Close Menu
    Demo

    Browsing: Tech

    tech news

    English News

    Building Smarter Autonomous Machines: NVIDIA Announces Early Access for Omniverse Sensor RTX​on January 7, 2025 at 2:30 am

    By

    Building Smarter Autonomous Machines: NVIDIA Announces Early Access for Omniverse Sensor RTX​on January 7, 2025 at 2:30 am

    Generative AI and foundation models let autonomous machines generalize beyond the operational design domains on which they’ve been trained. Using new AI techniques such as tokenization and large language and diffusion models, developers and researchers can now address longstanding hurdles to autonomy. These larger models require massive amounts of diverse data for training, fine-tuning and
    Read ArticleGenerative AI and foundation models let autonomous machines generalize beyond the operational design domains on which they’ve been trained. Using new AI techniques such as tokenization and large language and diffusion models, developers and researchers can now address longstanding hurdles to autonomy. These larger models require massive amounts of diverse data for training, fine-tuning and
    Read Article  

     

    Generative AI and foundation models let autonomous machines generalize beyond the operational design domains on which they’ve been trained. Using new AI techniques such as tokenization and large language and diffusion models, developers and researchers can now address longstanding hurdles to autonomy.

    These larger models require massive amounts of diverse data for training, fine-tuning and validation. But collecting such data — including from rare edge cases and potentially hazardous scenarios, like a pedestrian crossing in front of an autonomous vehicle (AV) at night or a human entering a welding robot work cell — can be incredibly difficult and resource-intensive.

    To help developers fill this gap, NVIDIA Omniverse Cloud Sensor RTX APIs enable physically accurate sensor simulation for generating datasets at scale. The application programming interfaces (APIs) are designed to support sensors commonly used for autonomy — including cameras, radar and lidar — and can integrate seamlessly into existing workflows to accelerate the development of autonomous vehicles and robots of every kind.

    Omniverse Sensor RTX APIs are now available to select developers in early access. Organizations such as Accenture, Foretellix, MITRE and Mcity are integrating these APIs via domain-specific blueprints to provide end customers with the tools they need to deploy the next generation of industrial manufacturing robots and self-driving cars.

    Powering Industrial AI With Omniverse Blueprints

    In complex environments like factories and warehouses, robots must be orchestrated to safely and efficiently work alongside machinery and human workers. All those moving parts present a massive challenge when designing, testing or validating operations while avoiding disruptions.

    Mega is an Omniverse Blueprint that offers enterprises a reference architecture of NVIDIA accelerated computing, AI, NVIDIA Isaac and NVIDIA Omniverse technologies. Enterprises can use it to develop digital twins and test AI-powered robot brains that drive robots, cameras, equipment and more to handle enormous complexity and scale.

    Integrating Omniverse Sensor RTX, the blueprint lets robotics developers simultaneously render sensor data from any type of intelligent machine in a factory for high-fidelity, large-scale sensor simulation.

    With the ability to test operations and workflows in simulation, manufacturers can save considerable time and investment, and improve efficiency in entirely new ways.

    International supply chain solutions company KION Group and Accenture are using the Mega blueprint to build Omniverse digital twins that serve as virtual training and testing environments for industrial AI’s robot brains, tapping into data from smart cameras, forklifts, robotic equipment and digital humans.

    The robot brains perceive the simulated environment with physically accurate sensor data rendered by the Omniverse Sensor RTX APIs. They use this data to plan and act, with each action precisely tracked with Mega, alongside the state and position of all the assets in the digital twin. With these capabilities, developers can continuously build and test new layouts before they’re implemented in the physical world.

    Driving AV Development and Validation

    Autonomous vehicles have been under development for over a decade, but barriers in acquiring the right training and validation data and slow iteration cycles have hindered large-scale deployment.

    To address this need for sensor data, companies are harnessing the NVIDIA Omniverse Blueprint for AV simulation, a reference workflow that enables physically accurate sensor simulation. The workflow uses Omniverse Sensor RTX APIs to render the camera, radar and lidar data necessary for AV development and validation.

    AV toolchain provider Foretellix has integrated the blueprint into its Foretify AV development toolchain to transform object-level simulation into physically accurate sensor simulation.

    The Foretify toolchain can generate any number of testing scenarios simultaneously. By adding sensor simulation capabilities to these scenarios, Foretify can now enable  developers to evaluate the completeness of their AV development, as well as train and test at the levels of fidelity and scale needed to achieve large-scale and safe deployment. In addition, Foretellix will use the newly announced NVIDIA Cosmos platform to generate an even greater diversity of scenarios for verification and validation.

    Nuro, an autonomous driving technology provider with one of the largest level 4 deployments in the U.S., is using the Foretify toolchain to train, test and validate its self-driving vehicles before deployment.

    In addition, research organization MITRE is collaborating with the University of Michigan’s Mcity testing facility to build a digital AV validation framework for regulatory use, including a digital twin of Mcity’s 32-acre proving ground for autonomous vehicles. The project uses the AV simulation blueprint to render physically accurate sensor data at scale in the virtual environment, boosting training effectiveness.

    The future of robotics and autonomy is coming into sharp focus, thanks to the power of high-fidelity sensor simulation. Learn more about these solutions at CES by visiting Accenture at Ballroom F at the Venetian and Foretellix booth 4016 in the West Hall of Las Vegas Convention Center.

    Learn more about the latest in automotive and generative AI technologies by joining NVIDIA at CES.

    See notice regarding software product information.

     

    Generative AI and foundation models let autonomous machines generalize beyond the operational design domains on which they’ve been trained. Using new AI techniques such as tokenization and large language and diffusion models, developers and researchers can now address longstanding hurdles to autonomy. These larger models require massive amounts of diverse data for training, fine-tuning and
    Read Article

    English News

    NVIDIA Blackwell GeForce RTX 50 Series Opens New World of AI Computer Graphics​on January 7, 2025 at 3:06 am

    By

    NVIDIA Blackwell GeForce RTX 50 Series Opens New World of AI Computer Graphics​on January 7, 2025 at 3:06 am

    NVIDIA today unveiled the most advanced consumer GPUs for gamers, creators and developers — the GeForce RTX™ 50 Series Desktop and Laptop GPUs.NVIDIA today unveiled the most advanced consumer GPUs for gamers, creators and developers — the GeForce RTX™ 50 Series Desktop and Laptop GPUs.  

     

    Next Generation of GeForce RTX GPUs Deliver Stunning Visual Realism and 2x Performance Increase, Made Possible by AI, Neural Shaders and DLSS 4

    CES—NVIDIA today unveiled the most advanced consumer GPUs for gamers, creators and developers — the GeForce RTX™ 50 Series Desktop and Laptop GPUs.

    Powered by the NVIDIA Blackwell architecture, fifth-generation Tensor Cores and fourth-generation RT Cores, the GeForce RTX 50 Series delivers breakthroughs in AI-driven rendering, including neural shaders, digital human technologies, geometry and lighting.

    “Blackwell, the engine of AI, has arrived for PC gamers, developers and creatives,” said Jensen Huang, founder and CEO of NVIDIA. “Fusing AI-driven neural rendering and ray tracing, Blackwell is the most significant computer graphics innovation since we introduced programmable shading 25 years ago.”

    The GeForce RTX 5090 GPU — the fastest GeForce RTX GPU to date — features 92 billion transistors, providing over 3,352 trillion AI operations per second (TOPS) of computing power. Blackwell architecture innovations and DLSS 4 mean the GeForce RTX 5090 GPU outperforms the GeForce RTX 4090 GPU by up to 2x.

    GeForce Blackwell comes to laptops with all the features of desktop models, bringing a considerable upgrade to portable computing, including extraordinary graphics capabilities and remarkable efficiency. The Blackwell generation of NVIDIA Max-Q technology extends battery life by up to 40%, and includes thin and light laptops that maintain their sleek design without sacrificing power or performance.

    NVIDIA DLSS 4 Boosts Performance by Up to 8x
    DLSS 4 debuts Multi Frame Generation to boost frame rates by using AI to generate up to three frames per rendered frame. It works in unison with the suite of DLSS technologies to increase performance by up to 8x over traditional rendering, while maintaining responsiveness with NVIDIA Reflex technology.

    DLSS 4 also introduces the graphics industry’s first real-time application of the transformer model architecture. Transformer-based DLSS Ray Reconstruction and Super Resolution models use 2x more parameters and 4x more compute to provide greater stability, reduced ghosting, higher details and enhanced anti-aliasing in game scenes. DLSS 4 will be supported on GeForce RTX 50 Series GPUs in over 75 games and applications the day of launch.

    NVIDIA Reflex 2 introduces Frame Warp, an innovative technique to reduce latency in games by updating a rendered frame based on the latest mouse input just before it is sent to the display. Reflex 2 can reduce latency by up to 75%. This gives gamers a competitive edge in multiplayer games and makes single-player titles more responsive.

    Blackwell Brings AI to Shaders

    Twenty-five years ago, NVIDIA introduced GeForce 3 and programmable shaders, which set the stage for two decades of graphics innovation, from pixel shading to compute shading to real-time ray tracing. Alongside GeForce RTX 50 Series GPUs, NVIDIA is introducing RTX Neural Shaders, which brings small AI networks into programmable shaders, unlocking film-quality materials, lighting and more in real-time games.

    Rendering game characters is one of the most challenging tasks in real-time graphics, as people are prone to notice the smallest errors or artifacts in digital humans. RTX Neural Faces takes a simple rasterized face and 3D pose data as input, and uses generative AI to render a temporally stable, high-quality digital face in real time.

    RTX Neural Faces is complemented by new RTX technologies for ray-traced hair and skin. Along with the new RTX Mega Geometry, which enables up to 100x more ray-traced triangles in a scene, these advancements are poised to deliver a massive leap in realism for game characters and environments.

    The power of neural rendering, DLSS 4 and the new DLSS transformer model is showcased on GeForce RTX 50 Series GPUs with Zorah, a groundbreaking new technology demo from NVIDIA.

    Autonomous Game Characters

    GeForce RTX 50 Series GPUs bring industry-leading AI TOPS to power autonomous game characters in parallel with game rendering.

    NVIDIA is introducing a suite of new NVIDIA ACE technologies that enable game characters to perceive, plan and act like human players. ACE-powered autonomous characters are being integrated into KRAFTON’s PUBG: BATTLEGROUNDS and InZOI, the publisher’s upcoming life simulation game, as well as Wemade Next’s MIR5.

    In PUBG, companions powered by NVIDIA ACE plan and execute strategic actions, dynamically working with human players to ensure survival. InZOI features Smart Zoi characters that autonomously adjust behaviors based on life goals and in-game events. In MIR5, large language model (LLM)-driven raid bosses adapt tactics based on player behavior, creating more dynamic, challenging encounters.

    AI Foundation Models for RTX AI PCs

    Showcasing how RTX enthusiasts and developers can use NVIDIA NIM microservices to build AI agents and assistants, NVIDIA will release a pipeline of NIM microservices and AI Blueprints for RTX AI PCs from top model developers such as Black Forest Labs, Meta, Mistral and Stability AI.

    Use cases span LLMs, vision language models, image generation, speech, embedding models for retrieval-augmented generation, PDF extraction and computer vision. The NIM microservices include all the necessary components for running AI on PCs and are optimized for deployment across all NVIDIA GPUs.

    To demonstrate how enthusiasts and developers can use NIM to build AI agents and assistants, NVIDIA today previewed Project R2X, a vision-enabled PC avatar that can put information at a user’s fingertips, assist with desktop apps and video conference calls, read and summarize documents, and more.

    AI-Powered Tools for Creators

    The GeForce RTX 50 Series GPUs supercharge creative workflows. RTX 50 Series GPUs are the first consumer GPUs to support FP4 precision, boosting AI image generation performance for models such as FLUX by 2x and enabling generative AI models to run locally in a smaller memory footprint, compared with previous-generation hardware.

    The NVIDIA Broadcast app gains two AI-powered beta features for livestreamers: Studio Voice, which upgrades microphone audio, and Virtual Key Light, which relights faces for polished streams. Streamlabs is introducing the Intelligent Streaming Assistant, powered by NVIDIA ACE and Inworld AI, which acts as a cohost, producer and technical assistant to enhance livestreams.

    Availability

    For desktop users, the GeForce RTX 5090 GPU with 3,352 AI TOPS and the GeForce RTX 5080 GPU with 1,801 AI TOPS will be available on Jan. 30 at $1,999 and $999, respectively.

    The GeForce RTX 5070 Ti GPU with 1,406 AI TOPS and GeForce RTX 5070 GPU with 988 AI TOPS will be available starting in February at $749 and $549, respectively.

    The NVIDIA Founders Editions of the GeForce RTX 5090, RTX 5080 and RTX 5070 GPUs will be available directly from nvidia.com and select retailers worldwide.

    Stock-clocked and factory-overclocked models will be available from top add-in card providers such as ASUS, Colorful, Gainward, GALAX, GIGABYTE, INNO3D, KFA2, MSI, Palit, PNY and ZOTAC, and in desktops from system builders including Falcon Northwest, Infiniarc, MAINGEAR, Mifcom, ORIGIN PC, PC Specialist and Scan Computers.

    Laptops with GeForce RTX 5090, RTX 5080 and RTX 5070 Ti Laptop GPUs will be available starting in March, and RTX 5070 Laptop GPUs will be available starting in April from the world’s top manufacturers, including Acer, ASUS, Dell, GIGABYTE, HP, Lenovo, MECHREVO, MSI and Razer.

     

    NVIDIA today unveiled the most advanced consumer GPUs for gamers, creators and developers — the GeForce RTX™ 50 Series Desktop and Laptop GPUs.

    English News

    NVIDIA Launches AI Foundation Models for RTX AI PCs​on January 7, 2025 at 3:25 am

    By

    NVIDIA Launches AI Foundation Models for RTX AI PCs​on January 7, 2025 at 3:25 am

    NVIDIA today announced foundation models running locally on NVIDIA RTX™ AI PCs that supercharge digital humans, content creation, productivity and development.NVIDIA today announced foundation models running locally on NVIDIA RTX™ AI PCs that supercharge digital humans, content creation, productivity and development.  

     

    NVIDIA NIM Microservices and AI Blueprints Help Developers and Enthusiasts Build AI Agents and Creative Workflows on PC

    CES—NVIDIA today announced foundation models running locally on NVIDIA RTX™ AI PCs that supercharge digital humans, content creation, productivity and development. 

    These models — offered as NVIDIA NIM™ microservices — are accelerated by new GeForce RTX™ 50 Series GPUs, which feature up to 3,352 trillion operations per second of AI performance and 32GB of VRAM. Built on the NVIDIA Blackwell architecture, RTX 50 Series are the first consumer GPUs to add support for FP4 compute, boosting AI inference performance by 2x and enabling generative AI models to run locally in a smaller memory footprint, compared with previous-generation hardware.

    GeForce™ has long been a vital platform for AI developers. The first GPU-accelerated deep learning network, AlexNet, was trained on the GeForce GTX™ 580 in 2012 — and last year, over 30% of published AI research papers cited the use of GeForce RTX.

    Now, with generative AI and RTX AI PCs, anyone can be a developer. A new wave of low-code and no-code tools, such as AnythingLLM, ComfyUI, Langflow and LM Studio, enable enthusiasts to use AI models in complex workflows via simple graphical user interfaces.

    NIM microservices connected to these GUIs will make it effortless to access and deploy the latest generative AI models. NVIDIA AI Blueprints, built on NIM microservices, provide easy-to-use, preconfigured reference workflows for digital humans, content creation and more.

    To meet the growing demand from AI developers and enthusiasts, every top PC manufacturer and system builder is launching NIM-ready RTX AI PCs with GeForce RTX 50 Series GPUs.

    “AI is advancing at light speed, from perception AI to generative AI and now agentic AI,” said Jensen Huang, founder and CEO of NVIDIA. “NIM microservices and AI Blueprints give PC developers and enthusiasts the building blocks to explore the magic of AI.”

    Making AI NIMble

    Foundation models — neural networks trained on immense amounts of raw data — are the building blocks for generative AI.

    NVIDIA will release a pipeline of NIM microservices for RTX AI PCs from top model developers such as Black Forest Labs, Meta, Mistral and Stability AI. Use cases span large language models (LLMs), vision language models, image generation, speech, embedding models for retrieval-augmented generation (RAG), PDF extraction and computer vision.

    “GeForce RTX 50 Series GPUs with FP4 compute will unlock a massive range of models that can run on PC, which were previously limited to large data centers,” said Robin Rombach, CEO of Black Forest Labs. “Making FLUX an NVIDIA NIM microservice increases the rate at which AI can be deployed and experienced by more users, while delivering incredible performance.”

    NVIDIA today also announced the Llama Nemotron family of open models that provide high accuracy on a wide range of agentic tasks. The Llama Nemotron Nano model will be offered as a NIM microservice for RTX AI PCs and workstations, and excels at agentic AI tasks like instruction following, function calling, chat, coding and math.

    NIM microservices include the key components for running AI on PCs and are optimized for deployment across NVIDIA GPUs — whether in RTX PCs and workstations or in the cloud.

    Developers and enthusiasts will be able to quickly download, set up and run these NIM microservices on Windows 11 PCs with Windows Subsystem for Linux (WSL).

    “AI is driving Windows 11 PC innovation at a rapid rate, and Windows Subsystem for Linux (WSL) offers a great cross-platform environment for AI development on Windows 11 alongside Windows Copilot Runtime,” said Pavan Davuluri, corporate vice president of Windows at Microsoft. “NVIDIA NIM microservices, optimized for Windows PCs, give developers and enthusiasts ready-to-integrate AI models for their Windows apps, further accelerating deployment of AI capabilities to Windows users.”

    The NIM microservices, running on RTX AI PCs, will be compatible with top AI development and agent frameworks, including AI Toolkit for VSCode, AnythingLLM, ComfyUI, CrewAI, Flowise AI, LangChain, Langflow and LM Studio. Developers can connect applications and workflows built on these frameworks to AI models running NIM microservices through industry-standard endpoints, enabling them to use the latest technology with a unified interface across the cloud, data centers, workstations and PCs.

    Enthusiasts will also be able to experience a range of NIM microservices using an upcoming release of the NVIDIA ChatRTX tech demo.

    Putting a Face on Agentic AI

    To demonstrate how enthusiasts and developers can use NIM to build AI agents and assistants, NVIDIA today previewed Project R2X, a vision-enabled PC avatar that can put information at a user’s fingertips, assist with desktop apps and video conference calls, read and summarize documents, and more.

    The avatar is rendered using NVIDIA RTX Neural Faces, a new generative AI algorithm that augments traditional rasterization with entirely generated pixels. The face is then animated by a new diffusion-based NVIDIA Audio2Face™-3D model that improves lip and tongue movement. R2X can be connected to cloud AI services such as OpenAI’s GPT4o and xAI’s Grok, and NIM microservices and AI Blueprints, such as PDF retrievers or alternative LLMs, via developer frameworks such as CrewAI, Flowise AI and Langflow. Sign up for Project R2X updates.

    AI Blueprints Coming to PC

    NIM microservices are also available to PC users through AI Blueprints — reference AI workflows that can run locally on RTX PCs. With these blueprints, developers can create podcasts from PDF documents, generate stunning images guided by 3D scenes and more.

    The blueprint for PDF to podcast extracts text, images and tables from a PDF to create a podcast script that can be edited by users. It can also generate a full audio recording from the script using voices available in the blueprint or based on a user’s voice sample. In addition, users can have a real-time conversation with the AI podcast host to learn more about specific topics.

    The blueprint uses NIM microservices like Mistral-Nemo-12B-Instruct for language, NVIDIA Riva for text-to-speech and automatic speech recognition, and the NeMo Retriever collection of microservices for PDF extraction.

    The AI Blueprint for 3D-guided generative AI gives artists finer control over image generation. While AI can generate amazing images from simple text prompts, controlling image composition using only words can be challenging. With this blueprint, creators can use simple 3D objects laid out in a 3D renderer like Blender to guide AI image generation. The artist can create 3D assets by hand or generate them using AI, place them in the scene and set the 3D viewport camera. Then, a prepackaged workflow powered by the FLUX NIM microservice will use the current composition to generate high-quality images that match the 3D scene.

    NVIDIA NIM microservices and AI Blueprints will be available starting in February with initial hardware support for GeForce RTX 50 Series, GeForce RTX 4090 and 4080, and NVIDIA RTX 6000 and 5000 professional GPUs. Additional GPUs will be supported in the future.

    NIM-ready RTX AI PCs will be available from Acer, ASUS, Dell, GIGABYTE, HP, Lenovo, MSI, Razer and Samsung, and from local system builders Corsair, Falcon Northwest, LDLC, Maingear, Mifcon, Origin PC, PCS and Scan.

    Learn more about how NIM microservices, AI Blueprints and NIM-ready RTX AI PCs are accelerating generative AI by joining NVIDIA at CES.

     

    NVIDIA today announced foundation models running locally on NVIDIA RTX™ AI PCs that supercharge digital humans, content creation, productivity and development.

    English News

    NVIDIA Launches Cosmos World Foundation Model Platform to Accelerate Physical AI Development​on January 7, 2025 at 3:41 am

    By

    NVIDIA Launches Cosmos World Foundation Model Platform to Accelerate Physical AI Development​on January 7, 2025 at 3:41 am

    NVIDIA today announced NVIDIA Cosmos™, a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline built to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots.NVIDIA today announced NVIDIA Cosmos™, a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline built to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots.  

     

    • New State-of-the-Art Models, Video Tokenizers and an Accelerated Data Processing Pipeline, Optimized for NVIDIA Data Center GPUs, Are Purpose-Built for Developing Robots and Autonomous Vehicles
    • First Wave of Open Models Available Now to Developer Community
    • Global Physical AI Leaders 1X, Agile Robots, Agility, Figure AI, Foretellix, Uber, Waabi and XPENG Among First to Adopt

    CES—NVIDIA today announced NVIDIA Cosmos™, a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline built to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots.

    Physical AI models are costly to develop, and require vast amounts of real-world data and testing. Cosmos world foundation models, or WFMs, offer developers an easy way to generate massive amounts of photoreal, physics-based synthetic data to train and evaluate their existing models. Developers can also build custom models by fine-tuning Cosmos WFMs.

    Cosmos models will be available under an open model license to accelerate the work of the robotics and AV community. Developers can preview the first models on the NVIDIA API catalog, or download the family of models and fine-tuning framework from the NVIDIA NGC™ catalog or Hugging Face.

    Leading robotics and automotive companies, including 1X, Agile Robots, Agility, Figure AI, Foretellix, Fourier, Galbot, Hillbot, IntBot, Neura Robotics, Skild AI, Virtual Incision, Waabi and XPENG, along with ridesharing giant Uber, are among the first to adopt Cosmos.

    “The ChatGPT moment for robotics is coming. Like large language models, world foundation models are fundamental to advancing robot and AV development, yet not all developers have the expertise and resources to train their own,” said Jensen Huang, founder and CEO of NVIDIA. “We created Cosmos to democratize physical AI and put general robotics in reach of every developer.”

    Open World Foundation Models to Accelerate the Next Wave of AI

    NVIDIA Cosmos’ suite of open models means developers can customize the WFMs with datasets, such as video recordings of AV trips or robots navigating a warehouse, according to the needs of their target application.

    Cosmos WFMs are purpose-built for physical AI research and development, and can generate physics-based videos from a combination of inputs, like text, image and video, as well as robot sensor or motion data. The models are built for physically based interactions, object permanence, and high-quality generation of simulated industrial environments — like warehouses or factories — and of driving environments, including various road conditions.

    In his opening keynote at CES, NVIDIA founder and CEO Jensen Huang showcased ways physical AI developers can use Cosmos models, including for:

    • Video search and understanding, enabling developers to easily find specific training scenarios, like snowy road conditions or warehouse congestion, from video data.
    • Physics-based photoreal synthetic data generation, using Cosmos models to generate photoreal videos from controlled 3D scenarios developed in the NVIDIA Omniverse™ platform.
    • Physical AI model development and evaluation, whether building a custom model on the foundation models, improving the models using Cosmos for reinforcement learning or testing how they perform given a specific simulated scenario.
    • Foresight and “multiverse” simulation, using Cosmos and Omniverse to generate every possible future outcome an AI model could take to help it select the best and most accurate path.

    Advanced World Model Development Tools

    Building physical AI models requires petabytes of video data and tens of thousands of compute hours to process, curate and label that data. To help save enormous costs in data curation, training and model customization, Cosmos features:

    • An NVIDIA AI and CUDA®-accelerated data processing pipeline, powered by NVIDIA NeMo™ Curator, that enables developers to process, curate and label 20 million hours of videos in 14 days using the NVIDIA Blackwell platform, instead of over three years using a CPU-only pipeline.
    • NVIDIA Cosmos Tokenizer, a state-of-the-art visual tokenizer for converting images and videos into tokens. It delivers 8x more total compression and 12x faster processing than today’s leading tokenizers.
    • The NVIDIA NeMo framework for highly efficient model training, customization and optimization.

    World’s Largest Physical AI Industries Adopt Cosmos

    Pioneers across the physical AI industry are already adopting Cosmos technologies.

    1X, an AI and humanoid robot company, launched the 1X World Model Challenge dataset using Cosmos Tokenizer. XPENG will use Cosmos to accelerate the development of its humanoid robot. And Hillbot and Skild AI are using Cosmos to fast-track the development of their general-purpose robots.

    “Data scarcity and variability are key challenges to successful learning in robot environments,” said Pras Velagapudi, chief technology officer at Agility. “Cosmos’ text-, image- and video-to-world capabilities allow us to generate and augment photorealistic scenarios for a variety of tasks that we can use to train models without needing as much expensive, real-world data capture.”

    Transportation leaders are also using Cosmos to build physical AI for AVs:

    • Waabi, a company pioneering generative AI for the physical world starting with autonomous vehicles, is evaluating Cosmos in the context of data curation for AV software development and simulation.
    • Wayve, which is developing AI foundation models for autonomous driving, is evaluating Cosmos as a tool to search for edge and corner case driving scenarios used for safety and validation.
    • AV toolchain provider Foretellix will use Cosmos, alongside NVIDIA Omniverse Sensor RTX APIs, to evaluate and generate high-fidelity testing scenarios and training data at scale.
    • Global ridesharing giant Uber is partnering with NVIDIA to accelerate autonomous mobility. Rich driving datasets from Uber, combined with the features of the Cosmos platform and NVIDIA DGX Cloud™, can help AV partners build stronger AI models even more efficiently.

    “Generative AI will power the future of mobility, requiring both rich data and very powerful compute,” said Dara Khosrowshahi, CEO of Uber. “By working with NVIDIA, we are confident that we can help supercharge the timeline for safe and scalable autonomous driving solutions for the industry.”

    Developing Open, Safe and Responsible AI

    NVIDIA Cosmos was developed in line with NVIDIA’s trustworthy AI principles, which prioritize privacy, safety, security, transparency and reducing unwanted bias.

    Trustworthy AI is essential for fostering innovation within the developer community and maintaining user trust. NVIDIA is committed to safe and trustworthy AI, in line with the White House’s voluntary AI commitments and other global AI safety initiatives.

    The open Cosmos platform includes guardrails designed to mitigate harmful text and images, and features a tool to enhance text prompts for accuracy. Videos generated with Cosmos autoregressive and diffusion models on the NVIDIA API catalog include invisible watermarks to identify AI-generated content, helping reduce the chances of misinformation and misattribution.

    NVIDIA encourages developers to adopt trustworthy AI practices and further enhance guardrail and watermarking solutions for their applications.

    Availability

    Cosmos WFMs are now available under NVIDIA’s open model license on Hugging Face and the NVIDIA NGC catalog. Cosmos models will soon be available as fully optimized NVIDIA NIM microservices.

    Developers can access NVIDIA NeMo Curator for accelerated video processing and customize their own world models with NVIDIA NeMo. NVIDIA DGX Cloud offers a fast and easy way to deploy these models, with enterprise support available through the NVIDIA AI Enterprise software platform.

    NVIDIA also announced new NVIDIA Llama Nemotron large language models and NVIDIA Cosmos Nemotron vision language models that developers can use for enterprise AI use cases in healthcare, financial services, manufacturing and more.

     

    NVIDIA today announced NVIDIA Cosmos™, a platform comprising state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline built to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots.

    English News

    NVIDIA Expands Omniverse With Generative Physical AI​on January 7, 2025 at 3:51 am

    By

    NVIDIA Expands Omniverse With Generative Physical AI​on January 7, 2025 at 3:51 am

    NVIDIA today announced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications such as robotics, autonomous vehicles and vision AI. Global leaders in software development and professional services are using Omniverse to develop new products and services that will accelerate the next era of industrial AI.NVIDIA today announced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications such as robotics, autonomous vehicles and vision AI. Global leaders in software development and professional services are using Omniverse to develop new products and services that will accelerate the next era of industrial AI.  

     

    • New Models, Including Cosmos World Foundation Models, and Omniverse Mega Factory and Robotic Digital Twin Blueprint Lay the Foundation for Industrial AI

    • Leading Developers Accenture, Altair, Ansys, Cadence, Microsoft and Siemens Among First to Adopt Platform Libraries

    CES—NVIDIA today announced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications such as robotics, autonomous vehicles and vision AI. Global leaders in software development and professional services are using Omniverse to develop new products and services that will accelerate the next era of industrial AI.

    Accenture, Altair, Ansys, Cadence, Foretellix, Microsoft and Neural Concept are among the first to integrate Omniverse into their next-generation software products and professional services. Siemens, a leader in industrial automation, announced today at the CES trade show the availability of Teamcenter Digital Reality Viewer — the first Siemens Xcelerator application powered by NVIDIA Omniverse libraries.

    “Physical AI will revolutionize the $50 trillion manufacturing and logistics industries. Everything that moves — from cars and trucks to factories and warehouses — will be robotic and embodied by AI,” said Jensen Huang, founder and CEO at NVIDIA. “NVIDIA’s Omniverse digital twin operating system and Cosmos physical AI serve as the foundational libraries for digitalizing the world’s physical industries.”

    New Models and Frameworks Accelerate World Building for Physical AI

    Creating 3D worlds for physical AI simulation requires three steps: world building, labeling the world with physical attributes and making it photoreal.

    NVIDIA offers generative AI models that accelerate each step. The USD Code and USD Search NVIDIA NIM™ microservices are now generally available, letting developers use text prompts to generate or search for OpenUSD assets. A new NVIDIA Edify SimReady generative AI model unveiled today can automatically label existing 3D assets with attributes like physics or materials, enabling developers to process 1,000 3D objects in minutes instead of over 40 hours manually.

    NVIDIA Omniverse, paired with new NVIDIA Cosmos™ world foundation models, creates a synthetic data multiplication engine — letting developers easily generate massive amounts of controllable, photoreal synthetic data. Developers can compose 3D scenarios in Omniverse and render images or videos as outputs. These can then be used with text prompts to condition Cosmos models to generate countless synthetic virtual environments for physical AI training.

    NVIDIA Omniverse Blueprints Speed Up Industrial, Robotic Workflows

    During the CES keynote, NVIDIA also announced four new blueprints that make it easier for developers to build Universal Scene Description (OpenUSD)-based Omniverse digital twins for physical AI. The blueprints include:

    New free Learn OpenUSD courses are also now available to help developers build OpenUSD-based worlds faster than ever.

    Market Leaders Supercharge Industrial AI Using NVIDIA Omniverse

    Global leaders in software development and professional services are using Omniverse to develop new products and services that are poised to accelerate the next era of industrial AI.

    Building on its adoption of Omniverse libraries in its Reality Digital Twin data center digital twin platform, Cadence, a leader in electronic systems design, announced further integration of Omniverse into Allegro, its leading electronic computer-aided design application used by the world’s largest semiconductor companies.

    Altair, a leader in computational intelligence, is adopting the Omniverse blueprint for real-time CAE digital twins for interactive computational fluid dynamics (CFD). Ansys is adopting Omniverse into Ansys Fluent, a leading CAE application. And Neural Concept is integrating Omniverse libraries into its next-generation software products, enabling real-time CFD and enhancing engineering workflows.

    Accenture, a leading global professional services company, is using Mega to help German supply chain solutions leader KION by building next-generation autonomous warehouses and robotic fleets for their network of global warehousing and distribution customers.

    AV toolchain provider Foretellix, a leader in data-driven autonomy development, is using the AV simulation blueprint to enable full 3D sensor simulation for optimized AV testing and validation. Research organization MITRE is also deploying the blueprint, in collaboration with the University of Michigan’s Mcity testing facility, to create an industry-wide AV validation platform.

    Katana Studio is using the Omniverse spatial streaming workflow to create custom car configurators for Nissan and Volkswagen, allowing them to design and review car models in an immersive experience while improving the customer decision-making process.

    Innoactive, an XR streaming platform for enterprises, used the workflow to add platform support for spatial streaming to Apple Vision Pro. The solution enables Volkswagen Group to conduct design and engineering project reviews at human-eye resolution. Innoactive also collaborated with Syntegon, a provider of processing and packaging technology solutions for pharmaceutical production, to enable Syntegon’s customers to walk through and review digital twins of custom installations before they are built.

     

    NVIDIA today announced generative AI models and blueprints that expand NVIDIA Omniverse™ integration further into physical AI applications such as robotics, autonomous vehicles and vision AI. Global leaders in software development and professional services are using Omniverse to develop new products and services that will accelerate the next era of industrial AI.

    English News

    Toyota, Aurora and Continental Join Growing List of NVIDIA Partners Rolling Out Next-Generation Highly Automated and Autonomous Vehicle Fleets​on January 7, 2025 at 3:53 am

    By

    Toyota, Aurora and Continental Join Growing List of NVIDIA Partners Rolling Out Next-Generation Highly Automated and Autonomous Vehicle Fleets​on January 7, 2025 at 3:53 am

    CES—NVIDIA announced today that Toyota, Aurora and Continental have joined the list of global mobility leaders developing and building their consumer and commercial vehicle fleets on NVIDIA …CES—NVIDIA announced today that Toyota, Aurora and Continental have joined the list of global mobility leaders developing and building their consumer and commercial vehicle fleets on NVIDIA …  

     

    CES—NVIDIA announced today that Toyota, Aurora and Continental have joined the list of global mobility leaders developing and building their consumer and commercial vehicle fleets on NVIDIA accelerated computing and AI.

    Toyota, the world’s largest automaker, will build its next-generation vehicles on NVIDIA DRIVE AGX Orin™, running the safety-certified NVIDIA DriveOS operating system. These vehicles will offer functionally safe, advanced driving assistance capabilities. 

    The majority of today’s auto manufacturers, truckmakers, robotaxi, and autonomous delivery vehicle companies, tier-one suppliers and mobility startups are developing on NVIDIA DRIVE AGX™ platform and technologies. With cutting-edge platforms spanning training in the cloud to simulation to compute in the car, NVIDIA’s automotive vertical business is expected to grow to approximately $5 billion in fiscal year 2026.

    “The autonomous vehicle revolution has arrived, and automotive will be one of the largest AI and robotics industries,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA is bringing two decades of automotive computing, safety expertise and its CUDA AV platform to transform the multitrillion dollar auto industry.”

    Aurora, Continental and NVIDIA this week also announced a long-term strategic partnership to deploy driverless trucks at scale, powered by NVIDIA DRIVE. NVIDIA’s accelerated compute running DriveOS will be integrated into the Aurora Driver, an SAE level 4 autonomous-driving system that Continental plans to mass-manufacture in 2027.

    Other mobility companies adopting NVIDIA DRIVE AGX for their next-generation advanced driver-assistance systems and autonomous vehicle roadmaps include BYD, JLR, Li Auto, Lucid, Mercedes-Benz, NIO, Nuro, Rivian, Volvo Cars, Waabi, Wayve, Xiaomi, ZEEKR, Zoox and many more.

    NVIDIA offers three core computing systems and the AI software essential for end-to-end autonomous vehicle development. NVIDIA DRIVE AGX is the in-vehicle computer. NVIDIA DGX™ processes the data from the fleet and trains AI models, and NVIDIA Omniverse™ and NVIDIA Cosmos™ running on NVIDIA OVX™ systems test and validate self-driving systems in simulation.

    Learn more about NVIDIA’s automotive and safety milestones at CES by tuning in to Huang’s opening keynote.

     

    CES—NVIDIA announced today that Toyota, Aurora and Continental have joined the list of global mobility leaders developing and building their consumer and commercial vehicle fleets on NVIDIA …

    English News

    NVIDIA DRIVE Hyperion Platform Achieves Critical Automotive Safety and Cybersecurity Milestones for AV Development​on January 7, 2025 at 3:56 am

    By

    NVIDIA DRIVE Hyperion Platform Achieves Critical Automotive Safety and Cybersecurity Milestones for AV Development​on January 7, 2025 at 3:56 am

    NVIDIA today announced that its autonomous vehicle (AV) platform, NVIDIA DRIVE AGX™ Hyperion, has passed industry-safety assessments by TÜV SÜD and TÜV Rheinland — two of the industry’s…NVIDIA today announced that its autonomous vehicle (AV) platform, NVIDIA DRIVE AGX™ Hyperion, has passed industry-safety assessments by TÜV SÜD and TÜV Rheinland — two of the industry’s…  

     

    Adopted and Backed by Automotive Manufacturers and Safety Authorities, Latest Iteration to Feature DRIVE Thor on NVIDIA Blackwell Running NVIDIA DriveOS

    CES—NVIDIA today announced that its autonomous vehicle (AV) platform, NVIDIA DRIVE AGX™ Hyperion, has passed industry-safety assessments by TÜV SÜD and TÜV Rheinland — two of the industry’s foremost authorities for automotive-grade safety and cybersecurity. This achievement raises the bar for AV safety, innovation and performance.

    DRIVE Hyperion™ is the industry’s first and only end-to-end autonomous driving platform. It includes the DRIVE AGX™ system-on-a-chip (SoC) and reference board design, the NVIDIA DriveOS automotive operating system, a sensor suite, and an active safety and level 2+ driving stack. 

    Automotive safety pioneers such as Mercedes-Benz, JLR and Volvo Cars are adopting the platform, which is designed to be modular, so customers can easily use what they need. It is also scalable and built to be upgradeable and compatible across future DRIVE SoC generations.

    Available in the first half of this year, the latest iteration of DRIVE Hyperion — designed for both passenger and commercial vehicles — will feature the high-performance DRIVE AGX Thor SoC built on the NVIDIA Blackwell architecture. 

    “A billion vehicles driving trillions of miles each year move the world. With autonomous vehicles — one of the largest robotics markets — now here, the NVIDIA Blackwell-powered platform will shift this revolution into high gear,” said Jensen Huang, founder and CEO of NVIDIA. “The next wave of autonomous machines will rely on physical AI world foundation models to understand and interact with the real world, and NVIDIA DRIVE is purpose-built for this new era, delivering unmatched functional safety and AI.”

    Driving Safety Forward: Certified Assurance for Next-Gen Vehicles

    Next-generation vehicles will be increasingly software-defined, capable of receiving new features and functionality over their lifetime. Tapping into NVIDIA’s 15,000 engineering years invested in vehicle safety, DRIVE Hyperion will help ensure advanced automotive systems with rich, AI-based functionalities are compliant with the automotive industry’s stringent functional safety and cybersecurity standards.

    NVIDIA recently received safety certifications and assessments from accredited third parties, including:

    • TÜV SÜD, which granted the ISO 21434 Cybersecurity Process certification to NVIDIA for automotive SoC, platform and software engineering processes. Additionally, NVIDIA DriveOS 6.0 conforms to ISO 26262 Automotive Safety Integrity Level (ASIL) D standards, pending certification release.
    • TÜV Rheinland, which performed an independent United Nations Economic Commission for Europe (UNECE) safety assessment of NVIDIA DRIVE AV related to safety requirements for complex electronic systems.

    In addition, NVIDIA is now accredited by the ANSI National Accreditation Board (ANAB) to provide safety and cybersecurity inspections for NVIDIA DRIVE™ ecosystem partners. The new NVIDIA DRIVE AI Systems Inspection Lab will help the NVIDIA DRIVE automotive ecosystem build autonomous driving software that meets the industry’s evolving safety and AI standards. 

    NVIDIA is the first platform company to receive a comprehensive set of third-party assessments for its automotive technologies — including the NVIDIA DRIVE end-to-end self-driving platform, spanning SoC, OS, sensor architecture and level 2+ application software — as well as independent accreditation as an AI systems safety and cybersecurity inspection lab for the automotive market.

    Intelligence Powered by Industry-Leading Compute

    NVIDIA DRIVE Thor, the core computer for DRIVE Hyperion, is the successor to the production-proven NVIDIA DRIVE Orin™. Its architecture compatibility and scalability means developers can use existing software from earlier DRIVE product generations, as well as integrate future updates, to achieve seamless development pipelines.

    DRIVE Thor is based on the NVIDIA Blackwell architecture and is optimized for the most demanding processing workloads, including those involving generative AI, vision language models and large language models. Its simplified architecture enhances generalization, reduces latency and boosts safety by harnessing powerful NVIDIA accelerated computing to run the end-to-end AV stack and a proven safety stack in parallel.

    DRIVE Thor paves the way for the next era of AV technology, known as AV 2.0, which involves delivering humanlike autonomous driving capabilities for navigating the most complex roadway scenarios.

    In addition to the DRIVE AGX in-vehicle computer, two other NVIDIA computers serve as the foundation for automotive-grade AV development: NVIDIA DGX™ systems for training advanced AI models and building a robust AV software stack in the cloud, and the NVIDIA Omniverse™ platform running on NVIDIA OVX™ systems for simulation and validation. These three computers, now enhanced with the new NVIDIA Cosmos™ world foundation model platform, are set to accelerate end-to-end AV development and mass deployment.

    To learn more about NVIDIA’s three-computer approach to automotive development and the Cosmos world foundation model platform along with other automotive news, tune in to Huang’s CES opening keynote.

     

    NVIDIA today announced that its autonomous vehicle (AV) platform, NVIDIA DRIVE AGX™ Hyperion, has passed industry-safety assessments by TÜV SÜD and TÜV Rheinland — two of the industry’s…

    English News

    NVIDIA Puts Grace Blackwell on Every Desk and at Every AI Developer’s Fingertips​on January 7, 2025 at 4:10 am

    By

    NVIDIA Puts Grace Blackwell on Every Desk and at Every AI Developer’s Fingertips​on January 7, 2025 at 4:10 am

    CES—NVIDIA today unveiled NVIDIA® Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace …CES—NVIDIA today unveiled NVIDIA® Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace …  

     

    NVIDIA Project DIGITS With New GB10 Superchip Debuts as World’s Smallest AI Supercomputer Capable of Running 200B-Parameter Models

    CES—NVIDIA today unveiled NVIDIA® Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace Blackwell platform.

    Project DIGITS features the new NVIDIA GB10 Grace Blackwell Superchip, offering a petaflop of AI computing performance for prototyping, fine-tuning and running large AI models.

    With Project DIGITS, users can develop and run inference on models using their own desktop system, then seamlessly deploy the models on accelerated cloud or data center infrastructure.

    “AI will be mainstream in every application for every industry. With Project DIGITS, the Grace Blackwell Superchip comes to millions of developers,” said Jensen Huang, founder and CEO of NVIDIA. “Placing an AI supercomputer on the desks of every data scientist, AI researcher and student empowers them to engage and shape the age of AI.”

    GB10 Superchip Provides a Petaflop of Power-Efficient AI Performance

    The GB10 Superchip is a system-on-a-chip (SoC) based on the NVIDIA Grace Blackwell architecture and delivers up to 1 petaflop of AI performance at FP4 precision.

    GB10 features an NVIDIA Blackwell GPU with latest-generation CUDA® cores and fifth-generation Tensor Cores, connected via NVLink®-C2C chip-to-chip interconnect to a high-performance NVIDIA Grace™ CPU, which includes 20 power-efficient cores built with the Arm architecture. MediaTek, a market leader in Arm-based SoC designs, collaborated on the design of GB10, contributing to its best-in-class power efficiency, performance and connectivity.

    The GB10 Superchip enables Project DIGITS to deliver powerful performance using only a standard electrical outlet. Each Project DIGITS features 128GB of unified, coherent memory and up to 4TB of NVMe storage. With the supercomputer, developers can run up to 200-billion-parameter large language models to supercharge AI innovation. In addition, using NVIDIA ConnectX® networking, two Project DIGITS AI supercomputers can be linked to run up to 405-billion-parameter models.

    Grace Blackwell AI Supercomputing Within Reach

    With the Grace Blackwell architecture, enterprises and researchers can prototype, fine-tune and test models on local Project DIGITS systems running Linux-based NVIDIA DGX OS, and then deploy them seamlessly on NVIDIA DGX Cloud™, accelerated cloud instances or data center infrastructure.

    This allows developers to prototype AI on Project DIGITS and then scale on cloud or data center infrastructure, using the same Grace Blackwell architecture and the NVIDIA AI Enterprise software platform.

    Project DIGITS users can access an extensive library of NVIDIA AI software for experimentation and prototyping, including software development kits, orchestration tools, frameworks and models available in the NVIDIA NGC catalog and on the NVIDIA Developer portal. Developers can fine-tune models with the NVIDIA NeMo™ framework, accelerate data science with NVIDIA RAPIDS™ libraries and run common frameworks such as PyTorch, Python and Jupyter notebooks.

    To build agentic AI applications, users can also harness NVIDIA Blueprints and NVIDIA NIM™ microservices, which are available for research, development and testing via the NVIDIA Developer Program. When AI applications are ready to move from experimentation to production environments, the NVIDIA AI Enterprise license provides enterprise-grade security, support and product releases of NVIDIA AI software. 

    Availability

    Project DIGITS will be available in May from NVIDIA and top partners, starting at $3,000. Sign up for notifications today.

     

    CES—NVIDIA today unveiled NVIDIA® Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace …

    English News

    NVIDIA Unveils ‘Mega’ Omniverse Blueprint for Building Industrial Robot Fleet Digital Twins​on January 7, 2025 at 4:15 am

    By

    NVIDIA Unveils ‘Mega’ Omniverse Blueprint for Building Industrial Robot Fleet Digital Twins​on January 7, 2025 at 4:15 am

    According to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms. Today’s 10
    Read ArticleAccording to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms. Today’s 10
    Read Article  

     

    According to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms.

    Today’s 10 million factories, nearly 200,000 warehouses and 40 million miles of highways form the “computing” fabric of our physical world. But that vast network of production facilities and distribution centers is still laboriously and manually designed, operated and optimized.

    In warehousing and distribution, operators face highly complex decision optimization problems — matrices of variables and interdependencies across human workers, robotic and agentic systems and equipment. Unlike the IT industry, the physical industrial market is still waiting for its own software-defined moment.

    That moment is coming.

    Virtual facility with people, machinery and robots all moving around the facility floor. Digital representations of the pathways and sensor inputs can be visualized with colorful arrays.
    Choreographed integration of human workers, robotic and agentic systems and equipment in a facility digital twin. Image courtesy of Accenture, KION Group.

    NVIDIA today at CES announced “Mega,” an Omniverse Blueprint for developing, testing and optimizing physical AI and robot fleets at scale in a digital twin before deployment into real-world facilities.

    Advanced warehouses and factories use fleets of hundreds of autonomous mobile robots, robotic arm manipulators and humanoids working alongside people. With implementations of increasingly complex systems of sensor and robot autonomy, it requires coordinated training in simulation to optimize operations, help ensure safety and avoid disruptions.

    Mega offers enterprises a reference architecture of NVIDIA accelerated computing, AI, NVIDIA Isaac and NVIDIA Omniverse technologies to develop and test digital twins for testing AI-powered robot brains that drive robots, video analytics AI agents, equipment and more for handling enormous complexity and scale. The new framework brings software-defined capabilities to physical facilities, enabling continuous development, testing, optimization and deployment.

    Developing AI Brains With World Simulator for Autonomous Orchestration

    With Mega-driven digital twins, including a world simulator that coordinates all robot activities and sensor data, enterprises can continuously update facility robot brains for intelligent routes and tasks for operational efficiencies.

    The blueprint uses Omniverse Cloud Sensor RTX APIs that enable robotics developers to render sensor data from any type of intelligent machine in the factory, simultaneously, for high-fidelity large-scale sensor simulation. This allows robots to be tested in an infinite number of scenarios within the digital twin, using synthetic data in a software-in–the-loop pipeline with NVIDIA Isaac ROS.

    Digital facility with workers and robots moving around the floor. Images on either side of this view are tapped into various sensors mounted on the virtual robots moving around the facility.
    Operational efficiency is gained with sensor simulation. Image courtesy of Accenture, KION Group.

    Supply chain solutions company KION Group is collaborating with Accenture and NVIDIA as the first to adopt Mega for optimizing operations in retail, consumer packaged goods, parcel services and more.

    Jensen Huang, founder and CEO of NVIDIA, offered a glimpse into the future of this collaboration on stage at CES, demonstrating how enterprises can navigate a complex web of decisions using the Mega Omniverse Blueprint.

    “At KION, we leverage AI-driven solutions as an integral part of our strategy to optimize our customers’ supply chains and increase their productivity,” said Rob Smith, CEO of KION GROUP AG. “With NVIDIA’s AI leadership and Accenture’s expertise in digital technologies, we are reinventing warehouse automation. Bringing these strong partners together, we are creating a vision for future warehouses that are part of a smart agile system, evolve with the world around them and can handle nearly any supply chain challenge.”

    Creating Operational Efficiencies With Mega Omniverse Blueprint

    Creating operational efficiencies, KION and Accenture are embracing the Mega Omniverse Blueprint to build next-generation supply chains for KION and its customers. KION can capture and digitalize a warehouse digital twin in Omniverse by using computer-aided design files, video, lidar, image and AI-generated data.

    KION uses the Omniverse digital twin as a virtual training and testing environment for its industrial AI’s robot brains, powered by NVIDIA Isaac, tapping into smart cameras, forklifts, robotic equipment and digital humans. Integrating the Omniverse digital twin, KION’s warehouse management software can create and assign missions for robot brains, like moving a load from one place to another.

    Digital facility with workers and robots moving around the floor. Dashboard metrics are placed over the viewport of the digital twin, which showcase various throughput and productivity metrics related to the scene.
    Graphical data is easily introduced into the Omniverse viewport showcasing productivity and throughput among other desired metrics. Image courtesy of Accenture, KION Group.

    These simulated robots can carry out tasks by perceiving and reasoning in environments, and they’re capable of planning next motions and then taking actions that are simulated in the digital twin. The robot brains perceive the results deciding the next action, and this cycle continues with Mega precisely tracking the state and position of all the assets in the digital twin.

    Delivering Services With Mega for Facilities Everywhere

    Accenture, global leader in professional services, is adopting Mega as part of its AI Refinery for Simulation and Robotics, built on NVIDIA AI and Omniverse, to help organizations use AI simulation to reinvent factory and warehouse design and ongoing operations.

    With the blueprint, Accenture is delivering new services — including Custom Robotics and Manufacturing Foundation Model Training and Finetuning; Intelligent Humanoid Robotics; and AI-Powered Industrial Manufacturing and Logistics Simulation and Optimization — to expand the power of physical AI and  simulation to the world’s factories and warehouse operators.  Now, for example, an organization can explore numerous options for their warehouse before choosing and implementing the best one.

    “As organizations enter the age of industrial AI, we are helping them use AI-powered simulation and autonomous robots to reinvent the process of designing new facilities and optimizing existing operations,” said Julie Sweet, chair and CEO of Accenture. “Our collaboration with NVIDIA and KION will help our clients plan their operations in digital twins, where they can run hundreds of options and quickly select the best for current or changing market conditions, such as seasonal market demand or workforce availability.  This represents a new frontier of value for our clients to achieve using technology, data and AI.”

    Join NVIDIA at CES. 

    See notice regarding software product information.

     

    According to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms. Today’s 10
    Read Article