• European Robot Makers Adopt NVIDIA Isaac, Omniverse and Halos to Develop Safe, Physical AI-Driven Robot Fleets

    In the face of growing labor shortages and need for sustainability, European manufacturers are racing to reinvent their processes to become software-defined and AI-driven.
    To achieve this, robot developers and industrial digitalization solution providers are working with NVIDIA to build safe, AI-driven robots and industrial technologies to drive modern, sustainable manufacturing.
    At NVIDIA GTC Paris at VivaTech, Europe’s leading robotics companies including Agile Robots, Extend Robotics, Humanoid, idealworks, Neura Robotics, SICK, Universal Robots, Vorwerk and Wandelbots are showcasing their latest AI-driven robots and automation breakthroughs, all accelerated by NVIDIA technologies. In addition, NVIDIA is releasing new models and tools to support the entire robotics ecosystem.
    NVIDIA Releases Tools for Accelerating Robot Development and Safety
    NVIDIA Isaac GR00T N1.5, an open foundation model for humanoid robot reasoning and skills, is now available for download on Hugging Face. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. The NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 open-source robotics simulation and learning frameworks, optimized for NVIDIA RTX PRO 6000 workstations, are available on GitHub for developer preview.
    In addition, NVIDIA announced that NVIDIA Halos — a full-stack, comprehensive safety system that unifies hardware architecture, AI models, software, tools and services — now expands to robotics, promoting safety across the entire development lifecycle of AI-driven robots.
    The NVIDIA Halos AI Systems Inspection Lab has earned accreditation from the ANSI National Accreditation Boardto perform inspections across functional safety for robotics, in addition to automotive vehicles.
    “NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines — from automotive to robotics — can meet the highest benchmarks for functional safety,” said R. Douglas Leonard Jr., executive director of ANAB.
    Arcbest, Advantech, Bluewhite, Boston Dynamics, FORT, Inxpect, KION, NexCobot — a NEXCOM company, and Synapticon are among the first robotics companies to join the Halos Inspection Lab, ensuring their products meet NVIDIA safety and cybersecurity requirements.
    To support robotics leaders in strengthening safety across the entire development lifecycle of AI-driven robots, Halos will now provide:

    Safety extension packages for the NVIDIA IGX platform, enabling manufacturers to easily program safety functions into their robots, supported by TÜV Rheinland’s inspection of NVIDIA IGX.
    A robotic safety platform, which includes IGX and NVIDIA Holoscan Sensor Bridge for a unified approach to designing sensor-to-compute architecture with built-in AI safety.
    An outside-in safety AI inspector — an AI-powered agent for monitoring robot operations, helping improve worker safety.

    Europe’s Robotics Ecosystem Builds on NVIDIA’s Three Computers
    Europe’s leading robotics developers and solution providers are integrating the NVIDIA Isaac robotics platform to train, simulate and deploy robots across different embodiments.
    Agile Robots is post-training the GR00T N1 model in Isaac Lab to train its dual-arm manipulator robots, which run on NVIDIA Jetson hardware, to execute a variety of tasks in industrial environments.
    Meanwhile, idealworks has adopted the Mega NVIDIA Omniverse Blueprint for robotic fleet simulation to extend the blueprint’s capabilities to humanoids. Building on the VDA 5050 framework, idealworks contributes to the development of guidance that supports tasks uniquely enabled by humanoid robots, such as picking, moving and placing objects.
    Neura Robotics is integrating NVIDIA Isaac to further enhance its robot development workflows. The company is using GR00T-Mimic to post-train the Isaac GR00T N1 robot foundation model for its service robot MiPA. Neura is also collaborating with SAP and NVIDIA to integrate SAP’s Joule agents with its robots, using the Mega NVIDIA Omniverse Blueprint to simulate and refine robot behavior in complex, realistic operational scenarios before deployment.
    Vorwerk is using NVIDIA technologies to power its AI-driven collaborative robots. The company is post-training GR00T N1 models in Isaac Lab with its custom synthetic data pipeline, which is built on Isaac GR00T-Mimic and powered by the NVIDIA Omniverse platform. The enhanced models are then deployed on NVIDIA Jetson AGX, Jetson Orin or Jetson Thor modules for advanced, real-time home robotics.
    Humanoid is using NVIDIA’s full robotics stack, including Isaac Sim and Isaac Lab, to cut its prototyping time down by six weeks. The company is training its vision language action models on NVIDIA DGX B200 systems to boost the cognitive abilities of its robots, allowing them to operate autonomously in complex environments using Jetson Thor onboard computing.
    Universal Robots is introducing UR15, its fastest collaborative robot yet, to the European market. Using UR’s AI Accelerator — developed on NVIDIA Isaac’s CUDA-accelerated libraries and AI models, as well as NVIDIA Jetson AGX Orin — manufacturers can build AI applications to embed intelligence into the company’s new cobots.
    Wandelbots is showcasing its NOVA Operating System, now integrated with Omniverse, to simulate, validate and optimize robotic behaviors virtually before deploying them to physical robots. Wandelbots also announced a collaboration with EY and EDAG to offer manufacturers a scalable automation platform on Omniverse that speeds up the transition from proof of concept to full-scale deployment.
    Extend Robotics is using the Isaac GR00T platform to enable customers to control and train robots for industrial tasks like visual inspection and handling radioactive materials. The company’s Advanced Mechanics Assistance System lets users collect demonstration data and generate diverse synthetic datasets with NVIDIA GR00T-Mimic and GR00T-Gen to train the GR00T N1 foundation model.
    SICK is enhancing its autonomous perception solutions by integrating new certified sensor models — as well as 2D and 3D lidars, safety scanners and cameras — into NVIDIA Isaac Sim. This enables engineers to virtually design, test and validate machines using SICK’s sensing models within Omniverse, supporting processes spanning product development to large-scale robotic fleet management.
    Toyota Material Handling Europe is working with SoftServe to simulate its autonomous mobile robots working alongside human workers, using the Mega NVIDIA Omniverse Blueprint. Toyota Material Handling Europe is testing and simulating a multitude of traffic scenarios — allowing the company to refine its AI algorithms before real-world deployment.
    NVIDIA’s partner ecosystem is enabling European industries to tap into intelligent, AI-powered robotics. By harnessing advanced simulation, digital twins and generative AI, manufacturers are rapidly developing and deploying safe, adaptable robot fleets that address labor shortages, boost sustainability and drive operational efficiency.
    Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.
    See notice regarding software product information.
    #european #robot #makers #adopt #nvidia
    European Robot Makers Adopt NVIDIA Isaac, Omniverse and Halos to Develop Safe, Physical AI-Driven Robot Fleets
    In the face of growing labor shortages and need for sustainability, European manufacturers are racing to reinvent their processes to become software-defined and AI-driven. To achieve this, robot developers and industrial digitalization solution providers are working with NVIDIA to build safe, AI-driven robots and industrial technologies to drive modern, sustainable manufacturing. At NVIDIA GTC Paris at VivaTech, Europe’s leading robotics companies including Agile Robots, Extend Robotics, Humanoid, idealworks, Neura Robotics, SICK, Universal Robots, Vorwerk and Wandelbots are showcasing their latest AI-driven robots and automation breakthroughs, all accelerated by NVIDIA technologies. In addition, NVIDIA is releasing new models and tools to support the entire robotics ecosystem. NVIDIA Releases Tools for Accelerating Robot Development and Safety NVIDIA Isaac GR00T N1.5, an open foundation model for humanoid robot reasoning and skills, is now available for download on Hugging Face. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. The NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 open-source robotics simulation and learning frameworks, optimized for NVIDIA RTX PRO 6000 workstations, are available on GitHub for developer preview. In addition, NVIDIA announced that NVIDIA Halos — a full-stack, comprehensive safety system that unifies hardware architecture, AI models, software, tools and services — now expands to robotics, promoting safety across the entire development lifecycle of AI-driven robots. The NVIDIA Halos AI Systems Inspection Lab has earned accreditation from the ANSI National Accreditation Boardto perform inspections across functional safety for robotics, in addition to automotive vehicles. “NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines — from automotive to robotics — can meet the highest benchmarks for functional safety,” said R. Douglas Leonard Jr., executive director of ANAB. Arcbest, Advantech, Bluewhite, Boston Dynamics, FORT, Inxpect, KION, NexCobot — a NEXCOM company, and Synapticon are among the first robotics companies to join the Halos Inspection Lab, ensuring their products meet NVIDIA safety and cybersecurity requirements. To support robotics leaders in strengthening safety across the entire development lifecycle of AI-driven robots, Halos will now provide: Safety extension packages for the NVIDIA IGX platform, enabling manufacturers to easily program safety functions into their robots, supported by TÜV Rheinland’s inspection of NVIDIA IGX. A robotic safety platform, which includes IGX and NVIDIA Holoscan Sensor Bridge for a unified approach to designing sensor-to-compute architecture with built-in AI safety. An outside-in safety AI inspector — an AI-powered agent for monitoring robot operations, helping improve worker safety. Europe’s Robotics Ecosystem Builds on NVIDIA’s Three Computers Europe’s leading robotics developers and solution providers are integrating the NVIDIA Isaac robotics platform to train, simulate and deploy robots across different embodiments. Agile Robots is post-training the GR00T N1 model in Isaac Lab to train its dual-arm manipulator robots, which run on NVIDIA Jetson hardware, to execute a variety of tasks in industrial environments. Meanwhile, idealworks has adopted the Mega NVIDIA Omniverse Blueprint for robotic fleet simulation to extend the blueprint’s capabilities to humanoids. Building on the VDA 5050 framework, idealworks contributes to the development of guidance that supports tasks uniquely enabled by humanoid robots, such as picking, moving and placing objects. Neura Robotics is integrating NVIDIA Isaac to further enhance its robot development workflows. The company is using GR00T-Mimic to post-train the Isaac GR00T N1 robot foundation model for its service robot MiPA. Neura is also collaborating with SAP and NVIDIA to integrate SAP’s Joule agents with its robots, using the Mega NVIDIA Omniverse Blueprint to simulate and refine robot behavior in complex, realistic operational scenarios before deployment. Vorwerk is using NVIDIA technologies to power its AI-driven collaborative robots. The company is post-training GR00T N1 models in Isaac Lab with its custom synthetic data pipeline, which is built on Isaac GR00T-Mimic and powered by the NVIDIA Omniverse platform. The enhanced models are then deployed on NVIDIA Jetson AGX, Jetson Orin or Jetson Thor modules for advanced, real-time home robotics. Humanoid is using NVIDIA’s full robotics stack, including Isaac Sim and Isaac Lab, to cut its prototyping time down by six weeks. The company is training its vision language action models on NVIDIA DGX B200 systems to boost the cognitive abilities of its robots, allowing them to operate autonomously in complex environments using Jetson Thor onboard computing. Universal Robots is introducing UR15, its fastest collaborative robot yet, to the European market. Using UR’s AI Accelerator — developed on NVIDIA Isaac’s CUDA-accelerated libraries and AI models, as well as NVIDIA Jetson AGX Orin — manufacturers can build AI applications to embed intelligence into the company’s new cobots. Wandelbots is showcasing its NOVA Operating System, now integrated with Omniverse, to simulate, validate and optimize robotic behaviors virtually before deploying them to physical robots. Wandelbots also announced a collaboration with EY and EDAG to offer manufacturers a scalable automation platform on Omniverse that speeds up the transition from proof of concept to full-scale deployment. Extend Robotics is using the Isaac GR00T platform to enable customers to control and train robots for industrial tasks like visual inspection and handling radioactive materials. The company’s Advanced Mechanics Assistance System lets users collect demonstration data and generate diverse synthetic datasets with NVIDIA GR00T-Mimic and GR00T-Gen to train the GR00T N1 foundation model. SICK is enhancing its autonomous perception solutions by integrating new certified sensor models — as well as 2D and 3D lidars, safety scanners and cameras — into NVIDIA Isaac Sim. This enables engineers to virtually design, test and validate machines using SICK’s sensing models within Omniverse, supporting processes spanning product development to large-scale robotic fleet management. Toyota Material Handling Europe is working with SoftServe to simulate its autonomous mobile robots working alongside human workers, using the Mega NVIDIA Omniverse Blueprint. Toyota Material Handling Europe is testing and simulating a multitude of traffic scenarios — allowing the company to refine its AI algorithms before real-world deployment. NVIDIA’s partner ecosystem is enabling European industries to tap into intelligent, AI-powered robotics. By harnessing advanced simulation, digital twins and generative AI, manufacturers are rapidly developing and deploying safe, adaptable robot fleets that address labor shortages, boost sustainability and drive operational efficiency. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. See notice regarding software product information. #european #robot #makers #adopt #nvidia
    BLOGS.NVIDIA.COM
    European Robot Makers Adopt NVIDIA Isaac, Omniverse and Halos to Develop Safe, Physical AI-Driven Robot Fleets
    In the face of growing labor shortages and need for sustainability, European manufacturers are racing to reinvent their processes to become software-defined and AI-driven. To achieve this, robot developers and industrial digitalization solution providers are working with NVIDIA to build safe, AI-driven robots and industrial technologies to drive modern, sustainable manufacturing. At NVIDIA GTC Paris at VivaTech, Europe’s leading robotics companies including Agile Robots, Extend Robotics, Humanoid, idealworks, Neura Robotics, SICK, Universal Robots, Vorwerk and Wandelbots are showcasing their latest AI-driven robots and automation breakthroughs, all accelerated by NVIDIA technologies. In addition, NVIDIA is releasing new models and tools to support the entire robotics ecosystem. NVIDIA Releases Tools for Accelerating Robot Development and Safety NVIDIA Isaac GR00T N1.5, an open foundation model for humanoid robot reasoning and skills, is now available for download on Hugging Face. This update enhances the model’s adaptability and ability to follow instructions, significantly improving its performance in material handling and manufacturing tasks. The NVIDIA Isaac Sim 5.0 and Isaac Lab 2.2 open-source robotics simulation and learning frameworks, optimized for NVIDIA RTX PRO 6000 workstations, are available on GitHub for developer preview. In addition, NVIDIA announced that NVIDIA Halos — a full-stack, comprehensive safety system that unifies hardware architecture, AI models, software, tools and services — now expands to robotics, promoting safety across the entire development lifecycle of AI-driven robots. The NVIDIA Halos AI Systems Inspection Lab has earned accreditation from the ANSI National Accreditation Board (ANAB) to perform inspections across functional safety for robotics, in addition to automotive vehicles. “NVIDIA’s latest evaluation with ANAB verifies the demonstration of competence and compliance with internationally recognized standards, helping ensure that developers of autonomous machines — from automotive to robotics — can meet the highest benchmarks for functional safety,” said R. Douglas Leonard Jr., executive director of ANAB. Arcbest, Advantech, Bluewhite, Boston Dynamics, FORT, Inxpect, KION, NexCobot — a NEXCOM company, and Synapticon are among the first robotics companies to join the Halos Inspection Lab, ensuring their products meet NVIDIA safety and cybersecurity requirements. To support robotics leaders in strengthening safety across the entire development lifecycle of AI-driven robots, Halos will now provide: Safety extension packages for the NVIDIA IGX platform, enabling manufacturers to easily program safety functions into their robots, supported by TÜV Rheinland’s inspection of NVIDIA IGX. A robotic safety platform, which includes IGX and NVIDIA Holoscan Sensor Bridge for a unified approach to designing sensor-to-compute architecture with built-in AI safety. An outside-in safety AI inspector — an AI-powered agent for monitoring robot operations, helping improve worker safety. Europe’s Robotics Ecosystem Builds on NVIDIA’s Three Computers Europe’s leading robotics developers and solution providers are integrating the NVIDIA Isaac robotics platform to train, simulate and deploy robots across different embodiments. Agile Robots is post-training the GR00T N1 model in Isaac Lab to train its dual-arm manipulator robots, which run on NVIDIA Jetson hardware, to execute a variety of tasks in industrial environments. Meanwhile, idealworks has adopted the Mega NVIDIA Omniverse Blueprint for robotic fleet simulation to extend the blueprint’s capabilities to humanoids. Building on the VDA 5050 framework, idealworks contributes to the development of guidance that supports tasks uniquely enabled by humanoid robots, such as picking, moving and placing objects. Neura Robotics is integrating NVIDIA Isaac to further enhance its robot development workflows. The company is using GR00T-Mimic to post-train the Isaac GR00T N1 robot foundation model for its service robot MiPA. Neura is also collaborating with SAP and NVIDIA to integrate SAP’s Joule agents with its robots, using the Mega NVIDIA Omniverse Blueprint to simulate and refine robot behavior in complex, realistic operational scenarios before deployment. Vorwerk is using NVIDIA technologies to power its AI-driven collaborative robots. The company is post-training GR00T N1 models in Isaac Lab with its custom synthetic data pipeline, which is built on Isaac GR00T-Mimic and powered by the NVIDIA Omniverse platform. The enhanced models are then deployed on NVIDIA Jetson AGX, Jetson Orin or Jetson Thor modules for advanced, real-time home robotics. Humanoid is using NVIDIA’s full robotics stack, including Isaac Sim and Isaac Lab, to cut its prototyping time down by six weeks. The company is training its vision language action models on NVIDIA DGX B200 systems to boost the cognitive abilities of its robots, allowing them to operate autonomously in complex environments using Jetson Thor onboard computing. Universal Robots is introducing UR15, its fastest collaborative robot yet, to the European market. Using UR’s AI Accelerator — developed on NVIDIA Isaac’s CUDA-accelerated libraries and AI models, as well as NVIDIA Jetson AGX Orin — manufacturers can build AI applications to embed intelligence into the company’s new cobots. Wandelbots is showcasing its NOVA Operating System, now integrated with Omniverse, to simulate, validate and optimize robotic behaviors virtually before deploying them to physical robots. Wandelbots also announced a collaboration with EY and EDAG to offer manufacturers a scalable automation platform on Omniverse that speeds up the transition from proof of concept to full-scale deployment. Extend Robotics is using the Isaac GR00T platform to enable customers to control and train robots for industrial tasks like visual inspection and handling radioactive materials. The company’s Advanced Mechanics Assistance System lets users collect demonstration data and generate diverse synthetic datasets with NVIDIA GR00T-Mimic and GR00T-Gen to train the GR00T N1 foundation model. SICK is enhancing its autonomous perception solutions by integrating new certified sensor models — as well as 2D and 3D lidars, safety scanners and cameras — into NVIDIA Isaac Sim. This enables engineers to virtually design, test and validate machines using SICK’s sensing models within Omniverse, supporting processes spanning product development to large-scale robotic fleet management. Toyota Material Handling Europe is working with SoftServe to simulate its autonomous mobile robots working alongside human workers, using the Mega NVIDIA Omniverse Blueprint. Toyota Material Handling Europe is testing and simulating a multitude of traffic scenarios — allowing the company to refine its AI algorithms before real-world deployment. NVIDIA’s partner ecosystem is enabling European industries to tap into intelligent, AI-powered robotics. By harnessing advanced simulation, digital twins and generative AI, manufacturers are rapidly developing and deploying safe, adaptable robot fleets that address labor shortages, boost sustainability and drive operational efficiency. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. See notice regarding software product information.
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  • Retail Reboot: Major Global Brands Transform End-to-End Operations With NVIDIA

    AI is packing and shipping efficiency for the retail and consumer packaged goodsindustries, with a majority of surveyed companies in the space reporting the technology is increasing revenue and reducing operational costs.
    Global brands are reimagining every facet of their businesses with AI, from how products are designed and manufactured to how they’re marketed, shipped and experienced in-store and online.
    At NVIDIA GTC Paris at VivaTech, industry leaders including L’Oréal, LVMH and Nestlé shared how they’re using tools like AI agents and physical AI — powered by NVIDIA AI and simulation technologies — across every step of the product lifecycle to enhance operations and experiences for partners, customers and employees.
    3D Digital Twins and AI Transform Marketing, Advertising and Product Design
    The meeting of generative AI and 3D product digital twins results in unlimited creative potential.
    Nestlé, the world’s largest food and beverage company, today announced a collaboration with NVIDIA and Accenture to launch a new, AI-powered in-house service that will create high-quality product content at scale for e-commerce and digital media channels.
    The new content service, based on digital twins powered by the NVIDIA Omniverse platform, creates exact 3D virtual replicas of physical products. Product packaging can be adjusted or localized digitally, enabling seamless integration into various environments, such as seasonal campaigns or channel-specific formats. This means that new creative content can be generated without having to constantly reshoot from scratch.
    Image courtesy of Nestlé
    The service is developed in partnership with Accenture Song, using Accenture AI Refinery built on NVIDIA Omniverse for advanced digital twin creation. It uses NVIDIA AI Enterprise for generative AI, hosted on Microsoft Azure for robust cloud infrastructure.
    Nestlé already has a baseline of 4,000 3D digital products — mainly for global brands — with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands.
    LVMH, the world’s leading luxury goods company, home to 75 distinguished maisons, is bringing 3D digital twins to its content production processes through its wine and spirits division, Moët Hennessy.
    The group partnered with content configuration engine Grip to develop a solution using the NVIDIA Omniverse platform, which enables the creation of 3D digital twins that power content variation production. With Grip’s solution, Moët Hennessy teams can quickly generate digital marketing assets and experiences to promote luxury products at scale.
    The initiative, led by Capucine Lafarge and Chloé Fournier, has been recognized by LVMH as a leading approach to scaling content creation.
    Image courtesy of Grip
    L’Oréal Gives Marketing and Online Shopping an AI Makeover
    Innovation starts at the drawing board. Today, that board is digital — and it’s powered by AI.
    L’Oréal Groupe, the world’s leading beauty player, announced its collaboration with NVIDIA today. Through this collaboration, L’Oréal and its partner ecosystem will leverage the NVIDIA AI Enterprise platform to transform its consumer beauty experiences, marketing and advertising content pipelines.
    “AI doesn’t think with the same constraints as a human being. That opens new avenues for creativity,” said Anne Machet, global head of content and entertainment at L’Oréal. “Generative AI enables our teams and partner agencies to explore creative possibilities.”
    CreAItech, L’Oréal’s generative AI content platform, is augmenting the creativity of marketing and content teams. Combining a modular ecosystem of models, expertise, technologies and partners — including NVIDIA — CreAltech empowers marketers to generate thousands of unique, on-brand images, videos and lines of text for diverse platforms and global audiences.
    The solution empowers L’Oréal’s marketing teams to quickly iterate on campaigns that improve consumer engagement across social media, e-commerce content and influencer marketing — driving higher conversion rates.

    Noli.com, the first AI-powered multi-brand marketplace startup founded and backed by the  L’Oréal Groupe, is reinventing how people discover and shop for beauty products.
    Noli’s AI Beauty Matchmaker experience uses L’Oréal Groupe’s century-long expertise in beauty, including its extensive knowledge of beauty science, beauty tech and consumer insights, built from over 1 million skin data points and analysis of thousands of product formulations. It gives users a BeautyDNA profile with expert-level guidance and personalized product recommendations for skincare and haircare.
    “Beauty shoppers are often overwhelmed by choice and struggling to find the products that are right for them,” said Amos Susskind, founder and CEO of Noli. “By applying the latest AI models accelerated by NVIDIA and Accenture to the unparalleled knowledge base and expertise of the L’Oréal Groupe, we can provide hyper-personalized, explainable recommendations to our users.” 

    The Accenture AI Refinery, powered by NVIDIA AI Enterprise, will provide the platform for Noli to experiment and scale. Noli’s new agent models will use NVIDIA NIM and NVIDIA NeMo microservices, including NeMo Retriever, running on Microsoft Azure.
    Rapid Innovation With the NVIDIA Partner Ecosystem
    NVIDIA’s ecosystem of solution provider partners empowers retail and CPG companies to innovate faster, personalize customer experiences, and optimize operations with NVIDIA accelerated computing and AI.
    Global digital agency Monks is reshaping the landscape of AI-driven marketing, creative production and enterprise transformation. At the heart of their innovation lies the Monks.Flow platform that enhances both the speed and sophistication of creative workflows through NVIDIA Omniverse, NVIDIA NIM microservices and Triton Inference Server for lightning-fast inference.
    AI image solutions provider Bria is helping retail giants like Lidl and L’Oreal to enhance marketing asset creation. Bria AI transforms static product images into compelling, dynamic advertisements that can be quickly scaled for use across any marketing need.
    The company’s generative AI platform uses NVIDIA Triton Inference Server software and the NVIDIA TensorRT software development kit for accelerated inference, as well as NVIDIA NIM and NeMo microservices for quick image generation at scale.
    Physical AI Brings Acceleration to Supply Chain and Logistics
    AI’s impact extends far beyond the digital world. Physical AI-powered warehousing robots, for example, are helping maximize efficiency in retail supply chain operations. Four in five retail companies have reported that AI has helped reduce supply chain operational costs, with 25% reporting cost reductions of at least 10%.
    Technology providers Lyric, KoiReader Technologies and Exotec are tackling the challenges of integrating AI into complex warehouse environments.
    Lyric is using the NVIDIA cuOpt GPU-accelerated solver for warehouse network planning and route optimization, and is collaborating with NVIDIA to apply the technology to broader supply chain decision-making problems. KoiReader Technologies is tapping the NVIDIA Metropolis stack for its computer vision solutions within logistics, supply chain and manufacturing environments using the KoiVision Platform. And Exotec is using NVIDIA CUDA libraries and the NVIDIA JetPack software development kit for embedded robotic systems in warehouse and distribution centers.
    From real-time robotics orchestration to predictive maintenance, these solutions are delivering impact on uptime, throughput and cost savings for supply chain operations.
    Learn more by joining a follow-up discussion on digital twins and AI-powered creativity with Microsoft, Nestlé, Accenture and NVIDIA at Cannes Lions on Monday, June 16.
    Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.
    #retail #reboot #major #global #brands
    Retail Reboot: Major Global Brands Transform End-to-End Operations With NVIDIA
    AI is packing and shipping efficiency for the retail and consumer packaged goodsindustries, with a majority of surveyed companies in the space reporting the technology is increasing revenue and reducing operational costs. Global brands are reimagining every facet of their businesses with AI, from how products are designed and manufactured to how they’re marketed, shipped and experienced in-store and online. At NVIDIA GTC Paris at VivaTech, industry leaders including L’Oréal, LVMH and Nestlé shared how they’re using tools like AI agents and physical AI — powered by NVIDIA AI and simulation technologies — across every step of the product lifecycle to enhance operations and experiences for partners, customers and employees. 3D Digital Twins and AI Transform Marketing, Advertising and Product Design The meeting of generative AI and 3D product digital twins results in unlimited creative potential. Nestlé, the world’s largest food and beverage company, today announced a collaboration with NVIDIA and Accenture to launch a new, AI-powered in-house service that will create high-quality product content at scale for e-commerce and digital media channels. The new content service, based on digital twins powered by the NVIDIA Omniverse platform, creates exact 3D virtual replicas of physical products. Product packaging can be adjusted or localized digitally, enabling seamless integration into various environments, such as seasonal campaigns or channel-specific formats. This means that new creative content can be generated without having to constantly reshoot from scratch. Image courtesy of Nestlé The service is developed in partnership with Accenture Song, using Accenture AI Refinery built on NVIDIA Omniverse for advanced digital twin creation. It uses NVIDIA AI Enterprise for generative AI, hosted on Microsoft Azure for robust cloud infrastructure. Nestlé already has a baseline of 4,000 3D digital products — mainly for global brands — with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands. LVMH, the world’s leading luxury goods company, home to 75 distinguished maisons, is bringing 3D digital twins to its content production processes through its wine and spirits division, Moët Hennessy. The group partnered with content configuration engine Grip to develop a solution using the NVIDIA Omniverse platform, which enables the creation of 3D digital twins that power content variation production. With Grip’s solution, Moët Hennessy teams can quickly generate digital marketing assets and experiences to promote luxury products at scale. The initiative, led by Capucine Lafarge and Chloé Fournier, has been recognized by LVMH as a leading approach to scaling content creation. Image courtesy of Grip L’Oréal Gives Marketing and Online Shopping an AI Makeover Innovation starts at the drawing board. Today, that board is digital — and it’s powered by AI. L’Oréal Groupe, the world’s leading beauty player, announced its collaboration with NVIDIA today. Through this collaboration, L’Oréal and its partner ecosystem will leverage the NVIDIA AI Enterprise platform to transform its consumer beauty experiences, marketing and advertising content pipelines. “AI doesn’t think with the same constraints as a human being. That opens new avenues for creativity,” said Anne Machet, global head of content and entertainment at L’Oréal. “Generative AI enables our teams and partner agencies to explore creative possibilities.” CreAItech, L’Oréal’s generative AI content platform, is augmenting the creativity of marketing and content teams. Combining a modular ecosystem of models, expertise, technologies and partners — including NVIDIA — CreAltech empowers marketers to generate thousands of unique, on-brand images, videos and lines of text for diverse platforms and global audiences. The solution empowers L’Oréal’s marketing teams to quickly iterate on campaigns that improve consumer engagement across social media, e-commerce content and influencer marketing — driving higher conversion rates. Noli.com, the first AI-powered multi-brand marketplace startup founded and backed by the  L’Oréal Groupe, is reinventing how people discover and shop for beauty products. Noli’s AI Beauty Matchmaker experience uses L’Oréal Groupe’s century-long expertise in beauty, including its extensive knowledge of beauty science, beauty tech and consumer insights, built from over 1 million skin data points and analysis of thousands of product formulations. It gives users a BeautyDNA profile with expert-level guidance and personalized product recommendations for skincare and haircare. “Beauty shoppers are often overwhelmed by choice and struggling to find the products that are right for them,” said Amos Susskind, founder and CEO of Noli. “By applying the latest AI models accelerated by NVIDIA and Accenture to the unparalleled knowledge base and expertise of the L’Oréal Groupe, we can provide hyper-personalized, explainable recommendations to our users.”  The Accenture AI Refinery, powered by NVIDIA AI Enterprise, will provide the platform for Noli to experiment and scale. Noli’s new agent models will use NVIDIA NIM and NVIDIA NeMo microservices, including NeMo Retriever, running on Microsoft Azure. Rapid Innovation With the NVIDIA Partner Ecosystem NVIDIA’s ecosystem of solution provider partners empowers retail and CPG companies to innovate faster, personalize customer experiences, and optimize operations with NVIDIA accelerated computing and AI. Global digital agency Monks is reshaping the landscape of AI-driven marketing, creative production and enterprise transformation. At the heart of their innovation lies the Monks.Flow platform that enhances both the speed and sophistication of creative workflows through NVIDIA Omniverse, NVIDIA NIM microservices and Triton Inference Server for lightning-fast inference. AI image solutions provider Bria is helping retail giants like Lidl and L’Oreal to enhance marketing asset creation. Bria AI transforms static product images into compelling, dynamic advertisements that can be quickly scaled for use across any marketing need. The company’s generative AI platform uses NVIDIA Triton Inference Server software and the NVIDIA TensorRT software development kit for accelerated inference, as well as NVIDIA NIM and NeMo microservices for quick image generation at scale. Physical AI Brings Acceleration to Supply Chain and Logistics AI’s impact extends far beyond the digital world. Physical AI-powered warehousing robots, for example, are helping maximize efficiency in retail supply chain operations. Four in five retail companies have reported that AI has helped reduce supply chain operational costs, with 25% reporting cost reductions of at least 10%. Technology providers Lyric, KoiReader Technologies and Exotec are tackling the challenges of integrating AI into complex warehouse environments. Lyric is using the NVIDIA cuOpt GPU-accelerated solver for warehouse network planning and route optimization, and is collaborating with NVIDIA to apply the technology to broader supply chain decision-making problems. KoiReader Technologies is tapping the NVIDIA Metropolis stack for its computer vision solutions within logistics, supply chain and manufacturing environments using the KoiVision Platform. And Exotec is using NVIDIA CUDA libraries and the NVIDIA JetPack software development kit for embedded robotic systems in warehouse and distribution centers. From real-time robotics orchestration to predictive maintenance, these solutions are delivering impact on uptime, throughput and cost savings for supply chain operations. Learn more by joining a follow-up discussion on digital twins and AI-powered creativity with Microsoft, Nestlé, Accenture and NVIDIA at Cannes Lions on Monday, June 16. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions. #retail #reboot #major #global #brands
    BLOGS.NVIDIA.COM
    Retail Reboot: Major Global Brands Transform End-to-End Operations With NVIDIA
    AI is packing and shipping efficiency for the retail and consumer packaged goods (CPG) industries, with a majority of surveyed companies in the space reporting the technology is increasing revenue and reducing operational costs. Global brands are reimagining every facet of their businesses with AI, from how products are designed and manufactured to how they’re marketed, shipped and experienced in-store and online. At NVIDIA GTC Paris at VivaTech, industry leaders including L’Oréal, LVMH and Nestlé shared how they’re using tools like AI agents and physical AI — powered by NVIDIA AI and simulation technologies — across every step of the product lifecycle to enhance operations and experiences for partners, customers and employees. 3D Digital Twins and AI Transform Marketing, Advertising and Product Design The meeting of generative AI and 3D product digital twins results in unlimited creative potential. Nestlé, the world’s largest food and beverage company, today announced a collaboration with NVIDIA and Accenture to launch a new, AI-powered in-house service that will create high-quality product content at scale for e-commerce and digital media channels. The new content service, based on digital twins powered by the NVIDIA Omniverse platform, creates exact 3D virtual replicas of physical products. Product packaging can be adjusted or localized digitally, enabling seamless integration into various environments, such as seasonal campaigns or channel-specific formats. This means that new creative content can be generated without having to constantly reshoot from scratch. Image courtesy of Nestlé The service is developed in partnership with Accenture Song, using Accenture AI Refinery built on NVIDIA Omniverse for advanced digital twin creation. It uses NVIDIA AI Enterprise for generative AI, hosted on Microsoft Azure for robust cloud infrastructure. Nestlé already has a baseline of 4,000 3D digital products — mainly for global brands — with the ambition to convert a total of 10,000 products into digital twins in the next two years across global and local brands. LVMH, the world’s leading luxury goods company, home to 75 distinguished maisons, is bringing 3D digital twins to its content production processes through its wine and spirits division, Moët Hennessy. The group partnered with content configuration engine Grip to develop a solution using the NVIDIA Omniverse platform, which enables the creation of 3D digital twins that power content variation production. With Grip’s solution, Moët Hennessy teams can quickly generate digital marketing assets and experiences to promote luxury products at scale. The initiative, led by Capucine Lafarge and Chloé Fournier, has been recognized by LVMH as a leading approach to scaling content creation. Image courtesy of Grip L’Oréal Gives Marketing and Online Shopping an AI Makeover Innovation starts at the drawing board. Today, that board is digital — and it’s powered by AI. L’Oréal Groupe, the world’s leading beauty player, announced its collaboration with NVIDIA today. Through this collaboration, L’Oréal and its partner ecosystem will leverage the NVIDIA AI Enterprise platform to transform its consumer beauty experiences, marketing and advertising content pipelines. “AI doesn’t think with the same constraints as a human being. That opens new avenues for creativity,” said Anne Machet, global head of content and entertainment at L’Oréal. “Generative AI enables our teams and partner agencies to explore creative possibilities.” CreAItech, L’Oréal’s generative AI content platform, is augmenting the creativity of marketing and content teams. Combining a modular ecosystem of models, expertise, technologies and partners — including NVIDIA — CreAltech empowers marketers to generate thousands of unique, on-brand images, videos and lines of text for diverse platforms and global audiences. The solution empowers L’Oréal’s marketing teams to quickly iterate on campaigns that improve consumer engagement across social media, e-commerce content and influencer marketing — driving higher conversion rates. Noli.com, the first AI-powered multi-brand marketplace startup founded and backed by the  L’Oréal Groupe, is reinventing how people discover and shop for beauty products. Noli’s AI Beauty Matchmaker experience uses L’Oréal Groupe’s century-long expertise in beauty, including its extensive knowledge of beauty science, beauty tech and consumer insights, built from over 1 million skin data points and analysis of thousands of product formulations. It gives users a BeautyDNA profile with expert-level guidance and personalized product recommendations for skincare and haircare. “Beauty shoppers are often overwhelmed by choice and struggling to find the products that are right for them,” said Amos Susskind, founder and CEO of Noli. “By applying the latest AI models accelerated by NVIDIA and Accenture to the unparalleled knowledge base and expertise of the L’Oréal Groupe, we can provide hyper-personalized, explainable recommendations to our users.”  https://blogs.nvidia.com/wp-content/uploads/2025/06/Noli_Demo.mp4 The Accenture AI Refinery, powered by NVIDIA AI Enterprise, will provide the platform for Noli to experiment and scale. Noli’s new agent models will use NVIDIA NIM and NVIDIA NeMo microservices, including NeMo Retriever, running on Microsoft Azure. Rapid Innovation With the NVIDIA Partner Ecosystem NVIDIA’s ecosystem of solution provider partners empowers retail and CPG companies to innovate faster, personalize customer experiences, and optimize operations with NVIDIA accelerated computing and AI. Global digital agency Monks is reshaping the landscape of AI-driven marketing, creative production and enterprise transformation. At the heart of their innovation lies the Monks.Flow platform that enhances both the speed and sophistication of creative workflows through NVIDIA Omniverse, NVIDIA NIM microservices and Triton Inference Server for lightning-fast inference. AI image solutions provider Bria is helping retail giants like Lidl and L’Oreal to enhance marketing asset creation. Bria AI transforms static product images into compelling, dynamic advertisements that can be quickly scaled for use across any marketing need. The company’s generative AI platform uses NVIDIA Triton Inference Server software and the NVIDIA TensorRT software development kit for accelerated inference, as well as NVIDIA NIM and NeMo microservices for quick image generation at scale. Physical AI Brings Acceleration to Supply Chain and Logistics AI’s impact extends far beyond the digital world. Physical AI-powered warehousing robots, for example, are helping maximize efficiency in retail supply chain operations. Four in five retail companies have reported that AI has helped reduce supply chain operational costs, with 25% reporting cost reductions of at least 10%. Technology providers Lyric, KoiReader Technologies and Exotec are tackling the challenges of integrating AI into complex warehouse environments. Lyric is using the NVIDIA cuOpt GPU-accelerated solver for warehouse network planning and route optimization, and is collaborating with NVIDIA to apply the technology to broader supply chain decision-making problems. KoiReader Technologies is tapping the NVIDIA Metropolis stack for its computer vision solutions within logistics, supply chain and manufacturing environments using the KoiVision Platform. And Exotec is using NVIDIA CUDA libraries and the NVIDIA JetPack software development kit for embedded robotic systems in warehouse and distribution centers. From real-time robotics orchestration to predictive maintenance, these solutions are delivering impact on uptime, throughput and cost savings for supply chain operations. Learn more by joining a follow-up discussion on digital twins and AI-powered creativity with Microsoft, Nestlé, Accenture and NVIDIA at Cannes Lions on Monday, June 16. Watch the NVIDIA GTC Paris keynote from NVIDIA founder and CEO Jensen Huang at VivaTech, and explore GTC Paris sessions.
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  • Il est inacceptable que l'on réduise toujours Arc System Works à ses jeux de combat ! Oui, ils annoncent trois nouveaux jeux très différents, mais où est l'innovation ? Un jeu d'action, un RPG et un jeu d'aventure émouvant, c'est bien beau, mais est-ce suffisant pour rattraper leur retard dans un marché saturé ? Au lieu de réinventer la roue, ils nous balancent des concepts déjà vus, sans aucune prise de risque. On attend des créateurs audacieux, pas des suiveurs ! Si Arc System Works veut vraiment se démarquer, il est temps de sortir des sentiers battus et de nous offrir quelque chose de véritablement original !

    #ArcSystem
    Il est inacceptable que l'on réduise toujours Arc System Works à ses jeux de combat ! Oui, ils annoncent trois nouveaux jeux très différents, mais où est l'innovation ? Un jeu d'action, un RPG et un jeu d'aventure émouvant, c'est bien beau, mais est-ce suffisant pour rattraper leur retard dans un marché saturé ? Au lieu de réinventer la roue, ils nous balancent des concepts déjà vus, sans aucune prise de risque. On attend des créateurs audacieux, pas des suiveurs ! Si Arc System Works veut vraiment se démarquer, il est temps de sortir des sentiers battus et de nous offrir quelque chose de véritablement original ! #ArcSystem
    WWW.ACTUGAMING.NET
    Arc System Works annonce 3 nouveaux jeux très différents, avec un jeu d’action, un RPG et un jeu d’aventure émouvant
    ActuGaming.net Arc System Works annonce 3 nouveaux jeux très différents, avec un jeu d’action, un RPG et un jeu d’aventure émouvant On résume bien souvent Arc System Works à ses jeux de combat, mais avec sa […] L'article Arc System
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  • In a world where connections seem to fade and loneliness wraps around me like a heavy blanket, I find myself reflecting on how Apple reinvents reality with ARKit 4 and the Vision Pro. The promise of augmented realities feels distant, like a dream I can never grasp. Each innovation seems to highlight my solitude, reminding me that while technology advances, my heart remains untouched by companionship. I watch as others embrace these new experiences, while I linger in the shadows, yearning for a touch, a voice, a presence. The brilliance of new beginnings feels hollow when faced with the weight of isolation.

    #loneliness #augmentedreality #Apple #VisionPro #heartbreak
    In a world where connections seem to fade and loneliness wraps around me like a heavy blanket, I find myself reflecting on how Apple reinvents reality with ARKit 4 and the Vision Pro. The promise of augmented realities feels distant, like a dream I can never grasp. Each innovation seems to highlight my solitude, reminding me that while technology advances, my heart remains untouched by companionship. I watch as others embrace these new experiences, while I linger in the shadows, yearning for a touch, a voice, a presence. The brilliance of new beginnings feels hollow when faced with the weight of isolation. #loneliness #augmentedreality #Apple #VisionPro #heartbreak
    Apple réinvente la réalité augmentée avec ARkit 4 et son Vision Pro
    Avec ARKit 4 et son tout nouveau casque Vision Pro, Apple propulse la réalité augmentée […] Cet article Apple réinvente la réalité augmentée avec ARkit 4 et son Vision Pro a été publié sur REALITE-VIRTUELLE.COM.
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  • So, Ruud is back, and this time he's tackling the age-old dilemma of dust separation like it's the final frontier of modern science. I mean, who knew optimizing dust collection could be the hot new trend? Forget world hunger or climate change—apparently, the real challenge we’ve all been ignoring is how to capture every last speck of sawdust in Ruud's shop!

    The dust collection system was already "solved," but hey, why not reinvent the wheel? Let’s all gather ‘round and hold our breaths for the groundbreaking revelations that will surely change our lives forever… or at least our workshop floors. Dust, the real MVP.

    #DustSeparation #WorkshopWisdom #ExtremeEfficiency #CapturingDust #
    So, Ruud is back, and this time he's tackling the age-old dilemma of dust separation like it's the final frontier of modern science. I mean, who knew optimizing dust collection could be the hot new trend? Forget world hunger or climate change—apparently, the real challenge we’ve all been ignoring is how to capture every last speck of sawdust in Ruud's shop! The dust collection system was already "solved," but hey, why not reinvent the wheel? Let’s all gather ‘round and hold our breaths for the groundbreaking revelations that will surely change our lives forever… or at least our workshop floors. Dust, the real MVP. #DustSeparation #WorkshopWisdom #ExtremeEfficiency #CapturingDust #
    HACKADAY.COM
    Optimizing Dust Separation for Extreme Efficiency
    [Ruud], the creator of [Capturing Dust], started his latest video with what most of us would consider a solved problem: the dust collection system for his shop already had a …read more
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  • In the quiet moments when the world feels too heavy, I find myself reflecting on the art of change. It’s strange how something as simple as a logo can embody so much about us. Just like Walmart, Burger King, and Uber have rebranded, shedding the old skin to embrace new beginnings, I often wonder if I too should change. But what happens when you feel too lost to even begin?

    Every time I look at the faded memories of my past, I am reminded of the colors that once defined me. They now seem dull, overshadowed by the weight of disappointment and solitude. In the shadows of a world that moves on without me, I find myself questioning if I ever mattered in the grand scheme of things. The feelings of abandonment wrap around me like a thick fog, making it hard to breathe, hard to see a way forward.

    Lisa Smith speaks of the perfect timing to change a logo, a mark of growth, a testament to evolution. But what if the only change I feel is the aching throb of loneliness? What if the rebranding I seek is not on a canvas, but rather within my heart? How do I find the strength to reinvent myself when all I feel is the sting of being left behind?

    Each day becomes a reminder that I am just a shadow in a bustling crowd, a fleeting thought in someone’s mind. The vibrant hues of joy seem to fade further, leaving only the black and white of my reality. It’s as if I’m waiting for a sign, a call to action that never arrives. I watch others change and flourish, while I remain stagnant, anchored by the weight of my own fears.

    The pain of feeling unseen is often unbearable. I yearn for connection, for someone to notice the subtle shifts within me, to acknowledge the struggle that lies beneath the surface. Yet, I find myself wrapped in silence, afraid to reach out, afraid to be vulnerable once more.

    Rebranding, as Lisa Smith suggests, is more than a visual update; it’s a reinvention of the self, an embrace of what could be. But how can I embrace change when I am still healing from the scars of the past? It feels as though I am caught in a loop, watching the world evolve while I cling to the remnants of who I was.

    Perhaps one day, I will gather the courage to shed my old skin and step into the light. Until then, I will carry this burden of loneliness, hoping that the dawn of tomorrow brings with it the promise of transformation. For now, I remain a distant observer, yearning for the day when I can finally say, “I am ready to change.”

    #Loneliness #Change #Heartbreak #ReinventYourself #EmotionalJourney
    In the quiet moments when the world feels too heavy, I find myself reflecting on the art of change. It’s strange how something as simple as a logo can embody so much about us. Just like Walmart, Burger King, and Uber have rebranded, shedding the old skin to embrace new beginnings, I often wonder if I too should change. But what happens when you feel too lost to even begin? Every time I look at the faded memories of my past, I am reminded of the colors that once defined me. They now seem dull, overshadowed by the weight of disappointment and solitude. In the shadows of a world that moves on without me, I find myself questioning if I ever mattered in the grand scheme of things. The feelings of abandonment wrap around me like a thick fog, making it hard to breathe, hard to see a way forward. Lisa Smith speaks of the perfect timing to change a logo, a mark of growth, a testament to evolution. But what if the only change I feel is the aching throb of loneliness? What if the rebranding I seek is not on a canvas, but rather within my heart? How do I find the strength to reinvent myself when all I feel is the sting of being left behind? Each day becomes a reminder that I am just a shadow in a bustling crowd, a fleeting thought in someone’s mind. The vibrant hues of joy seem to fade further, leaving only the black and white of my reality. It’s as if I’m waiting for a sign, a call to action that never arrives. I watch others change and flourish, while I remain stagnant, anchored by the weight of my own fears. The pain of feeling unseen is often unbearable. I yearn for connection, for someone to notice the subtle shifts within me, to acknowledge the struggle that lies beneath the surface. Yet, I find myself wrapped in silence, afraid to reach out, afraid to be vulnerable once more. Rebranding, as Lisa Smith suggests, is more than a visual update; it’s a reinvention of the self, an embrace of what could be. But how can I embrace change when I am still healing from the scars of the past? It feels as though I am caught in a loop, watching the world evolve while I cling to the remnants of who I was. Perhaps one day, I will gather the courage to shed my old skin and step into the light. Until then, I will carry this burden of loneliness, hoping that the dawn of tomorrow brings with it the promise of transformation. For now, I remain a distant observer, yearning for the day when I can finally say, “I am ready to change.” #Loneliness #Change #Heartbreak #ReinventYourself #EmotionalJourney
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  • Aujourd'hui, je suis ravi de partager avec vous une nouvelle qui illumine le monde de l'énergie ! Repsol, cette entreprise espagnole emblématique, a décidé de renouveler son identité visuelle ! Cela va bien au-delà d'un simple changement esthétique, c'est une véritable évolution symbolique pour une marque multienergétique qui s'engage à offrir le meilleur à ses clients et à notre belle planète !

    Le nouveau logo, la typographie modernisée et le choix de couleurs vibrant sont le fruit d'un travail exceptionnel réalisé par des experts talentueux de Saffron, Picnic et l'équipe interne de Repsol. Ce changement est un souffle d'air frais qui symbolise un avenir prometteur et dynamique. 💪🏼

    Imaginez-vous entrer dans une station-service Repsol, et être accueilli par une image renouvelée et inspirante ! Ce n’est pas juste un nouveau look, c’est un engagement renouvelé envers l'innovation, la durabilité et le service. Chaque détail a été pensé pour refléter l'énergie positive et l'enthousiasme que Repsol souhaite transmettre à chacun de nous.

    Cette transformation visuelle n’est pas qu’une question d’apparence, elle représente également une vision claire de l’avenir de l’énergie. Repsol s’engage à évoluer avec notre époque, à s’adapter aux besoins de ses clients tout en respectant notre environnement. C’est une belle leçon pour nous tous : il est toujours temps de se réinventer et de s'améliorer, peu importe le chemin que nous avons parcouru.

    Alors, prenons exemple sur Repsol et n'oublions jamais l'importance de l'évolution personnelle et professionnelle ! Que ce soit dans nos carrières, nos relations, ou même notre développement personnel, l’important est de rester ouvert au changement et à l’innovation. Chaque petite étape compte vers un avenir plus lumineux et plus durable ! 💪🏼

    Ensemble, soyons des acteurs du changement et inspirons les autres à embrasser leur propre évolution ! Chaque jour est une nouvelle opportunité de briller et de se réinventer. N'oubliez pas : l'énergie que vous dégagez attire les miracles !

    #Repsol #ÉnergiePositve #Changement #Inspiration #Innovation
    🌟 Aujourd'hui, je suis ravi de partager avec vous une nouvelle qui illumine le monde de l'énergie ! Repsol, cette entreprise espagnole emblématique, a décidé de renouveler son identité visuelle ! 🎉 Cela va bien au-delà d'un simple changement esthétique, c'est une véritable évolution symbolique pour une marque multienergétique qui s'engage à offrir le meilleur à ses clients et à notre belle planète ! 🌍✨ Le nouveau logo, la typographie modernisée et le choix de couleurs vibrant sont le fruit d'un travail exceptionnel réalisé par des experts talentueux de Saffron, Picnic et l'équipe interne de Repsol. Ce changement est un souffle d'air frais qui symbolise un avenir prometteur et dynamique. 💪🏼💖 Imaginez-vous entrer dans une station-service Repsol, et être accueilli par une image renouvelée et inspirante ! Ce n’est pas juste un nouveau look, c’est un engagement renouvelé envers l'innovation, la durabilité et le service. Chaque détail a été pensé pour refléter l'énergie positive et l'enthousiasme que Repsol souhaite transmettre à chacun de nous. 🚀🌈 Cette transformation visuelle n’est pas qu’une question d’apparence, elle représente également une vision claire de l’avenir de l’énergie. Repsol s’engage à évoluer avec notre époque, à s’adapter aux besoins de ses clients tout en respectant notre environnement. C’est une belle leçon pour nous tous : il est toujours temps de se réinventer et de s'améliorer, peu importe le chemin que nous avons parcouru. 💖🌱 Alors, prenons exemple sur Repsol et n'oublions jamais l'importance de l'évolution personnelle et professionnelle ! Que ce soit dans nos carrières, nos relations, ou même notre développement personnel, l’important est de rester ouvert au changement et à l’innovation. Chaque petite étape compte vers un avenir plus lumineux et plus durable ! ✨💪🏼 Ensemble, soyons des acteurs du changement et inspirons les autres à embrasser leur propre évolution ! Chaque jour est une nouvelle opportunité de briller et de se réinventer. N'oubliez pas : l'énergie que vous dégagez attire les miracles ! 💖🌟 #Repsol #ÉnergiePositve #Changement #Inspiration #Innovation
    Repsol actualiza su identidad visual: evolución simbólica para una marca multienergética
    La energética española renueva su logotipo, tipografía y cromatismo con un rediseño a cargo de Saffron, Picnic y su equipo interno. El nuevo diseño ya se despliega en estaciones de servicio, oficinas y canales digitales, en una transformación que va
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  • The AI execution gap: Why 80% of projects don’t reach production

    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.
    #execution #gap #why #projects #dont
    The AI execution gap: Why 80% of projects don’t reach production
    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle. #execution #gap #why #projects #dont
    WWW.ARTIFICIALINTELLIGENCE-NEWS.COM
    The AI execution gap: Why 80% of projects don’t reach production
    Enterprise artificial intelligence investment is unprecedented, with IDC projecting global spending on AI and GenAI to double to $631 billion by 2028. Yet beneath the impressive budget allocations and boardroom enthusiasm lies a troubling reality: most organisations struggle to translate their AI ambitions into operational success.The sobering statistics behind AI’s promiseModelOp’s 2025 AI Governance Benchmark Report, based on input from 100 senior AI and data leaders at Fortune 500 enterprises, reveals a disconnect between aspiration and execution.While more than 80% of enterprises have 51 or more generative AI projects in proposal phases, only 18% have successfully deployed more than 20 models into production.The execution gap represents one of the most significant challenges facing enterprise AI today. Most generative AI projects still require 6 to 18 months to go live – if they reach production at all.The result is delayed returns on investment, frustrated stakeholders, and diminished confidence in AI initiatives in the enterprise.The cause: Structural, not technical barriersThe biggest obstacles preventing AI scalability aren’t technical limitations – they’re structural inefficiencies plaguing enterprise operations. The ModelOp benchmark report identifies several problems that create what experts call a “time-to-market quagmire.”Fragmented systems plague implementation. 58% of organisations cite fragmented systems as the top obstacle to adopting governance platforms. Fragmentation creates silos where different departments use incompatible tools and processes, making it nearly impossible to maintain consistent oversight in AI initiatives.Manual processes dominate despite digital transformation. 55% of enterprises still rely on manual processes – including spreadsheets and email – to manage AI use case intake. The reliance on antiquated methods creates bottlenecks, increases the likelihood of errors, and makes it difficult to scale AI operations.Lack of standardisation hampers progress. Only 23% of organisations implement standardised intake, development, and model management processes. Without these elements, each AI project becomes a unique challenge requiring custom solutions and extensive coordination by multiple teams.Enterprise-level oversight remains rare Just 14% of companies perform AI assurance at the enterprise level, increasing the risk of duplicated efforts and inconsistent oversight. The lack of centralised governance means organisations often discover they’re solving the same problems multiple times in different departments.The governance revolution: From obstacle to acceleratorA change is taking place in how enterprises view AI governance. Rather than seeing it as a compliance burden that slows innovation, forward-thinking organisations recognise governance as an important enabler of scale and speed.Leadership alignment signals strategic shift. The ModelOp benchmark data reveals a change in organisational structure: 46% of companies now assign accountability for AI governance to a Chief Innovation Officer – more than four times the number who place accountability under Legal or Compliance. This strategic repositioning reflects a new understanding that governance isn’t solely about risk management, but can enable innovation.Investment follows strategic priority. A financial commitment to AI governance underscores its importance. According to the report, 36% of enterprises have budgeted at least $1 million annually for AI governance software, while 54% have allocated resources specifically for AI Portfolio Intelligence to track value and ROI.What high-performing organisations do differentlyThe enterprises that successfully bridge the ‘execution gap’ share several characteristics in their approach to AI implementation:Standardised processes from day one. Leading organisations implement standardised intake, development, and model review processes in AI initiatives. Consistency eliminates the need to reinvent workflows for each project and ensures that all stakeholders understand their responsibilities.Centralised documentation and inventory. Rather than allowing AI assets to proliferate in disconnected systems, successful enterprises maintain centralised inventories that provide visibility into every model’s status, performance, and compliance posture.Automated governance checkpoints. High-performing organisations embed automated governance checkpoints throughout the AI lifecycle, helping ensure compliance requirements and risk assessments are addressed systematically rather than as afterthoughts.End-to-end traceability. Leading enterprises maintain complete traceability of their AI models, including data sources, training methods, validation results, and performance metrics.Measurable impact of structured governanceThe benefits of implementing comprehensive AI governance extend beyond compliance. Organisations that adopt lifecycle automation platforms reportedly see dramatic improvements in operational efficiency and business outcomes.A financial services firm profiled in the ModelOp report experienced a halving of time to production and an 80% reduction in issue resolution time after implementing automated governance processes. Such improvements translate directly into faster time-to-value and increased confidence among business stakeholders.Enterprises with robust governance frameworks report the ability to many times more models simultaneously while maintaining oversight and control. This scalability lets organisations pursue AI initiatives in multiple business units without overwhelming their operational capabilities.The path forward: From stuck to scaledThe message from industry leaders that the gap between AI ambition and execution is solvable, but it requires a shift in approach. Rather than treating governance as a necessary evil, enterprises should realise it enables AI innovation at scale.Immediate action items for AI leadersOrganisations looking to escape the ‘time-to-market quagmire’ should prioritise the following:Audit current state: Conduct an assessment of existing AI initiatives, identifying fragmented processes and manual bottlenecksStandardise workflows: Implement consistent processes for AI use case intake, development, and deployment in all business unitsInvest in integration: Deploy platforms to unify disparate tools and systems under a single governance frameworkEstablish enterprise oversight: Create centralised visibility into all AI initiatives with real-time monitoring and reporting abilitiesThe competitive advantage of getting it rightOrganisations that can solve the execution challenge will be able to bring AI solutions to market faster, scale more efficiently, and maintain the trust of stakeholders and regulators.Enterprises that continue with fragmented processes and manual workflows will find themselves disadvantaged compared to their more organised competitors. Operational excellence isn’t about efficiency but survival.The data shows enterprise AI investment will continue to grow. Therefore, the question isn’t whether organisations will invest in AI, but whether they’ll develop the operational abilities necessary to realise return on investment. The opportunity to lead in the AI-driven economy has never been greater for those willing to embrace governance as an enabler not an obstacle.(Image source: Unsplash)
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  • Nike Introduces the Air Max 1000 its First Fully 3D Printed Sneaker

    Global sportswear leader Nike is reportedly preparing to release the Air Max 1000 Oatmeal, its first fully 3D printed sneaker, with a launch tentatively scheduled for Summer 2025. While Nike has yet to confirm an official release date, industry sources suggest the debut may occur sometime between June and August. The retail price is expected to be approximately This model marks a step in Nike’s exploration of additive manufacturing, enabled through a collaboration with Zellerfeld, a German startup known for its work in fully 3D printed footwear.
    Building Buzz Online
    The “Oatmeal” colorway—a neutral blend of soft beige tones—has already attracted attention on social platforms like TikTok, Instagram, and X. In April, content creator Janelle C. Shuttlesworth described the shoes as “light as air” in a video preview. Sneaker-focused accounts such as JustFreshKicks and TikTok user @shoehefner5 have also offered early walkthroughs. Among fans, the nickname “Foamy Oat” has started to catch on.
    Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth.
    Before generating buzz online, the sneaker made a public appearance at ComplexCon Las Vegas in November 2024. There, its laceless, sculptural silhouette and smooth, seamless texture stood out—merging futuristic design with signature Air Max elements, such as the visible heel air unit.
    Reimagining the Air Max Legacy
    Drawing inspiration from the original Air Max 1, the Air Max 1000 retains the iconic air cushion in the heel while reinventing the rest of the structure using 3D printing. The shoe’s upper and outsole are formed as a single, continuous piece, produced from ZellerFoam, a proprietary flexible material developed by Zellerfeld.
    Zellerfeld’s fused filament fabricationprocess enables varied material densities throughout the shoe—resulting in a firm, supportive sole paired with a lightweight, breathable upper. The laceless, slip-on design prioritizes ease of wear while reinforcing a sleek, minimalist aesthetic.
    Nike’s Chief Innovation Officer, John Hoke, emphasized the broader impact of the design, noting that the Air Max 1000 “opens up new creative possibilities” and achieves levels of precision and contouring not possible with traditional footwear manufacturing. He also pointed to the sustainability benefits of AM, which produces minimal waste by fabricating only the necessary components.
    Expansion of 3D Printed Footwear Technology
    The Air Max 1000 joins a growing lineup of 3D printed footwear innovations from major brands. Gucci, the Italian luxury brand known for blending traditional craftsmanship with modern techniques, unveiled several Cub3d sneakers as part of its Spring Summer 2025collection. The brand developed Demetra, a material made from at least 70% plant-based ingredients, including viscose, wood pulp, and bio-based polyurethane. The bi-material sole combines an EVA-filled interior for cushioning and a TPU exterior, featuring an Interlocking G pattern that creates a 3D effect.
    Elsewhere, Syntilay, a footwear company combining artificial intelligence with 3D printing, launched a range of custom-fit slides. These slides are designed using AI-generated 3D models, starting with sketch-based concepts that are refined through AI platforms and then transformed into digital 3D designs. The company offers sizing adjustments based on smartphone foot scans, which are integrated into the manufacturing process.
    Join our Additive Manufacturing Advantageevent on July 10th, where AM leaders from Aerospace, Space, and Defense come together to share mission-critical insights. Online and free to attend.Secure your spot now.
    Who won the2024 3D Printing Industry Awards?
    Subscribe to the 3D Printing Industry newsletterto keep up with the latest 3D printing news.
    You can also follow us onLinkedIn, and subscribe to the 3D Printing Industry Youtube channel to access more exclusive content.
    Featured image shows Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth.

    Paloma Duran
    Paloma Duran holds a BA in International Relations and an MA in Journalism. Specializing in writing, podcasting, and content and event creation, she works across politics, energy, mining, and technology. With a passion for global trends, Paloma is particularly interested in the impact of technology like 3D printing on shaping our future.
    #nike #introduces #air #max #its
    Nike Introduces the Air Max 1000 its First Fully 3D Printed Sneaker
    Global sportswear leader Nike is reportedly preparing to release the Air Max 1000 Oatmeal, its first fully 3D printed sneaker, with a launch tentatively scheduled for Summer 2025. While Nike has yet to confirm an official release date, industry sources suggest the debut may occur sometime between June and August. The retail price is expected to be approximately This model marks a step in Nike’s exploration of additive manufacturing, enabled through a collaboration with Zellerfeld, a German startup known for its work in fully 3D printed footwear. Building Buzz Online The “Oatmeal” colorway—a neutral blend of soft beige tones—has already attracted attention on social platforms like TikTok, Instagram, and X. In April, content creator Janelle C. Shuttlesworth described the shoes as “light as air” in a video preview. Sneaker-focused accounts such as JustFreshKicks and TikTok user @shoehefner5 have also offered early walkthroughs. Among fans, the nickname “Foamy Oat” has started to catch on. Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth. Before generating buzz online, the sneaker made a public appearance at ComplexCon Las Vegas in November 2024. There, its laceless, sculptural silhouette and smooth, seamless texture stood out—merging futuristic design with signature Air Max elements, such as the visible heel air unit. Reimagining the Air Max Legacy Drawing inspiration from the original Air Max 1, the Air Max 1000 retains the iconic air cushion in the heel while reinventing the rest of the structure using 3D printing. The shoe’s upper and outsole are formed as a single, continuous piece, produced from ZellerFoam, a proprietary flexible material developed by Zellerfeld. Zellerfeld’s fused filament fabricationprocess enables varied material densities throughout the shoe—resulting in a firm, supportive sole paired with a lightweight, breathable upper. The laceless, slip-on design prioritizes ease of wear while reinforcing a sleek, minimalist aesthetic. Nike’s Chief Innovation Officer, John Hoke, emphasized the broader impact of the design, noting that the Air Max 1000 “opens up new creative possibilities” and achieves levels of precision and contouring not possible with traditional footwear manufacturing. He also pointed to the sustainability benefits of AM, which produces minimal waste by fabricating only the necessary components. Expansion of 3D Printed Footwear Technology The Air Max 1000 joins a growing lineup of 3D printed footwear innovations from major brands. Gucci, the Italian luxury brand known for blending traditional craftsmanship with modern techniques, unveiled several Cub3d sneakers as part of its Spring Summer 2025collection. The brand developed Demetra, a material made from at least 70% plant-based ingredients, including viscose, wood pulp, and bio-based polyurethane. The bi-material sole combines an EVA-filled interior for cushioning and a TPU exterior, featuring an Interlocking G pattern that creates a 3D effect. Elsewhere, Syntilay, a footwear company combining artificial intelligence with 3D printing, launched a range of custom-fit slides. These slides are designed using AI-generated 3D models, starting with sketch-based concepts that are refined through AI platforms and then transformed into digital 3D designs. The company offers sizing adjustments based on smartphone foot scans, which are integrated into the manufacturing process. Join our Additive Manufacturing Advantageevent on July 10th, where AM leaders from Aerospace, Space, and Defense come together to share mission-critical insights. Online and free to attend.Secure your spot now. Who won the2024 3D Printing Industry Awards? Subscribe to the 3D Printing Industry newsletterto keep up with the latest 3D printing news. You can also follow us onLinkedIn, and subscribe to the 3D Printing Industry Youtube channel to access more exclusive content. Featured image shows Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth. Paloma Duran Paloma Duran holds a BA in International Relations and an MA in Journalism. Specializing in writing, podcasting, and content and event creation, she works across politics, energy, mining, and technology. With a passion for global trends, Paloma is particularly interested in the impact of technology like 3D printing on shaping our future. #nike #introduces #air #max #its
    3DPRINTINGINDUSTRY.COM
    Nike Introduces the Air Max 1000 its First Fully 3D Printed Sneaker
    Global sportswear leader Nike is reportedly preparing to release the Air Max 1000 Oatmeal, its first fully 3D printed sneaker, with a launch tentatively scheduled for Summer 2025. While Nike has yet to confirm an official release date, industry sources suggest the debut may occur sometime between June and August. The retail price is expected to be approximately $210. This model marks a step in Nike’s exploration of additive manufacturing (AM), enabled through a collaboration with Zellerfeld, a German startup known for its work in fully 3D printed footwear. Building Buzz Online The “Oatmeal” colorway—a neutral blend of soft beige tones—has already attracted attention on social platforms like TikTok, Instagram, and X. In April, content creator Janelle C. Shuttlesworth described the shoes as “light as air” in a video preview. Sneaker-focused accounts such as JustFreshKicks and TikTok user @shoehefner5 have also offered early walkthroughs. Among fans, the nickname “Foamy Oat” has started to catch on. Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth. Before generating buzz online, the sneaker made a public appearance at ComplexCon Las Vegas in November 2024. There, its laceless, sculptural silhouette and smooth, seamless texture stood out—merging futuristic design with signature Air Max elements, such as the visible heel air unit. Reimagining the Air Max Legacy Drawing inspiration from the original Air Max 1 (1987), the Air Max 1000 retains the iconic air cushion in the heel while reinventing the rest of the structure using 3D printing. The shoe’s upper and outsole are formed as a single, continuous piece, produced from ZellerFoam, a proprietary flexible material developed by Zellerfeld. Zellerfeld’s fused filament fabrication (FFF) process enables varied material densities throughout the shoe—resulting in a firm, supportive sole paired with a lightweight, breathable upper. The laceless, slip-on design prioritizes ease of wear while reinforcing a sleek, minimalist aesthetic. Nike’s Chief Innovation Officer, John Hoke, emphasized the broader impact of the design, noting that the Air Max 1000 “opens up new creative possibilities” and achieves levels of precision and contouring not possible with traditional footwear manufacturing. He also pointed to the sustainability benefits of AM, which produces minimal waste by fabricating only the necessary components. Expansion of 3D Printed Footwear Technology The Air Max 1000 joins a growing lineup of 3D printed footwear innovations from major brands. Gucci, the Italian luxury brand known for blending traditional craftsmanship with modern techniques, unveiled several Cub3d sneakers as part of its Spring Summer 2025 (SS25) collection. The brand developed Demetra, a material made from at least 70% plant-based ingredients, including viscose, wood pulp, and bio-based polyurethane. The bi-material sole combines an EVA-filled interior for cushioning and a TPU exterior, featuring an Interlocking G pattern that creates a 3D effect. Elsewhere, Syntilay, a footwear company combining artificial intelligence with 3D printing, launched a range of custom-fit slides. These slides are designed using AI-generated 3D models, starting with sketch-based concepts that are refined through AI platforms and then transformed into digital 3D designs. The company offers sizing adjustments based on smartphone foot scans, which are integrated into the manufacturing process. Join our Additive Manufacturing Advantage (AMAA) event on July 10th, where AM leaders from Aerospace, Space, and Defense come together to share mission-critical insights. Online and free to attend.Secure your spot now. Who won the2024 3D Printing Industry Awards? Subscribe to the 3D Printing Industry newsletterto keep up with the latest 3D printing news. You can also follow us onLinkedIn, and subscribe to the 3D Printing Industry Youtube channel to access more exclusive content. Featured image shows Nike’s 3D printed Air Max 1000 Oatmeal. Photo via Janelle C. Shuttlesworth. Paloma Duran Paloma Duran holds a BA in International Relations and an MA in Journalism. Specializing in writing, podcasting, and content and event creation, she works across politics, energy, mining, and technology. With a passion for global trends, Paloma is particularly interested in the impact of technology like 3D printing on shaping our future.
    0 Комментарии 0 Поделились
  • From Networks to Business Models, AI Is Rewiring Telecom

    Artificial intelligence is already rewriting the rules of wireless and telecom — powering predictive maintenance, streamlining network operations, and enabling more innovative services.
    As AI scales, the disruption will be faster, deeper, and harder to reverse than any prior shift in the industry.
    Compared to the sweeping changes AI is set to unleash, past telecom innovations look incremental.
    AI is redefining how networks operate, services are delivered, and data is secured — across every device and digital touchpoint.
    AI Is Reshaping Wireless Networks Already
    Artificial intelligence is already transforming wireless through smarter private networks, fixed wireless access, and intelligent automation across the stack.
    AI detects and resolves network issues before they impact service, improving uptime and customer satisfaction. It’s also opening the door to entirely new revenue streams and business models.
    Each wireless generation brought new capabilities. AI, however, marks a more profound shift — networks that think, respond, and evolve in real time.
    AI Acceleration Will Outpace Past Tech Shifts
    Many may underestimate the speed and magnitude of AI-driven change.
    The shift from traditional voice and data systems to AI-driven network intelligence is already underway.
    Although predictions abound, the true scope remains unclear.
    It’s tempting to assume we understand AI’s trajectory, but history suggests otherwise.

    Today, AI is already automating maintenance and optimizing performance without user disruption. The technologies we’ll rely on in the near future may still be on the drawing board.
    Few predicted that smartphones would emerge from analog beginnings—a reminder of how quickly foundational technologies can be reimagined.
    History shows that disruptive technologies rarely follow predictable paths — and AI is no exception. It’s already upending business models across industries.
    Technological shifts bring both new opportunities and complex trade-offs.
    AI Disruption Will Move Faster Than Ever
    The same cycle of reinvention is happening now — but with AI, it’s moving at unprecedented speed.
    Despite all the discussion, many still treat AI as a future concern — yet the shift is already well underway.
    As with every major technological leap, there will be gains and losses. The AI transition brings clear trade-offs: efficiency and innovation on one side, job displacement, and privacy erosion on the other.
    Unlike past tech waves that unfolded over decades, the AI shift will reshape industries in just a few years — and that change wave will only continue to move forward.
    AI Will Reshape All Sectors and Companies
    This shift will unfold faster than most organizations or individuals are prepared to handle.
    Today’s industries will likely look very different tomorrow. Entirely new sectors will emerge as legacy models become obsolete — redefining market leadership across industries.
    Telecom’s past holds a clear warning: market dominance can vanish quickly when companies ignore disruption.
    Eventually, the Baby Bells moved into long-distance service, while AT&T remained barred from selling local access — undermining its advantage.
    As the market shifted and competitors gained ground, AT&T lost its dominance and became vulnerable enough that SBC, a former regional Bell, acquired it and took on its name.

    It’s a case study of how incumbents fall when they fail to adapt — precisely the kind of pressure AI is now exerting across industries.
    SBC’s acquisition of AT&T flipped the power dynamic — proof that size doesn’t protect against disruption.
    The once-crowded telecom field has consolidated into just a few dominant players — each facing new threats from AI-native challengers.
    Legacy telecom models are being steadily displaced by faster, more flexible wireless, broadband, and streaming alternatives.
    No Industry Is Immune From AI Disruption
    AI will accelerate the next wave of industrial evolution — bringing innovations and consequences we’re only beginning to grasp.
    New winners will emerge as past leaders struggle to hang on — a shift that will also reshape the investment landscape. Startups leveraging AI will likely redefine leadership in sectors where incumbents have grown complacent.
    Nvidia’s rise is part of a broader trend: the next market leaders will emerge wherever AI creates a clear competitive advantage — whether in chips, code, or entirely new markets.
    The AI-driven future is arriving faster than most organizations are ready for. Adapting to this accelerating wave of change is no longer optional — it’s essential. Companies that act decisively today will define the winners of tomorrow.
    #networks #business #models #rewiring #telecom
    From Networks to Business Models, AI Is Rewiring Telecom
    Artificial intelligence is already rewriting the rules of wireless and telecom — powering predictive maintenance, streamlining network operations, and enabling more innovative services. As AI scales, the disruption will be faster, deeper, and harder to reverse than any prior shift in the industry. Compared to the sweeping changes AI is set to unleash, past telecom innovations look incremental. AI is redefining how networks operate, services are delivered, and data is secured — across every device and digital touchpoint. AI Is Reshaping Wireless Networks Already Artificial intelligence is already transforming wireless through smarter private networks, fixed wireless access, and intelligent automation across the stack. AI detects and resolves network issues before they impact service, improving uptime and customer satisfaction. It’s also opening the door to entirely new revenue streams and business models. Each wireless generation brought new capabilities. AI, however, marks a more profound shift — networks that think, respond, and evolve in real time. AI Acceleration Will Outpace Past Tech Shifts Many may underestimate the speed and magnitude of AI-driven change. The shift from traditional voice and data systems to AI-driven network intelligence is already underway. Although predictions abound, the true scope remains unclear. It’s tempting to assume we understand AI’s trajectory, but history suggests otherwise. Today, AI is already automating maintenance and optimizing performance without user disruption. The technologies we’ll rely on in the near future may still be on the drawing board. Few predicted that smartphones would emerge from analog beginnings—a reminder of how quickly foundational technologies can be reimagined. History shows that disruptive technologies rarely follow predictable paths — and AI is no exception. It’s already upending business models across industries. Technological shifts bring both new opportunities and complex trade-offs. AI Disruption Will Move Faster Than Ever The same cycle of reinvention is happening now — but with AI, it’s moving at unprecedented speed. Despite all the discussion, many still treat AI as a future concern — yet the shift is already well underway. As with every major technological leap, there will be gains and losses. The AI transition brings clear trade-offs: efficiency and innovation on one side, job displacement, and privacy erosion on the other. Unlike past tech waves that unfolded over decades, the AI shift will reshape industries in just a few years — and that change wave will only continue to move forward. AI Will Reshape All Sectors and Companies This shift will unfold faster than most organizations or individuals are prepared to handle. Today’s industries will likely look very different tomorrow. Entirely new sectors will emerge as legacy models become obsolete — redefining market leadership across industries. Telecom’s past holds a clear warning: market dominance can vanish quickly when companies ignore disruption. Eventually, the Baby Bells moved into long-distance service, while AT&T remained barred from selling local access — undermining its advantage. As the market shifted and competitors gained ground, AT&T lost its dominance and became vulnerable enough that SBC, a former regional Bell, acquired it and took on its name. It’s a case study of how incumbents fall when they fail to adapt — precisely the kind of pressure AI is now exerting across industries. SBC’s acquisition of AT&T flipped the power dynamic — proof that size doesn’t protect against disruption. The once-crowded telecom field has consolidated into just a few dominant players — each facing new threats from AI-native challengers. Legacy telecom models are being steadily displaced by faster, more flexible wireless, broadband, and streaming alternatives. No Industry Is Immune From AI Disruption AI will accelerate the next wave of industrial evolution — bringing innovations and consequences we’re only beginning to grasp. New winners will emerge as past leaders struggle to hang on — a shift that will also reshape the investment landscape. Startups leveraging AI will likely redefine leadership in sectors where incumbents have grown complacent. Nvidia’s rise is part of a broader trend: the next market leaders will emerge wherever AI creates a clear competitive advantage — whether in chips, code, or entirely new markets. The AI-driven future is arriving faster than most organizations are ready for. Adapting to this accelerating wave of change is no longer optional — it’s essential. Companies that act decisively today will define the winners of tomorrow. #networks #business #models #rewiring #telecom
    From Networks to Business Models, AI Is Rewiring Telecom
    Artificial intelligence is already rewriting the rules of wireless and telecom — powering predictive maintenance, streamlining network operations, and enabling more innovative services. As AI scales, the disruption will be faster, deeper, and harder to reverse than any prior shift in the industry. Compared to the sweeping changes AI is set to unleash, past telecom innovations look incremental. AI is redefining how networks operate, services are delivered, and data is secured — across every device and digital touchpoint. AI Is Reshaping Wireless Networks Already Artificial intelligence is already transforming wireless through smarter private networks, fixed wireless access (FWA), and intelligent automation across the stack. AI detects and resolves network issues before they impact service, improving uptime and customer satisfaction. It’s also opening the door to entirely new revenue streams and business models. Each wireless generation brought new capabilities. AI, however, marks a more profound shift — networks that think, respond, and evolve in real time. AI Acceleration Will Outpace Past Tech Shifts Many may underestimate the speed and magnitude of AI-driven change. The shift from traditional voice and data systems to AI-driven network intelligence is already underway. Although predictions abound, the true scope remains unclear. It’s tempting to assume we understand AI’s trajectory, but history suggests otherwise. Today, AI is already automating maintenance and optimizing performance without user disruption. The technologies we’ll rely on in the near future may still be on the drawing board. Few predicted that smartphones would emerge from analog beginnings—a reminder of how quickly foundational technologies can be reimagined. History shows that disruptive technologies rarely follow predictable paths — and AI is no exception. It’s already upending business models across industries. Technological shifts bring both new opportunities and complex trade-offs. AI Disruption Will Move Faster Than Ever The same cycle of reinvention is happening now — but with AI, it’s moving at unprecedented speed. Despite all the discussion, many still treat AI as a future concern — yet the shift is already well underway. As with every major technological leap, there will be gains and losses. The AI transition brings clear trade-offs: efficiency and innovation on one side, job displacement, and privacy erosion on the other. Unlike past tech waves that unfolded over decades, the AI shift will reshape industries in just a few years — and that change wave will only continue to move forward. AI Will Reshape All Sectors and Companies This shift will unfold faster than most organizations or individuals are prepared to handle. Today’s industries will likely look very different tomorrow. Entirely new sectors will emerge as legacy models become obsolete — redefining market leadership across industries. Telecom’s past holds a clear warning: market dominance can vanish quickly when companies ignore disruption. Eventually, the Baby Bells moved into long-distance service, while AT&T remained barred from selling local access — undermining its advantage. As the market shifted and competitors gained ground, AT&T lost its dominance and became vulnerable enough that SBC, a former regional Bell, acquired it and took on its name. It’s a case study of how incumbents fall when they fail to adapt — precisely the kind of pressure AI is now exerting across industries. SBC’s acquisition of AT&T flipped the power dynamic — proof that size doesn’t protect against disruption. The once-crowded telecom field has consolidated into just a few dominant players — each facing new threats from AI-native challengers. Legacy telecom models are being steadily displaced by faster, more flexible wireless, broadband, and streaming alternatives. No Industry Is Immune From AI Disruption AI will accelerate the next wave of industrial evolution — bringing innovations and consequences we’re only beginning to grasp. New winners will emerge as past leaders struggle to hang on — a shift that will also reshape the investment landscape. Startups leveraging AI will likely redefine leadership in sectors where incumbents have grown complacent. Nvidia’s rise is part of a broader trend: the next market leaders will emerge wherever AI creates a clear competitive advantage — whether in chips, code, or entirely new markets. The AI-driven future is arriving faster than most organizations are ready for. Adapting to this accelerating wave of change is no longer optional — it’s essential. Companies that act decisively today will define the winners of tomorrow.
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