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.

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

Telecom companies last year spent nearly $295 billion in capital expenditures and over $1 trillion in operating expenditures. These large expenses are due in part to laborious manual processes that telcos face when operating networks that require continuous optimizations. For example, telcos must constantly tune network parameters for tasks — such as transferring calls from one network to another or distributing network traffic across multiple servers — based on the time of day, user behavior, mobility and traffic type. These factors directly affect network performance, user experience and energy consumption. To automate these optimization processes and save costs for telcos across the globe, NVIDIA today unveiled at GTC Paris its first AI Blueprint for telco network configuration. At the blueprint’s core are customized large language models trained specifically on telco network data — as well as the full technical and operational architecture for turning the LLMs into an autonomous, goal-driven AI agent for telcos. Automate Network Configuration With the AI Blueprint NVIDIA AI Blueprints — available on build.nvidia.com — are customizable AI workflow examples. They include reference code, documentation and deployment tools that show enterprise developers how to deliver business value with NVIDIA NIM microservices. The AI Blueprint for telco network configuration — built with BubbleRAN 5G solutions and datasets — enables developers, network engineers and telecom providers to automatically optimize the configuration of network parameters using agentic AI. This can streamline operations, reduce costs and significantly improve service quality by embedding continuous learning and adaptability directly into network infrastructures. Traditionally, network configurations required manual intervention or followed rigid rules to adapt to dynamic network conditions. These approaches limited adaptability and increased operational complexities, costs and inefficiencies. The new blueprint helps shift telco operations from relying on static, rules-based systems to operations based on dynamic, AI-driven automation. It enables developers to build advanced, telco-specific AI agents that make real-time, intelligent decisions and autonomously balance trade-offs — such as network speed versus interference, or energy savings versus utilization — without human input. Powered and Deployed by Industry Leaders Trained on 5G data generated by BubbleRAN, and deployed on the BubbleRAN 5G O-RAN platform, the blueprint provides telcos with insight on how to set various parameters to reach performance goals, like achieving a certain bitrate while choosing an acceptable signal-to-noise ratio — a measure that impacts voice quality and thus user experience. With the new AI Blueprint, network engineers can confidently set initial parameter values and update them as demanded by continuous network changes. Norway-based Telenor Group, which serves over 200 million customers globally, is the first telco to integrate the AI Blueprint for telco network configuration as part of its initiative to deploy intelligent, autonomous networks that meet the performance and agility demands of 5G and beyond. “The blueprint is helping us address configuration challenges and enhance quality of service during network installation,” said Knut Fjellheim, chief technology innovation officer at Telenor Maritime. “Implementing it is part of our push toward network automation and follows the successful deployment of agentic AI for real-time network slicing in a private 5G maritime use case.” Industry Partners Deploy Other NVIDIA-Powered Autonomous Network Technologies The AI Blueprint for telco network configuration is just one of many announcements at NVIDIA GTC Paris showcasing how the telecom industry is using agentic AI to make autonomous networks a reality. Beyond the blueprint, leading telecom companies and solutions providers are tapping into NVIDIA accelerated computing, software and microservices to provide breakthrough innovations poised to vastly improve networks and communications services — accelerating the progress to autonomous networks and improving customer experiences. NTT DATA is powering its agentic platform for telcos with NVIDIA accelerated compute and the NVIDIA AI Enterprise software platform. Its first agentic use case is focused on network alarms management, where NVIDIA NIM microservices help automate and power observability, troubleshooting, anomaly detection and resolution with closed loop ticketing. Tata Consultancy Services is delivering agentic AI solutions for telcos built on NVIDIA DGX Cloud and using NVIDIA AI Enterprise to develop, fine-tune and integrate large telco models into AI agent workflows. These range from billing and revenue assurance, autonomous network management to hybrid edge-cloud distributed inference. For example, the company’s anomaly management agentic AI model includes real-time detection and resolution of network anomalies and service performance optimization. This increases business agility and improves operational efficiencies by up to 40% by eliminating human intensive toils, overheads and cross-departmental silos. Prodapt has introduced an autonomous operations workflow for networks, powered by NVIDIA AI Enterprise, that offers agentic AI capabilities to support autonomous telecom networks. AI agents can autonomously monitor networks, detect anomalies in real time, initiate diagnostics, analyze root causes of issues using historical data and correlation techniques, automatically execute corrective actions, and generate, enrich and assign incident tickets through integrated ticketing systems. Accenture announced its new portfolio of agentic AI solutions for telecommunications through its AI Refinery platform, built on NVIDIA AI Enterprise software and accelerated computing. The first available solution, the NOC Agentic App, boosts network operations center tasks by using a generative AI-driven, nonlinear agentic framework to automate processes such as incident and fault management, root cause analysis and configuration planning. Using the Llama 3.1 70B NVIDIA NIM microservice and the AI Refinery Distiller Framework, the NOC Agentic App orchestrates networks of intelligent agents for faster, more efficient decision-making. Infosys is announcing its agentic autonomous operations platform, called Infosys Smart Network Assurance (ISNA), designed to accelerate telecom operators’ journeys toward fully autonomous network operations. ISNA helps address long-standing operational challenges for telcos — such as limited automation and high average time to repair — with an integrated, AI-driven platform that reduces operational costs by up to 40% and shortens fault resolution times by up to 30%. NVIDIA NIM and NeMo microservices enhance the platform’s reasoning and hallucination-detection capabilities, reduce latency and increase accuracy. Get started with the new blueprint today. Learn more about the latest AI advancements for telecom and other industries at NVIDIA GTC Paris, running through Thursday, June 12, at VivaTech, including a keynote from NVIDIA founder and CEO Jensen Huang and a special address from Ronnie Vasishta, senior vice president of telecom at NVIDIA. Plus, hear from industry leaders in a panel session with Orange, Swisscom, Telenor and NVIDIA.

Riot Games has announced that it will begin officially sanctioning sports-betting sponsorships for esports teams in its Tier 1 League of Legends and Valorant leagues. While the company states that it still won't allow advertisements in its official broadcasts, teams themselves will be able to take money from sports-betting companies for advertising through their own channels.In a blog post, President of Publishing and Esports John Needham writes that the move is designed to take advantage of the rapidly growing sports-betting industry and to make esports-related betting more regulated. Seemingly to address concerns and head off potential criticism, Needham explains that the company is authorizing sports-betting sponsorships under a "guardrails first" strategy.These "guardrails," Needham states, are essentially the rules by which any sponsorship must be executed. First, sports-betting companies need to be vetted and approved by Riot itself, although the company has not shared the criteria on which this vetting is done. Second, to ensure that sports-betting companies are on a level playing field, Riot is mandating that official partners all use GRID, the officially sanctioned data platform for League of Legends and Valorant. Third, esports teams must launch and maintain internal integrity programs to protect against violations of league rules due to the influence of sports betting. Fourth and last, Riot will use some of the revenue from these sponsorships to support its Tier 2 (lower division) esports leagues.Continue Reading at GameSpot

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

Windows users will dread the familiar sight of the Blue Screen of Death (BSOD) whenever they encounter an error. But after nearly 40 years, Microsoft will be retiring this infamous error message, or rather giving it a new color.The company has redesigned the error screen to what will soon be known as the Black Screen of Death. Compared to the current screen, which includes a frowning emoticon and sometimes a QR code, this black screen is more simplified, listing the stop code and faulty system driver.In an interview with The Verge, Microsoft's vice president of enterprise and OS security David Weston said, “This is really an attempt on clarity and providing better information and allowing us and customers to really get to what the core of the issue is so we can fix it faster. Part of it is just cleaner information on what exactly went wrong, where it’s Windows versus a component.”Continue Reading at GameSpot

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

To speed up AI adoption across industries, HPE and NVIDIA today launched new AI factory offerings at HPE Discover in Las Vegas. The new lineup includes everything from modular AI factory infrastructure and HPE’s AI-ready RTX PRO Servers (HPE ProLiant Compute DL380a Gen12), to the next generation of HPE’s turnkey AI platform, HPE Private Cloud AI. The goal: give enterprises a framework to build and scale generative, agentic and industrial AI. The NVIDIA AI Computing by HPE portfolio is now among the broadest in the market. The portfolio combines NVIDIA Blackwell accelerated computing, NVIDIA Spectrum-X Ethernet and NVIDIA BlueField-3 networking technologies, NVIDIA AI Enterprise software and HPE’s full portfolio of servers, storage, services and software. This now includes HPE OpsRamp Software, a validated observability solution for the NVIDIA Enterprise AI Factory, and HPE Morpheus Enterprise Software for orchestration. The result is a pre-integrated, modular infrastructure stack to help teams get AI into production faster. This includes the next-generation HPE Private Cloud AI, co-engineered with NVIDIA and validated as part of the NVIDIA Enterprise AI Factory framework. This full-stack, turnkey AI factory solution will offer HPE ProLiant Compute DL380a Gen12 servers with the new NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs. These new NVIDIA RTX PRO Servers from HPE provide a universal data center platform for a wide range of enterprise AI and industrial AI use cases, and are now available to order from HPE. HPE Private Cloud AI includes the latest NVIDIA AI Blueprints, including the NVIDIA AI-Q Blueprint for AI agent creation and workflows. HPE also announced a new NVIDIA HGX B300 system, the HPE Compute XD690, built with NVIDIA Blackwell Ultra GPUs. It’s the latest entry in the NVIDIA AI Computing by HPE lineup and is expected to ship in October. In Japan, KDDI is working with HPE to build NVIDIA AI infrastructure to accelerate global adoption. The HPE-built KDDI system will be based on the NVIDIA GB200 NVL72 platform, built on the NVIDIA Grace Blackwell architecture, at the KDDI Osaka Sakai Data Center. To accelerate AI for financial services, HPE will co-test agentic AI workflows built on Accenture’s AI Refinery with NVIDIA, running on HPE Private Cloud AI. Initial use cases include sourcing, procurement and risk analysis. HPE said it’s adding 26 new partners to its “Unleash AI” ecosystem to support more NVIDIA AI use cases. The company now offers more than 70 packaged AI workloads, from fraud detection and video analytics to sovereign AI and cybersecurity. Security and governance were a focus, too. HPE Private Cloud AI supports air-gapped management, multi-tenancy and post-quantum cryptography. HPE’s try-before-you-buy program lets customers test the system in Equinix data centers before purchase. HPE also introduced new programs, including AI Acceleration Workshops with NVIDIA, to help scale AI deployments. Watch the keynote: HPE CEO Antonio Neri announced the news from the Las Vegas Sphere on Tuesday at 9 a.m. PT. Register for the livestream and watch the replay. Explore more: Learn how NVIDIA and HPE build AI factories for every industry. Visit the partner page.

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

By TREVOR HOGG Images courtesy of Prime Video. For those seeking an alternative to the MCU, Prime Video has two offerings of the live-action and animated variety that take the superhero genre into R-rated territory where the hands of the god-like figures get dirty, bloodied and severed. “The Boys is about the intersection of celebrity and politics using superheroes,” states Stephan Fleet, VFX Supervisor on The Boys. “Sometimes I see the news and I don’t even know we can write to catch up to it! But we try. Invincible is an intense look at an alternate DC Universe that has more grit to the superhero side of it all. On one hand, I was jealous watching Season 1 of Invincible because in animation you can do things that you can’t do in real life on a budget.” Season 4 does not tone down the blood, gore and body count. Fleet notes, “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” When Splinter (Rob Benedict) splits in two, the cloning effect was inspired by cellular mitosis. “The writers almost have this dialogue with us. Sometimes, they’ll write in the script, ‘And Fleet will come up with a cool visual effect for how to kill this person.’ Or, ‘Chhiu, our fight coordinator, will make an awesome fight.’ It is a frequent topic of conversation. We’re constantly trying to be inventive and create new ways to kill people!” —Stephan Fleet, VFX Supervisor A total of 1,600 visual effects shots were created for the eight episodes by ILM, Pixomondo, MPC Toronto, Spin VFX, DNEG, Untold Studios, Luma Pictures and Rocket Science VFX. Previs was a critical part of the process. “We have John Griffith [Previs Director], who owns a small company called CNCPT out of Texas, and he does wonderful Unreal Engine level previs,” Fleet remarks. “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” Founding Director of Federal Bureau of Superhuman Affairs, Victoria Neuman, literally gets ripped in half by two tendrils coming out of Compound V-enhanced Billy Butcher, the leader of superhero resistance group The Boys. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” Multiple plates were shot to enable Simon Pegg to phase through the actor laying in a hospital bed. Testing can get rather elaborate. “For that end scene with Butcher’s tendrils, the room was two stories, and we were able to put the camera up high along with a bunch of blood cannons,” Fleet recalls. “When the body rips in half and explodes, there is a practical component. We rained down a bunch of real blood and guts right in front of Huey. It’s a known joke that we like to douse Jack Quaid with blood as much as possible! In this case, the special effects team led by Hudson Kenny needed to test it the day before, and I said, “I’ll be the guinea pig for the test.’ They covered the whole place with plastic like it was a Dexter kill room because you don’t want to destroy the set. I’m standing there in a white hazmat suit with goggles on, covered from head to toe in plastic and waiting as they’re tweaking all of these things. It sounds like World War II going on. They’re on walkie talkies to each other, and then all of a sudden, it’s ‘Five, four, three, two, one…’  And I get exploded with blood. I wanted to see what it was like, and it’s intense.” “On set, we have a cartoon of what is going to be done, and you’ll be amazed, specifically for action and heavy visual effects stuff, how close those shots are to the previs when we finish.” —Stephan Fleet, VFX Supervisor The Deep has a love affair with an octopus called Ambrosius, voiced by Tilda Swinton. “It’s implied bestiality!” Fleet laughs. “I would call it more of a romance. What was fun from my perspective is that I knew what the look was going to be [from Season 3], so then it’s about putting in the details and the animation. One of the instincts that you always have when you’re making a sea creature that talks to a human [is] you tend to want to give it human gestures and eyebrows. Erik Kripke [Creator, Executive Producer, Showrunner, Director, Writer] said, ‘No. We have to find things that an octopus could do that conveys the same emotion.’ That’s when ideas came in, such as putting a little The Deep toy inside the water tank. When Ambrosius is trying to have an intimate moment or connect with him, she can wrap a tentacle around that. My favorite experience doing Ambrosius was when The Deep is reading poetry to her on a bed. CG creatures touching humans is one of the more complicated things to do and make look real. Ambrosius’ tentacles reach for his arm, and it becomes an intimate moment. More than touching the skin, displacing the bedsheet as Ambrosius moved ended up becoming a lot of CG, and we had to go back and forth a few times to get that looking right; that turned out to be tricky.” A building is replaced by a massive crowd attending a rally being held by Homelander. In a twisted form of sexual foreplay, Sister Sage has The Deep perform a transorbital lobotomy on her. “Thank you, Amazon for selling lobotomy tools as novelty items!” Fleet chuckles. “We filmed it with a lobotomy tool on set. There is a lot of safety involved in doing something like that. Obviously, you don’t want to put any performer in any situation where they come close to putting anything real near their eye. We created this half lobotomy tool and did this complicated split screen with the lobotomy tool on a teeter totter. The Deep was [acting in a certain way] in one shot and Sister Sage reacted in the other shot. To marry the two ended up being a lot of CG work. Then there are these close-ups which are full CG. I always keep a dummy head that is painted gray that I use all of the time for reference. In macrophotography I filmed this lobotomy tool going right into the eye area. I did that because the tool is chrome, so it’s reflective and has ridges. It has an interesting reflective property. I was able to see how and what part of the human eye reflects onto the tool. A lot of that shot became about realistic reflections and lighting on the tool. Then heavy CG for displacing the eye and pushing the lobotomy tool into it. That was one of the more complicated sequences that we had to achieve.” In order to create an intimate moment between Ambrosius and The Deep, a toy version of the superhero was placed inside of the water tank that she could wrap a tentacle around. “The word that we like to use on this show is ‘grounded,’ and I like to say ‘grounded’ with an asterisk in this day and age because we’re grounded until we get to killing people in the craziest ways. In this case, having someone floating in the air and being ripped in half by two tendrils was all CG.” —Stephan Fleet, VFX Supervisor Sheep and chickens embark on a violent rampage courtesy of Compound V with the latter piercing the chest of a bodyguard belonging to Victoria Neuman. “Weirdly, that was one of our more traditional shots,’ Fleet states. “What is fun about that one is I asked for real chickens as reference. The chicken flying through his chest is real. It’s our chicken wrangler in green suit gently tossing a chicken. We blended two real plates together with some CG in the middle.” A connection was made with a sci-fi classic. “The sheep kill this bull, and we shot it is in this narrow corridor of fencing. When they run, I always equated it as the Trench Run in Star Wars and looked at the sheep as TIE fighters or X-wings coming at them.” The scene was one of the scarier moments for the visual effects team. Fleet explains, “When I read the script, I thought this could be the moment where we jump the shark. For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” The sheep injected with Compound V develop the ability to fly and were shot in an imperfect manner to help ground the scenes. Once injected with Compound V, Hugh Campbell Sr. (Simon Pegg) develops the ability to phase through objects, including human beings. “We called it the Bro-nut because his name in the script is Wall Street Bro,” Fleet notes. “That was a complicated motion control shot, repeating the move over and over again. We had to shoot multiple plates of Simon Pegg and the guy in the bed. Special effects and prosthetics created a dummy guy with a hole in his chest with practical blood dripping down. It was meshing it together and getting the timing right in post. On top of that, there was the CG blood immediately around Simon Pegg.” The phasing effect had to avoid appearing as a dissolve. “I had this idea of doing high-frequency vibration on the X axis loosely based on how The Flash vibrates through walls. You want everything to have a loose motivation that then helps trigger the visuals. We tried not to overcomplicate that because, ultimately, you want something like that to be quick. If you spend too much time on phasing, it can look cheesy. In our case, it was a lot of false walls. Simon Pegg is running into a greenscreen hole which we plug in with a wall or coming out of one. I went off the actor’s action, and we added a light opacity mix with some X-axis shake.” Providing a different twist to the fights was the replacement of spurting blood with photoreal rubber duckies during a drug-induced hallucination. Homelander (Anthony Starr) breaks a mirror which emphasizes his multiple personality disorder. “The original plan was that special effects was going to pre-break a mirror, and we were going to shoot Anthony Starr moving his head doing all of the performances in the different parts of the mirror,” Fleet reveals. “This was all based on a photo that my ex-brother-in-law sent me. He was walking down a street in Glendale, California, came across a broken mirror that someone had thrown out, and took a photo of himself where he had five heads in the mirror. We get there on the day, and I’m realizing that this is really complicated. Anthony has to do these five different performances, and we have to deal with infinite mirrors. At the last minute, I said, ‘We have to do this on a clean mirror.’ We did it on a clear mirror and gave Anthony different eyelines. The mirror break was all done in post, and we were able to cheat his head slightly and art-direct where the break crosses his chin. Editorial was able to do split screens for the timing of the dialogue.” “For the shots where the sheep are still and scream to the camera, Untold Studios did a bunch of R&D and came up with baboon teeth. I tried to keep anything real as much as possible, but, obviously, when sheep are flying, they have to be CG. I call it the Battlestar Galactica theory, where I like to shake the camera, overshoot shots and make it sloppy when they’re in the air so you can add motion blur. Comedy also helps sell visual effects.” —Stephan Fleet, VFX Supervisor Initially, the plan was to use a practical mirror, but creating a digital version proved to be the more effective solution. A different spin on the bloodbath occurs during a fight when a drugged Frenchie (Tomer Capone) hallucinates as Kimiko Miyashiro (Karen Fukuhara) goes on a killing spree. “We went back and forth with a lot of different concepts for what this hallucination would be,” Fleet remarks. “When we filmed it, we landed on Frenchie having a synesthesia moment where he’s seeing a lot of abstract colors flying in the air. We started getting into that in post and it wasn’t working. We went back to the rubber duckies, which goes back to the story of him in the bathtub. What’s in the bathtub? Rubber duckies, bubbles and water. There was a lot of physics and logic required to figure out how these rubber duckies could float out of someone’s neck. We decided on bubbles when Kimiko hits people’s heads. At one point, we had water when she got shot, but it wasn’t working, so we killed it. We probably did about 100 different versions. We got really detailed with our rubber duckie modeling because we didn’t want it to look cartoony. That took a long time.” Ambrosius, voiced by Tilda Swinton, gets a lot more screentime in Season 4. When Splinter (Rob Benedict) splits in two was achieved heavily in CG. “Erik threw out the words ‘cellular mitosis’ early on as something he wanted to use,” Fleet states. “We shot Rob Benedict on a greenscreen doing all of the different performances for the clones that pop out. It was a crazy amount of CG work with Houdini and particle and skin effects. We previs’d the sequence so we had specific actions. One clone comes out to the right and the other pulls backwards.” What tends to go unnoticed by many is Splinter’s clones setting up for a press conference being held by Firecracker (Valorie Curry). “It’s funny how no one brings up the 22-hour motion control shot that we had to do with Splinter on the stage, which was the most complicated shot!” Fleet observes. “We have this sweeping long shot that brings you into the room and follows Splinter as he carries a container to the stage and hands it off to a clone, and then you reveal five more of them interweaving each other and interacting with all of these objects. It’s like a minute-long dance. First off, you have to choreograph it. We previs’d it, but then you need to get people to do it. We hired dancers and put different colored armbands on them. The camera is like another performer, and a metronome is going, which enables you to find a pace. That took about eight hours of rehearsal. Then Rob has to watch each one of their performances and mimic it to the beat. When he is handing off a box of cables, it’s to a double who is going to have to be erased and be him on the other side. They have to be almost perfect in their timing and lineup in order to take it over in visual effects and make it work.”