Nvidia's CES Announcements - Nvidia announced a new media system and advancements in humanoid robotics during the CES keynote [1] - The company introduced Media 2, an AI-powered system transforming content creation, streaming, and live media experiences [2] - Nvidia unveiled a new chip, desktop computer, and Cosmos platform for developing physical AI systems like robots and self-driving vehicles [3] Nvidia's Market Position and Partnerships - Nvidia has reached a $3.5 trillion market capitalization under CEO Jensen Huang's leadership [1] - Hollywood sectors like visual effects and animation heavily rely on Nvidia's products and services [1] - Partners including Shutterstock, Getty Images, Verizon, and Comcast's Sky are utilizing Nvidia technology [3] AI and Robotics Industry Outlook - Nvidia's CEO highlighted the potential of autonomous vehicles, predicting it to be the first multi-trillion-dollar robotics industry [4] - The company's advancements in AI and robotics are expected to drive greater interactivity and accessibility for customers worldwide [3]

Collaboration and Innovation - MediaTek collaborates with NVIDIA to design the NVIDIA GB10 Grace Blackwell Superchip for NVIDIA Project DIGITS, a personal AI supercomputer [1] - The collaboration aligns with MediaTek's vision of making advanced technology accessible and ushering in a new era of AI innovation [3] - MediaTek integrates NVIDIA's next-gen GPU-accelerated AI computing and NVIDIA RTX graphics into its Dimensity Auto Cockpit chips [3] MediaTek's Market Position and Expertise - MediaTek is the world's leading chip supplier for smartphones, smart TVs, Arm-based Chromebooks, Android tablets, and voice assistant devices [2] - The company has invested heavily in AI, connectivity, and multi-media experiences for Arm-based SoC devices, achieving best-in-class power efficiency [2] - MediaTek enables nearly 2 billion connected devices annually and is a market leader in innovative SoC development for mobile, home entertainment, connectivity, and IoT products [5] AI and Product Portfolio - MediaTek delivers advanced AI capabilities across its product portfolio, including Dimensity for smartphones and tablets, Genio for IoT devices, Pentonic for smart TVs, Kompanio for Chromebooks, and Dimensity Auto for vehicles [4] - The company integrates NVIDIA TAO, an AI model training and optimization toolkit, with its NeuroPilot SDK to enhance edge AI capabilities for IoT applications [3] Leadership and Vision - MediaTek's Vice Chairman and CEO emphasizes the company's commitment to making great technology accessible and driving AI innovation [3] - NVIDIA's CEO highlights the combination of MediaTek's CPU performance and power efficiency with NVIDIA's accelerated computing technologies as a driver for the next wave of innovation [3]

Nvidia's Automotive Partnerships and Technology - Nvidia has secured key design wins for autonomous vehicles with major car manufacturers including Toyota, Aurora, and Continental [1] - These partnerships are part of Nvidia's growing list of collaborations for next-generation highly automated and autonomous vehicle fleets [1] - The announcements were made by Nvidia CEO Jensen Huang during his opening keynote at CES 2025 [1] Toyota's Adoption of Nvidia Technology - Toyota, the world's largest automaker, will build its next-generation vehicles on Nvidia's Drive AGX Orin system-on-a-chip (SoC) [2] - These vehicles will run the safety-certified Nvidia DriveOS operating system and offer advanced driving assistance capabilities [2] Nvidia's Automotive Business Growth - Nvidia's automotive vertical business is expected to grow to approximately $5 billion in fiscal year 2026 [3] - The majority of auto manufacturers, truckmakers, robotaxi companies, and mobility startups are developing on Nvidia's Drive AGX platform and technologies [3] Strategic Partnerships and Future Plans - Aurora, Continental, and Nvidia announced a long-term strategic partnership to deploy driverless trucks at scale, powered by Nvidia Drive [4] - Nvidia's accelerated compute running DriveOS will be integrated into the Aurora Driver, an SAE level 4 autonomous-driving system, with mass-manufacturing planned for 2027 [4] Nvidia's Core Computing Systems for Autonomous Vehicles - Nvidia offers three core computing systems essential for end-to-end autonomous vehicle development [6] - These include the Nvidia Drive in-vehicle computer for real-time sensor data processing, Nvidia DGX systems for AI model training, and the Nvidia Omniverse platform for testing and validating self-driving systems in simulation [6] Industry-Wide Adoption of Nvidia Technology - Other mobility companies adopting Nvidia Drive accelerated compute for 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, and Zoox [5]

大戏开场！ 黄仁勋表示，在接下来的几年里，人类产生的数据量将超过人类自始至今所产生的所有数据。"因此， 我们仍在产生大量的数据，并且这些数据正变得多模态，包括视频、图像和声音。我们还利用AI反馈 和合成数据生成，使自我练习成为可能，通过反复尝试学习，直到获得正确答案。" 黄仁勋透露，Blackwell已全面投入生产，所有主要云服务提供商均已建立系统，提供约200种不同型号 和配置，来自约15家硬件制造商。我们拥有多种（计算）系统，如NVLink 36x2和NVLink 72x1，能够 满足全球几乎所有数据中心的需求，目前在约45家工厂生产。Blackwell相比于前一代在性能上实现了 四倍的提升。 2025国际消费电子展（CES 2025）于2025年1月7日～10日在拉斯维加斯举行，预计将吸引超过13万名 参会者，其中来自中国的参展商有1300余家，创历史新高。而在此次展览上最引人注目的还是英伟达创 始人黄仁勋的演讲。 当地时间1月6日下午6点30分，英伟达CEO黄仁勋在现场发表主题演讲。黄仁勋表示，正在目睹各个技 术层面发生的革命性变革，从手动编码的CPU软件工具到能够在GPU上创建和优化神经网络的先进机 ...

Project DIGITS Overview - NVIDIA unveiled Project DIGITS, a personal AI supercomputer designed for AI researchers, data scientists, and students, powered by the NVIDIA Grace Blackwell platform [1] - Project DIGITS features the NVIDIA GB10 Grace Blackwell Superchip, delivering 1 petaflop of AI computing performance for prototyping, fine-tuning, and running large AI models [1] GB10 Superchip Specifications - The GB10 Superchip is a system-on-a-chip (SoC) based on the NVIDIA Grace Blackwell architecture, offering 1 petaflop of AI performance at FP4 precision [3] - It includes an NVIDIA Blackwell GPU with latest-generation CUDA cores and fifth-generation Tensor Cores, connected via NVLink-C2C to a high-performance NVIDIA Grace CPU with 20 power-efficient Arm-based cores [4] - The GB10 Superchip enables Project DIGITS to deliver powerful performance using only a standard electrical outlet, with 128GB of unified memory and up to 4TB of NVMe storage [5] AI Model Capabilities - Project DIGITS allows developers to run up to 200-billion-parameter large language models, and linking two systems can support up to 405-billion-parameter models [5] - Users can prototype, fine-tune, and test models locally on Project DIGITS systems running Linux-based NVIDIA DGX OS, then deploy them on NVIDIA DGX Cloud or data center infrastructure [6][7] Software and Development Tools - Project DIGITS provides access to an extensive library of NVIDIA AI software, including SDKs, orchestration tools, frameworks, and models available in the NVIDIA NGC catalog and Developer portal [8] - Developers can fine-tune models with the NVIDIA NeMo framework, accelerate data science with NVIDIA RAPIDS libraries, and run common frameworks like PyTorch, Python, and Jupyter notebooks [8] - Users can also leverage NVIDIA Blueprints and NVIDIA NIM microservices for building agentic AI applications [9] Availability and Pricing - Project DIGITS will be available in May 2025, starting at $3,000 [10] Industry Impact - NVIDIA CEO Jensen Huang emphasized that AI will be mainstream in every application for every industry, and Project DIGITS brings the Grace Blackwell Superchip to millions of developers [3] - The project aims to empower data scientists, AI researchers, and students by placing an AI supercomputer on their desks, enabling them to shape the age of AI [3]

LAS VEGAS, Jan. 06, 2025 (GLOBE NEWSWIRE) -- 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 ...

NVIDIA DRIVE AGX Hyperion Platform - NVIDIA DRIVE AGX Hyperion is the industry's first and only end-to-end autonomous driving platform, featuring DRIVE AGX SoC, DriveOS, a sensor suite, and a level 2+ driving stack [2] - The platform is modular, scalable, and upgradeable, with adoption by automotive safety pioneers such as Mercedes-Benz, JLR, and Volvo Cars [2] - The latest iteration, available in the first half of 2025, will feature the DRIVE AGX Thor SoC built on the NVIDIA Blackwell architecture, designed for both passenger and commercial vehicles [3] Safety and Certification - NVIDIA DRIVE AGX Hyperion has passed safety assessments by TÜV SÜD and TÜV Rheinland, raising the bar for AV safety, innovation, and performance [1] - NVIDIA received ISO 21434 Cybersecurity Process certification for automotive SoC, platform, and software engineering processes from TÜV SÜD [13] - NVIDIA DriveOS 6.0 conforms to ISO 26262 Automotive Safety Integrity Level (ASIL) D standards, pending certification release [13] - NVIDIA is accredited by the ANSI National Accreditation Board (ANAB) to provide safety and cybersecurity inspections for NVIDIA DRIVE ecosystem partners [5] DRIVE Thor and Blackwell Architecture - DRIVE Thor, the core computer for DRIVE Hyperion, is the successor to DRIVE Orin and is optimized for demanding workloads, including generative AI and large language models [6][7] - The NVIDIA Blackwell architecture enhances generalization, reduces latency, and boosts safety by running the end-to-end AV stack and a proven safety stack in parallel [7] - DRIVE Thor paves the way for AV 2.0, delivering humanlike autonomous driving capabilities for complex roadway scenarios [8] NVIDIA's Three-Computer Approach - NVIDIA's automotive-grade AV development is supported by three computers: DRIVE AGX in-vehicle computer, NVIDIA DGX systems for AI model training, and NVIDIA Omniverse platform for simulation and validation [9] - These systems, enhanced by the NVIDIA Cosmos world foundation model platform, accelerate end-to-end AV development and mass deployment [9] Industry Impact and Vision - NVIDIA's platform is designed to support next-generation vehicles, which are increasingly software-defined and capable of receiving new features and functionality over their lifetime [4] - The company has invested 15,000 engineering years in vehicle safety, ensuring compliance with stringent functional safety and cybersecurity standards [4] - NVIDIA's CEO, Jensen Huang, emphasized that the Blackwell-powered platform will shift the autonomous vehicle revolution into high gear, relying on physical AI world foundation models to understand and interact with the real world [3]

NVIDIA's Announcements at CES 2025 - NVIDIA announced generative AI models and blueprints that expand NVIDIA Omniverse integration into physical AI applications such as robotics, autonomous vehicles, and vision AI [1] - The company introduced new models including Cosmos World Foundation Models and Omniverse Mega Factory and Robotic Digital Twin Blueprint, laying the foundation for industrial AI [1] - Leading developers such as Accenture, Altair, Ansys, Cadence, Microsoft, and Siemens are among the first to adopt the platform libraries [1][2] Adoption of NVIDIA Omniverse by Industry Leaders - Siemens announced the availability of Teamcenter Digital Reality Viewer, the first Siemens Xcelerator application powered by NVIDIA Omniverse libraries [2] - Cadence integrated Omniverse into Allegro, its leading electronic computer-aided design application used by major semiconductor companies [8] - Altair is adopting the Omniverse blueprint for real-time CAE digital twins for interactive computational fluid dynamics (CFD) [9] - Ansys is integrating Omniverse into Ansys Fluent, a leading CAE application [9] - Neural Concept is integrating Omniverse libraries into its next-generation software products to enable real-time CFD and enhance engineering workflows [9] Applications of NVIDIA Omniverse in Industrial AI - NVIDIA Omniverse, paired with Cosmos world foundation models, creates a synthetic data multiplication engine, enabling developers to generate massive amounts of controllable, photoreal synthetic data [5] - Developers can compose 3D scenarios in Omniverse and render images or videos as outputs, which can be used with text prompts to generate synthetic virtual environments for physical AI training [5] - NVIDIA announced four new blueprints to help developers build Universal Scene Description (OpenUSD)-based Omniverse digital twins for physical AI [6] Real-World Use Cases of NVIDIA Omniverse - Accenture is using Omniverse to help KION build next-generation autonomous warehouses and robotic fleets for global warehousing and distribution customers [10] - Foretellix is using the AV simulation blueprint to enable full 3D sensor simulation for optimized AV testing and validation [11] - Katana Studio is using Omniverse spatial streaming workflow to create custom car configurators for Nissan and Volkswagen, improving the customer decision-making process [12] - Innoactive used Omniverse to add platform support for spatial streaming to Apple Vision Pro, enabling Volkswagen Group to conduct design and engineering project reviews at human-eye resolution [13] NVIDIA's Vision for Physical AI - NVIDIA's CEO Jensen Huang stated that physical AI will revolutionize the $50 trillion manufacturing and logistics industries, with everything that moves being robotic and embodied by AI [3] - NVIDIA's Omniverse digital twin operating system and Cosmos physical AI serve as the foundational libraries for digitalizing the world's physical industries [3] New Models and Frameworks for Physical AI - NVIDIA offers generative AI models that accelerate world building, labeling the world with physical attributes, and making it photoreal [4] - The USD Code and USD Search NVIDIA NIM microservices are now generally available, allowing developers to use text prompts to generate or search for OpenUSD assets [4] - The new NVIDIA Edify SimReady generative AI model can automatically label existing 3D assets with attributes like physics or materials, processing 1,000 3D objects in minutes instead of over 40 hours manually [4]

NVIDIA Cosmos Platform Overview - NVIDIA announced NVIDIA Cosmos™, a platform designed to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots [1] - The platform includes state-of-the-art generative world foundation models, advanced tokenizers, guardrails, and an accelerated video processing pipeline [1] Key Features of Cosmos - Cosmos world foundation models (WFMs) enable developers to generate massive amounts of photoreal, physics-based synthetic data for training and evaluating models [2] - Developers can fine-tune Cosmos WFMs to build custom models [2] - Cosmos models are available under an open model license, accessible via the NVIDIA API catalog, NVIDIA NGC™ catalog, or Hugging Face [3] Industry Adoption - 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 Uber, are among the first to adopt Cosmos [4][11] - 1X launched the 1X World Model Challenge dataset using Cosmos Tokenizer, while XPENG is using Cosmos to accelerate humanoid robot development [11] - Hillbot and Skild AI are leveraging Cosmos to fast-track general-purpose robot development [11] Applications of Cosmos - Cosmos WFMs are purpose-built for physical AI research, generating physics-based videos from text, image, video, robot sensor, or motion data [6] - The platform supports advanced world model development tools, including an NVIDIA AI and CUDA®-accelerated data processing pipeline that can process 20 million hours of videos in 14 days using the NVIDIA Blackwell platform [7][10] - Cosmos enables video search and understanding, physics-based photoreal synthetic data generation, physical AI model development and evaluation, and foresight simulation [9] Partnerships and Use Cases - Uber is partnering with NVIDIA to accelerate autonomous mobility, leveraging rich driving datasets and Cosmos platform features [17] - Waabi is evaluating Cosmos for AV software development and simulation, while Wayve is using it to search for edge and corner case driving scenarios [17] - Foretellix is using Cosmos alongside NVIDIA Omniverse Sensor RTX APIs to generate high-fidelity testing scenarios and training data at scale [17] Open and Trustworthy AI - Cosmos was developed in line with NVIDIA's trustworthy AI principles, prioritizing privacy, safety, security, transparency, and reducing bias [13] - The platform includes guardrails to mitigate harmful content and features invisible watermarks on AI-generated videos to reduce misinformation [14] Availability and Additional Tools - Cosmos WFMs are available under NVIDIA's open model license on Hugging Face and the NVIDIA NGC catalog [15] - NVIDIA also announced new NVIDIA Llama Nemotron large language models and NVIDIA Cosmos Nemotron vision language models for enterprise AI use cases [16] - The NVIDIA NeMo framework is available for efficient model training, customization, and optimization [16] Industry Impact - Cosmos is seen as a democratizing force for physical AI, enabling developers to build general robotics without requiring extensive expertise or resources [5] - The platform is expected to accelerate the development of autonomous vehicles and robotics, addressing challenges like data scarcity and variability [12]

NVIDIA NIM Microservices and AI Blueprints - NVIDIA announced NIM microservices and AI Blueprints, enabling developers and enthusiasts to build AI agents and creative workflows on PCs [1] - NIM microservices are accelerated by GeForce RTX 50 Series GPUs, offering up to 3,352 trillion operations per second of AI performance and 32GB of VRAM [1] - The RTX 50 Series GPUs, built on NVIDIA Blackwell architecture, support FP4 compute, boosting AI inference performance by 2x and enabling generative AI models to run locally with a smaller memory footprint [1] GeForce RTX and AI Development - GeForce has been a key platform for AI developers, with over 30% of published AI research papers citing the use of GeForce RTX last year [2] - New low-code and no-code tools like AnythingLLM, ComfyUI, Langflow, and LM Studio allow enthusiasts to use AI models in complex workflows via simple graphical user interfaces [2] NIM Microservices and AI Blueprints Integration - NIM microservices connected to GUIs make it effortless to access and deploy the latest generative AI models [3] - NVIDIA AI Blueprints, built on NIM microservices, provide preconfigured reference workflows for digital humans, content creation, and more [3] - Top PC manufacturers and system builders are launching NIM-ready RTX AI PCs with GeForce RTX 50 Series GPUs to meet growing demand [3] NVIDIA's Vision for AI Development - NVIDIA's CEO Jensen Huang emphasized that NIM microservices and AI Blueprints provide building blocks for PC developers and enthusiasts to explore AI [4] - Foundation models, trained on immense amounts of raw data, are the building blocks for generative AI [4] NIM Microservices Pipeline - NVIDIA will release a pipeline of NIM microservices for RTX AI PCs from top model developers like Black Forest Labs, Meta, Mistral, and Stability AI [5] - Use cases include large language models (LLMs), vision language models, image generation, speech, embedding models for retrieval-augmented generation (RAG), PDF extraction, and computer vision [5] GeForce RTX 50 Series GPUs and AI Models - GeForce RTX 50 Series GPUs with FP4 compute will unlock a massive range of models that can run on PCs, previously limited to large data centers [6] - NVIDIA announced the Llama Nemotron family of open models, with the Llama Nemotron Nano model offered as a NIM microservice for RTX AI PCs and workstations [6] NIM Microservices Deployment - NIM microservices are optimized for deployment across NVIDIA GPUs, whether in RTX PCs, workstations, or the cloud [7] - Developers and enthusiasts can quickly download, set up, and run NIM microservices on Windows 11 PCs with Windows Subsystem for Linux (WSL) [7] Windows 11 and AI Development - AI is driving Windows 11 PC innovation, with Windows Subsystem for Linux (WSL) offering a cross-platform environment for AI development alongside Windows Copilot Runtime [8] - NIM microservices, optimized for Windows PCs, provide ready-to-integrate AI models for Windows apps, accelerating AI deployment to Windows users [8] Project R2X and AI Agents - NVIDIA previewed Project R2X, a vision-enabled PC avatar that assists with desktop apps, video conference calls, document reading, and summarization [10] - The avatar uses NVIDIA RTX Neural Faces and NVIDIA Audio2Face-3D model for realistic rendering and animation [11] AI Blueprints for PC Users - AI Blueprints provide reference AI workflows that can run locally on RTX PCs, enabling developers to create podcasts from PDF documents and generate images guided by 3D scenes [12] - The PDF to podcast blueprint extracts text, images, and tables from PDFs to create podcast scripts and audio recordings [15] - The 3D-guided generative AI blueprint allows artists to control image generation using 3D objects in tools like Blender [17] Availability and Hardware Support - 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 [18] - NIM-ready RTX AI PCs will be available from top PC manufacturers and system builders [18]