Posts in category: nVidia AI

Austin is drawing people to jobs, music venues, comedy clubs, barbecue and more. But with this boom has come a big city blues: traffic jams.

Rekor, which offers traffic management and public safety analytics, has a front-row seat to the increasing traffic from an influx of new residents migrating to Austin. Rekor works with the Texas Department of Transportation, which has a $7 billion project addressing this, to help mitigate the roadway concerns.

“Texas has been trying to meet that growth and demand on the roadways by investing a lot in infrastructure, and they’re focusing a lot on digital infrastructure,” said Shervin Esfahani, vice president of global marketing and communications at Rekor. “It’s super complex, and they realized their traditional systems were unable to really manage and understand it in real time.”

Rekor, based in Columbia, Maryland, has been harnessing NVIDIA Metropolis for real-time video understanding and NVIDIA Jetson Xavier NX modules for edge AI in Texas, Florida, Philadelphia, Georgia, Nevada, Oklahoma and many more U.S. destinations as well as in Israel and other places internationally.

Metropolis is an application framework for smart infrastructure development with vision AI. It provides developer tools, including the NVIDIA DeepStream SDK, NVIDIA TAO Toolkit, pretrained models on the NVIDIA NGC catalog and NVIDIA TensorRT. NVIDIA Jetson is a compact, powerful and energy-efficient accelerated computing platform used for embedded and robotics applications.

Rekor’s efforts in Texas and Philadelphia to help better manage roads with AI are the latest development in an ongoing story for traffic safety and traffic management.

Reducing Rubbernecking, Pileups, Fatalities and Jams

Rekor offers two main products: Rekor Command and Rekor Discover. Command is an AI-driven platform for traffic management centers, providing rapid identification of traffic events and zones of concern. It offers departments of transportation with real-time situational awareness and alerts that allows them to keep city roadways safer and more congestion-free.

Discover taps into Rekor’s edge system to fully automate the capture of comprehensive traffic and vehicle data and provides robust traffic analytics that turn roadway data into measurable, reliable traffic knowledge. With Rekor Discover, departments of transportation can see a full picture of how vehicles move on roadways and the impact they make, allowing them to better organize and execute their future city-building initiatives.

The company has deployed Command across Austin to help detect issues, analyze incidents and respond to roadway activity with a real-time view.

“For every minute an incident happens and stays on the road, it creates four minutes of traffic, which puts a strain on the road, and the likelihood of a secondary incident like an accident from rubbernecking massively goes up,” said Paul-Mathew Zamsky, vice president of strategic growth and partnerships at Rekor. “Austin deployed Rekor Command and saw a 159% increase in incident detections, and they were able to respond eight and a half minutes faster to those incidents.”

Rekor Command takes in many feeds of data — like traffic camera footage, weather, connected car info and construction updates — and taps into any other data infrastructure, as well as third-party data. It then uses AI to make connections and surface up anomalies, like a roadside incident. That information is presented in workflows to traffic management centers for review, confirmation and response.

“They look at it and respond to it, and they are doing it faster than ever before,” said Esfahani. “It helps save lives on the road, and it also helps people’s quality of life, helps them get home faster and stay out of traffic, and it reduces the strain on the system in the city of Austin.”

In addition to adopting NVIDIA’s full-stack accelerated computing for roadway intelligence, Rekor is going all in on NVIDIA AI and NVIDIA AI Blueprints, which are reference workflows for generative AI use cases, built with NVIDIA NIM microservices as part of the NVIDIA AI Enterprise software platform. NVIDIA NIM is a set of easy-to-use inference microservices for accelerating deployments of foundation models on any cloud or data center while keeping data secure.

Rekor has multiple large language models and vision language models  running on NVIDIA Triton Inference Server in production,” according to Shai Maron, senior vice president of global software and data engineering at Rekor. 

“Internally, we’ll use it for data annotation, and it will help us optimize different aspects of our day to day,” he said. “LLMs externally will help us calibrate our cameras in a much more efficient way and configure them.”

Rekor is using the NVIDIA AI Blueprint for video search and summarization to build AI agents for city services, particularly in areas such as traffic management, public safety and optimization of city infrastructure. NVIDIA recently announced a new AI Blueprint for video search and summarization enabling a range of interactive visual AI agents that extracts complex activities from massive volumes of live or archived video.

Philadelphia Monitors Roads, EV Charger Needs, Pollution

Philadelphia Navy Yard is a tourism hub run by the Philadelphia Industrial Development Corporation (PIDC), which has some challenges in road management and gathering data on new developments for the popular area. The Navy Yard location, occupying 1,200 acres, has more than 150 companies and 15,000 employees, but a $6 billion redevelopment plan there promises to bring in 12,000-plus new jobs and thousands more as residents to the area.

PIDC sought greater visibility into the effects of road closures and construction projects on mobility and how to improve mobility during significant projects and events. PIDC also looked to strengthen the Navy Yard’s ability to understand the volume and traffic flow of car carriers or other large vehicles and quantify the impact of speed-mitigating devices deployed across hazardous stretches of roadway.

Discover provided PIDC insights into additional infrastructure projects that need to be deployed to manage any changes in traffic.

Understanding the number of electric vehicles, and where they’re entering and leaving the Navy Yard, provides PIDC with clear insights on potential sites for electric vehicle (EV) charge station deployment in the future. By pulling insights from Rekor’s edge systems, built with NVIDIA Jetson Xavier NX modules for powerful edge processing and AI, Rekor Discover lets Navy Yard understand the number of EVs and where they’re entering and leaving, allowing PIDC to better plan potential sites for EV charge station deployment in the future.

Rekor Discover enabled PIDC planners to create a hotspot map of EV traffic by looking at data provided by the AI platform. The solution relies on real-time traffic analysis using NVIDIA’s DeepStream data pipeline and Jetson. Additionally, it uses NVIDIA Triton Inference Server to enhance LLM capabilities.

The PIDC wanted to address public safety issues related to speeding and collisions as well as decrease property damage. Using speed insights, it’s deploying traffic calming measures where average speeds are exceeding what’s ideal on certain segments of roadway.

NVIDIA Jetson Xavier NX to Monitor Pollution in Real Time

Traditionally, urban planners can look at satellite imagery to try to understand pollution locations, but Rekor’s vehicle recognition models, running on NVIDIA Jetson Xavier NX modules, were able to track it to the sources, taking it a step further toward mitigation.

“It’s about air quality,” said Shobhit Jain, senior vice president of product management at Rekor. “We’ve built models to be really good at that. They can know how much pollution each vehicle is putting out.”

Looking ahead, Rekor is examining how NVIDIA Omniverse might be used for digital twins development in order to simulate traffic mitigation with different strategies. Omniverse is a platform for developing OpenUSD applications for industrial digitalization and generative physical AI.

Developing digital twins with Omniverse for municipalities has enormous implications for reducing traffic, pollution and road fatalities — all areas Rekor sees as hugely beneficial to its customers.

“Our data models are granular, and we’re definitely exploring Omniverse,” said Jain. “We’d like to see how we can support those digital use cases.”

Learn about the NVIDIA AI Blueprint for building AI agents for video search and summarization.

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Enterprises and public sector organizations around the world are developing AI agents to boost the capabilities of workforces that rely on visual information from a growing number of devices — including cameras, IoT sensors and vehicles.

To support their work, a new NVIDIA AI Blueprint for video search and summarization will enable developers in virtually any industry to build visual AI agents that analyze video and image content. These agents can answer user questions, generate summaries and enable alerts for specific scenarios.

Part of NVIDIA Metropolis, a set of developer tools for building vision AI applications, the blueprint is a customizable workflow that combines NVIDIA computer vision and generative AI technologies.

Global systems integrators and technology solutions providers including Accenture, Dell Technologies and Lenovo are bringing the NVIDIA AI Blueprint for visual search and summarization to businesses and cities worldwide, jump-starting the next wave of AI applications that can be deployed to boost productivity and safety in factories, warehouses, shops, airports, traffic intersections and more.

Announced ahead of the Smart City Expo World Congress, the NVIDIA AI Blueprint gives visual computing developers a full suite of optimized software for building and deploying generative AI-powered agents that can ingest and understand massive volumes of live video streams or data archives.

Users can customize these visual AI agents with natural language prompts instead of rigid software code, lowering the barrier to deploying virtual assistants across industries and smart city applications.

NVIDIA AI Blueprint Harnesses Vision Language Models

Visual AI agents are powered by vision language models (VLMs), a class of generative AI models that combine computer vision and language understanding to interpret the physical world and perform reasoning tasks.

The NVIDIA AI Blueprint for video search and summarization can be configured with NVIDIA NIM microservices for VLMs like NVIDIA VILA, LLMs like Meta’s Llama 3.1 405B and AI models for GPU-accelerated question answering and context-aware retrieval-augmented generation. Developers can easily swap in other VLMs, LLMs and graph databases and fine-tune them using the NVIDIA NeMo platform for their unique environments and use cases.

Adopting the NVIDIA AI Blueprint could save developers months of effort on investigating and optimizing generative AI models for smart city applications. Deployed on NVIDIA GPUs at the edge, on premises or in the cloud, it can vastly accelerate the process of combing through video archives to identify key moments.

In a warehouse environment, an AI agent built with this workflow could alert workers if safety protocols are breached. At busy intersections, an AI agent could identify traffic collisions and generate reports to aid emergency response efforts. And in the field of public infrastructure, maintenance workers could ask AI agents to review aerial footage and identify degrading roads, train tracks or bridges to support proactive maintenance.

Beyond smart spaces, visual AI agents could also be used to summarize videos for people with impaired vision, automatically generate recaps of sporting events and help label massive visual datasets to train other AI models.

The video search and summarization workflow joins a collection of NVIDIA AI Blueprints that make it easy to create AI-powered digital avatars, build virtual assistants for personalized customer service and extract enterprise insights from PDF data.

NVIDIA AI Blueprints are free for developers to experience and download, and can be deployed in production across accelerated data centers and clouds with NVIDIA AI Enterprise, an end-to-end software platform that accelerates data science pipelines and streamlines generative AI development and deployment.

AI Agents to Deliver Insights From Warehouses to World Capitals

Enterprise and public sector customers can also harness the full collection of NVIDIA AI Blueprints with the help of NVIDIA’s partner ecosystem.

Global professional services company Accenture has integrated NVIDIA AI Blueprints into its Accenture AI Refinery, which is built on NVIDIA AI Foundry and enables customers to develop custom AI models trained on enterprise data.

Global systems integrators in Southeast Asia — including ITMAX in Malaysia and FPT in Vietnam — are building AI agents based on the video search and summarization NVIDIA AI Blueprint for smart city and intelligent transportation applications.

Developers can also build and deploy NVIDIA AI Blueprints on NVIDIA AI platforms with compute, networking and software provided by global server manufacturers.

Dell will use VLM and agent approaches with Dell’s NativeEdge platform to enhance existing edge AI applications and create new edge AI-enabled capabilities. Dell Reference Designs for the Dell AI Factory with NVIDIA and the NVIDIA AI Blueprint for video search and summarization will support VLM capabilities in dedicated AI workflows for data center, edge and on-premises multimodal enterprise use cases.

NVIDIA AI Blueprints are also incorporated in Lenovo Hybrid AI solutions powered by NVIDIA.

Companies like K2K, a smart city application provider in the NVIDIA Metropolis ecosystem, will use the new NVIDIA AI Blueprint to build AI agents that analyze live traffic cameras in real time. This will enable city officials to ask questions about street activity and receive recommendations on ways to improve operations. The company also is working with city traffic managers in Palermo, Italy, to deploy visual AI agents using NIM microservices and NVIDIA AI Blueprints.

Discover more about the NVIDIA AI Blueprint for video search and summarization by visiting the NVIDIA booth at the Smart Cities Expo World Congress, taking place in Barcelona through Nov. 7.

Learn how to build a visual AI agent.

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A new AI-powered, imaging-based technology that creates accurate three-dimensional models of tumors, veins and other soft tissue offers a promising new method to help surgeons operate on, and better treat, breast cancers.

The technology, from Illinois-based startup SimBioSys, converts routine black-and-white MRI images into spatially accurate, volumetric images of a patient’s breasts. It then illuminates different parts of the breast with distinct colors — the vascular system, or veins, may be red; tumors are shown in blue; surrounding tissue is gray.

Surgeons can then easily manipulate the 3D visualization on a computer screen, gaining important insight to help guide surgeries and influence treatment plans. The technology, called TumorSight, calculates key surgery-related measurements, including a tumor’s volume and how far tumors are from the chest wall and nipple.

It also provides key data about a tumor’s volume in relation to a breast’s overall volume, which can help determine — before a procedure begins — whether surgeons should try to preserve a breast or choose a mastectomy, which often presents cosmetic and painful side effects. Last year, TumorSight received FDA clearance.

Across the world, nearly 2.3 million women are diagnosed with breast cancer each year, according to the World Health Organization. Every year, breast cancer is responsible for the deaths of more than 500,000 women. Around 100,000 women in the U.S. annually undergo some form of mastectomy, according to the Brigham and Women’s Hospital.

According to Jyoti Palaniappan, chief commercial officer at SimBioSys, the company’s visualization technology offers a step-change improvement over the kind of data surgeons typically see before they begin surgery.

“Typically, surgeons will get a radiology report, which tells them, ‘Here’s the size and location of the tumor,’ and they’ll get one or two pictures of the patient’s tumor,” said Palaniappan. “If the surgeon wants to get more information, they’ll need to find the radiologist and have a conversation with them — which doesn’t always happen — and go through the case with them.”

Dr. Barry Rosen, the company’s chief medical officer, said one of the technology’s primary goals is to uplevel and standardize presurgical imaging, which he believes can have broad positive impacts on outcomes.

“We’re trying to move the surgical process from an art to a science by harnessing the power of AI to improve surgical planning,” Dr. Rosen said.

SimBioSys uses NVIDIA A100 Tensor Core GPUs in the cloud for pretraining its models. It also uses NVIDIA MONAI for training and validation data, and NVIDIA CUDA-X libraries including cuBLAS and MONAI Deploy to run its imaging technology. SimBioSys is part of the NVIDIA Inception program for startups.

SimBioSys is already working on additional AI use cases it hopes can improve breast cancer survival rates.

It has developed a novel technique to reconcile MRI images of a patient’s breasts, taken when the patient is lying face down, and converts those images into virtual, realistic 3D visualizations that show how the tumor and surrounding tissue will appear during surgery — when a patient is lying face up.

This 3D visualization is especially relevant for surgeons so they can visualize what a breast  and any tumors will look like once surgery begins.

To create this imagery, the technology calculates gravity’s impact on different kinds of breast tissue and accounts for how different kinds of skin elasticity impact a breast’s shape when a patient is lying on the operating table.

The startup is also working on a new strategy that also relies on AI to quickly provide insights that can help avoid cancer recurrence.

Currently, hospital labs run pathology tests on tumors that surgeons have removed. The biopsies are then sent to a different outside lab, which conducts a more comprehensive molecular analysis.

This process routinely takes up to six weeks. Without knowing how aggressive a cancer in the removed tumor is, or how that type of cancer might respond to different treatments, patients and doctors are unable to quickly chart out treatment plans to avoid recurrence.

SimBioSys’s new technology uses an AI model to analyze the 3D volumetric features of the just-removed tumor, the hospital’s initial tumor pathology report and a patient’s demographic data. From that information, SimBioSys generates — in a matter of hours — a risk analysis for that patient’s cancer, which helps doctors quickly determine the best treatment to avoid recurrence.

According to SimBioSys’s Palaniappan, the startup’s new method matches or exceeds the risk of recurrence scoring ability of more traditional methodologies, based upon its internal studies. It also takes a fraction of the time of these other methods while costing far less money.

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Even post-spooky season, GFN Thursday has some treats for GeForce NOW members: a new batch of 17 games joining the cloud in November.

Catch the five games available to stream this week, including Dragon Age: The Veilguard, the highly anticipated next installment in BioWare’s beloved fantasy role-playing game series. Players who purchased the GeForce NOW Ultimate bundle can stream the game at launch for free starting today.

Unite the Veilguard

In Dragon Age: The Veilguard, take on the role of Rook and stop a pair of corrupt ancient gods who’ve broken free from centuries of darkness, hellbent on destroying the world. Set in the rich world of Thedas, the game includes an epic story with meaningful choices, deep character relationships, and a mix of familiar and new companions to go on adventures with.

Select from three classes, each with distinct weapon types, and harness the classes’ unique, powerful abilities while coordinating with a team of seven companions, who have their own rich lives and deep backstories. An expansive skill-tree system allows for diverse character builds across the Warrior, Rogue and Mage classes.

Experience the adventure in the vibrant world of Thedas with enhanced visual fidelity and performance by tapping into a GeForce NOW membership. Performance members can enjoy the game at up to 1440p resolution and 60 frames per second (fps). Ultimate members can take advantage of 4K resolution, up to 120 fps and advanced features like NVIDIA DLSS 3, low-latency gameplay with NVIDIA Reflex, and enhanced image quality and immersion with ray-traced ambient occlusion and reflections, even on low-powered devices.

‘Resident Evil 4’ in the Cloud

Capcom’s Resident Evil 4 is now available on GeForce NOW, bringing the horror to cloud gaming.

Survival is just the beginning. Six years have passed since the biological disaster in Raccoon City.

Agent Leon S. Kennedy, one of the incident’s survivors, has been sent to rescue the president’s kidnapped daughter. The agent tracks her to a secluded European village, where there’s something terribly wrong with the locals. The curtain rises on this story of daring rescue and grueling horror where life and death, terror and catharsis intersect.

Featuring modernized gameplay, a reimagined storyline and vividly detailed graphics, Resident Evil 4 marks the rebirth of an industry juggernaut. Relive the nightmare that revolutionized survival horror, with stunning high-dynamic-range visuals and immersive ray-tracing technology for Performance and Ultimate members.

Life Is Great With New Games

A new season for “Year 6” in Tom Clancy’s The Division 2 from Ubisoft is now available for members to stream. In Shades of Red, rogue ex-Division agent Aaron Keener has given himself up and is now in custody at the White House. The Division must learn what he knows to secure the other members of his team. New Seasonal Modifiers change gameplay and gear usage for players. A new revamped progression is also available. The Seasonal Journey comprises a series of missions, each containing a challenge-style objective for players to complete.

Look for the following games available to stream in the cloud this week:

• Life Is Strange: Double Exposure (New release on Steam and Xbox, available in the Microsoft store, Oct. 29)
• Dragon Age: The Veilguard (New release on Steam and EA App, Oct. 31)
• Resident Evil 4 (Steam)
• Resident Evil 4 Chainsaw Demo (Steam)
• VRChat (Steam)

Here’s what members can expect for the rest of November:

• Metal Slug Tactics (New release on Steam, Nov. 5)
• Planet Coaster 2 (New release on Steam, Nov. 6)
• Teenage Mutant Ninja Turtles: Splintered Fate (New Release on Steam, Nov. 6)
• Empire of the Ants (New release on Steam, Nov. 7)
• Unrailed 2: Back on Track (New release on Steam, Nov. 7)
• Farming Simulator 25 (New release on Steam, Nov. 12)
• Sea Power: Naval Combat in the Missile Age (New release on Steam, Nov. 12)
• Industry Giant 4.0 (New release Steam, Nov. 15)
• Towers of Aghasba (New release on Steam, Nov. 19)
• S.T.A.L.K.E.R. 2: Heart of Chornobyl (New release on Steam and Xbox, available on PC Game Pass, Nov .20)
• Star Wars Outlaws (New release on Steam, Nov. 21)
• Dungeons & Degenerate Gamblers (Steam)
• Headquarters: World War II (Steam)
• PANICORE (Steam)
• Slime Rancher (Steam)
• Sumerian Six (Steam)
• TCG Card Shop Simulator (Steam)

Outstanding October

In addition to the 22 games announced last month, eight more joined the GeForce NOW library:

• Empyrion – Galactic Survival (New release on Epic Games Store, Oct. 10)
• Assassin’s Creed Mirage (New release on Steam, Oct. 17)
• Windblown (New release on Steam, Oct. 24)
• Call of Duty HQ, including Call of Duty: Modern Warfare III and Call of Duty: Warzone (Xbox, available on PC Game Pass)
• Dungeon Tycoon (Steam)
• Off the Grid (Epic Games Store)
• South Park: The Fractured but Whole (Available on PC Game Pass, Oct 16. Members need to activate access.)
• Star Trucker (Steam and Xbox, available on PC Game Pass)

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

What’s video game character you’ve dressed up as for Halloween?

— NVIDIA GeForce NOW (@NVIDIAGFN) October 29, 2024

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Among the artists using AI to enhance and accelerate their creative endeavors is Sabour Amirazodi, a creator and tech marketing and workflow specialist at NVIDIA.

Using his over 20 years of multi-platform experience in location-based entertainment and media production, he decorates his home every year with an incredible Halloween installation — dubbed the Haunted Sanctuary.

The project is a massive undertaking requiring projection mapping, the creation and assembly of 3D scenes, compositing and editing in Adobe After Effects and Premiere Pro, and more. The creation process was accelerated using the NVIDIA Studio content creation platform and Amirazodi’s NVIDIA RTX 6000 GPU.

This year, Amirazodi deployed new AI workflows in ComfyUI, Adobe Firefly and Photoshop to create digital portraits — inspired by his family — as part of the installation.

Give ’em Pumpkin to Talk About

ComfyUI is a node-based interface that generates images and videos from text. It’s designed to be highly customizable, allowing users to design workflows, adjust settings and see results immediately. It can combine various AI models and third-party extensions to achieve a higher degree of control.

For example, this workflow below requires entering a prompt, the details and characteristics of the desired image, and a negative prompt to help omit any undesired visual effects.

Since Amirazodi wanted his digital creations to closely resemble his family, he started by applying Run IP Adapters, which use reference images to inform generated content.

From there, he tinkered with the settings to achieve the desired look and feel of each character.

ComfyUI has NVIDIA TensorRT acceleration, so RTX users can generate images from prompts up to 60% faster.

Get started with ComfyUI.

In Darkness, Let There Be Light

Adobe Firefly is a family of creative generative AI models that offer new ways to ideate and create while assisting creative workflows. They’re designed to be safe for commercial use and were trained, using NVIDIA GPUs, on licensed content like Adobe Stock Images and public domain content where copyright has expired.

To make the digital portraits fit as desired, Amirazodi needed to expand the background.

Adobe Photoshop features a Generative Fill tool called Generative Expand that allows artists to extend the border of their image with the Crop tool and automatically fill the space with content that matches the existing image.

Photoshop also features “Neural Filters that allow artists to explore creative ideas and make complex adjustments to images in just seconds, saving them hours of tedious, manual work.

With Smart Portrait Neural Filters, artists can easily experiment with facial characteristics such as gaze direction and lighting angles simply by dragging a slider. Amirazodi used the feature to apply the final touches to his portraits, adjusting colors, textures, depth blur and facial expressions.

NVIDIA RTX GPUs help power AI-based tasks, accelerating the Neural Filters in Photoshop.

Learn more about the latest Adobe features and tools in this blog.

AI is already helping accelerate and automate tasks across content creation, gaming and everyday life — and the speedups are only multiplied with an NVIDIA RTX- or GeForce RTX GPU-equipped system.

Check out and share Halloween- and fall-themed art as a part of the NVIDIA Studio #HarvestofCreativity challenge on Instagram, X, Facebook and Threads for a chance to be featured on the social media channels.

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As the world transitions from general-purpose to accelerated computing, finding a path to building data center infrastructure at scale is becoming more important than ever. Enterprises must navigate uncharted waters when designing and deploying infrastructure to support these new AI workloads.

Constant developments in model capabilities and software frameworks, along with the novelty of these workloads, mean best practices and standardized approaches are still in their infancy. This state of flux can make it difficult for enterprises to establish long-term strategies and invest in infrastructure with confidence.

To address these challenges, NVIDIA is unveiling Enterprise Reference Architectures (Enterprise RAs). These comprehensive blueprints help NVIDIA systems partners and joint customers build their own AI factories — high-performance, scalable and secure data centers for manufacturing intelligence.

Building AI Factories to Unlock Enterprise Growth

NVIDIA Enterprise RAs help organizations avoid pitfalls when designing AI factories by providing full-stack hardware and software recommendations, and detailed guidance on optimal server, cluster and network configurations for modern AI workloads.

Enterprise RAs can reduce the time and cost of deploying AI infrastructure solutions by providing a streamlined approach for building flexible and cost-effective accelerated infrastructure, while ensuring compatibility and interoperability.

Each Enterprise RA includes recommendations for:

• Accelerated infrastructure based on an optimized NVIDIA-Certified server configuration, featuring the latest NVIDIA GPUs, CPUs and networking technologies, that’s been tested and validated to deliver performance at scale.
• AI-optimized networking with the NVIDIA Spectrum-X AI Ethernet platform and NVIDIA BlueField-3 DPUs to deliver peak network performance, and guidance on optimal network configurations at multiple design points to address varying workload and scale requirements.
• The NVIDIA AI Enterprise software platform for production AI, which includes NVIDIA NeMo and NVIDIA NIM microservices for easily building and deploying AI applications, and NVIDIA Base Command Manager Essentials for infrastructure provisioning, workload management and resource monitoring.

Businesses that deploy AI workloads on partner solutions based upon Enterprise RAs, which are informed by NVIDIA’s years of expertise in designing and building large-scale computing systems, will benefit from:

• Accelerated time to market: By using NVIDIA’s structured approach and recommended designs, enterprises can deploy AI solutions faster, reducing the time to achieve business value.
• Performance: Build upon tested and validated technologies with the confidence that AI workloads will run at peak performance.
• Scalability and manageability: Develop AI infrastructure while incorporating design best practices that enable flexibility and scale and help ensure optimal network performance.
• Security: Run workloads securely on AI infrastructure that’s engineered with zero trust in mind, supports confidential computing and is optimized for the latest cybersecurity AI innovations.
• Reduced complexity: Accelerate deployment timelines, while avoiding design and planning pitfalls, through optimal server, cluster and network configurations for AI workloads.

Availability

Solutions based upon NVIDIA Enterprise RAs are available from NVIDIA’s global partners, including Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro.

Learn more about NVIDIA-Certified Systems and NVIDIA Enterprise Reference Architectures.

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An overwhelming 91% of financial services industry (FSI) companies are either assessing artificial intelligence or already have it in the bag as a tool that’s driving innovation, improving operational efficiency and enhancing customer experiences.

Generative AI — powered by NVIDIA NIM microservices and accelerated computing — can help organizations improve portfolio optimization, fraud detection, customer service and risk management.

Among the companies harnessing these technologies to boost financial services applications are Ntropy, Contextual AI and NayaOne — all members of the NVIDIA Inception program for cutting-edge startups.

And Silicon Valley-based startup Securiti, which offers a centralized, intelligent platform for the safe use of data and generative AI, is using NVIDIA NIM to build an AI-powered copilot for financial services.

At Money20/20, a leading fintech conference running this week in Las Vegas, the companies will demonstrate how their technologies can turn disparate, often complex FSI data into actionable insights and advanced innovation opportunities for banks, fintechs, payment providers and other organizations.

Ntropy Brings Order to Unstructured Financial Data

New York-based Ntropy is helping remove various states of entropy — disorder, randomness or uncertainty — from financial services workflows.

“Whenever money is moved from point A to point B, text is left in bank statements, PDF receipts and other forms of transaction history,” said Naré Vardanyan, cofounder and CEO of Ntropy. “Traditionally, that unstructured data has been very hard to clean up and use for financial applications.”

The company’s transaction enrichment application programming interface (API) standardizes financial data from across different sources and geographies, acting as a common language that can help financial services applications understand any transaction with humanlike accuracy in just milliseconds, at 10,000x lower cost than traditional methods.

It’s built on the Llama 3 NVIDIA NIM microservice and NVIDIA Triton Inference Server running on NVIDIA H100 Tensor Core GPUs. Using the Llama 3 NIM microservice, Ntropy achieved up to 20x better utilization and throughput for its large language models (LLMs) compared with running the native models.

Airbase, a leading procure-to-pay software platform provider, boosts transaction authorization processes using LLMs and the Ntropy data enricher.

At Money20/20, Ntropy will discuss how its API can be used to clean up customers’ merchant data, which boosts fraud detection by improving the accuracy of risk-detection models. This in turn reduces both false transaction declines and revenue loss.

Another demo will highlight how an automated loan agent taps into the Ntropy API to analyze information on a bank’s website and generate a relevant investment report to speed loan dispersal and decision-making processes for users.

Contextual AI Advances Retrieval-Augmented Generation for FSI

Contextual AI — based in Mountain View, California — offers a production-grade AI platform, powered by retrieval-augmented generation (RAG) and ideal for building enterprise AI applications in knowledge-intensive FSI use cases.

“RAG is the answer to delivering enterprise AI into production,” said Douwe Kiela, CEO and cofounder of Contextual AI. “Tapping into NVIDIA technologies and large language models, the Contextual AI RAG 2.0 platform can bring accurate, auditable AI to FSI enterprises looking to optimize operations and offer new generative AI-powered products.”

The Contextual AI platform integrates the entire RAG pipeline — including extraction, retrieval, reranking and generation — into a single optimized system that can be deployed in minutes, and further tuned and specialized based on customer needs, delivering much greater accuracy in context-dependent tasks.

HSBC plans to use Contextual AI to provide research insights and process guidance support through retrieving and synthesizing relevant market outlooks, financial news and operational documents. Other financial organizations are also harnessing Contextual AI’s pre-built applications, including for financial analysis, policy-compliance report generation, financial advice query resolution and more.

For example, a user could ask, “What’s our forecast for central bank rates by Q4 2025?” The Contextual AI platform would provide a brief explanation and an accurate answer grounded in factual documents, including citations to specific sections in the source.

Contextual AI uses NVIDIA Triton Inference Server and the open-source NVIDIA TensorRT-LLM library for accelerating and optimizing LLM inference performance.

NayaOne Provides Digital Sandbox for Financial Services Innovation

London-based NayaOne offers an AI sandbox that allows customers to securely test and validate AI applications prior to commercial deployment. Its technology platform allows financial institutions the ability to create synthetic data and gives them access to a marketplace of hundreds of fintechs.

Customers can use the digital sandbox to benchmark applications for fairness, transparency, accuracy and other compliance measures and to better ensure top performance and successful integration.

“The demand for AI-driven solutions in financial services is accelerating, and our collaboration with NVIDIA allows institutions to harness the power of generative AI in a controlled, secure environment,” said Karan Jain, CEO of NayaOne. “We’re creating an ecosystem where financial institutions can prototype faster and more effectively, leading to real business transformation and growth initiatives.”

Using NVIDIA NIM microservices, NayaOne’s AI Sandbox lets customers explore and experiment with optimized AI models, and take them to deployment more easily. With NVIDIA accelerated computing, NayaOne achieves up to 10x faster processing for the large datasets used in its fraud detection models, at up to 40% lower infrastructure costs compared with running extensive CPU-based models.

The digital sandbox also uses the open-source NVIDIA RAPIDS set of data science and AI libraries to accelerate fraud detection and prevention capabilities in money movement applications. The company will demonstrate its digital sandbox at the NVIDIA AI Pavilion at Money20/20.

Securiti Improves Financial Planning With AI Copilot

Powering a broad range of generative AI applications — including safe enterprise AI copilots and LLM training and tuning — Securiti’s highly flexible Data+AI platform lets users build safe, end-to-end enterprise AI systems.

The company is now building an NVIDIA NIM-powered financial planning assistant. The copilot chatbot accesses diverse financial data while adhering to privacy and entitlement policies to provide context-aware responses to users’ finance-related questions.

“Banks struggle to provide personalized financial advice at scale while maintaining data security, privacy and compliance with regulations,” said Jack Berkowitz, chief data officer at Securiti. “With robust data protection and role-based access for secure, scalable support, Securiti helps build safe AI copilots that offer personalized financial advice tailored to individual goals.”

The chatbot retrieves data from a variety of sources, such as earnings transcripts, client profiles and account balances, and investment research documents. Securiti’s solution safely ingests and prepares it for use with high-performance, NVIDIA-powered LLMs, preserving controls such as access entitlements. Finally, it provides users with customized responses through a simple consumer interface.

Using the Llama 3 70B-Instruct NIM microservice, Securiti optimized the performance of the LLM, while ensuring the safe use of data. The company will demonstrate its generative AI solution at Money20/20.

NIM microservices and Triton Inference Server are available through the NVIDIA AI Enterprise software platform.

Learn more about AI for financial services by joining NVIDIA at Money20/20, running through Wednesday, Oct. 30. 

Explore a new NVIDIA AI workflow for fraud detection.

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Financial losses from worldwide credit card transaction fraud are expected to reach $43 billion by 2026.

A new NVIDIA AI workflow for fraud detection running on Amazon Web Services (AWS) can help combat this burgeoning epidemic — using accelerated data processing and advanced algorithms to improve AI’s ability to detect and prevent credit card transaction fraud.

Launched this week at the Money20/20 fintech conference, the workflow enables financial institutions to identify subtle patterns and anomalies in transaction data based on user behavior to improve accuracy and reduce false positives compared with traditional methods.

Users can streamline the migration of their fraud detection workflows from traditional compute to accelerated compute using the NVIDIA AI Enterprise software platform and NVIDIA GPU instances.

Businesses embracing comprehensive machine learning tools and strategies can observe up to an estimated 40% improvement in fraud detection accuracy, boosting their ability to identify and stop fraudsters faster and mitigate harm.

As such, leading financial organizations like American Express and Capital One have been using AI to build proprietary solutions that mitigate fraud and enhance customer protection.

The new NVIDIA workflow accelerates data processing, model training and inference, and demonstrates how these components can be wrapped into a single, easy-to-use software offering, powered by NVIDIA AI.

Currently optimized for credit card transaction fraud, the workflow could be adapted for use cases such as new account fraud, account takeover and money laundering.

Accelerated Computing for Fraud Detection

As AI models expand in size, intricacy and diversity, it’s more important than ever for organizations across industries — including financial services — to harness cost- and energy-efficient computing power.

Traditional data science pipelines lack the necessary compute acceleration to handle the massive volumes of data required to effectively fight fraud amid rapidly growing losses across the industry. Leveraging NVIDIA RAPIDS Accelerator for Apache Spark could help payment companies reduce data processing times and save on their data processing costs.

To efficiently manage large-scale datasets and deliver real-time AI performance with complex AI models, financial institutions are turning to NVIDIA’s AI and accelerated computing platforms.

The use of gradient-boosted decision trees — a type of machine learning algorithm — tapping into libraries such as XGBoost, has long been the standard for fraud detection.

The new NVIDIA AI workflow for fraud detection enhances XGBoost using the NVIDIA RAPIDS suite of AI libraries with graph neural network (GNN) embeddings as additional features to help reduce false positives.

The GNN embeddings are fed into XGBoost to create and train a model that can then be orchestrated with the NVIDIA Morpheus Runtime Core library and NVIDIA Triton Inference Server for real-time inferencing.

The NVIDIA Morpheus framework securely inspects and classifies all incoming data, tagging it with patterns and flagging potentially suspicious activity. NVIDIA Triton Inference Server simplifies inference of all types of AI model deployments in production, while optimizing throughput, latency and utilization.

NVIDIA Morpheus, RAPIDS and Triton Inference Server are available through NVIDIA AI Enterprise.

Leading Financial Services Organizations Adopt AI

During a time when many large North American financial institutions are reporting online or mobile fraud losses continue to increase, AI is helping to combat this trend.

American Express, which began using AI to fight fraud in 2010, leverages fraud detection algorithms to monitor all customer transactions globally in real time, generating fraud decisions in just milliseconds. Using a combination of advanced algorithms, one of which tapped into the NVIDIA AI platform, American Express enhanced model accuracy, advancing the company’s ability to better fight fraud.

European digital bank bunq uses generative AI and large language models to help detect fraud and money laundering. Its AI-powered transaction-monitoring system achieved nearly 100x faster model training speeds with NVIDIA accelerated computing.

BNY announced in March that it became the first major bank to deploy an NVIDIA DGX SuperPOD with DGX H100 systems, which will help build solutions that support fraud detection and other use cases.

And now, systems integrators, software vendors and cloud service providers can integrate the new NVIDIA AI workflow for fraud detection to boost their financial services applications and help keep customers’ money, identities and digital accounts safe.

Explore the fraud detection NVIDIA AI workflow and read this NVIDIA Technical Blog on supercharging fraud detection with GNNs.

Learn more about AI for fraud detection by visiting the NVIDIA AI Pavilion featuring AWS at Money 20/20, running this week in Las Vegas.

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Ahead of a visit to the hospital for a surgical procedure, patients often have plenty of questions about what to expect — and can be plenty nervous.

To help minimize presurgery jitters, Deloitte is enhancing its Quartz Frontline AI, an AI solution for customer service powered by NVIDIA AI, to now include AI agents to bring the next generation of digital, frontline teammates to patients before they even step foot inside the hospital.

These virtual teammates, built with the NVIDIA AI Enterprise software platform, can have natural, human-like conversations with patients, answer a wide range of questions and provide support prior to preadmission appointments at hospitals.

Working with NVIDIA, Deloitte has added Frontline AI Teammate to its Quartz platform for use in settings like hospitals, where the digital avatar can have practical conversations — in multiple languages — that give the end user, such as a patient, instant answers to pressing questions.

“Avatar-based conversational AI agents offer an incredible opportunity to reduce the productivity paradox that our healthcare system faces with digitization,” said Niraj Dalmia, partner at Deloitte Canada. “It could possibly be the complementary innovation that reduces administrative burden, complements our healthcare human resources to free up capacity and helps solve for patient experience challenges.”

Next-Gen Technologies Powering Digital Humans

Digital human technology can provide lifelike interactions that can enhance experiences for doctors and patients.

Deloitte’s Frontline AI Teammate, built with NVIDIA AI Enterprise and Deloitte’s Conversational AI Framework, is designed to deliver human-to-machine experiences in healthcare settings. Developed on the NVIDIA Omniverse platform, Deloitte’s lifelike avatar can respond to complex, domain-specific questions that are pivotal in healthcare delivery.

Developers can tap into NVIDIA NIM microservices, which streamline the path for developing AI-powered applications and moving AI models into production, to craft digital humans for healthcare industry applications.

NVIDIA NIM Agent Blueprints offer a customizable, reference AI workflow for creating interactive, AI-driven avatars that are ideal for telehealth — and include best practices for how to use NVIDIA NeMo Retriever, an industry-leading embedding, retrieval and re-ranking model that allows for fast responses based on up-to-date healthcare data.

Customizable digital humans — like James, an interactive demo developed by NVIDIA — can handle tasks such as scheduling appointments, filling out intake forms and answering questions about upcoming health services. This can make healthcare services more efficient while also improving patient access.

In addition to NIM microservices, the James interactive demo also uses NVIDIA ACE to provide natural, low-latency responses.

NVIDIA ACE is a suite of AI, graphics and simulation technologies for bringing digital humans to life. It can integrate every aspect of a digital human into healthcare applications — from speech and translation abilities capable of understanding diverse accents and languages, to realistic animations of facial and body movements.

Personalized Experiences for Hospital Patients

Patients can get overwhelmed with the amount of preoperative information. Typically, they have only one pre-admission appointment, often many weeks before the surgery, which can leave them with lingering questions and escalating concerns. The stress of a serious diagnosis may also prevent them from asking all the necessary questions during these brief interactions, leaving them without comprehensive knowledge about the appointment’s purpose, duration, location and necessary documents — and potentially leading to delays or even rescheduling of their surgeries.

To enhance patient preparation and reduce pre-procedure anxiety, The Ottawa Hospital is using AI agents, powered by NVIDIA and Deloitte’s technologies, to provide more consistent, accurate and continuous access to information.

With the Frontline AI teammate, patients can experience benefits including:

• 24/7 access to the digital teammate using a smartphone, tablet or home computer.
• Reliable, preapproved answers to detailed questions, including information around anesthesia or the procedure itself.
• Postsurgery consultation to resolve any questions about the recovery process, potentially improving treatment adherence and health outcomes.

In user acceptance testing conducted this summer, a majority of the testers noted that responses provided were clear, relevant and met the needs of the given interaction.

“The Frontline AI Teammate offers a novel and innovative solution to help combat our health human resource crisis — it has the potential to reduce the administrative burden, giving back time to healthcare providers to provide the quality care our population deserves and expects from The Ottawa Hospital,” said Mathieu LeBreton, digital experience lead at The Ottawa Hospital. “The opportunity to explore these technologies is well-timed, given the planning of the New Campus Development, a new hospital project in Ottawa. Proper identification of the problems we are trying to solve is imperative to ensure this is done responsibly and transparently.”

Deloitte is working with other hospitals and healthcare institutions to deploy digital agents. A patient-facing pilot with Ottawa Hospital is expected to go live by the end of the year.

Developers can get started by accessing the digital human NIM Agent Blueprint.

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Artificial intelligence will be the driving force behind India’s digital transformation, fueling innovation, economic growth, and global leadership, NVIDIA founder and CEO Jensen Huang said Thursday at NVIDIA’s AI Summit in Mumbai.

Addressing a crowd of entrepreneurs, developers, academics and business leaders, Huang positioned AI as the cornerstone of the country’s future.

India has an “amazing natural resource” in its IT and computer science expertise,” Huang said, nothing the vast potential waiting to be unlocked.

To capitalize on this country’s talent and India’s immense data resources, the country’s leading cloud infrastructure providers are rapidly accelerating their data center capacity. NVIDIA is playing a key role, with NVIDIA GPU deployments expected to grow nearly 10x by year’s end, creating the backbone for an AI-driven economy.

Together with NVIDIA, these companies are at the cutting edge of a shift Huang compared to the seismic change in computing introduced by IBM’s System 360 in 1964, calling it the most profound platform shift since then.

“This industry, the computing industry, is going to become the intelligence industry,” Huang said, pointing to India’s unique strengths to lead this industry,  thanks to its enormous amounts of data and large population.

With this rapid expansion in infrastructure, AI factories will play a critical role in India’s future, serving as the backbone of the nation’s AI-driven growth.

“It makes complete sense that India should manufacture its own AI,” Huang said. “You should not export data to import intelligence,” he added, noting the importance of India building its own AI infrastructure.

Huang identified three areas where AI will transform industries: sovereign AI, where nations use their own data to drive innovation; agentic AI, which automates knowledge-based work; and physical AI, which applies AI to industrial tasks through robotics and autonomous systems. India, Huang noted, is uniquely positioned to lead in all three areas.

India’s startups are already harnessing NVIDIA technology to drive innovation across industries and are positioning themselves as global players, bringing the country’s AI solutions to the world.

Meanwhile, India’s robotics ecosystem is adopting NVIDIA Isaac and Omniverse to power the next generation of physical AI, revolutionizing industries like manufacturing and logistics with advanced automation.

Huang’s also keynote featured a surprise appearance by actor and producer Akshay Kumar.

Following Huang’s remarks, the focus shifted to a fireside chat between Huang and Reliance Industries Chairman Mukesh Ambani, where the two leaders explored how AI will shape the future of Indian industries, particularly in sectors like energy, telecommunications and manufacturing.

Ambani emphasized that AI is central to this continued growth. Reliance, in partnership with NVIDIA, is building AI factories to automate industrial tasks and transform processes in sectors like energy and manufacturing.

Both men discussed their companies’ joint efforts to pioneer AI infrastructure in India.

Ambani underscored the role of AI in public sector services, explaining how India’s data combined with AI is already transforming governance and service delivery.

Huang added that AI promises to democratize technology.

“The ability to program AI is something that everyone can do … if AI could be put into the hands of every citizen, it would elevate and put into the hands of everyone this incredible capability,” he said.

Huang emphasized NVIDIA’s role in preparing India’s workforce for an AI-driven future.

NVIDIA is partnering with India’s IT giants such as Infosys, TCS, Tech Mahindra and Wipro to upskill nearly half a million developers, ensuring India leads the AI revolution with a highly trained workforce.

“India’s technical talent is unmatched,” Huang said.

Ambani echoed these sentiments, stressing that “India will be one of the biggest intelligence markets,” pointing to the nation’s youthful, technically talented population.

A Vision for India’s AI-Driven Future

As the session drew to a close, Huang and Ambani reflected on their vision for India’s AI-driven future.

With its vast talent pool, burgeoning tech ecosystem and immense data resources, the country, they agreed, has the potential to contribute globally in sectors such as energy, healthcare, finance and manufacturing.

“This cannot be done by any one company, any one individual, but we all have to work together to bring this intelligence age safely to the world so that we can create a more equal world, a more prosperous world,” Ambani said.

Huang echoed the sentiment, adding: “Let’s make it a promise today that we will work together so that India can take advantage of the intelligence revolution that’s ahead of us.”

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