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. 

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

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While IO Interactive may be heavily focused on its inaugural James Bond game, 2026’s 007 First Light, it’s still providing ambitious new levels and updates for Hitman: World of Assassination and its new science fiction action game MindsEye. To continue to build hype for First Light and IOI’s growing partnership with the James Bond brand, the latest World of Assassination level is a Bond crossover, as Hitman protagonist Agent 47 targets Le Chiffre, the main villain of the 2006 movie Casino Royale. Available through July 6, 2025, the Le Chiffre event in World of Assassination features actor Mads Mikkelsen reprising his fan-favorite Bond villain role, not only providing his likeness but voicing the character as he confronts the contract killer in France. Den of Geek attended the first-ever in-person IO Interactive Showcase, a partner event with Summer Game Fest held at The Roosevelt Hotel in Hollywood. Mikkelsen and the developers shared insight on the surprise new World of Assassination level, with the level itself playable in its entirety to attendees on the Nintendo Switch 2 and PlayStation Portal. The developers also included an extended gameplay preview for MindsEye, ahead of its June 10 launch, while sharing some details about the techno-thriller. Matching his background from Casino Royale, Le Chiffre is a terrorist financier who manipulates the stock market by any means necessary to benefit himself and his clients. After an investment deal goes wrong, Le Chiffre tries to recoup a brutal client’s losses through a high-stakes poker game in France, with Agent 47 hired to assassinate the criminal mastermind on behalf of an unidentified backer. The level opens with 47 infiltrating a high society gala linked to the poker game, with the contract killer entering under his oft-used assumed name of Tobias Rieper, a facade that Le Chiffre immediately sees through. At the IO Interactive Showcase panel, Mikkelsen observed that the character of Le Chiffre is always one that he enjoyed and held a special place for him and his career. Reprising his villainous role also gave Mikkelsen the chance to reunite with longtime Agent 47 voice actor David Bateson since their ‘90s short film Tom Merritt, though both actors recorded their respective lines separately. Mikkelsen enjoyed that Le Chiffre’s appearance in World of Assassination gave him a more physical role than he had in Casino Royale, rather than largely placing him at a poker table. Of course, like most Hitman levels, there are multiple different ways that players can accomplish their main objective of killing Le Chiffre and escaping the premises. The game certainly gives players multiple avenues to confront the evil financier over a game of poker before closing in for the kill, but it’s by no means the only way to successfully assassinate him. We won’t give away how we ultimately pulled off the assassination, but rest assured that it took multiple tries, careful plotting, and with all the usual trial-and-error that comes from playing one of Hitman’s more difficult and immersively involved levels. Moving away from its more grounded action titles, IO Interactive also provided a deeper look at its new sci-fi game MindsEye, developed by Build a Rocket Boy. Set in the fictional Redrock City, the extended gameplay sneak peek at the showcase featured protagonist Adam Diaz fighting shadowy enemies in the futuristic city’s largely abandoned streets. While there were no hands-on demos at the showcase itself, the preview demonstrated Diaz using his abilities and equipment, including an accompanying drone, to navigate the city from a third-person perspective and use an array of weapons to dispatch those trying to hunt him down. MindsEye marks the first game published through IOI Partners, an initiative that has IOI publish games from smaller, external developers. The game did not have a hands-on demo at the showcase and, given its bug-heavy and poorly-received launch, this distinction is not particularly surprising. Build a Robot Boy has since pledged to support the game through June to fix its technical issues but, given the game’s hands-on access at the IOI Showcase, there were already red flags surrounding the game’s performance. With that in mind, most of the buzz at the showcase was unsurprisingly centered around 007 First Light and updates to Hitman: World of Assassination, and IO Interactive did not disappoint in that regard. Even with Hitman: World of Assassination over four years old now, the game continues to receive impressive post-release support from IO Interactive, both in bringing the title to the Nintendo Switch 2 and with additional DLC. At the showcase, IOI hinted at additional special levels for World of Assassintation with high-profile guest targets like Le Chiffre, without identifying who or if they’re also explicitly tied to the James Bond franchise. But with 007 First Light slated for its eagerly anticipated launch next year, it’s a safe bet that IOI has further plans to hype its own role in building out the James Bond legacy for the foreseeable future. The Hitman: World of Assassination special Le Chiffre level is available now through July 6, 2025 on all the game’s major platforms, including the Nintendo Switch 2. MindsEye is now on sale for PlayStation 5, Xbox Series X|S, and PC.

Generative AI has reshaped how people create, imagine and interact with digital content. As AI models continue to grow in capability and complexity, they require more VRAM, or video random access memory. The base Stable Diffusion 3.5 Large model, for example, uses over 18GB of VRAM — limiting the number of systems that can run it well. By applying quantization to the model, noncritical layers can be removed or run with lower precision. NVIDIA GeForce RTX 40 Series and the Ada Lovelace generation of NVIDIA RTX PRO GPUs support FP8 quantization to help run these quantized models, and the latest-generation NVIDIA Blackwell GPUs also add support for FP4. NVIDIA collaborated with Stability AI to quantize its latest model, Stable Diffusion (SD) 3.5 Large, to FP8 — reducing VRAM consumption by 40%. Further optimizations to SD3.5 Large and Medium with the NVIDIA TensorRT software development kit (SDK) double performance. In addition, TensorRT has been reimagined for RTX AI PCs, combining its industry-leading performance with just-in-time (JIT), on-device engine building and an 8x smaller package size for seamless AI deployment to more than 100 million RTX AI PCs. TensorRT for RTX is now available as a standalone SDK for developers. RTX-Accelerated AI NVIDIA and Stability AI are boosting the performance and reducing the VRAM requirements of Stable Diffusion 3.5, one of the world’s most popular AI image models. With NVIDIA TensorRT acceleration and quantization, users can now generate and edit images faster and more efficiently on NVIDIA RTX GPUs. Stable Diffusion 3.5 quantized FP8 (right) generates images in half the time with similar quality as FP16 (left). Prompt: A serene mountain lake at sunrise, crystal clear water reflecting snow-capped peaks, lush pine trees along the shore, soft morning mist, photorealistic, vibrant colors, high resolution. To address the VRAM limitations of SD3.5 Large, the model was quantized with TensorRT to FP8, reducing the VRAM requirement by 40% to 11GB. This means five GeForce RTX 50 Series GPUs can run the model from memory instead of just one. SD3.5 Large and Medium models were also optimized with TensorRT, an AI backend for taking full advantage of Tensor Cores. TensorRT optimizes a model’s weights and graph — the instructions on how to run a model — specifically for RTX GPUs. FP8 TensorRT boosts SD3.5 Large performance by 2.3x vs. BF16 PyTorch, with 40% less memory use. For SD3.5 Medium, BF16 TensorRT delivers a 1.7x speedup. Combined, FP8 TensorRT delivers a 2.3x performance boost on SD3.5 Large compared with running the original models in BF16 PyTorch, while using 40% less memory. And in SD3.5 Medium, BF16 TensorRT provides a 1.7x performance increase compared with BF16 PyTorch. The optimized models are now available on Stability AI’s Hugging Face page. NVIDIA and Stability AI are also collaborating to release SD3.5 as an NVIDIA NIM microservice, making it easier for creators and developers to access and deploy the model for a wide range of applications. The NIM microservice is expected to be released in July. TensorRT for RTX SDK Released Announced at Microsoft Build — and already available as part of the new Windows ML framework in preview — TensorRT for RTX is now available as a standalone SDK for developers. Previously, developers needed to pre-generate and package TensorRT engines for each class of GPU — a process that would yield GPU-specific optimizations but required significant time. With the new version of TensorRT, developers can create a generic TensorRT engine that’s optimized on device in seconds. This JIT compilation approach can be done in the background during installation or when they first use the feature. The easy-to-integrate SDK is now 8x smaller and can be invoked through Windows ML — Microsoft’s new AI inference backend in Windows. Developers can download the new standalone SDK from the NVIDIA Developer page or test it in the Windows ML preview. For more details, read this NVIDIA technical blog and this Microsoft Build recap. Join NVIDIA at GTC Paris At NVIDIA GTC Paris at VivaTech — Europe’s biggest startup and tech event — NVIDIA founder and CEO Jensen Huang yesterday delivered a keynote address on the latest breakthroughs in cloud AI infrastructure, agentic AI and physical AI. Watch a replay. GTC Paris runs through Thursday, June 12, with hands-on demos and sessions led by industry leaders. Whether attending in person or joining online, there’s still plenty to explore at the event. Each week, the RTX AI Garage blog series features community-driven AI innovations and content for those looking to learn more about NVIDIA NIM microservices and AI Blueprints, as well as building AI agents, creative workflows, digital humans, productivity apps and more on AI PCs and workstations.  Plug in to NVIDIA AI PC on Facebook, Instagram, TikTok and X — and stay informed by subscribing to the RTX AI PC newsletter. Follow NVIDIA Workstation on LinkedIn and X.  See notice regarding software product information.

When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Microsoft accidentally replaced Windows 11 startup sound with one from Vista Taras Buria Neowin @TarasBuria · Jun 14, 2025 14:46 EDT The recently released Windows 11 Dev and Beta builds introduced some welcome changes and improvements. However, those preview builds are not flawless and have a pretty long list of known issues. One of those issues, though, is a rather delightful one: Windows 11's default startup jingle has been accidentally replaced with one from 2006. After Windows Insiders discovered that Windows 11 now plays the Windows Vista startup sound and reported it to Microsoft, the company acknowledged it and added it to the list of known bugs in the latest Windows 11 Dev and Beta builds: This week’s flight comes with a delightful blast from the past and will play the Windows Vista boot sound instead of the Windows 11 boot sound. We’re working on a fix. Although Windows Vista is nearly two decades old, it was brought to everyone's attention this week after Apple introduced macOS 26 Tahoe with its controversial "Liquid Glass" redesign, which many consider a rather miserable remix of Windows Aero from Windows Vista and Windows 7. While it is definitely an interesting coincidence, Microsoft did not intentionally replace the startup sound in Windows 11 preview builds. Brandon LeBlanc from the Windows Insider team confirmed in his X that that is a bug after joking about everyone talking about Windows Vista once again in light of Apple's latest announcements: It is worth noting that if you miss the startup sound of Windows Vista, you can still use it in modern Windows versions. All it takes is the original WAV file and a few clicks in the Windows Registry and Sound settings. And for those who want a shot of nostalgia, here is the sound of Windows Vista startup: What startup jingle do you like more: Windows Vista or Windows 11? Share your thoughts in the comments. Tags Report a problem with article Follow @NeowinFeed

Outdated coding practices and memory-unsafe languages like C are putting software, including cryptographic libraries, at risk. Fortunately, memory-safe languages like Rust, along with formal verification tools, are now mature enough to be used at scale, helping prevent issues like crashes, data corruption, flawed implementation, and side-channel attacks. To address these vulnerabilities and improve memory safety, we’re rewriting SymCrypt (opens in new tab)—Microsoft’s open-source cryptographic library—in Rust. We’re also incorporating formal verification methods. SymCrypt is used in Windows, Azure Linux, Xbox, and other platforms. Currently, SymCrypt is primarily written in cross-platform C, with limited use of hardware-specific optimizations through intrinsics (compiler-provided low-level functions) and assembly language (direct processor instructions). It provides a wide range of algorithms, including AES-GCM, SHA, ECDSA, and the more recent post-quantum algorithms ML-KEM and ML-DSA.  Formal verification will confirm that implementations behave as intended and don’t deviate from algorithm specifications, critical for preventing attacks. We’ll also analyze compiled code to detect side-channel leaks caused by timing or hardware-level behavior. Proving Rust program properties with Aeneas Program verification is the process of proving that a piece of code will always satisfy a given property, no matter the input. Rust’s type system profoundly improves the prospects for program verification by providing strong ownership guarantees, by construction, using a discipline known as “aliasing xor mutability”. For example, reasoning about C code often requires proving that two non-const pointers are live and non-overlapping, a property that can depend on external client code. In contrast, Rust’s type system guarantees this property for any two mutably borrowed references. As a result, new tools have emerged specifically for verifying Rust code. We chose Aeneas (opens in new tab) because it helps provide a clean separation between code and proofs. Developed by Microsoft Azure Research in partnership with Inria, the French National Institute for Research in Digital Science and Technology, Aeneas connects to proof assistants like Lean (opens in new tab), allowing us to draw on a large body of mathematical proofs—especially valuable given the mathematical nature of cryptographic algorithms—and benefit from Lean’s active user community. Compiling Rust to C supports backward compatibility   We recognize that switching to Rust isn’t feasible for all use cases, so we’ll continue to support, extend, and certify C-based APIs as long as users need them. Users won’t see any changes, as Rust runs underneath the existing C APIs. Some users compile our C code directly and may rely on specific toolchains or compiler features that complicate the adoption of Rust code. To address this, we will use Eurydice (opens in new tab), a Rust-to-C compiler developed by Microsoft Azure Research, to replace handwritten C code with C generated from formally verified Rust. Eurydice (opens in new tab) compiles directly from Rust’s MIR intermediate language, and the resulting C code will be checked into the SymCrypt repository alongside the original Rust source code. As more users adopt Rust, we’ll continue supporting this compilation path for those who build SymCrypt from source code but aren’t ready to use the Rust compiler. In the long term, we hope to transition users to either use precompiled SymCrypt binaries (via C or Rust APIs), or compile from source code in Rust, at which point the Rust-to-C compilation path will no longer be needed. Microsoft research podcast Ideas: AI and democracy with Madeleine Daepp and Robert Osazuwa Ness As the “biggest election year in history” comes to an end, researchers Madeleine Daepp and Robert Osazuwa Ness and Democracy Forward GM Ginny Badanes discuss AI’s impact on democracy, including the tech’s use in Taiwan and India. Listen now Opens in a new tab Timing analysis with Revizor  Even software that has been verified for functional correctness can remain vulnerable to low-level security threats, such as side channels caused by timing leaks or speculative execution. These threats operate at the hardware level and can leak private information, such as memory load addresses, branch targets, or division operands, even when the source code is provably correct.  To address this, we’re extending Revizor (opens in new tab), a tool developed by Microsoft Azure Research, to more effectively analyze SymCrypt binaries. Revizor models microarchitectural leakage and uses fuzzing techniques to systematically uncover instructions that may expose private information through known hardware-level effects.   Earlier cryptographic libraries relied on constant-time programming to avoid operations on secret data. However, recent research has shown that this alone is insufficient with today’s CPUs, where every new optimization may open a new side channel.  By analyzing binary code for specific compilers and platforms, our extended Revizor tool enables deeper scrutiny of vulnerabilities that aren’t visible in the source code. Verified Rust implementations begin with ML-KEM This long-term effort is in alignment with the Microsoft Secure Future Initiative and brings together experts across Microsoft, building on decades of Microsoft Research investment in program verification and security tooling. A preliminary version of ML-KEM in Rust is now available on the preview feature/verifiedcrypto (opens in new tab) branch of the SymCrypt repository. We encourage users to try the Rust build and share feedback (opens in new tab). Looking ahead, we plan to support direct use of the same cryptographic library in Rust without requiring C bindings.  Over the coming months, we plan to rewrite, verify, and ship several algorithms in Rust as part of SymCrypt. As our investment in Rust deepens, we expect to gain new insights into how to best leverage the language for high-assurance cryptographic implementations with low-level optimizations.  As performance is key to scalability and sustainability, we’re holding new implementations to a high bar using our benchmarking tools to match or exceed existing systems. Looking forward  This is a pivotal moment for high-assurance software. Microsoft’s investment in Rust and formal verification presents a rare opportunity to advance one of our key libraries. We’re excited to scale this work and ultimately deliver an industrial-grade, Rust-based, FIPS-certified cryptographic library. Opens in a new tab

“Wait, can users actually add products to the cart?”Every prototype faces that question or one like it. You start to explain it’s “just Figma,” “just dummy data,” but what if you didn’t need disclaimers?What if you could hand clients—or your team—a working, data-connected mock-up of their website, or new pages and components, in less time than it takes to wireframe?That’s the challenge we’ll tackle today. But first, we need to look at:The problem with today’s prototyping toolsPick two: speed, flexibility, or interactivity.The prototyping ecosystem, despite having amazing software that addresses a huge variety of needs, doesn’t really have one tool that gives you all three.Wireframing apps let you draw boxes in minutes but every button is fake. Drag-and-drop builders animate scroll triggers until you ask for anything off-template. Custom code frees you… after you wave goodbye to a few afternoons.AI tools haven’t smashed the trade-off; they’ve just dressed it in flashier costumes. One prompt births a landing page, the next dumps a 2,000-line, worse-than-junior-level React file in your lap. The bottleneck is still there. Builder’s approach to website mockupsWe’ve been trying something a little different to maintain speed, flexibility, and interactivity while mocking full websites. Our AI-driven visual editor:Spins up a repo in seconds or connects to your existing one to use the code as design inspiration. React, Vue, Angular, and Svelte all work out of the box. Lets you shape components via plain English, visual edits, copy/pasted Figma frames, web inspos, MCP tools, and constant visual awareness of your entire website. Commits each change as a clean GitHub pull request your team can review like hand-written code. All your usual CI checks and lint rules apply.And if you need a tweak, you can comment to @builderio-bot right in the GitHub PR to make asynchronous changes without context switching.This results in a live site the café owner can interact with today, and a branch your devs can merge tomorrow. Stakeholders get to click actual buttons and trigger real state—no more “so, just imagine this works” demos.Let’s see it in action.From blank canvas to working mockup in five promptsToday, I’m going to mock up a fake business website. You’re welcome to create a real one.Before we fire off a single prompt, grab a note and write:Business name & vibe Core pages Primary goal Brand palette & toneThat’s it. Don’t sweat the details—we can always iterate. For mine, I wrote:1. Sunny Trails Bakery — family-owned, feel-good, smells like warm cinnamon. 2. Home, About, Pricing / Subscription Box, Menu (with daily specials). 3. Drive online orders and foot traffic—every CTA should funnel toward “Order Now” or “Reserve a Table.” 4. Warm yellow, chocolate brown, rounded typography, playful copy.We’re not trying to fit everything here. What matters is clarity on what we’re creating, so the AI has enough context to produce usable scaffolds, and so later tweaks stay aligned with the client’s vision. Builder will default to using React, Vite, and Tailwind. If you want a different JS framework, you can link an existing repo in that stack. In the near future, you won’t need to do this extra step to get non-React frameworks to function.(Free tier Builder gives you 5 AI credits/day and 25/month—plenty to follow along with today’s demo. Upgrade only when you need it.)An entire website from the first promptNow, we’re ready to get going.Head over to Builder.io and paste in this prompt or your own:Create a cozy bakery website called “Sunny Trails Bakery” with pages for: • Home • About • Pricing • Menu Brand palette: warm yellow and chocolate brown. Tone: playful, inviting. The restaurant is family-owned, feel-good, and smells like cinnamon. The goal of this site is to drive online orders and foot traffic—every CTA should funnel toward "Order Now" or "Reserve a Table."Once you hit enter, Builder will spin up a new dev container, and then inside that container, the AI will build out the first version of your site. You can leave the page and come back when it’s done.Now, before we go further, let’s create our repo, so that we get version history right from the outset. Click “Create Repo” up in the top right, and link your GitHub account.Once the process is complete, you’ll have a brand new repo.If you need any help on this step, or any of the below, check out these docs.Making the mockup’s order system workFrom our one-shot prompt, we’ve already got a really nice start for our client. However, when we press the “Order Now” button, we just get a generic alert. Let’s fix this.The best part about connecting to GitHub is that we get version control. Head back to your dashboard and edit the settings of your new project. We can give it a better name, and then, in the “Advanced” section, we can change the “Commit Mode” to “Pull Requests.”Now, we have the ability to create new branches right within Builder, allowing us to make drastic changes without worrying about the main version. This is also helpful if you’d like to show your client or team a few different versions of the same prototype.On a new branch, I’ll write another short prompt:Can you make the "Order Now" button work, even if it's just with dummy JSON for now?As you can see in the GIF above, Builder creates an ordering system and a fully mobile-responsive cart and checkout flow.Now, we can click “Send PR” in the top right, and we have an ordinary GitHub PR that can be reviewed and merged as needed.This is what’s possible in two prompts. For our third, let’s gussy up the style.If you’re like me, you might spend a lot of time admiring other people’s cool designs and learning how to code up similar components in your own style.Luckily, Builder has this capability, too, with our Chrome extension. I found a “Featured Posts” section on OpenAI’s website, where I like how the layout and scrolling work. We can copy and paste it onto our “Featured Treats” section, retaining our cafe’s distinctive brand style.Don’t worry—OpenAI doesn’t mind a little web scraping.You can do this with any component on any website, so your own projects can very quickly become a “best of the web” if you know what you’re doing.Plus, you can use Figma designs in much the same way, with even better design fidelity. Copy and paste a Figma frame with our Figma plugin, and tell the AI to either use the component as inspiration or as a 1:1 to reference for what the design should be.(You can grab our design-to-code guide for a lot more ideas of what this can help you accomplish.)Now, we’re ready to send our PR. This time, let’s take a closer look at the code the AI has created.As you can see, the code is neatly formatted into two reusable components. Scrolling down further, I find a CSS file and then the actual implementation on the homepage, with clean JSON to represent the dummy post data.Design tweaks to the mockup with visual editsOne issue that cropped up when the AI brought in the OpenAI layout is that it changed my text from “Featured Treats” to “Featured Stories & Treats.” I’ve realized I don’t like either, and I want to replace that text with: “Fresh Out of the Bakery.”It would be silly, though, to prompt the AI just for this small tweak. Let’s switch into edit mode.Edit Mode lets you select any component and change any of its content or underlying CSS directly. You get a host of Webflow-like options to choose from, so that you can finesse the details as needed.Once you’ve made all the visual changes you want—maybe tweaking a button color or a border radius—you can click “Apply Edits,” and the AI will ensure the underlying code matches your repo’s style.Async fixes to the mockup with Builder BotNow, our pull request is nearly ready to merge, but I found one issue with it:When we copied the OpenAI website layout earlier, one of the blog posts had a video as its featured graphic instead of just an image. This is cool for OpenAI, but for our bakery, I just wanted images in this section. Since I didn’t instruct Builder’s AI otherwise, it went ahead and followed the layout and created extra code for video capability.No problem. We can fix this inside GItHub with our final prompt. We just need to comment on the PR and tag builderio-bot. Within about a minute, Builder Bot has successfully removed the video functionality, leaving a minimal diff that affects only the code it needed to. For example: Returning to my project in Builder, I can see that the bot’s changes are accounted for in the chat window as well, and I can use the live preview link to make sure my site works as expected:Now, if this were a real project, you could easily deploy this to the web for your client. After all, you’ve got a whole GitHub repo. This isn’t just a mockup; it’s actual code you can tweak—with Builder or Cursor or by hand—until you’re satisfied to run the site in production.So, why use Builder to mock up your website?Sure, this has been a somewhat contrived example. A real prototype is going to look prettier, because I’m going to spend more time on pieces of the design that I don’t like as much.But that’s the point of the best AI tools: they don’t take you, the human, out of the loop.You still get to make all the executive decisions, and it respects your hard work. Since you can constantly see all the code the AI creates, work in branches, and prompt with component-level precision, you can stop worrying about AI overwriting your opinions and start using it more as the tool it’s designed to be.You can copy in your team’s Figma designs, import web inspos, connect MCP servers to get Jira tickets in hand, and—most importantly—work with existing repos full of existing styles that Builder will understand and match, just like it matched OpenAI’s layout to our little cafe.So, we get speed, flexibility, and interactivity all the way from prompt to PR to production.Try Builder today.