Posts in category: nVidia AI

Taiwan’s leading consumer electronics giants are making advances with AI automation for manufacturing, as fleets of robots and millions of cameras and sensors drive efficiencies across the smart factories of the future.

Dozens of electronics manufacturing and automation specialists — including Foxconn, Pegatron and Wistron — are showcasing their use of the NVIDIA software at COMPUTEX, in Taipei, and are called out in NVIDIA founder and CEO Jensen Huang’s keynote address.

Companies displayed the latest in computer vision and generative AI using NVIDIA Metropolis for everything from automating product manufacturing to improving worker safety and device performance.

Creating Factory Autonomy

With increasing production challenges, manufacturers are seeing a need to turn factories into autonomous machines, with generative AI and digital twins as a foundation. AI agents — driven by large language models (LLMs) — are being built that can talk and assist on warehouse floors to boost productivity and increase safety. And digital twins are helping manufacturers simulate and develop factories and AI-powered automation before being deployed in real factories.

Foxconn and its Ingrasys subsidiary use NVIDIA Omniverse and Metropolis to build digital twins for factories, planning efficiency optimizations and worker safety improvement at a number of manufacturing sites. At COMPUTEX, Foxconn is showing how it uses digital twins to plan placements of many video cameras in factories to optimize its data capture for collecting key insights.

Bringing Generative AI to the Factory Floor

Generative AI is creating productivity leaps across industries. Researcher McKinsey forecasts that generative AI will deliver as much as $290 billion in value for the advanced manufacturing industry, while bringing $4.4 trillion annually to the global economy.

At GTC in March, NVIDIA launched NVIDIA NIM, a set of microservices designed to speed up generative AI deployment in enterprises. Supporting a wide range of AI models, it ensures seamless, scalable AI inferencing, on premises or in the cloud, using industry-standard application programming interfaces.

Billions of IoT devices worldwide can tap into Metropolis and NVIDIA NIM for improvements in AI perception to enhance their capabilities.

Advancing Manufacturing With NVIDIA NIM

Linker Vision, an AI vision insights specialist, is adopting NVIDIA NIM to assist factories in deploying AI agents that can respond to natural language queries.

The Taipei company uses NVIDIA Visual Insight Agent (VIA) in manufacturing environments for always-on video feed monitoring of factory floors. With user prompts, these ChatGPT-like systems can enable operators to ask for video of factory floors to be monitored for insights and safety alerts, like when workers are not wearing hardhats.

Operators can ask questions and receive instant, context-aware responses from AI agents, which can tap into organizational knowledge via retrieval-augmented generation, an integration of AI that can enhance operational efficiency.

Leading manufacturer Pegatron has factories that span more than 20 million square feet and the facilities process and build more than 15 million assemblies per month, while deploying more than 3,500 robots across factory floors. It has announced efforts based on NVIDIA NIM and is using Metropolis multi-camera tracking reference workflows to help with worker safety and productivity on factory lines. Pegatron’s workflow fuses digital twins in Omniverse and Metropolis real-time AI to better monitor and optimize operations.

Boosting Automated Visual Inspections

Adoption of NVIDIA Metropolis is helping Taiwan’s largest electronics manufacturers streamline operations and reduce cost as they build and inspect some of the world’s most complex and high-volume products.

Quality control with manual inspections in manufacturing is a multitrillion-dollar challenge. While automated optical inspection systems have been relied upon for some time, legacy AOI systems have high false detection rates, requiring costly secondary manual inspections for verification.

NVIDIA Metropolis for Factories offers a state-of-the-art AI reference workflow for bringing sophisticated and accurate AOI inspection applications to production faster.

TRI, Taiwan’s leading AOI equipment maker, has announced integrating NVIDIA Metropolis for Factories workflow and capabilities into its latest AOI systems and is also planning to use NVIDIA NIM to further optimize system performance.

Wistron is expanding its OneAI platform for visual inspection and AOI with Metropolis. OneAI has been deployed in more than 10 Wistron factories globally, spanning hundreds of inspection points.

MediaTek, a leading innovator in connectivity and multimedia, and one of Taiwan’s largest IoT silicon vendors, announced at COMPUTEX that it’s teaming with NVIDIA to integrate NVIDIA TAO training and pretrained models into its AI development workflow for IoT device customers. The collaboration brings Metropolis and the latest advances in AI and visual perception to billions of IoT far-edge devices and streamlines software development for MediaTek’s next phase of growth in edge IoT.

Learn about NVIDIA Metropolis for Factories, NVIDIA NIM and the NVIDIA Metropolis multi-camera tracking workflow, which developers can use to build state-of-the-art real-time locating services and worker safety into their factory or warehouse operations. 

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Foxconn operates more than 170 factories around the world — the latest one a virtual plant pushing the state of the art in industrial automation.

It’s the digital twin of a new factory in Guadalajara, hub of Mexico’s electronics industry. Foxconn’s engineers are defining processes and training robots in this virtual environment, so the physical plant can produce at high efficiency the next engine of accelerated computing, NVIDIA Blackwell HGX systems.

To design an optimal assembly line, factory engineers need to find the best placement for dozens of robotic arms, each weighing hundreds of pounds. To accurately monitor the overall process, they situate thousands of sensors, including many networked video cameras in a matrix to show plant operators all the right details.

Virtual Factories Create Real Savings

Such challenges are why companies like Foxconn are increasingly creating virtual factories for simulation and testing.

“Our digital twin will guide us to new levels of automation and industrial efficiency, saving time, cost and energy,” said Young Liu, chairman of the company that last year had revenues of nearly $200 billion.

Based on its efforts so far, the company anticipates that it can increase the manufacturing efficiency of complex servers using the simulated plant, leading to significant cost savings and reducing kilowatt-hour usage by over 30% annually.

Foxconn Teams With NVIDIA, Siemens

Foxconn is building its digital twin with software from the Siemens Xcelerator portfolio including Teamcenter and NVIDIA Omniverse, a platform for developing 3D workflows and applications based on OpenUSD.

NVIDIA and Siemens announced in March that they will connect Siemens Xcelerator applications to NVIDIA Omniverse Cloud API microservices. Foxconn will be among the first to employ the combined services, so its digital twin is physically accurate and visually realistic.

Engineers will employ Teamcenter with Omniverse APIs to design robot work cells and assembly lines. Then they’ll use Omniverse to pull all the 3D CAD elements into one virtual factory where their robots will be trained with NVIDIA Isaac Sim.

Robots Attend a Virtual School

A growing set of manufacturers is building digital twins to streamline factory processes. Foxconn is among the first to take the next step in automation — training their AI robots in the digital twin.

Inside the Foxconn virtual factory, robot arms from manufacturers such as Epson can learn how to see, grasp and move objects with NVIDIA Isaac Manipulator, a collection of NVIDIA-accelerated libraries and AI foundation models for robot arms.

For example, the robot arms may learn how to pick up a Blackwell server and place it on an autonomous mobile robot (AMR). The arms can use Isaac Manipulator’s cuMotion to find inspection paths for products, even when objects are placed in the way.

Foxconn’s AMRs, from Taiwan’s FARobot, will learn how to see and navigate the factory floor using NVIDIA Perceptor, software that helps them build a real-time 3D map that indicates any obstacles. The robot’s routes are generated and optimized by NVIDIA cuOpt, a world-record holding route optimization microservice.

Unlike many transport robots that need to stick to carefully drawn lines on the factory floor, these smart AMRs will navigate around obstacles to get wherever they need to go.

A Global Trend to Industrial Digitization

The Guadalajara factory is just the beginning. Foxconn is starting to design digital twins of factories around the world, including one in Taiwan where it will manufacture electric buses.

Foxconn is also deploying NVIDIA Metropolis, an application framework for smart cities and spaces, to give cameras on the shop floor AI-powered vision. That gives plant managers deeper insights into daily operations and opportunities to further streamline operations and improve worker safety.

With an estimated 10 million factories worldwide, the $46 trillion manufacturing sector is a rich field for industrial digitalization.

Delta Electronics, MediaTek, MSI and Pegatron are among other top electronics makers revealed at COMPUTEX this week how they’re using NVIDIA AI and Omniverse to build digital twins of their factories.

Like Foxconn, they’re racing to make their factories more agile, autonomous and sustainable to serve the demand for more than a billion smartphones, PCs and servers a year.

A reference architecture shows how to develop factory digital twins  with the NVIDIA AI and Omniverse platforms. And learn about the experiences of five companies doing this work.

Watch NVIDIA founder and CEO Jensen Huang’s COMPUTEX keynote to get the latest on AI and more.

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Meta Llama 3, Meta’s openly available state-of-the-art large language model — trained and optimized using NVIDIA accelerated computing — is dramatically boosting healthcare and life sciences workflows, helping deliver applications that aim to improve patients’ lives.

Now available as a downloadable NVIDIA NIM inference microservice at ai.nvidia.com, Llama 3 is equipping healthcare developers, researchers and companies to innovate responsibly across a wide variety of applications. The NIM comes with a standard application programming interface that can be deployed anywhere.

For use cases spanning surgical planning and digital assistants to drug discovery and clinical trial optimization, developers can use Llama 3 to easily deploy optimized generative AI models for copilots, chatbots and more.

At COMPUTEX, one of the world’s premier technology events, NVIDIA today announced that hundreds of AI ecosystem partners are embedding NIM into their solutions.

More than 40 of these adopters are healthcare and life sciences startups and enterprises using the Llama 3 NIM to build and run applications that accelerate digital biology, digital surgery and digital health.

Advancing Digital Biology

Techbio and pharmaceutical companies, along with life sciences platform providers, use NVIDIA NIM for generative biology, chemistry and molecular prediction. With the Llama 3 NIM for intelligent assistants and NVIDIA BioNeMo NIM microservices for digital biology, researchers can build and scale end-to-end workflows for drug discovery and clinical trials.

Deloitte is driving efficiency for garnering data-based insights from gene to function for research copilots, scientific research mining, chemical property prediction and drug repurposing with its Atlas AI drug discovery accelerator, powered by the NVIDIA BioNeMo, NeMo and Llama 3 NIM microservices.

Transcripta Bio harnesses Llama 3 and BioNeMo for accelerated intelligent drug discovery. Its proprietary artificial intelligence modeling suite, Conductor AI, uses its Drug-Gene Atlas to help discover and predict the effects of new drugs at transcriptome scale.

Bolstering Clinical Trials

Quantiphi — an AI-first digital engineering company and an Elite Service Delivery Partner in the NVIDIA Partner Network — is using NVIDIA NIM to develop generative AI solutions for clinical research and development, diagnostics and patient care. These innovations are enabling organizations to save substantial cost, enhance workforce productivity and improve patient outcomes.

ConcertAI is advancing a broad set of translational and clinical development solutions within its CARA AI platform. The company has integrated the Llama 3 NIM to support population-scale patient matching to clinical trials, study automation and research site copilots with real-time insights and model management for large-scale AI applications.

Mendel AI is developing clinically focused AI solutions that can understand nuances in medical data at scale to provide actionable insights, with applications across clinical research, real-world evidence generation and cohort selection. It has deployed a fine-tuned Llama 3 NIM for its Hypercube copilot, offering a 36% performance improvement. Mendel is also exploring potential use cases with Llama 3 NIM to extract clinical information from patient records and to translate natural language into clinical queries.

Improving Digital Surgery

The operating room is bolstered by AI and the latest digital technologies, too.

Activ Surgical is using Llama 3 to accelerate development of its AI copilot and augmented-reality solution for real-time surgical guidance. The company’s ActivSight technology, which allows surgeons to view critical physiological structures and functions, aims to reduce surgical complication rates, improving patient care and safety.

Enhancing Digital Health

Generative AI-powered digital health applications enhance patient-doctor interactions, helping to improve patient outcomes and deliver more efficient healthcare.

Precision medicine company SimBioSys recently downloaded the Llama 3 NIM to help analyze a breast cancer patient’s diagnosis and tailor guidance for the physician regarding the patient’s unique characteristics.

Artisight, a startup focused on smart hospital transformation, uses Llama 3 to automate documentation and care coordination in all its clinical locations with ambient voice and vision systems.

AITEM, which offers medical and veterinary AI diagnostic solutions, is building healthcare-specific chatbots with the model.

And Abridge, which offers a generative AI platform for clinical conversations, is using the NIM to build a physician-patient encounter summarization solution.

Transcripta Bio, Activ Surgical, SimBioSys, Artisight, AITEM and Abridge are all members of NVIDIA Inception, a free program that helps startups evolve faster through cutting-edge technology, opportunities to connect with venture capitalists and access to the latest technical resources from NVIDIA.

The NVIDIA NIM collection of inference microservices is available with NVIDIA AI Enterprise, a software platform that streamlines development and deployment of production-grade copilots and other generative AI applications.

Download the Meta Llama 3 NIM now and learn more about how generative AI is reshaping healthcare and other industries by joining NVIDIA at COMPUTEX, running through June 7 in Taipei, Taiwan.

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Fueled by generative AI, enterprises globally are creating “AI factories,” where data comes in and intelligence comes out.

Critical to this movement are validated systems and reference architectures that reduce the risk and time involved in deploying specialized infrastructure that can support complex, computationally intensive generative AI workloads.

At the COMPUTEX trade show, NVIDIA today announced the expansion of its NVIDIA-Certified Systems program, which designates leading partner systems as suited for AI and accelerated computing, so customers can confidently deploy these platforms from the data center to the edge.

Two new certification types are now included: NVIDIA-Certified Spectrum-X Ready systems for AI in the data center and NVIDIA-Certified IGX systems for AI at the edge.

Each NVIDIA-Certified System undergoes rigorous testing and is validated to provide enterprise-grade performance, manageability, security and scalability for NVIDIA AI Enterprise software workloads, including generative AI applications built with NVIDIA NIM inference microservices. The systems provide a trusted pathway to design and implement efficient, reliable infrastructure.

NVIDIA-Certified Spectrum-X Ready Systems

The world’s first Ethernet fabric built for AI, the NVIDIA Spectrum-X AI Ethernet platform combines the NVIDIA Spectrum-4 SN5000 Ethernet switch series, NVIDIA BlueField-3 SuperNICs and networking acceleration software to deliver 1.6x AI networking performance over traditional Ethernet fabrics.

NVIDIA-Certified Spectrum-X Ready servers will act as building blocks for high-performance AI computing clusters and support powerful NVIDIA Hopper architecture and NVIDIA L40S GPUs.

NVIDIA-Certified IGX Systems

NVIDIA IGX Orin is an enterprise-ready AI platform for the industrial edge and medical applications that features industrial-grade hardware, a production-grade software stack and long-term enterprise support. It includes the latest technologies in device security, remote provisioning and management, along with built-in extensions, to deliver high-performance AI and proactive safety for low-latency, real-time applications in such areas as medical diagnostics, manufacturing, industrial robotics, agriculture and more.

Expanding Partner Portfolio

Top NVIDIA ecosystem partners are set to achieve the new certifications.

ASUS, Dell Technologies, GIGABYTE, Hewlett Packard Enterprise, Ingrasys, Lenovo, QCT and Supermicro will soon offer NVIDIA-Certified Spectrum-X Ready systems.

And NVIDIA-Certified IGX systems will soon be available from ADLINK, Advantech, Aetina, Ahead, Cosmo Intelligent Medical Devices (a division of Cosmo Pharmaceuticals), Dedicated Computing, Leadtek, Onyx and YUAN.

Learn more about NVIDIA-Certified Systems and the latest generative AI technologies by joining NVIDIA at COMPUTEX.

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Taiwan’s leading medical centers — the National Health Research Institute (NHRI) and Chang Gung Memorial Hospital (CGMH) — are set to advance biomedical research and healthcare for patients.

The centers are embracing accelerated computing and generative AI for everything from imaging to enhancing patient care, from streamlining clinical workflows to drug discovery research.

“The use of AI in healthcare will fundamentally change the way we approach disease prevention and treatment,” said Dr. Hung-Yi Chiou, director of the Institute of Population Health Sciences (IPHS) at NHRI. “With AI’s ability to analyze vast amounts of data quickly and accurately, we can develop personalized medicine strategies and early intervention methods that were previously unattainable.”

“The future of AI in healthcare is incredibly promising,” said Dr. Wen-Jin Cherng at CGMH.

With the assistance of AI in smart healthcare, future diagnoses will become more accurate, treatment plans will have better predictions and patients will experience faster recovery, Dr. Cherng explained. And in complex analytical processes, AI can enable more efficient and cost-effective decision-making in healthcare, he added.

“The transformative potential of the NVIDIA Blackwell platform allows us to integrate advanced AI capabilities into our medical practices, enhancing patient care and streamlining clinical workflows like never before,” he said.

NHRI, the leading medical research institution in Taiwan, plays a crucial role in advancing public health through biomedical research and innovation. The integration of NVIDIA accelerated computing into its IT infrastructure marks a significant leap forward in the realm of AI-driven healthcare.

NHRI’s collaboration with NVIDIA also extends to the development of large language models tailored specifically for Taiwan’s healthcare needs.

“Traditional Chinese medical records and genomic data present unique challenges that require localized solutions,” said Dr. Feng-Chi Chen, deputy director of IPHS at the NHRI.

These challenges include the complexity of language variations and the need for precise genomic interpretations specific to Taiwan’s population, Dr. Chen explained.

“NVIDIA accelerated computing enables us to create these solutions, ensuring that our healthcare system remains at the cutting edge of medical research,” he said.

CGMH, one of the largest healthcare systems in Taiwan, operates a network of 10 hospitals with a combined inpatient capacity of over 11,000 beds. It also serves millions of people in outpatient services. It’s a cornerstone of Taiwan’s healthcare system, which is one of the most advanced in the world.

“With the computational power of Blackwell, we can expand our language model services to all hospitals under our umbrella, enhancing professional support, patient care and streamlining clinical workflows,” said Dr. Chang-Fu Kuo, director of the AI center at CGMH. “It addresses the needs of various medical disciplines and diverse patient populations, enabling healthcare professionals to focus on critical clinical tasks and ultimately improve patient outcomes.”

NHRI, CGMH Pioneering Medical AI

NHRI currently uses six NVIDIA DGX A100 systems for cloud and data center services, focusing on biomedical model training and genomic analysis.

By harnessing the power of NVIDIA accelerated computing, NHRI is also tackling pressing public health issues. One of its key projects involves using AI to predict the risk of chronic diseases such as diabetes and cardiovascular conditions by analyzing a multitude of genetic and environmental parameters.

“This level of analysis was previously unattainable due to computational constraints,” said Dr. Chen. “Now, with the power of NVIDIA accelerated computing, we will be able to offer more accurate risk assessments and preventative strategies.”

CGMH also has a diverse array of NVIDIA hardware, including NVIDIA H100, A100, and other Tensor Core GPUs, which it uses for medical imaging development and deployment. The foundation serves 46 models daily and intends to use Blackwell for LLM training and the deployment of service robots in hospitals.

Running these systems on premises and keeping the data within the hospital’s infrastructure are key to ensuring patient data privacy as well as faster data processing and reduced latency, said Dr. Chihung Lin, deputy director of the CGMH AI center.

These technologies may be used in various medical applications, including:

• Clinical Decision Support System: Developed on premises to ensure patient data confidentiality and privacy, this system assists clinicians by providing access to up-to-date data and guidelines and using models to answer questions and prepare medical decisions.
• Patient Interaction System: Allows patients to interact with a robot to get answers about their medication and medical conditions, reducing the burden on medical staff. Medical staff review the robot’s responses to ensure accuracy.
• Medical Imaging: Enhances radiology and other imaging tasks using AI. This project is one of the most mature AI technologies in CGMH’s healthcare system.
• Precision Medicine: Handles large-scale genomic data and transforms sequences into readable medical reports for doctors. Focused on building computational facilities to support whole genome and exome sequencing.
• Expansion of AI Services: Aims to extend the language model services to all hospitals under CGMH’s umbrella, leveraging the computational capacity from the Blackwell platform to support this expansion.

Other applications include early detection of colorectal cancer via endoscopy, autoimmune disease screening through microscope images and kidney disease prediction using general imaging techniques.

NHRI and CGMH’s adoption of accelerated computing underscores the growing importance of AI and advanced computing in medical research and healthcare delivery.

With these tools, Taiwan is poised to make strides in improving patient outcomes and advancing biomedical science.

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Weather forecasters in Taiwan had their hair blown back when they saw a typhoon up close, created on a computer that slashed the time and energy needed for the job.

It’s a reaction that users in many fields are feeling as generative AI shows them how new levels of performance contribute to reductions in total cost of ownership.

Inside the AI of the Storm

Tracking a typhoon provided a great test case of generative AI’s prowess. The work traditionally begins with clusters of CPUs cranking on complex algorithms to create atmospheric models with a 25-kilometer resolution.

Enter CorrDiff, a generative AI model that’s part of NVIDIA Earth-2, a set of services and software for weather and climate research.

Using a class of diffusion models that power today’s text-to-image services, CorrDiff resolved the 25-km models to two kilometers 1,000x faster, using 3,000x less energy for a single inference than traditional methods.

CorrDiff Cuts Costs 50x, Energy Use 25x

CorrDiff shines on the NVIDIA AI platform, even when retraining the model once a year and using statistical groups of a thousand forecasts to boost the accuracy of predictions. Compared to traditional methods under these conditions, it slashes cost by 50x cost and energy use by 25x a year.

That means work that used to require nearly $3 million for a cluster of CPUs and the energy to run them can be done for about $60,000 on a single system with an NVIDIA H100 Tensor Core GPU. It’s a massive reduction that shows how generative AI and accelerated computing increases energy efficiency and lowers total cost of ownership.

The technology also helps forecasters see more precisely where a typhoon will land, potentially saving lives.

“NVIDIA’s CorrDiff generative AI model opens the door to the use of AI-generated kilometer-scale weather forecasts, enabling Taiwan to prepare better for typhoons,” said Hongey Chen, a director of Taiwan’s National Science and Technology Center for Disaster Reduction.

The Taiwan forecasters could save nearly a gigawatt-hour a year, using CorrDiff. Energy savings could balloon if the nearly 200 regional weather data centers around the world adopt the technology for more sustainable computing.

Companies that sell commercial forecasts are also adopting CorrDiff, attracted by its speed and savings.

Broad Horizons for Energy Efficiency

NVIDIA Earth-2 takes these capabilities to a planetary scale. It fuses AI, physics simulations and observed data to help countries and companies respond to global issues like climate change. That will help address the impacts of climate change, which is expected to cost a million lives and $1.7 trillion per year by 2050.

Accelerated computing and generative AI are bringing new levels of performance and energy efficiency to many applications. Explainers on green computing and why GPUs are great for AI provide more context and some examples.

Compare the costs and energy consumption of popular workloads running on an x86 CPU-based server versus an NVIDIA GPU server with this simple calculator. And watch Huang’s keynote address at COMPUTEX to get the big picture.

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AI gives every company an opportunity to turn its processes into a data flywheel, NVIDIA founder and CEO Jensen Huang told thousands of attendees Monday at the Snowflake Data Cloud Summit.

Companies need to “take all the most important processes they do, capture them in a data flywheel and turn that into the company’s AI to drive that flywheel even further,” said Huang, joining from Taipei a virtual fireside chat with Snowflake’s CEO Sridhar Ramaswamy in San Francisco.

The two executives described how the combination of the Snowflake AI Data Cloud and NVIDIA AI will simplify and accelerate enterprise AI.

“You want to jump on this train as fast as you can, don’t let it fly by because you can use it to transform your business or go into new businesses,” said Huang, the day after he gave a keynote kicking off COMPUTEX in Taiwan.

Snowflake Users Can Tap Into NVIDIA AI Enterprise

For example, businesses will be able to deploy Snowflake Arctic, an enterprise-focused large language model (LLM), in seconds using NVIDIA NIM inference microservices, part of the NVIDIA AI Enterprise software platform. 

Arctic was trained on NVIDIA H100 Tensor Core GPUs and is available on the NVIDIA API catalog, fully supported by NVIDIA TensorRT-LLM, software that accelerates generative AI inference.

The two companies also will integrate Snowflake Cortex AI and NVIDIA NeMo Retriever, so businesses can link their AI-powered applications to information sources, ensuring highly accurate results with retrieval-augmented generation (RAG).

Ramaswamy gave examples of generative AI applications developed with the NVIDIA NeMo framework and Snowpark Container Services that will be available on Snowflake Marketplace for use by thousands of Snowflake’s customers.

“NVIDIA’s industry-leading accelerated computing is game changing for our customers and our own research team that used it to create the state-of-the-art Artic model for our customers,” said Ramaswamy.

To learn more, watch NVIDIA GTC on-demand sessions presented by Snowflake on how to build chatbots with a RAG architecture and how to leverage LLMs for life sciences.

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After the 2008 financial crisis and increased risk-management regulations that followed, Pierre Spatz anticipated banks would focus on reducing computing expenses.

As head of quantitative research at Murex, a trading and risk management software company based in Paris, Spatz adopted NVIDIA’s CUDA and GPU-accelerated computing, aiming for top performance and energy efficiency.

Always seeking the latest technologies, the company’s quants team has begun trials of the NVIDIA Grace Hopper Superchip. The effort is focused on helping customers better price and manage credit and market risk exposures of derivatives contracts.

More than 60,000 daily users in 65 countries rely on the Murex MX.3 platform. MX.3 assists banks, asset managers, pension funds and other financial institutions with their trading, risk and operations across asset classes.

Managing Risk With MX.3 Driven by Grace Hopper

Financial institutions need high-performance computing infrastructure to run risk models on vast amounts of data for pricing and risk calculations, and to deliver real-time decision-making capabilities.

MX.3 coverage includes both credit and market risk, fundamental review of the trading book and x-valuation adjustment (XVA). XVA is used for different types of valuation adjustments related to derivative contracts, such as the credit value adjustment (CVA), the margin value adjustment and the funding valuation adjustment.

Murex is testing Grace Hopper on the MX.3 platform for XVA calculations, as well as for market risk calibration, pricing evaluation, sensitivity, and profit and loss calculations on various asset classes.

Grace Hopper offers faster calculation as well as power savings to the Murex platform.

“On counterparty credit risk workloads such as CVA, Grace Hopper is the perfect fit, leveraging a heterogeneous architecture with a unique mix of CPU and GPU computations,” Spatz said. “On risk calculations, Grace is not only the fastest processor, but also far more power-efficient, making green IT a reality in the trading world.”

When running XVA workloads in MX.3, the Murex research and development lab has noticed Grace Hopper can offer a 4x reduction in energy consumption and a 7x performance improvement compared with CPU-based systems.

Pricing FX Barrier Options in MX.3 With Grace Hopper 

To price foreign exchange (FX) barrier options, Murex has used its flagship and latest stochastic local volatility model and also noticed impressive performance improvements when running on Grace Hopper. A barrier option is a derivative with a payoff that relies on whether its underlying asset price reaches or crosses a specified threshold during the span of the option contract.

The pricing evaluation is done with a 2D partial differential equation, which is more cost-effective on the Arm-based NVIDIA Grace CPU in GH200. Pricing this derivative with MX.3 on Grace Hopper goes 2.3x faster compared with Intel Xeon Gold 6148.

The NVIDIA Grace CPU also offers significant power efficiencies for FX barrier calculations on a watts-per-server basis, and it’s 5x better.

NVIDIA’s next-generation accelerated computing platform is driving energy efficiency and cost-saving for high-performance computing for quantitative analytics in capital markets, says Murex, pointing to the results above.

Learn about NVIDIA AI solutions for financial services.

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NVIDIA has introduced a self-paced course, called AI Infrastructure and Operations Fundamentals, to provide enterprise professionals with essential training on the infrastructure and operational aspects of AI and accelerated computing. 

From enhancing speech recognition systems to powering self-driving cars, AI is transforming everyday life. The new course explains how to deploy and manage scalable infrastructure to support AI-based solutions, helping IT pros realize AI’s potential and stay competitive in the rapidly changing technological landscape. 

Course Overview  

The course is ideal for anyone seeking to expand their knowledge of AI and its applications. It was created and taught by NVIDIA experts with real-world experience and deep technical domain expertise.

The course is divided into three modules. The first, Introduction to AI, covers foundational AI concepts and principles. Learners will:   

• Discover how AI is being applied in various sectors, to drive innovation and efficiency  
• Trace the progression of AI from basic machine learning to advanced deep learning to generative AI — and learn how each phase unlocked new capabilities  
• Explore how GPUs revolutionized AI, providing the computational power necessary for complex AI tasks  
• Understand the importance of a robust software stack in ensuring optimal performance and efficiency  
• Delve into the environments where AI workloads operate, whether on premises or in the cloud  

AI Infrastructure, the second module, dives into the critical infrastructure components that support AI operations. Learners will:  

• Gain knowledge about the hardware that powers AI, including the latest advancements in compute platforms, networking and storage   
• Explore practices that reduce data center carbon footprints and energy usage 
• Discover how reference architectures can serve as a foundation for building the most effective AI designs  
• Evaluate the benefits of transitioning from on-premises data centers to cloud-based solutions  

AI Operations, the final module, focuses on the practical aspect of managing AI infrastructure. Learners will:  

• Gain insights into the tools and techniques that enable effective infrastructure management and monitoring  
• Learn about orchestrating AI clusters and scheduling tasks to maximize performance and resource efficiency  

Certification: AI Infrastructure and Operations Associate  

Alongside the course, NVIDIA offers a new AI Infrastructure and Operations associate certification. This entry-level credential validates knowledge of the foundational concepts of adopting AI computing with NVIDIA solutions. Topics covered in this exam include: 

• Accelerated computing use cases 
• AI, machine learning and deep learning 
• GPU architecture 
• NVIDIA’s software suite 
• Infrastructure and operation considerations for adopting NVIDIA solutions 

Whether attendees want to enhance existing skills, support projects, advance career paths, or embark on a new professional trajectory, this AI course and certification will further the knowledge and skills needed to excel in using AI. 

Learn more about this training and certification.  

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World of Warcraft comes to the cloud this week, part of the 17 games joining the GeForce NOW library, with seven available to stream this week.

Plus, it’s time to get rewarded. Get a free in-game mount in Elder Scrolls Online starting today by opting into GeForce NOW’s Rewards program.

Heroes Rise to the Cloud

Dive into the immersive realms of World of Warcraft, including the latest expansion Dragonflight, the nostalgic journey of World of Warcraft Classic and the recently launched World of Warcraft Cataclysm Classic. These popular, massively multiplayer, online role-playing experiences from Blizzard Entertainment immerse players in legendary battles.

Embark on a journey of endless adventure in the rich and dynamic universe of Azeroth in the latest modern expansion, World of Warcraft: Dragonflight. The expansive landscapes of the Dragon Isles are available to explore — even on the back of a fearsome dragon. The newly awakened Dracthyr Evokers are also available, World of Warcraft’s first-ever playable race-and-class combo. GeForce NOW Priority and Ultimate members can get immersed in the cinematic gameplay with support for RTX ON.

Face the return of Deathwing the Destroyer, whose violent emergence shatters and reshapes the continent of Azeroth. Journey into an era of fire and destruction in World of Warcraft Cataclysm Classic and usher in a new era for Azeroth. The updated game brings new dungeons and raids, fresh race and class combinations, and more.

Whether a seasoned adventurer or a newcomer to the game, head to the Azeroth of yesteryear in World of Warcraft Classic and relive the experience of the game as it was upon its initial launch, with a few new upgrades. Explore the Eastern Kingdoms and Kalimdor, venture into iconic dungeons or engage in legendary player-vs-player battles.

Experience it all with a GeForce NOW membership, which means no waiting for downloads or games to update, even for the upcoming World of Warcraft expansion The War Within.

Mount Up

GeForce NOW members get access to rewards that enhance the gaming experience. This week The Elder Scrolls Online 10-year celebration continues with an in-game reward for GeForce NOW members.

Mounts offer a great way to travel the world and provide a completely different experience to traveling on foot. This new free reward provides members with a trusty companion beyond the starter option. The mount has a sunny disposition, matching its vibrant, multihued coat. It’s an excellent horse for a new rider or one who regularly ventures into treacherous situations.

Members can claim their free mount starting today by opting into rewards and checking their email for instructions on how to redeem. Ultimate and Priority members can redeem starting today, while free members will be able to claim it starting May 31. It’s available until June 30, first come first served.

New Games, Assemble!

Build a team of heroes and fight to take back the city in Capes, a turn-based strategy game from Daedlic Entertainment. Recruit, train and deploy a team to take back the city from the villains that hold it hostage. Level up heroes to gain access to new abilities and powerful upgrades — plus, each hero gains a unique team-up ability from each of their allies.

Check out the full list of new games this week:

• The Rogue Prince of Persia (New release on Steam, May 27)
• Capes (New release on Steam, May 29)
• Lords of the Fallen (New release on Xbox, available on PC Game Pass, May 30)
• Soulmask (New release on Steam, May 31)
• Path of Exile (Steam)
• World of Warcraft: Dragonflight (Battle.net)
• World of Warcraft Classic (Battle.net)
• World of Warcraft Cataclysm Classic (Battle.net)

And members can look for the following later this month:

• Autopsy Simulator (New release on Steam, June 6)
• Chornobyl Liquidators (New release on Steam, June 6)
• SunnySide (New release on Steam, June 14)
• Still Wakes the Deep (New release on Steam and Xbox, available on PC Game Pass, June 18)
• Disney Speedstorm (Steam and Xbox, available on PC Game Pass)
• Farm Together 2 (Steam)
• Resident Evil Village (Steam)
• Star Traders: Frontiers (Steam)
• Street Fighter 6 (Steam)
• Torque Drift 2 (Epic Games Store)

More to May

In addition to the 24 games announced last month, four more joined the GeForce NOW library:

• Senua’s Saga: Hellblade II (New release on Steam and Xbox, available on PC Game Pass, May 21)
• Serum (New release on Steam, May 23)
• Palworld (Steam, and Xbox, available on PC Game Pass)
• Tomb Raider: Definitive Edition (Xbox, available on PC Game Pass)

Gestalt, Norland and Sunnyside have delayed their launch dates to later this year. Stay tuned to GFN Thursday for updates.

From Tamriel to Teyvet, Night City to Sanctuary, GeForce NOW brings the world of PC gaming to nearly any device. Share your favorite gaming destinations all month long using #GreetingsFromGFN for a chance to be featured on the @NVIDIAGFN channels.

What are you planning to play this weekend? Let us know on X or in the comments below.

https://x.com/NVIDIAGFN/status/1795847572793274591

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