Core Insights - NVIDIA is establishing a research center in Boston to advance quantum computing technologies in collaboration with leading hardware and software companies [1][2] - The NVIDIA Accelerated Quantum Research Center (NVAQC) aims to integrate quantum hardware with AI supercomputers, addressing significant challenges in quantum computing [2][4] - Collaborations with innovators like Quantinuum, Quantum Machines, and QuEra Computing, as well as academic institutions such as Harvard and MIT, will drive advancements in quantum computing [3][6] Company Developments - The NVAQC will utilize NVIDIA's GB200 NVL72 rack-scale systems, the most powerful hardware for quantum applications, to facilitate complex simulations and quantum error correction [4][5] - The center will employ the NVIDIA CUDA-Q™ quantum development platform to enable the development of new hybrid quantum algorithms and applications [5][7] - The NVAQC is expected to commence operations later in 2025, enhancing the Boston area's quantum ecosystem [7] Industry Impact - Quantum computing is anticipated to augment AI supercomputers, addressing critical issues in fields such as drug discovery and materials development [4][10] - The collaboration between commercial and academic partners at the NVAQC is expected to accelerate research in quantum error correction and practical quantum computing applications [6][7] - The establishment of the NVAQC signifies a strategic move by NVIDIA to position itself at the forefront of quantum computing innovation [1][4]

SAN JOSE, Calif., March 18, 2025 (GLOBE NEWSWIRE) -- GTC -- NVIDIA today announced a collaboration with GE HealthCare to advance innovation in autonomous imaging, focused on developing autonomous X-ray technologies and ultrasound applications. Building autonomy into systems like X-ray and ultrasound requires medical imaging systems to understand and operate in the physical world. This enables the automation of complex workflows such as patient placement, image scanning and quality checking. To accomplish th ...

Core Insights - NVIDIA, Alphabet, and Google are launching new initiatives to enhance AI, democratize access to AI tools, and transform various industries including healthcare, manufacturing, and energy [1][20] AI and Robotics Development - Engineers and researchers from Alphabet and NVIDIA are collaborating to develop robots with advanced grasping skills and optimize energy grids using AI and simulation technologies [2] - The partnership includes the use of NVIDIA platforms such as Omniverse™, Cosmos™, and Isaac™ to facilitate these developments [2] AI Infrastructure and Tools - Google Cloud will adopt NVIDIA's GB300 NVL72 rack-scale solution and RTX PRO™ 6000 Blackwell Server Edition GPU to enhance AI research and production capabilities [3][15] - NVIDIA will implement Google DeepMind's SynthID technology for watermarking AI-generated content, ensuring intellectual property protection [3][6] Open Models and Innovation - Google DeepMind and NVIDIA are optimizing Gemma, a family of lightweight open models, to run efficiently on NVIDIA GPUs, enhancing accessibility for developers [7] - The collaboration aims to improve the performance of AI models and facilitate their integration into various applications [7] Robotics and Manufacturing - Intrinsic, an Alphabet company, is focused on creating adaptive AI for robotics, aiming to simplify the programming of industrial robots [9] - The partnership with NVIDIA aims to enhance developer workflows and support universal robot grasping capabilities, significantly reducing application development time [10] Drug Discovery and Healthcare - Isomorphic Labs is leveraging AI for drug discovery, utilizing a state-of-the-art drug design engine on Google Cloud with NVIDIA GPUs to advance human health [12] Energy Solutions - Tapestry, a project under Alphabet's X, is working with NVIDIA to develop AI-powered solutions for optimizing electric grid simulations and integrating new energy sources [13][14] Advanced AI Infrastructure - Google Cloud is among the first to offer NVIDIA's latest Blackwell GPUs, which provide significant performance improvements for AI applications [15][16] - The GB300 NVL72 delivers 1.5 times more AI performance compared to its predecessor, enhancing revenue opportunities for AI factories [16] Collaboration and Future Directions - The ongoing partnership between NVIDIA and Alphabet is set to advance agentic AI and physical AI applications across various sectors [20]

G42, JBA Risk Management, Spire Among First to Adopt NVIDIA Omniverse Blueprint for Earth-2 Weather Analytics NVIDIA Earth-2 NVIDIA Omniverse Blueprints for Earth-2 weather analytics make it easier for climate tech and weather companies to develop high-resolution, accurate weather-forecasting solutions. SAN JOSE, Calif., March 18, 2025 (GLOBE NEWSWIRE) -- GTC -- NVIDIA today announced the NVIDIA Omniverse Blueprint for Earth-2 weather analytics to accelerate the development of more accurate weather forec ...

Core Insights - NVIDIA has introduced the NVIDIA AI Data Platform, a customizable reference design aimed at building AI infrastructure for enterprise storage platforms that support demanding AI inference workloads [1][12] - The platform enables storage providers to create AI query agents that enhance data insights generation in near real-time using NVIDIA's AI Enterprise software [2][5] Group 1: Infrastructure and Technology - The NVIDIA AI Data Platform allows certified storage providers to optimize their infrastructure with NVIDIA Blackwell GPUs, BlueField DPUs, and Spectrum-X networking to enhance AI reasoning workloads [3][6] - BlueField DPUs can deliver up to 1.6 times higher performance than traditional CPU-based storage while reducing power consumption by up to 50%, achieving over 3 times higher performance per watt [6] - Spectrum-X networking can accelerate AI storage traffic by up to 48% compared to traditional Ethernet through adaptive routing and congestion control [6] Group 2: Collaboration and Industry Impact - Leading storage providers such as DDN, Dell Technologies, and IBM are collaborating with NVIDIA to develop customized AI data platforms that leverage enterprise data for complex query responses [4][13] - Jensen Huang, CEO of NVIDIA, emphasized the importance of data as a key resource in the AI era, stating that the collaboration aims to build infrastructure necessary for deploying and scaling agentic AI across hybrid data centers [5] Group 3: AI Query Agents and Capabilities - AI query agents developed using the NVIDIA AI-Q Blueprint can access and process various data types, including structured, semi-structured, and unstructured data from multiple sources [8] - The AI-Q Blueprint utilizes NVIDIA NeMo Retriever microservices to accelerate data extraction and retrieval by up to 15 times on NVIDIA GPUs [7]

Core Insights - NVIDIA announced that leading CAE software vendors, including Ansys, Altair, Cadence, Siemens, and Synopsys, are enhancing their simulation tools by up to 50 times using the NVIDIA Blackwell platform [1][2] - The integration of NVIDIA Blackwell with CUDA-X libraries allows industries such as automotive, aerospace, energy, manufacturing, and life sciences to significantly reduce product development time, cut costs, and improve design accuracy while maintaining energy efficiency [2][3] Ecosystem Support - A growing ecosystem of software providers is integrating Blackwell into their offerings, including companies like Altair, Ansys, Cadence, Siemens, and Synopsys, enabling customers to develop real-time digital twins with enhanced interactivity [4][3] - Rescale has launched a CAE Hub that streamlines access to NVIDIA technologies and CUDA-accelerated software, providing high-performance computing and AI technologies in the cloud powered by NVIDIA GPUs [8] Industry Applications - Cadence is utilizing NVIDIA Grace Blackwell-accelerated systems to tackle challenges in computational fluid dynamics, achieving multibillion cell simulations in under 24 hours, which previously required extensive CPU resources [5][6] - Boom Supersonic plans to use NVIDIA Omniverse Blueprint and Blackwell-accelerated CFD solvers on Rescale CAE Hub to design and optimize its new supersonic passenger jet, enabling 4 times more design explorations [9][10] Performance Enhancements - The collaboration between NVIDIA and various software providers is leading to significant performance improvements, with GPU-based simulations being up to 1.6 times faster compared to previous generations [7] - The combination of NVIDIA Blackwell architecture with Siemens' digital twins is expected to drastically reduce development times and costs, enhancing efficiency in design and manufacturing processes [7]

Accenture, Ansys, Cadence, Databricks, Dematic, Hexagon, Omron, SAP, Schneider Electric With ETAP, Siemens Connect Omniverse to Leading Software ToolsFour New Blueprints Enable Robot-Ready Factories and Large-Scale Synthetic Data GenerationFoxconn, General Motors, Hyundai Motor Group, KION Group, Mercedes-Benz, Pegatron and Schaeffler Adopt Omniverse for Industrial AI Transformation SAN JOSE, Calif., March 18, 2025 (GLOBE NEWSWIRE) -- GTC -- NVIDIA today unveiled that leading industrial software and service ...

Core Insights - NVIDIA has launched the NVIDIA DGX SuperPOD, the most advanced enterprise AI infrastructure, utilizing NVIDIA Blackwell Ultra GPUs for enhanced AI reasoning capabilities [1][3] - The new DGX systems, including DGX GB300 and DGX B300, are designed to provide out-of-the-box AI supercomputing solutions, significantly improving performance for AI applications [2][9] Product Features - The DGX GB300 systems feature 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell Ultra GPUs, designed for real-time responses in advanced reasoning models [3][7] - DGX GB300 systems deliver up to 70 times more AI performance compared to previous NVIDIA Hopper systems, with 38TB of fast memory for complex reasoning tasks [7] - Each DGX GB300 system includes 72 NVIDIA ConnectX-8 SuperNICs, achieving networking speeds of up to 800Gb/s, which is double the performance of the previous generation [8][11] Market Strategy - NVIDIA introduced the NVIDIA Instant AI Factory, a managed service that will be first offered by Equinix, providing preconfigured AI infrastructure in 45 global markets [5][10] - The Instant AI Factory aims to meet the increasing demand for advanced AI infrastructure, allowing businesses to deploy AI capabilities without extensive pre-deployment planning [15][14] Software and Ecosystem - NVIDIA Mission Control software has been announced to automate the management of AI infrastructure, enhancing operational efficiency for enterprises [12][13] - The DGX systems support the NVIDIA AI Enterprise software platform, which includes tools and frameworks for optimizing AI agent performance [13]

Core Insights - NVIDIA has announced the release of new Cosmos world foundation models (WFMs) aimed at enhancing physical AI development, providing developers with customizable reasoning models for world generation [1][3][21] - The introduction of two new blueprints powered by NVIDIA Omniverse and Cosmos platforms will facilitate large-scale synthetic data generation for robots and autonomous vehicles, with early adopters including industry leaders like 1X and Uber [2][21] Group 1: Cosmos World Foundation Models - Cosmos WFMs enable the generation of controllable photorealistic video outputs from structured video inputs, streamlining perception AI training [3][4] - The models are designed to enhance robotics and physical industries, allowing for significant advancements in these fields [3][21] - Cosmos Predict WFMs can generate virtual world states from multimodal inputs, enabling multi-frame generation and customized training for physical AI applications [7][8] Group 2: Synthetic Data Generation - The Cosmos Transfer model allows for the transformation of 3D simulations into photorealistic videos, significantly improving the efficiency of synthetic data generation [4][6] - Companies like Agility Robotics and Foretellix are leveraging these models to create diverse datasets for training their robotic and autonomous systems [5][8] - The GR00T Blueprint combines Omniverse and Cosmos Transfer to reduce data collection time from days to hours, enhancing the efficiency of synthetic manipulation motion generation [6] Group 3: Multimodal Reasoning and Data Curation - Cosmos Reason is a customizable model that utilizes chain-of-thought reasoning to interpret video data and predict interaction outcomes, improving data annotation and curation for physical AI [9][10] - Developers can utilize NVIDIA's NeMo framework for accelerated data processing and curation, with applications in training large vision language models [11][12] - Companies like Linker Vision and Milestone Systems are employing these tools for video data curation to enhance their AI capabilities [12] Group 4: Responsible AI and Availability - NVIDIA emphasizes responsible AI practices by implementing open guardrails across all Cosmos WFMs and collaborating with Google DeepMind to watermark AI-generated outputs [13] - The Cosmos WFMs are available for preview in the NVIDIA API catalog and listed in the Vertex AI Model Garden on Google Cloud, with some models accessible on platforms like Hugging Face and GitHub [14]

Core Insights - NVIDIA has launched the Llama Nemotron family of models, which are designed to provide advanced AI reasoning capabilities for developers and enterprises [1][4] - The new models enhance multistep math, coding, reasoning, and complex decision-making through extensive post-training, improving accuracy by up to 20% and optimizing inference speed by 5x compared to other leading models [2][3] Model Features - The Llama Nemotron model family is available in three sizes: Nano, Super, and Ultra, each tailored for different deployment needs, with the Nano model optimized for PCs and edge devices, the Super model for single GPU throughput, and the Ultra model for multi-GPU servers [5] - The models are built on high-quality curated synthetic data and additional datasets co-created by NVIDIA, ensuring flexibility for enterprises to develop custom reasoning models [6] Industry Collaboration - Major industry players such as Microsoft, SAP, and Accenture are collaborating with NVIDIA to integrate Llama Nemotron models into their platforms, enhancing AI capabilities across various applications [4][7][8][10] - Microsoft is incorporating these models into Azure AI Foundry, while SAP is using them to improve its Business AI solutions and AI copilot, Joule [7][8] Deployment and Accessibility - The Llama Nemotron models and NIM microservices are available as hosted APIs, with free access for NVIDIA Developer Program members for development, testing, and research [12] - Enterprises can run these models in production using NVIDIA AI Enterprise on accelerated data center and cloud infrastructure, with additional tools and software to facilitate advanced reasoning in collaborative AI systems [16]