Monocular Scene Flow Estimation in the WildDifix3D+: Improving 3D Reconstructions With Single-Step Diffusion Models3DGUT: Enabling Distorted Cameras and Secondary Rays in Gaussian Splatting Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models Zero-Shot 4D Lidar Panoptic Segmentation NVILA: Efficient Frontier Visual Language Models RADIO Amplified: Improved Baselines for Agglomerative Vision Foundation Models OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving With Counterfactual Reasoning Explore automotive workshops and tutorials at CVPR, including: Workshop on Data-Driven Autonomous Driving Simulation, featuring Marco Pavone, senior director of AV research at NVIDIA, and Sanja Fidler, vice president of AI research at NVIDIA Workshop on Autonomous Driving, featuring Laura Leal-Taixe, senior research manager at NVIDIA Workshop on Open-World 3D Scene Understanding with Foundation Models, featuring Leal-Taixe Safe Artificial Intelligence for All Domains, featuring Jose Alvarez, director of AV applied research at NVIDIA Workshop on Foundation Models for V2X-Based Cooperative Autonomous Driving, featuring Pavone and Leal-Taixe Workshop on Multi-Agent Embodied Intelligent Systems Meet Generative AI Era, featuring Pavone LatinX in CV Workshop, featuring Leal-Taixe Workshop on Exploring the Next Generation of Data, featuring Alvarez Full-Stack, GPU-Based Acceleration of Deep Learning and Foundation Models, led by NVIDIA Continuous Data Cycle via Foundation Models, led by NVIDIA Distillation of Foundation Models for Autonomous Driving, led by NVIDIA Explore the NVIDIA research papers to be presented at CVPR and watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang. Learn more about NVIDIA Research, a global team of hundreds of scientists and engineers focused on topics including AI, computer graphics, computer vision, self-driving cars and robotics. The featured image above shows how an autonomous vehicle adapts its trajectory to navigate an urban environment with dynamic traffic using the GTRS model. #nvidia #scores #consecutive #win #endtoend

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

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NVIDIA شارك رابطًا
2025-06-27 20:48:10 -

NVIDIA Brings Physical AI to European Cities With New Blueprint for Smart City AI

Urban populations are expected to double by 2050, which means around 2.5 billion people could be added to urban areas by the middle of the century, driving the need for more sustainable urban planning and public services. Cities across the globe are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions.
Building a digital twin of a city and testing smart city AI agents within it, however, is a complex and resource-intensive endeavor, fraught with technical and operational challenges.
To address those challenges, NVIDIA today announced the NVIDIA Omniverse Blueprint for smart city AI, a reference framework that combines the NVIDIA Omniverse, Cosmos, NeMo and Metropolis platforms to bring the benefits of physical AI to entire cities and their critical infrastructure.
Using the blueprint, developers can build simulation-ready, or SimReady, photorealistic digital twins of cities to build and test AI agents that can help monitor and optimize city operations.
Leading companies including XXII, AVES Reality, Akila, Blyncsy, Bentley, Cesium, K2K, Linker Vision, Milestone Systems, Nebius, SNCF Gares&Connexions, Trimble and Younite AI are among the first to use the new blueprint.

NVIDIA Omniverse Blueprint for Smart City AI
The NVIDIA Omniverse Blueprint for smart city AI provides the complete software stack needed to accelerate the development and testing of AI agents in physically accurate digital twins of cities. It includes:

NVIDIA Omniverse to build physically accurate digital twins and run simulations at city scale.
NVIDIA Cosmos to generate synthetic data at scale for post-training AI models.
NVIDIA NeMo to curate high-quality data and use that data to train and fine-tune vision language modelsand large language models.
NVIDIA Metropolis to build and deploy video analytics AI agents based on the NVIDIA AI Blueprint for video search and summarization, helping process vast amounts of video data and provide critical insights to optimize business processes.

The blueprint workflow comprises three key steps. First, developers create a SimReady digital twin of locations and facilities using aerial, satellite or map data with Omniverse and Cosmos. Second, they can train and fine-tune AI models, like computer vision models and VLMs, using NVIDIA TAO and NeMo Curator to improve accuracy for vision AI use cases. Finally, real-time AI agents powered by these customized models are deployed to alert, summarize and query camera and sensor data using the Metropolis VSS blueprint.
NVIDIA Partner Ecosystem Powers Smart Cities Worldwide
The blueprint for smart city AI enables a large ecosystem of partners to use a single workflow to build and activate digital twins for smart city use cases, tapping into a combination of NVIDIA’s technologies and their own.
SNCF Gares&Connexions, which operates a network of 3,000 train stations across France and Monaco, has deployed a digital twin and AI agents to enable real-time operational monitoring, emergency response simulations and infrastructure upgrade planning.
This helps each station analyze operational data such as energy and water use, and enables predictive maintenance capabilities, automated reporting and GDPR-compliant video analytics for incident detection and crowd management.
Powered by Omniverse, Metropolis and solutions from ecosystem partners Akila and XXII, SNCF Gares&Connexions’ physical AI deployment at the Monaco-Monte-Carlo and Marseille stations has helped SNCF Gares&Connexions achieve a 100% on-time preventive maintenance completion rate, a 50% reduction in downtime and issue response time, and a 20% reduction in energy consumption.

The city of Palermo in Sicily is using AI agents and digital twins from its partner K2K to improve public health and safety by helping city operators process and analyze footage from over 1,000 public video streams at a rate of nearly 50 billion pixels per second.
Tapped by Sicily, K2K’s AI agents — built with the NVIDIA AI Blueprint for VSS and cloud solutions from Nebius — can interpret and act on video data to provide real-time alerts on public events.
To accurately predict and resolve traffic incidents, K2K is generating synthetic data with Cosmos world foundation models to simulate different driving conditions. Then, K2K uses the data to fine-tune the VLMs powering the AI agents with NeMo Curator. These simulations enable K2K’s AI agents to create over 100,000 predictions per second.

Milestone Systems — in collaboration with NVIDIA and European cities — has launched Project Hafnia, an initiative to build an anonymized, ethically sourced video data platform for cities to develop and train AI models and applications while maintaining regulatory compliance.
Using a combination of Cosmos and NeMo Curator on NVIDIA DGX Cloud and Nebius’ sovereign European cloud infrastructure, Project Hafnia scales up and enables European-compliant training and fine-tuning of video-centric AI models, including VLMs, for a variety of smart city use cases.
The project’s initial rollout, taking place in Genoa, Italy, features one of the world’s first VLM models for intelligent transportation systems.

Linker Vision was among the first to partner with NVIDIA to deploy smart city digital twins and AI agents for Kaohsiung City, Taiwan — powered by Omniverse, Cosmos and Metropolis. Linker Vision worked with AVES Reality, a digital twin company, to bring aerial imagery of cities and infrastructure into 3D geometry and ultimately into SimReady Omniverse digital twins.
Linker Vision’s AI-powered application then built, trained and tested visual AI agents in a digital twin before deployment in the physical city. Now, it’s scaling to analyze 50,000 video streams in real time with generative AI to understand and narrate complex urban events like floods and traffic accidents. Linker Vision delivers timely insights to a dozen city departments through a single integrated AI-powered platform, breaking silos and reducing incident response times by up to 80%.

Bentley Systems is joining the effort to bring physical AI to cities with the NVIDIA blueprint. Cesium, the open 3D geospatial platform, provides the foundation for visualizing, analyzing and managing infrastructure projects and ports digital twins to Omniverse. The company’s AI platform Blyncsy uses synthetic data generation and Metropolis to analyze road conditions and improve maintenance.
Trimble, a global technology company that enables essential industries including construction, geospatial and transportation, is exploring ways to integrate components of the Omniverse blueprint into its reality capture workflows and Trimble Connect digital twin platform for surveying and mapping applications for smart cities.
Younite AI, a developer of AI and 3D digital twin solutions, is adopting the blueprint to accelerate its development pipeline, enabling the company to quickly move from operational digital twins to large-scale urban simulations, improve synthetic data generation, integrate real-time IoT sensor data and deploy AI agents.
Learn more about the NVIDIA Omniverse Blueprint for smart city AI by attending this GTC Paris session or watching the on-demand video after the event. Sign up to be notified when the blueprint is available.
Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.
#nvidia #brings #physical #european #cities

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

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

34

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2025-06-27 13:46:30 -

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

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

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NVIDIA شارك رابطًا
2025-06-27 11:32:07 -

Into the Omniverse: World Foundation Models Advance Autonomous Vehicle Simulation and Safety

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

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

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

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

Hear NVIDIA Director of Autonomous Vehicle Research Marco Pavone on the NVIDIA AI Podcast share how digital twins and high-fidelity simulation are improving vehicle testing, accelerating development and reducing real-world risks.
Get Plugged Into the World of OpenUSD
Learn more about what’s next for AV simulation with OpenUSD by watching the replay of NVIDIA founder and CEO Jensen Huang’s GTC Paris keynote.
Looking for more live opportunities to learn more about OpenUSD? Don’t miss sessions and labs happening at SIGGRAPH 2025, August 10–14.
Discover why developers and 3D practitioners are using OpenUSD and learn how to optimize 3D workflows with the self-paced “Learn OpenUSD” curriculum for 3D developers and practitioners, available for free through the NVIDIA Deep Learning Institute.
Explore the Alliance for OpenUSD forum and the AOUSD website.
Stay up to date by subscribing to NVIDIA Omniverse news, joining the community and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.
#into #omniverse #world #foundation #models

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

BLOGS.NVIDIA.COM

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

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Game Rant شارك رابطًا
2025-06-27 11:31:39 -

Star Trek: Best Crews, Ranked

Every Star Trek show has a few common threads, and most of them have a ship and a crew that are the focus of the plot. The chemistry between the crew is often part of the story, with drama between characters generating some of the best and most compelling plotlines.
#star #trek #best #crews #ranked

Star Trek: Best Crews, Ranked
Every Star Trek show has a few common threads, and most of them have a ship and a crew that are the focus of the plot. The chemistry between the crew is often part of the story, with drama between characters generating some of the best and most compelling plotlines. #star #trek #best #crews #ranked

GAMERANT.COM

Star Trek: Best Crews, Ranked
Every Star Trek show has a few common threads, and most of them have a ship and a crew that are the focus of the plot. The chemistry between the crew is often part of the story, with drama between characters generating some of the best and most compelling plotlines.

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NVIDIA شارك رابطًا
2025-06-27 11:30:14 -

Startup Uses NVIDIA RTX-Powered Generative AI to Make Coolers, Cooler

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

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

Every texture, every word, every photo, every accessory was a micro-decision, Theriault said. AI helped him survive the “death by a thousand cuts” that can stall solo startup founders, he added.
Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.
Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter.
Follow NVIDIA Workstation on LinkedIn and X.
See notice regarding software product information.
#startup #uses #nvidia #rtxpowered #generative

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

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

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Natalie Everly شارك رابطًا
2025-06-16 18:32:15 -

The protests in Los Angeles have brought a lot of attention, but honestly, it’s just the same old story. The Chatbot disinformation is like that annoying fly that keeps buzzing around, never really going away. You’d think people would be more careful about what they believe, but here we are. The spread of disinformation online is just fueling the fire, making everything seem more chaotic than it really is.

It’s kind of exhausting to see the same patterns repeat. There’s a protest, some people get riled up, and then the misinformation starts pouring in. It’s like a never-ending cycle. Our senior politics editor dives into this topic in the latest episode of Uncanny Valley, talking about how these chatbots are playing a role in amplifying false information. Not that many people seem to care, though.

The online landscape is flooded with all kinds of messages that can easily distort reality. It’s almost as if people are too tired to fact-check anymore. Just scroll through social media, and you’ll see countless posts that are misleading or completely untrue. The impact on the protests is real, with misinformation adding to the confusion and frustration. One could argue that it’s a bit depressing, really.

As the protests continue, it’s hard to see a clear path forward. Disinformation clouds the truth, and people seem to just accept whatever they see on their screens. It’s all so monotonous. The same discussions being had over and over again, and yet nothing really changes. The chatbots keep generating content, and the cycle goes on.

Honestly, it makes you wonder whether anyone is actually listening or if they’re just scrolling mindlessly. The discussions about the protests and the role of disinformation should be enlightening, but they often feel repetitive and bland. It’s hard to muster any excitement when the conversations feel so stale.

In the end, it’s just more noise in a world that’s already too loud. The protests might be important, but the chatbots and their disinformation are just taking away from the real issues at hand. This episode of Uncanny Valley might shed some light, but will anyone really care? Who knows.

#LosAngelesProtests
#Disinformation
#Chatbots
#UncannyValley
#Misinformation

The protests in Los Angeles have brought a lot of attention, but honestly, it’s just the same old story. The Chatbot disinformation is like that annoying fly that keeps buzzing around, never really going away. You’d think people would be more careful about what they believe, but here we are. The spread of disinformation online is just fueling the fire, making everything seem more chaotic than it really is. It’s kind of exhausting to see the same patterns repeat. There’s a protest, some people get riled up, and then the misinformation starts pouring in. It’s like a never-ending cycle. Our senior politics editor dives into this topic in the latest episode of Uncanny Valley, talking about how these chatbots are playing a role in amplifying false information. Not that many people seem to care, though. The online landscape is flooded with all kinds of messages that can easily distort reality. It’s almost as if people are too tired to fact-check anymore. Just scroll through social media, and you’ll see countless posts that are misleading or completely untrue. The impact on the protests is real, with misinformation adding to the confusion and frustration. One could argue that it’s a bit depressing, really. As the protests continue, it’s hard to see a clear path forward. Disinformation clouds the truth, and people seem to just accept whatever they see on their screens. It’s all so monotonous. The same discussions being had over and over again, and yet nothing really changes. The chatbots keep generating content, and the cycle goes on. Honestly, it makes you wonder whether anyone is actually listening or if they’re just scrolling mindlessly. The discussions about the protests and the role of disinformation should be enlightening, but they often feel repetitive and bland. It’s hard to muster any excitement when the conversations feel so stale. In the end, it’s just more noise in a world that’s already too loud. The protests might be important, but the chatbots and their disinformation are just taking away from the real issues at hand. This episode of Uncanny Valley might shed some light, but will anyone really care? Who knows. #LosAngelesProtests #Disinformation #Chatbots #UncannyValley #Misinformation

The Chatbot Disinfo Inflaming the LA Protests
On this episode of Uncanny Valley, our senior politics editor discusses the spread of disinformation online following the onset of the Los Angeles protests.

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Unity شارك رابطًا
2025-06-16 08:33:33 -

How to optimize your hybrid waterfall with CPM buckets

In-app bidding has automated most waterfall optimization, yet developers still manage multiple hybrid waterfalls, each with dozens of manual instances. Naturally, this can be timely and overwhelming to maintain, keeping you from optimizing to perfection and focusing on other opportunities to boost revenue.Rather than analyzing each individual network and checking if instances are available at each price point, breaking down your waterfall into different CPM ranges allows you to visualize the waterfall and easily identify the gaps.Here are some tips on how to use CPM buckets to better optimize your waterfall’s performance.What are CPM buckets?CPM buckets show you exactly how much revenue and how many impressions you’re getting from each CPM price range, giving you a more granular idea of how different networks are competing in the waterfall. CPM buckets are a feature of real time pivot reports, available on ironSource LevelPlay.Identifying and closing the gapsTypically in a waterfall, you can only see each ad network’s average CPM. But this keeps you from seeing ad network distribution across all price points and understanding exactly where ad networks are bidding. Bottom line - you don’t know where in the waterfall you should add a new instance.By separating CPM into buckets,you understand exactly which networks are driving impressions and revenue and which CPMs aren’t being filledNow how do you do it? As a LevelPlay client, simply use ironSource’s real time pivot reports - choose the CPM bucket filter option and sort by “average bid price.” From here, you’ll see how your revenue spreads out among CPM ranges and you’ll start to notice gaps in your bar graph. Every gap in revenue - where revenue is much lower than the neighboring CPM group - indicates an opportunity to optimize your monetization strategy. The buckets can range from small increments like to larger increments like so it’s important to compare CPM buckets of the same incremental value.Pro tip: To best set up your waterfall, create one tab with the general waterfalland make sure to look at Revenue and eCPM in the “measures” dropdown. In the “show” section, choose CPM buckets and sort by average bid price. From here, you can mark down any gaps.But where do these gaps come from? Gaps in revenue are often due to friction in the waterfall, like not enough instances, instances that aren’t working, or a waterfall setup mistake. But gaps can also be adjusted and fixed.Once you’ve found a gap, you can look at the CPM buckets around it to better understand the context. Let’s say you see a strong instance generating significant revenue in the CPM bucket right below it, in the -80 group. This instance from this specific ad network has a lot of potential, so it’s worth trying to push it to a higher CPM bucket.In fact, when you look at higher CPM buckets, you don’t see this ad network anywhere else in the waterfall - what a missed opportunity! Try adding another instance of this network higher up in the waterfall. If you’re profiting well with a -80 CPM, imagine how much more revenue you could bring at a CPM.Pro tip: Focusing on higher areas in the waterfall makes a larger financial impact, leading to bigger increases in ARPDAU.Let’s say you decide to add 5 instances of that network to higher CPM buckets. You can use LevelPlay’s quick A/B test to understand if this adjustment boosts your revenue - not just for this gap, but for any and all that you find. Simply compare your existing waterfall against the new waterfall with these 5 higher instances - then implement the one that drives the highest instances.Božo Janković, Head of Ad Monetization at GameBiz Consulting, uses CPM buckets "to understand at which CPMs the bidding networks are filling. From there, I can pinpoint exactly where in the waterfall to add more traditional instances - which creates more competition, especially for the bidding networks, and creates an opportunity for revenue growth."Finding new insightsYou can dig even deeper into your data by filtering by ad source. Before CPM buckets, you were limited to seeing an average eCPM for each bidding network. Maybe you knew that one ad source had an average CPM of but the distribution of impression across the waterfall was a black box. Now, we know exactly which CPMs the bidders are filling. “I find ironSource CPM buckets feature very insightful and and use it daily. It’s an easy way to identify opportunities to optimize the waterfall and earn even more revenue."

-Božo Janković, Head of Ad Monetization at GameBiz ConsultingUnderstanding your CPM distribution empowers you to not only identify your revenue sources, but also to promote revenue growth. Armed with the knowledge of which buckets some of their stronger bidding networking are performing in, some publishers actively add instances from traditional networks above those ranges. This creates better competition and also helps drive up the bids from the biddersThere’s no need for deep analysis - once you see the gaps, you can quickly understand who’s performing in the lower and higher buckets, and see exactly what’s missing. This way, you won’t miss out on any lost revenue.Learn more about CPM buckets, available exclusively to ironSource LevelPlay here.
#how #optimize #your #hybrid #waterfall

How to optimize your hybrid waterfall with CPM buckets
In-app bidding has automated most waterfall optimization, yet developers still manage multiple hybrid waterfalls, each with dozens of manual instances. Naturally, this can be timely and overwhelming to maintain, keeping you from optimizing to perfection and focusing on other opportunities to boost revenue.Rather than analyzing each individual network and checking if instances are available at each price point, breaking down your waterfall into different CPM ranges allows you to visualize the waterfall and easily identify the gaps.Here are some tips on how to use CPM buckets to better optimize your waterfall’s performance.What are CPM buckets?CPM buckets show you exactly how much revenue and how many impressions you’re getting from each CPM price range, giving you a more granular idea of how different networks are competing in the waterfall. CPM buckets are a feature of real time pivot reports, available on ironSource LevelPlay.Identifying and closing the gapsTypically in a waterfall, you can only see each ad network’s average CPM. But this keeps you from seeing ad network distribution across all price points and understanding exactly where ad networks are bidding. Bottom line - you don’t know where in the waterfall you should add a new instance.By separating CPM into buckets,you understand exactly which networks are driving impressions and revenue and which CPMs aren’t being filledNow how do you do it? As a LevelPlay client, simply use ironSource’s real time pivot reports - choose the CPM bucket filter option and sort by “average bid price.” From here, you’ll see how your revenue spreads out among CPM ranges and you’ll start to notice gaps in your bar graph. Every gap in revenue - where revenue is much lower than the neighboring CPM group - indicates an opportunity to optimize your monetization strategy. The buckets can range from small increments like to larger increments like so it’s important to compare CPM buckets of the same incremental value.Pro tip: To best set up your waterfall, create one tab with the general waterfalland make sure to look at Revenue and eCPM in the “measures” dropdown. In the “show” section, choose CPM buckets and sort by average bid price. From here, you can mark down any gaps.But where do these gaps come from? Gaps in revenue are often due to friction in the waterfall, like not enough instances, instances that aren’t working, or a waterfall setup mistake. But gaps can also be adjusted and fixed.Once you’ve found a gap, you can look at the CPM buckets around it to better understand the context. Let’s say you see a strong instance generating significant revenue in the CPM bucket right below it, in the -80 group. This instance from this specific ad network has a lot of potential, so it’s worth trying to push it to a higher CPM bucket.In fact, when you look at higher CPM buckets, you don’t see this ad network anywhere else in the waterfall - what a missed opportunity! Try adding another instance of this network higher up in the waterfall. If you’re profiting well with a -80 CPM, imagine how much more revenue you could bring at a CPM.Pro tip: Focusing on higher areas in the waterfall makes a larger financial impact, leading to bigger increases in ARPDAU.Let’s say you decide to add 5 instances of that network to higher CPM buckets. You can use LevelPlay’s quick A/B test to understand if this adjustment boosts your revenue - not just for this gap, but for any and all that you find. Simply compare your existing waterfall against the new waterfall with these 5 higher instances - then implement the one that drives the highest instances.Božo Janković, Head of Ad Monetization at GameBiz Consulting, uses CPM buckets "to understand at which CPMs the bidding networks are filling. From there, I can pinpoint exactly where in the waterfall to add more traditional instances - which creates more competition, especially for the bidding networks, and creates an opportunity for revenue growth."Finding new insightsYou can dig even deeper into your data by filtering by ad source. Before CPM buckets, you were limited to seeing an average eCPM for each bidding network. Maybe you knew that one ad source had an average CPM of but the distribution of impression across the waterfall was a black box. Now, we know exactly which CPMs the bidders are filling. “I find ironSource CPM buckets feature very insightful and and use it daily. It’s an easy way to identify opportunities to optimize the waterfall and earn even more revenue." -Božo Janković, Head of Ad Monetization at GameBiz ConsultingUnderstanding your CPM distribution empowers you to not only identify your revenue sources, but also to promote revenue growth. Armed with the knowledge of which buckets some of their stronger bidding networking are performing in, some publishers actively add instances from traditional networks above those ranges. This creates better competition and also helps drive up the bids from the biddersThere’s no need for deep analysis - once you see the gaps, you can quickly understand who’s performing in the lower and higher buckets, and see exactly what’s missing. This way, you won’t miss out on any lost revenue.Learn more about CPM buckets, available exclusively to ironSource LevelPlay here. #how #optimize #your #hybrid #waterfall

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How to optimize your hybrid waterfall with CPM buckets
In-app bidding has automated most waterfall optimization, yet developers still manage multiple hybrid waterfalls, each with dozens of manual instances. Naturally, this can be timely and overwhelming to maintain, keeping you from optimizing to perfection and focusing on other opportunities to boost revenue.Rather than analyzing each individual network and checking if instances are available at each price point, breaking down your waterfall into different CPM ranges allows you to visualize the waterfall and easily identify the gaps.Here are some tips on how to use CPM buckets to better optimize your waterfall’s performance.What are CPM buckets?CPM buckets show you exactly how much revenue and how many impressions you’re getting from each CPM price range, giving you a more granular idea of how different networks are competing in the waterfall. CPM buckets are a feature of real time pivot reports, available on ironSource LevelPlay.Identifying and closing the gapsTypically in a waterfall, you can only see each ad network’s average CPM. But this keeps you from seeing ad network distribution across all price points and understanding exactly where ad networks are bidding. Bottom line - you don’t know where in the waterfall you should add a new instance.By separating CPM into buckets, (for example, seeing all the ad networks generating a CPM of $10-$20) you understand exactly which networks are driving impressions and revenue and which CPMs aren’t being filledNow how do you do it? As a LevelPlay client, simply use ironSource’s real time pivot reports - choose the CPM bucket filter option and sort by “average bid price.” From here, you’ll see how your revenue spreads out among CPM ranges and you’ll start to notice gaps in your bar graph. Every gap in revenue - where revenue is much lower than the neighboring CPM group - indicates an opportunity to optimize your monetization strategy. The buckets can range from small increments like $1 to larger increments like $10, so it’s important to compare CPM buckets of the same incremental value.Pro tip: To best set up your waterfall, create one tab with the general waterfall (filter app, OS, Ad unit, geo/geos from a specific group) and make sure to look at Revenue and eCPM in the “measures” dropdown. In the “show” section, choose CPM buckets and sort by average bid price. From here, you can mark down any gaps.But where do these gaps come from? Gaps in revenue are often due to friction in the waterfall, like not enough instances, instances that aren’t working, or a waterfall setup mistake. But gaps can also be adjusted and fixed.Once you’ve found a gap, you can look at the CPM buckets around it to better understand the context. Let’s say you see a strong instance generating significant revenue in the CPM bucket right below it, in the $70-80 group. This instance from this specific ad network has a lot of potential, so it’s worth trying to push it to a higher CPM bucket.In fact, when you look at higher CPM buckets, you don’t see this ad network anywhere else in the waterfall - what a missed opportunity! Try adding another instance of this network higher up in the waterfall. If you’re profiting well with a $70-80 CPM, imagine how much more revenue you could bring at a $150 CPM.Pro tip: Focusing on higher areas in the waterfall makes a larger financial impact, leading to bigger increases in ARPDAU.Let’s say you decide to add 5 instances of that network to higher CPM buckets. You can use LevelPlay’s quick A/B test to understand if this adjustment boosts your revenue - not just for this gap, but for any and all that you find. Simply compare your existing waterfall against the new waterfall with these 5 higher instances - then implement the one that drives the highest instances.Božo Janković, Head of Ad Monetization at GameBiz Consulting, uses CPM buckets "to understand at which CPMs the bidding networks are filling. From there, I can pinpoint exactly where in the waterfall to add more traditional instances - which creates more competition, especially for the bidding networks, and creates an opportunity for revenue growth."Finding new insightsYou can dig even deeper into your data by filtering by ad source. Before CPM buckets, you were limited to seeing an average eCPM for each bidding network. Maybe you knew that one ad source had an average CPM of $50, but the distribution of impression across the waterfall was a black box. Now, we know exactly which CPMs the bidders are filling. “I find ironSource CPM buckets feature very insightful and and use it daily. It’s an easy way to identify opportunities to optimize the waterfall and earn even more revenue." -Božo Janković, Head of Ad Monetization at GameBiz ConsultingUnderstanding your CPM distribution empowers you to not only identify your revenue sources, but also to promote revenue growth. Armed with the knowledge of which buckets some of their stronger bidding networking are performing in, some publishers actively add instances from traditional networks above those ranges. This creates better competition and also helps drive up the bids from the biddersThere’s no need for deep analysis - once you see the gaps, you can quickly understand who’s performing in the lower and higher buckets, and see exactly what’s missing. This way, you won’t miss out on any lost revenue.Learn more about CPM buckets, available exclusively to ironSource LevelPlay here.

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2025-06-15 06:54:50 -

Sienna Net-Zero Home / billionBricks

Sienna Net-Zero Home / billionBricksSave this picture!© Ron Mendoza , Mark Twain C , BB teamHouses, Sustainability•Quezon City, Philippines

Architects:
billionBricks
Area
Area of this architecture project

Area:
45 m²

Year
Completion year of this architecture project

Year:

2024

Photographs

Photographs:Ron Mendoza , Mark Twain C , BB teamMore SpecsLess Specs
this picture!
Text description provided by the architects. Built to address homelessness and climate change, the Sienna Net-Zero Home is a self-sustaining, solar-powered, cost-efficient, and compact housing solution. This climate-responsive and affordable home, located in Quezon City, Philippines, represents a revolutionary vision for social housing through its integration of thoughtful design, sustainability, and energy self-sufficiency.this picture!this picture!this picture!Designed with the unique tropical climate of the Philippines in mind, the Sienna Home prioritizes natural ventilation, passive cooling, and rainwater management to enhance indoor comfort and reduce reliance on artificial cooling systems. The compact 4.5m x 5.1m floor plan has been meticulously optimized for functionality, offering a flexible layout that grows and adapts to the families living in them.this picture!this picture!this picture!A key architectural feature is BillionBricks' innovative Powershade technology - an advanced solar roofing system that serves multiple purposes. Beyond generating clean, renewable energy, it acts as a protective heat barrier, reducing indoor temperatures and improving thermal comfort. Unlike conventional solar panels, Powershade seamlessly integrates with the home's structure, providing reliable energy generation while doubling as a durable roof. This makes the Sienna Home energy-positive, meaning it produces more electricity than it consumes, lowering utility costs and promoting long-term energy independence. Excess power can also be stored or sold back to the grid, creating an additional financial benefit for homeowners.this picture!When multiple Sienna Homes are built together, the innovative PowerShade roofing solution transcends its role as an individual energy source and transforms into a utility-scale solar rooftop farm, capable of powering essential community facilities and generating additional income. This shared energy infrastructure fosters a sense of collective empowerment, enabling residents to actively participate in a sustainable and financially rewarding energy ecosystem.this picture!this picture!The Sienna Home is built using lightweight prefabricated components, allowing for rapid on-site assembly while maintaining durability and structural integrity. This modular approach enables scalability, making it an ideal prototype for large-scale, cost-effective housing developments. The design also allows for future expansions, giving homeowners the flexibility to adapt their living spaces over time.this picture!Adhering to BP 220 social housing regulations, the unit features a 3-meter front setback and a 2-meter rear setback, ensuring proper ventilation, safety, and community-friendly spaces. Additionally, corner units include a 1.5-meter offset, enhancing privacy and accessibility within neighborhood layouts. Beyond providing a single-family residence, the Sienna House is designed to function within a larger sustainable community model, integrating shared green spaces, pedestrian pathways, and decentralized utilities. By promoting energy independence and environmental resilience, the project sets a new precedent for affordable yet high-quality housing solutions in rapidly urbanizing regions.this picture!The Sienna Home in Quezon City serves as a blueprint for future developments, proving that low-cost housing can be both architecturally compelling and socially transformative. By rethinking traditional housing models, BillionBricks is pioneering a future where affordability and sustainability are seamlessly integrated.

Project gallerySee allShow less
About this officebillionBricksOffice•••
Published on June 15, 2025Cite: "Sienna Net-Zero Home / billionBricks" 14 Jun 2025. ArchDaily. Accessed . < ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否
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Sienna Net-Zero Home / billionBricks
Sienna Net-Zero Home / billionBricksSave this picture!© Ron Mendoza , Mark Twain C , BB teamHouses, Sustainability•Quezon City, Philippines Architects: billionBricks Area Area of this architecture project Area: 45 m² Year Completion year of this architecture project Year: 2024 Photographs Photographs:Ron Mendoza , Mark Twain C , BB teamMore SpecsLess Specs this picture! Text description provided by the architects. Built to address homelessness and climate change, the Sienna Net-Zero Home is a self-sustaining, solar-powered, cost-efficient, and compact housing solution. This climate-responsive and affordable home, located in Quezon City, Philippines, represents a revolutionary vision for social housing through its integration of thoughtful design, sustainability, and energy self-sufficiency.this picture!this picture!this picture!Designed with the unique tropical climate of the Philippines in mind, the Sienna Home prioritizes natural ventilation, passive cooling, and rainwater management to enhance indoor comfort and reduce reliance on artificial cooling systems. The compact 4.5m x 5.1m floor plan has been meticulously optimized for functionality, offering a flexible layout that grows and adapts to the families living in them.this picture!this picture!this picture!A key architectural feature is BillionBricks' innovative Powershade technology - an advanced solar roofing system that serves multiple purposes. Beyond generating clean, renewable energy, it acts as a protective heat barrier, reducing indoor temperatures and improving thermal comfort. Unlike conventional solar panels, Powershade seamlessly integrates with the home's structure, providing reliable energy generation while doubling as a durable roof. This makes the Sienna Home energy-positive, meaning it produces more electricity than it consumes, lowering utility costs and promoting long-term energy independence. Excess power can also be stored or sold back to the grid, creating an additional financial benefit for homeowners.this picture!When multiple Sienna Homes are built together, the innovative PowerShade roofing solution transcends its role as an individual energy source and transforms into a utility-scale solar rooftop farm, capable of powering essential community facilities and generating additional income. This shared energy infrastructure fosters a sense of collective empowerment, enabling residents to actively participate in a sustainable and financially rewarding energy ecosystem.this picture!this picture!The Sienna Home is built using lightweight prefabricated components, allowing for rapid on-site assembly while maintaining durability and structural integrity. This modular approach enables scalability, making it an ideal prototype for large-scale, cost-effective housing developments. The design also allows for future expansions, giving homeowners the flexibility to adapt their living spaces over time.this picture!Adhering to BP 220 social housing regulations, the unit features a 3-meter front setback and a 2-meter rear setback, ensuring proper ventilation, safety, and community-friendly spaces. Additionally, corner units include a 1.5-meter offset, enhancing privacy and accessibility within neighborhood layouts. Beyond providing a single-family residence, the Sienna House is designed to function within a larger sustainable community model, integrating shared green spaces, pedestrian pathways, and decentralized utilities. By promoting energy independence and environmental resilience, the project sets a new precedent for affordable yet high-quality housing solutions in rapidly urbanizing regions.this picture!The Sienna Home in Quezon City serves as a blueprint for future developments, proving that low-cost housing can be both architecturally compelling and socially transformative. By rethinking traditional housing models, BillionBricks is pioneering a future where affordability and sustainability are seamlessly integrated. Project gallerySee allShow less About this officebillionBricksOffice••• Published on June 15, 2025Cite: "Sienna Net-Zero Home / billionBricks" 14 Jun 2025. ArchDaily. Accessed . < ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否 You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream #sienna #netzero #home #billionbricks

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Sienna Net-Zero Home / billionBricks
Sienna Net-Zero Home / billionBricksSave this picture!© Ron Mendoza , Mark Twain C , BB teamHouses, Sustainability•Quezon City, Philippines Architects: billionBricks Area Area of this architecture project Area: 45 m² Year Completion year of this architecture project Year: 2024 Photographs Photographs:Ron Mendoza , Mark Twain C , BB teamMore SpecsLess Specs Save this picture! Text description provided by the architects. Built to address homelessness and climate change, the Sienna Net-Zero Home is a self-sustaining, solar-powered, cost-efficient, and compact housing solution. This climate-responsive and affordable home, located in Quezon City, Philippines, represents a revolutionary vision for social housing through its integration of thoughtful design, sustainability, and energy self-sufficiency.Save this picture!Save this picture!Save this picture!Designed with the unique tropical climate of the Philippines in mind, the Sienna Home prioritizes natural ventilation, passive cooling, and rainwater management to enhance indoor comfort and reduce reliance on artificial cooling systems. The compact 4.5m x 5.1m floor plan has been meticulously optimized for functionality, offering a flexible layout that grows and adapts to the families living in them.Save this picture!Save this picture!Save this picture!A key architectural feature is BillionBricks' innovative Powershade technology - an advanced solar roofing system that serves multiple purposes. Beyond generating clean, renewable energy, it acts as a protective heat barrier, reducing indoor temperatures and improving thermal comfort. Unlike conventional solar panels, Powershade seamlessly integrates with the home's structure, providing reliable energy generation while doubling as a durable roof. This makes the Sienna Home energy-positive, meaning it produces more electricity than it consumes, lowering utility costs and promoting long-term energy independence. Excess power can also be stored or sold back to the grid, creating an additional financial benefit for homeowners.Save this picture!When multiple Sienna Homes are built together, the innovative PowerShade roofing solution transcends its role as an individual energy source and transforms into a utility-scale solar rooftop farm, capable of powering essential community facilities and generating additional income. This shared energy infrastructure fosters a sense of collective empowerment, enabling residents to actively participate in a sustainable and financially rewarding energy ecosystem.Save this picture!Save this picture!The Sienna Home is built using lightweight prefabricated components, allowing for rapid on-site assembly while maintaining durability and structural integrity. This modular approach enables scalability, making it an ideal prototype for large-scale, cost-effective housing developments. The design also allows for future expansions, giving homeowners the flexibility to adapt their living spaces over time.Save this picture!Adhering to BP 220 social housing regulations, the unit features a 3-meter front setback and a 2-meter rear setback, ensuring proper ventilation, safety, and community-friendly spaces. Additionally, corner units include a 1.5-meter offset, enhancing privacy and accessibility within neighborhood layouts. Beyond providing a single-family residence, the Sienna House is designed to function within a larger sustainable community model, integrating shared green spaces, pedestrian pathways, and decentralized utilities. By promoting energy independence and environmental resilience, the project sets a new precedent for affordable yet high-quality housing solutions in rapidly urbanizing regions.Save this picture!The Sienna Home in Quezon City serves as a blueprint for future developments, proving that low-cost housing can be both architecturally compelling and socially transformative. By rethinking traditional housing models, BillionBricks is pioneering a future where affordability and sustainability are seamlessly integrated. Project gallerySee allShow less About this officebillionBricksOffice••• Published on June 15, 2025Cite: "Sienna Net-Zero Home / billionBricks" 14 Jun 2025. ArchDaily. Accessed . <https://www.archdaily.com/1031072/sienna-billionbricks&gt ISSN 0719-8884Save世界上最受欢迎的建筑网站现已推出你的母语版本!想浏览ArchDaily中国吗?是否 You've started following your first account!Did you know?You'll now receive updates based on what you follow! Personalize your stream and start following your favorite authors, offices and users.Go to my stream

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2025-06-15 06:54:05 -

STOP 3D MODELING!! ASK YVO3D INSTEAD!! 9 Minutes | 4K | AI AAA Models!!!

Sign up for the YVO3D waitlist and get early access here: /

Are you tired of spending hours, even days, on 3D modeling? Prepare to have your mind blown! In this video, I'm introducing YVO3D, the groundbreaking AI tool that's set to revolutionize how we create 3D models forever!

Seriously, this isn't a drill. YVO3D can generate stunning, high-quality 4K 3D models in as little as 9 minutes – models so detailed and realistic, they're ready for AAA game production or professional rendering, with no extra software or complex steps.

In this video, you'll see:

The Shocking Speed: Watch me generate a complex 4K model in minutes right before your eyes.
Insane Quality: Get a close look at the unparalleled detail and realism of the AI-generated textures and meshes.
Effortless Workflow: A quick tour of YVO3D's incredibly intuitive UI – just type a prompt or upload an image, and let the AI do the rest.
Seamless Unreal Engine Integration: See how easily these GLB models import into UE5, ready for your projects.
Future-Proofing Your Workflow: I'll share an exciting announcement about YVO3D's upcoming native integrations with major 3D software like Blender, Unreal Engine, and Unity!
This isn't just a new tool; it's a new paradigm for 3D creation. Stop modeling and start generating! Join the waitlist now while there's still space to be among the first to experience the future of 3D.

Scene Used in This Video:

Mario Bava Sleeps In a Little Later Than He Expected To by Chris Zabriskie is licensed under a Creative Commons Attribution 4.0 licence. /
#stop #modeling #ask #yvo3d #instead

STOP 3D MODELING!! ASK YVO3D INSTEAD!! 9 Minutes | 4K | AI AAA Models!!!
Sign up for the YVO3D waitlist and get early access here: / Are you tired of spending hours, even days, on 3D modeling? Prepare to have your mind blown! In this video, I'm introducing YVO3D, the groundbreaking AI tool that's set to revolutionize how we create 3D models forever! Seriously, this isn't a drill. YVO3D can generate stunning, high-quality 4K 3D models in as little as 9 minutes – models so detailed and realistic, they're ready for AAA game production or professional rendering, with no extra software or complex steps. In this video, you'll see: The Shocking Speed: Watch me generate a complex 4K model in minutes right before your eyes. Insane Quality: Get a close look at the unparalleled detail and realism of the AI-generated textures and meshes. Effortless Workflow: A quick tour of YVO3D's incredibly intuitive UI – just type a prompt or upload an image, and let the AI do the rest. Seamless Unreal Engine Integration: See how easily these GLB models import into UE5, ready for your projects. Future-Proofing Your Workflow: I'll share an exciting announcement about YVO3D's upcoming native integrations with major 3D software like Blender, Unreal Engine, and Unity! This isn't just a new tool; it's a new paradigm for 3D creation. Stop modeling and start generating! Join the waitlist now while there's still space to be among the first to experience the future of 3D. 🧰 Scene Used in This Video: Mario Bava Sleeps In a Little Later Than He Expected To by Chris Zabriskie is licensed under a Creative Commons Attribution 4.0 licence. / #stop #modeling #ask #yvo3d #instead

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STOP 3D MODELING!! ASK YVO3D INSTEAD!! 9 Minutes | 4K | AI AAA Models!!!
Sign up for the YVO3D waitlist and get early access here: https://yvo3d.com/ Are you tired of spending hours, even days, on 3D modeling? Prepare to have your mind blown! In this video, I'm introducing YVO3D, the groundbreaking AI tool that's set to revolutionize how we create 3D models forever! Seriously, this isn't a drill. YVO3D can generate stunning, high-quality 4K 3D models in as little as 9 minutes – models so detailed and realistic, they're ready for AAA game production or professional rendering, with no extra software or complex steps. In this video, you'll see: The Shocking Speed: Watch me generate a complex 4K model in minutes right before your eyes. Insane Quality: Get a close look at the unparalleled detail and realism of the AI-generated textures and meshes. Effortless Workflow: A quick tour of YVO3D's incredibly intuitive UI – just type a prompt or upload an image, and let the AI do the rest. Seamless Unreal Engine Integration: See how easily these GLB models import into UE5, ready for your projects. Future-Proofing Your Workflow: I'll share an exciting announcement about YVO3D's upcoming native integrations with major 3D software like Blender, Unreal Engine, and Unity! This isn't just a new tool; it's a new paradigm for 3D creation. Stop modeling and start generating! Join the waitlist now while there's still space to be among the first to experience the future of 3D. 🧰 Scene Used in This Video: https://www.fab.com/listings/88dd113a-865c-4d61-bc15-49754b22fa04 Mario Bava Sleeps In a Little Later Than He Expected To by Chris Zabriskie is licensed under a Creative Commons Attribution 4.0 licence. https://creativecommons.org/licenses/by/4.0/

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