Turning AI Concepts into Reality at Booth #2121Summary:SAN JOSE, Calif., March 18, 2025 /PRNewswire/ -- ADLINK Technology Inc., a global leader in edge computing and an NVIDIA Elite Partner, is set to showcase its Edge AI, generative AI, and robotics solutions at the upcoming 2025 NVIDIA GTC conference, at booth #2121. ADLINK Edge AI and Generative AI Innovations Accelerating Economical Generative AI at the EdgeGenerative AI adoption at edge devices is often limited by DRAM capacity constraints when r ...

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]

Core Insights - NVIDIA has announced a collaboration with GE HealthCare to innovate in autonomous imaging, specifically focusing on autonomous X-ray technologies and ultrasound applications [1][3] - The partnership aims to enhance access to healthcare services globally, as nearly two-thirds of the global population currently lacks access to essential imaging technologies [3] Company Collaboration - GE HealthCare is utilizing NVIDIA's Isaac™ for Healthcare platform, which includes pretrained models and physics-based simulations to accelerate the development of autonomous imaging systems [2][6] - The collaboration has been ongoing for nearly two decades, focusing on innovative image-reconstruction techniques across various imaging modalities [4] Technological Advancements - Isaac for Healthcare is a physical AI platform that integrates NVIDIA's advanced computing systems, enabling robotic systems to learn and operate in medical environments [6][9] - The platform allows for multi-scale simulation, covering everything from microscopic structures to full hospital facilities, facilitating training for robotic systems in various medical scenarios [8][9] Industry Impact - The healthcare industry is increasingly adopting AI technologies to address the growing demand for services, with NVIDIA and GE HealthCare aiming to improve patient care and access through autonomous imaging [3][5] - Early adopters of the Isaac for Healthcare platform include companies like Moon Surgical, Neptune Medical, and Xcath, indicating a rapid expansion of the healthcare robotics ecosystem [9][10]

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]

Core Insights - NVIDIA has introduced the Omniverse Blueprint for Earth-2 weather analytics to enhance the accuracy of weather forecasting solutions [1][2] - The climate-related weather events have caused a $2 trillion impact on the global economy over the past decade, highlighting the need for improved risk management and disaster preparedness [2] - The Omniverse Blueprint provides reference workflows, including GPU acceleration libraries and AI frameworks, to facilitate the transition from prototyping to production in weather forecast models [3] Technology and Tools - The blueprint includes NVIDIA NIM microservices such as CorrDiff for downscaling and FourCastNet for predicting global atmospheric dynamics, which are already in use by various weather technology companies and government agencies [4][10] - The Earth-2 platform allows developers to create solutions that provide rapid warnings and updated forecasts, significantly faster than traditional CPU-driven models, with a market size of $20 billion in climate tech [6] - NVIDIA's CorrDiff model is noted for being 500 times faster and 10,000 times more energy-efficient than traditional methods for delivering high-resolution weather predictions [10] Industry Adoption - Companies like G42, JBA Risk Management, and Spire are among the first to adopt the Omniverse Blueprint, developing AI-augmented solutions for advanced weather forecasting and disaster management [5][8] - G42 is integrating the blueprint with its AI-driven forecasting models to enhance the UAE's National Center of Meteorology's capabilities [7] - Spire Global is utilizing AI components from the blueprint to create new products that integrate satellite data for medium-range forecasts, achieving a speed increase of 1,000 times compared to traditional models [8] Collaboration and Ecosystem - The blueprint supports collaboration with industry leaders, including Esri and OroraTech, to enhance geospatial technology and data integration [11] - Tomorrow.io is contributing satellite data to help create an NVIDIA digital twin of Earth for advanced AI model training [12] - The Omniverse platform enables independent software vendors to develop AI-augmented solutions, enhancing the speed and accuracy of weather forecasting [11] Computational Power - The Omniverse Blueprint leverages NVIDIA DGX Cloud for full-stack acceleration in AI-augmented weather forecasting, utilizing advanced supercomputers for climate simulations [14]

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]

Core Insights - NVIDIA has announced that several leading industrial software and service providers are integrating the NVIDIA Omniverse platform to enhance industrial digitalization with physical AI [1][9][10] - New Omniverse Blueprints are available to facilitate robot-ready facilities and large-scale synthetic data generation for physical AI development [2][8] Industrial Adoption - Major companies such as Schaeffler, Accenture, Hyundai Motor Group, and Mercedes-Benz are utilizing Omniverse Blueprints to optimize their manufacturing operations [4][12] - In electronics manufacturing, Pegatron and Foxconn are leveraging the Mega blueprint for improving factory operations and worker safety [5][6] Technological Advancements - The Omniverse platform is described as an operating system that connects physical data to physical AI, enabling the creation of new applications that enhance industrial ecosystems [3][10] - New Blueprints like Mega and the AI factory digital twins are designed to maximize efficiency in industrial settings [7][9] Cloud Integration - NVIDIA Omniverse is now available as virtual desktop images on AWS and Microsoft Azure, simplifying the development and deployment of OpenUSD-based applications [13][14] Collaboration and Ecosystem - Companies such as Databricks, Ansys, and Siemens are integrating Omniverse technologies into their software solutions to accelerate product development and optimize manufacturing processes [10][11]

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]