Posts in category: nVidia AI

AI agents — which can understand, adapt to and support each user’s unique journey — are making online shopping and digital marketing more efficient and personalized. Plus, these intelligent systems are poised to turn marketing interactions into valuable customer research data.

In this episode of the NVIDIA AI Podcast, Jon Heller, co-CEO and founder of Firsthand, discusses how the company’s Brand Agents are revolutionizing the relationship between consumers, marketers and publishers. By using a company’s own knowledge, Firsthand Brand Agents act as AI-powered guides that engage customers on a brand’s website and beyond — assisting at every step of the customer’s journey, from finding solutions to making purchases.

Drawing on decades of industry experience including leadership roles at advertising companies DoubleClick and FreeWheel, Heller explains Firsthand’s vision of AI as a new medium rather than just a technology.

AI agents are enabling companies in the retail and consumer-packaged goods (CPG) industries to increase internal efficiency and productivity while improving customer service.

Two of the top use cases for generative AI in retail are: personalized marketing and advertising, and digital shopping assistants or copilots. Learn more about AI’s rapid integration across businesses in NVIDIA’s second annual State of AI in Retail and CPG survey report.

Time Stamps

2:10 — How large language models revealed a new approach to digital marketing.

12:46 — How Firsthand Brand Agents can use various AI capabilities beyond traditional chat.

16:33 — How Firsthand Brand Agents create a connected customer journey by maintaining context across touchpoints.

23:57 — The technical challenges in building agents while maintaining brand safety.

30:10 — How AI can generate unprecedented insights into consumer needs and preferences.

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Imbue CEO Kanjun Qiu on Transforming AI Agents Into Personal Collaborators

Imbue is building software infused with intelligence through collaborative AI systems that work alongside users. CEO Kanjun Qiu discusses her company’s approach to AI agents and compares the personal computer revolution of the late 1970s and 80s to today’s AI agent transformation.

Media.Monk’s Lewis Smithingham on Enhancing Media and Marketing With AI

Media.Monks’ platform Wormhole streamlines marketing and content creation with AI-powered insights. Hear from Lewis Smithingham, senior vice president of innovation and special operations at Media.Monks, as he addresses AI’s potential in entertainment and advertising.

Snowflake’s Baris Gultekin on Unlocking the Value of Data With Large Language Models

Snowflake is using AI to help enterprises transform data into insights and applications. Baris Gultekin, head of AI at Snowflake, explains how the company’s AI Data Cloud platform separates the storage of data from compute, enabling organizations across the world to connect via cloud technology and work on a unified platform.

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Editor’s note: This post is part of Into the Omniverse, a series focused on how developers, 3D practitioners and enterprises can transform their workflows using the latest advances in Universal Scene Description (OpenUSD) and NVIDIA Omniverse.

The next frontier of AI is physical AI. Physical AI models can understand instructions and perceive, interact and perform complex actions in the real world to power autonomous machines like robots and self-driving cars.

Similar to how large language models can process and generate text, physical AI models can understand the world and generate actions. To do this, these models must be trained in simulation environments to comprehend physical dynamics, like gravity, friction or inertia — and understand geometric and spatial relationships, as well as the principles of cause and effect.

Global leaders in software development and professional services are using NVIDIA Omniverse, powered by OpenUSD, to build new products and services that will accelerate the development of AI and controllable simulations to enable the creation of true-to-reality virtual worlds, known as digital twins, that can be used to train physical AI with unprecedented accuracy and detail.

Generate Exponentially More Synthetic Data With Omniverse and NVIDIA Cosmos

At CES, NVIDIA announced generative AI models and blueprints that expand Omniverse integration further into physical AI applications such as robotics, autonomous vehicles and vision AI.

Among these announcements was NVIDIA Cosmos, a platform of state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline — all designed to accelerate physical AI development.

Developing physical AI models is a costly, resource- and time-intensive process that requires vast amounts of real-world data and testing. Cosmos’ world foundation models (WFM),  which predict future world states as videos based on multimodal inputs,  provide an easy way for developers to generate massive amounts of photoreal, physics-based synthetic data to train and evaluate AI for robotics, autonomous vehicles and machines. Developers can also fine-tune Cosmos WFMs to build downstream world models or improve quality and efficiency for specific physical AI use cases.

When paired with Omniverse, Cosmos creates a powerful synthetic data multiplication engine. Developers can use Omniverse to create 3D scenarios, then feed the outputs into Cosmos to generate controlled videos and variations. This can drastically accelerate the development of physical AI systems such as autonomous vehicles and robots by rapidly generating exponentially more training data covering a variety of environments and interactions.

OpenUSD ensures the data in these scenarios is seamlessly integrated and consistently represented, enhancing the realism and effectiveness of the simulations.

Leading robotics and automotive companies, including 1X, Agile Robots, Agility Robotics, Figure AI, Foretellix, Fourier, Galbot, Hillbot, IntBot, Neura Robotics, Skild AI, Virtual Incision, Waabi and XPENG, along with ridesharing giant Uber, are among the first to adopt Cosmos.

Learn more about how world foundation models will advance physical AI by listening to the NVIDIA AI Podcast episode with Ming-Yu Liu, vice president of research at NVIDIA.

See Cosmos in Action for Physical AI Use Cases

Cosmos WFMs are revolutionizing industries by providing a unified framework for developing, training and deploying large-scale AI models across various applications. Enterprises in the automotive, industrial and robotics sectors can harness the power of generative physical AI and simulation to accelerate innovation and operational efficiency.

• Humanoid robots: The NVIDIA Isaac GR00T Blueprint for synthetic motion generation helps developers generate massive synthetic motion datasets to train humanoid robots using imitation learning. With GR00T workflows, users can capture human actions and use Cosmos to exponentially increase the size and variety of the dataset, making it more robust for training physical AI systems.
• Autonomous vehicles: Autonomous vehicle (AV) simulation powered by Omniverse Sensor RTX application programming interfaces lets AV developers replay driving data, generate new ground-truth data and perform closed-loop testing to accelerate their pipelines. With Cosmos, developers can generate synthetic driving scenarios to amplify training data by orders of magnitude, accelerating physical AI model development for autonomous vehicles. Global ridesharing giant Uber is partnering with NVIDIA to accelerate autonomous mobility. Rich driving datasets from Uber, combined with Cosmos and NVIDIA DGX Cloud, can help AV partners build stronger AI models more efficiently.
• Industrial settings: Mega is an Omniverse Blueprint for developing, testing and optimizing physical AI and robot fleets at scale in a USD-based digital twin before deployment in factories and warehouses. The blueprint uses Omniverse Cloud Sensor RTX APIs to simultaneously render multisensor data from any type of intelligent machine, enabling high-fidelity sensor simulation at scale. Cosmos can enhance Mega by generating synthetic edge case scenarios to amplify training data, significantly improving the robustness and efficiency of training robots in simulation. KION Group, a supply chain solutions company, is among the first to adopt Mega to drive warehouse automation in retail, consumer packaged goods, parcel services and more.

Get Plugged Into the World of OpenUSD

For more on Cosmos, watch the replay of NVIDIA CEO Jensen Huang’s CES keynote, and get started with Cosmos WFMs available now under an open model license on Hugging Face and the NVIDIA NGC catalog. Join the upcoming livestream on Wednesday, February 5 for a deep dive into Cosmos WFMs and physical AI workflows.

Continue to optimize OpenUSD workflows with the new self-paced Learn OpenUSD curriculum for 3D developers and practitioners, available at no cost through the NVIDIA Deep Learning Institute. For more resources on OpenUSD, explore the Alliance for OpenUSD forum and the AOUSD website.

Meet Cosmos, OpenUSD and physical AI experts at NVIDIA GTC, the conference for the era of AI, taking place March 17-21 at the San Jose Convention Center.

Stay up to date by subscribing to NVIDIA news, joining the community, and following NVIDIA Omniverse on Instagram, LinkedIn, Medium and X.

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More than 90 million new vehicles are introduced to roads across the globe every year, leading to an annual 12% increase in traffic congestion — according to NoTraffic, a member of the NVIDIA Inception program for cutting-edge startups and the NVIDIA Metropolis vision AI ecosystem.

Still, 99% of the world’s traffic signals run on fixed timing plans, leading to unnecessary congestion and delays.

To reduce such inefficiencies, mitigate car accidents and reduce carbon emissions from vehicles, NoTraffic’s AI Mobility platform predicts road scenarios, helps ensure continuous traffic flow, minimizes stops and optimizes safety at intersections across the U.S., Canada and elsewhere.

The platform — which enables road infrastructure management at both local-intersection and city-grid scale — integrates NVIDIA-powered software and hardware at the edge, under a cloud-based operating system.

It’s built using the NVIDIA Jetson edge AI platform, NVIDIA accelerated computing and the NVIDIA Metropolis vision AI developer stack.

“With NVIDIA accelerated computing, we achieved a 3x speedup in AI training and doubled AI Mobility’s energy efficiency,” said Uriel Katz, cofounder and chief technology officer of NoTraffic. “These optimizations in time, money and energy efficiency are all bolstered by NVIDIA Jetson, which sped our image preprocessing tasks by 40x compared with a CPU-only workflow. Plus, GPU-accelerated NVIDIA CUDA libraries increased our model throughput by 30x.”

These libraries include the NVIDIA TensorRT ecosystem of application programming interfaces for high-performance deep learning inference and the NVIDIA cuDNN library of primitives for deep neural networks.

Taming Traffic in Tuscon, Vancouver and Beyond

In Tuscon, Arizona, more than 80 intersections are tapping into the NoTraffic AI Mobility platform, which has enabled up to a 46% reduction in road delays during rush hours — and a half-mile reduction in peak queue length.

The work is an expansion of NoTraffic’s initial deployment on Tuscon’s West Ajo Way. That effort led to an average delay reduction of 23% for drivers.

Since installation, NoTraffic technology has helped free Tucson drivers from over 1.25 million hours stuck in traffic, the company estimates, representing an economic benefit of over $24.3 million. The company has also tracked a nearly 80% reduction in red-light runners since its platform was deployed, helping improve safety at Tucson intersections.

By reducing travel times, drivers have also saved over $1.6 million in gas, cutting emissions and improving air quality to make the equivalent impact of planting 650,000 trees.

In Vancouver, Canada, the University of British Columbia (UBC) is using the NoTraffic platform and Rogers Communications’ 5G-connected, AI-enabled smart-traffic platform to reduce both pedestrian delays and greenhouse gas emissions.

Rogers Communications’ 5G networks provide robust and stable connectivity to the sensors embedded on the traffic poles.

This advanced network infrastructure enhances the NoTraffic platform’s efficacy and scalability, as the improved speed and reduced latency of 5G networks means traffic data can be processed in real time. This is critical for predicting numerous potential traffic scenarios, adjusting signal timings and prioritizing road users accordingly.

With AI Mobility deployed at seven intersections across the campus, the university experienced an up to 40% reduction in pedestrian delays and significant decreases in vehicle wait time.

In addition, UBC reduces 74 tons of carbon dioxide emissions each year thanks to the NoTraffic and Rogers solution, which is powered by NVIDIA edge AI and accelerated computing.

The platform is also in action on the roads of Phoenix, Arizona; Baltimore, Maryland; and in 35 states through 200+ agencies across the U.S. and Canada.

Honk If You Love Reducing Congestion, Carbon Emissions

The NoTraffic AI Mobility platform offers local AI-based predictions that, based on sensor inputs at multiple intersections, analyze numerous traffic scenarios up to two minutes in advance.

It can adapt to real-time changes in traffic patterns and volumes, send messages between intersections and run optimization algorithms that control traffic signals to improve overall transportation efficiency and safety through cloud connectivity.

Speedups in the AI Mobility platform mean quicker optimizations of traffic signals — and reduced congestion on the roads means reduced carbon emissions from vehicles.

NoTraffic estimates that for every city optimized with this platform, eight hours of traffic time could be saved per driver. Plus, with over 300,000 signalized intersections in the U.S., the company says this could result in a total of $14 billion in economic savings per year.

Learn more about the NVIDIA Metropolis platform and how it’s used in smart cities and spaces.

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AI agents are poised to transform productivity for the world’s billion knowledge workers with “knowledge robots” that can accomplish a variety of tasks. To develop AI agents, enterprises need to address critical concerns like trust, safety, security and compliance.

New NVIDIA NIM microservices for AI guardrails — part of the NVIDIA NeMo Guardrails collection of software tools — are portable, optimized inference microservices that help companies improve the safety, precision and scalability of their generative AI applications.

Central to the orchestration of the microservices is NeMo Guardrails, part of the NVIDIA NeMo platform for curating, customizing and guardrailing AI. NeMo Guardrails helps developers integrate and manage AI guardrails in large language model (LLM) applications. Industry leaders Amdocs, Cerence AI and Lowe’s are among those using NeMo Guardrails to safeguard AI applications.

Developers can use the NIM microservices to build more secure, trustworthy AI agents that provide safe, appropriate responses within context-specific guidelines and are bolstered against jailbreak attempts. Deployed in customer service across industries like automotive, finance, healthcare, manufacturing and retail, the agents can boost customer satisfaction and trust.

One of the new microservices, built for moderating content safety, was trained using the Aegis Content Safety Dataset — one of the highest-quality, human-annotated data sources in its category. Curated and owned by NVIDIA, the dataset is publicly available on Hugging Face and includes over 35,000 human-annotated data samples flagged for AI safety and jailbreak attempts to bypass system restrictions.

NVIDIA NeMo Guardrails Keeps AI Agents on Track

AI is rapidly boosting productivity for a broad range of business processes. In customer service, it’s helping resolve customer issues up to 40% faster. However, scaling AI for customer service and other AI agents requires secure models that prevent harmful or inappropriate outputs and ensure the AI application behaves within defined parameters.

NVIDIA has introduced three new NIM microservices for NeMo Guardrails that help AI agents operate at scale while maintaining controlled behavior:

• Content safety NIM microservice that safeguards AI against generating biased or harmful outputs, ensuring responses align with ethical standards.
• Topic control NIM microservice that keeps conversations focused on approved topics, avoiding digression or inappropriate content.
• Jailbreak detection NIM microservice that adds protection against jailbreak attempts, helping maintain AI integrity in adversarial scenarios.

By applying multiple lightweight, specialized models as guardrails, developers can cover gaps that may occur when only more general global policies and protections exist — as a one-size-fits-all approach doesn’t properly secure and control complex agentic AI workflows.

Small language models, like those in the NeMo Guardrails collection, offer lower latency and are designed to run efficiently, even in resource-constrained or distributed environments. This makes them ideal for scaling AI applications in industries such as healthcare, automotive and manufacturing, in locations like hospitals or warehouses.

Industry Leaders and Partners Safeguard AI With NeMo Guardrails

NeMo Guardrails, available to the open-source community, helps developers orchestrate multiple AI software policies — called rails — to enhance LLM application security and control. It works with NVIDIA NIM microservices to offer a robust framework for building AI systems that can be deployed at scale without compromising on safety or performance.

Amdocs, a leading global provider of software and services to communications and media companies, is harnessing NeMo Guardrails to enhance AI-driven customer interactions by delivering safer, more accurate and contextually appropriate responses.

“Technologies like NeMo Guardrails are essential for safeguarding generative AI applications, helping make sure they operate securely and ethically,” said Anthony Goonetilleke, group president of technology and head of strategy at Amdocs. “By integrating NVIDIA NeMo Guardrails into our amAIz platform, we are enhancing the platform’s ‘Trusted AI’ capabilities to deliver agentic experiences that are safe, reliable and scalable. This empowers service providers to deploy AI solutions safely and with confidence, setting new standards for AI innovation and operational excellence.”

Cerence AI, a company specializing in AI solutions for the automotive industry, is using NVIDIA NeMo Guardrails to help ensure its in-car assistants deliver contextually appropriate, safe interactions powered by its CaLLM family of large and small language models.

“Cerence AI relies on high-performing, secure solutions from NVIDIA to power our in-car assistant technologies,” said Nils Schanz, executive vice president of product and technology at Cerence AI. “Using NeMo Guardrails helps us deliver trusted, context-aware solutions to our automaker customers and provide sensible, mindful and hallucination-free responses. In addition, NeMo Guardrails is customizable for our automaker customers and helps us filter harmful or unpleasant requests, securing our CaLLM family of language models from unintended or inappropriate content delivery to end users.”

Lowe’s, a leading home improvement retailer, is leveraging generative AI to build on the deep expertise of its store associates. By providing enhanced access to comprehensive product knowledge, these tools empower associates to answer customer questions, helping them find the right products to complete their projects and setting a new standard for retail innovation and customer satisfaction.

“We’re always looking for ways to help associates to above and beyond for our customers,” said Chandhu Nair, senior vice president of data, AI and innovation at Lowe’s. “With our recent deployments of NVIDIA NeMo Guardrails, we ensure AI-generated responses are safe, secure and reliable, enforcing conversational boundaries to deliver only relevant and appropriate content.”

To further accelerate AI safeguards adoption in AI application development and deployment in retail, NVIDIA recently announced at the NRF show that its NVIDIA AI Blueprint for retail shopping assistants incorporates NeMo Guardrails microservices for creating more reliable and controlled customer interactions during digital shopping experiences.

Consulting leaders Taskus, Tech Mahindra and Wipro are also integrating NeMo Guardrails into their solutions to provide their enterprise clients safer, more reliable and controlled generative AI applications.

NeMo Guardrails is open and extensible, offering integration with a robust ecosystem of leading AI safety model and guardrail providers, as well as AI observability and development tools. It supports integration with ActiveFence’s ActiveScore, which filters harmful or inappropriate content in conversational AI applications, and provides visibility, analytics and monitoring.

Hive, which provides its AI-generated content detection models for images, video and audio content as NIM microservices, can be easily integrated and orchestrated in AI applications using NeMo Guardrails.

The Fiddler AI Observability platform easily integrates with NeMo Guardrails to enhance AI guardrail monitoring capabilities. And Weights & Biases, an end-to-end AI developer platform, is expanding the capabilities of W&B Weave by adding integrations with NeMo Guardrails microservices. This enhancement builds on Weights & Biases’ existing portfolio of NIM integrations for optimized AI inferencing in production.

NeMo Guardrails Offers Open-Source Tools for AI Safety Testing

Developers ready to test the effectiveness of applying safeguard models and other rails can use NVIDIA Garak — an open-source toolkit for LLM and application vulnerability scanning developed by the NVIDIA Research team.

With Garak, developers can identify vulnerabilities in systems using LLMs by assessing them for issues such as data leaks, prompt injections, code hallucination and jailbreak scenarios. By generating test cases involving inappropriate or incorrect outputs, Garak helps developers detect and address potential weaknesses in AI models to enhance their robustness and safety.

Availability

NVIDIA NeMo Guardrails microservices, as well as NeMo Guardrails for rail orchestration and the NVIDIA Garak toolkit, are now available for developers and enterprises. Developers can get started building AI safeguards into AI agents for customer service using NeMo Guardrails with this tutorial.

See notice regarding software product information.

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Time to suit up, members. The multiverse is about to get a whole lot cloudier as GeForce NOW opens a portal to the first season of hit game Marvel Rivals from NetEase Games.

Members can now game in a new dimension with expanded support for virtual- and mixed-reality devices. This week’s GeForce NOW app update 2.0.70 begins rolling out compatibility for Apple Vision Pro spatial computers, Meta Quest 3 and 3S, and Pico 4 and 4 Ultra devices.

Plus, no GFN Thursday is complete without new games. Get ready for seven new titles joining the cloud this week, including multiplayer online battle arena game SMITE 2.

Invisible No More

Eternal night falls for Marvel Rivals, the superhero, team-based player vs. player shooter that lets players assemble an ever-evolving all-star squad of Super Heroes and Super Villains battling with unique powers across a dynamic lineup of destructible maps from the Marvel Multiverse.

The Fantastic Four will be playable in season one of the game. For Eternal Night Falls, Invisible Woman and Mister Fantastic will be released in the first half of the season, followed by Human Torch and The Thing in the second. Season one will also feature three new maps, special events and an all-new Doom Match game mode.

Stream it all with a GeForce NOW membership across devices, from an underpowered laptop, Mac devices, a Steam Deck or the supported platform of virtual- and mixed-reality devices.

Head in the Clouds

The latest GeForce NOW app update is expanding cloud streaming capabilities to Apple Vision Pro spatial computers, Meta Quest 3 and 3S, and Pico 4 and 4 Ultra virtual- and mixed-reality headsets starting this week.

These newly supported devices will give members access to an extensive library of games to stream through GeForce NOW. Members can gain access by visiting play.geforcenow.com or via the Android-native client on the PICO store. The rollout will be complete on Tuesday, Jan. 21.

Members will be able to transform their space into a personal gaming theater by playing, on massive virtual screens, their favorite PC games, such as the latest season of Marvel Rivals, Dragon Age and more. With access to NVIDIA technologies, including ray tracing and NVIDIA DLSS on supported games, these devices now provide an enhanced visual experience with the highest frame rates and lowest latency.

Here Comes The New

SMITE 2 is now free to play and has brought a huge update to mark the start of open beta. New god Aladdin joins, along with SMITE 1 fan favourites Geb, Agni, Mulan and Ullr — bringing the total god roster to 45. Twenty of the gods now feature Aspects — an optional spin on each god’s ability kit that opens up even more strategic options. The 3v3 mode Joust has also arrived, featuring a brand-new, Arthurian-themed map. Assault and Duel game modes are also available. Finally, the Conquest mode brings a wealth of updates to the map, features and balance.

• Hyper Light Breaker (New release on Steam, Jan. 14)
• Aloft (New release on Steam, Jan. 15)
• Assetto Corsa EVO (New release on Steam, Jan. 16)
• Generation Zero (Xbox, available on PC Game Pass)
• HOT WHEELS UNLEASHED 2 – Turbocharged (Xbox, available on PC Game Pass)
• SMITE 2 (Steam)
• Voidwrought (Steam)

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

Which role is your main?

Tank
Damage
Support

— NVIDIA GeForce NOW (@NVIDIAGFN) January 15, 2025

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Troves of unwatched surgical video footage are finding new life, fueling AI tools that help make surgery safer and enhance surgical education. The Surgical Data Science Collective (SDSC) is transforming global surgery through AI-driven video analysis, helping to close the gaps in surgical training and practice.

In this episode of the NVIDIA AI Podcast, Margaux Masson-Forsythe, director of machine learning at SDSC, discusses the unique challenges of doing AI research as a nonprofit, how the collective distills insights from massive amounts of video data and ways AI can help address the stark reality that five billion people still lack access to safe surgery.

Learn more about SDSC, and hear more about the future of AI in healthcare by listening to the J.P. Morgan Healthcare Conference talk by Kimberly Powell, vice president of healthcare at NVIDIA.

Time Stamps

8:01 – What are the opportunities and challenges of analyzing surgical videos?

12:50 – Masson-Forsythe on trying new models and approaches to stay on top of the field.

18:14 – How does a nonprofit approach conducting AI research?

24:05 – How the community can get involved with SDSC.

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Harrison.ai has developed annalise.ai, an AI system that automates radiology image analysis to improve diagnosis speed and accuracy, and is now working on Franklin.ai to enhance histopathology diagnosis. CEO Aengus Tran emphasizes the importance of using AI in healthcare to reduce misdiagnoses and improve patient outcomes.

Matice Founder Jessica Whited on Harnessing Regenerative Species for Medical Breakthroughs 

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Subscribe to the AI Podcast

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Quantum computing is one of the most exciting areas in computer science, promising progress in accelerated computing beyond what’s considered possible today.

It’s expected that the technology will tackle myriad problems that were once deemed impractical, or even impossible to solve. Quantum computing promises huge leaps forward for fields spanning drug discovery and materials development to financial forecasting.

But just as exciting as quantum computing’s future are the breakthroughs already being made today in quantum hardware, error correction and algorithms.

NVIDIA is celebrating and exploring this remarkable progress in quantum computing by announcing its first Quantum Day at GTC 2025 on March 20. This new focus area brings together leading experts for a comprehensive and balanced perspective on what businesses should expect from quantum computing in the coming decades — mapping the path toward useful quantum applications.

Discussing the state of the art in quantum computing, NVIDIA founder and CEO Jensen Huang will share the stage with executives from industry leaders, including:

• Alice & Bob
• Atom Computing
• D-Wave
• Infleqtion
• IonQ
• Pasqal
• PsiQuantum
• Quantinuum
• Quantum Circuits
• QuEra Computing
• Rigetti
• SEEQC

Learn About Quantum Computing at NVIDIA GTC 

Quantum Day will feature:

• Sessions exploring what’s possible and available now in quantum computing, and where quantum technologies are headed, hosted by Huang and representatives from across the quantum community.
• A developer day session outlining how partners are working with NVIDIA to advance quantum computing.
• Educational sessions providing attendees with hands-on training on how to use the most advanced tools to explore and develop quantum hardware and applications.
• A Quantum Day special address, unveiling the latest news and advances from NVIDIA in quantum computing shortening the timeline to useful applications.

Quantum Day at GTC 2025 is the destination for leaders and experts seeking to chart a course into the future of quantum computing.

Register for GTC.

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AI is making inroads across the entire healthcare industry — from genomic research to drug discovery, clinical trial workflows and patient care.

In a fireside chat Monday during the annual J.P. Morgan Healthcare Conference in San Francisco, NVIDIA founder and CEO Jensen Huang took the stage with industry leaders progressing each of these areas to advance biomedical science and meet the global demand for patient care.

Healthcare has a more severe labor shortage than any other field — the industry is expected to be short 10 million workers by the end of the decade, according to the World Health Organization. By deploying foundation models to narrow the field of potential drug molecules and streamlining workflows with agentic AI, these innovators are helping meet the global demand by enabling clinicians and researchers to achieve more with their limited time.

They include industry luminaries Patrick Collison, cofounder of Stripe and the Arc Institute nonprofit research organization; Christina Zorn, chief administrative officer at Mayo Clinic; Jacob Thaysen, CEO of DNA sequencing technology leader Illumina; and Ari Bousbib, chairman and CEO of clinical research and commercial services provider IQVIA.

The four organizations at J.P. Morgan Healthcare announced partnerships with NVIDIA to advance drug discovery, accelerate pathology, enhance genomic research and augment healthcare with agentic AI, respectively.

AI’s Evolution, From Predicting to Reasoning

Huang opened the event by reflecting on the tremendous progress in AI over the past year, spanning large language models, visual generative AI and physical AI for robotics — and outlining a vision for a future involving agentic AI models that are capable of reasoning and problem-solving.

“The future of AI is likely to involve a fair amount of thinking,” he said. “The ability for AI to now reason, plan and act is foundational to the way we’re going to go forward.”

To support the development of these AI models, NVIDIA recently unveiled NVIDIA Cosmos, a physical AI platform that includes state-of-the art generative world foundation models. These models apply the same technique as a language model that predicts the next word in a sentence — instead predicting the next action a robot should take.

“The idea that you can generate the next frame for a video has become common sense,” Huang said. “And if that’s the case, is it possible that generating the next articulation could be common sense? And the answer is absolutely.”

AI for Every Modality

Channeling a late-night talk show host, Huang called up the guest speakers one by one to discuss their work accelerating biomedical research with AI innovation.

First up was Collison, who shared the Arc Institute’s mission to help researchers tackle long-term scientific challenges by providing multiyear funding that enables them to focus on innovative research instead of grant writing — which he believes will spur breakthroughs that are unfeasible to pursue under today’s funding models.

“A lot of the low-hanging fruit, the stuff that is easier to discover, we did,” Collison said, referring to the development of groundbreaking treatments like antibiotics, chemotherapy and more in decades past. “Today, it’s immensely harder.”

Already, Arc Institute’s investments have resulted in Evo, a powerful foundation model that understands the languages of DNA, RNA and proteins. The institute is now working with NVIDIA on foundation models for biology that can advance applications for drug discovery, synthetic biology across multiple scales of complexity, disease and evolution research, and more.

Next, Mayo Clinic’s Zorn shared how the research hospital is applying NVIDIA technology to one of the world’s largest pathology databases to transform cancer care with AI insights.

“We saw a paradigm shift in healthcare. You’re either going to disrupt from within or you’re going to be disrupted,” she said. “We knew we had to embrace tech in a way that was really going to optimize everything we do.”

Zorn also shared how Mayo Clinic is approaching the future healthcare worker shortage by investing in robotics.

“We’re going to use, essentially, the robots to be a member of the healthcare team in the healthcare spaces,” she said.

The evening wrapped with two leaders in healthcare information reflecting on ways multimodal AI models can uncover insights and streamline processes to boost the capabilities of human experts.

“Combining other information, other modalities, other ‘omics’…is going to give us much deeper insight into biology. But while DNA was very difficult itself, when you then combine all the omics, it becomes exponentially more challenging,” said Illumina’s Thaysen. “It’s getting so complicated that we do need huge computing power and AI to really understand and process it.”

IQVIA is working with NVIDIA to build custom foundation models and agentic AI workflows trained on the organization’s vast healthcare-specific information and deep domain expertise. Use cases include boosting the efficiency of clinical trials and optimizing planning for the launch of therapies and medical devices.

The company is committed to using AI responsibly, ensuring that its AI-powered capabilities are grounded in privacy, regulatory compliance and patient safety.

“The opportunity here is to try to reduce the dependencies and sequential series of steps that require a lot of interactions, and handle them without human touch,” said Bousbib.  “AI agents will be able to eliminate the white space, that is, the time waiting for humans to complete those tasks. There’s a great opportunity to reduce time and costs.”

NVIDIA at J.P. Morgan Healthcare

The fireside chat followed a presentation at the conference by Kimberly Powell, NVIDIA’s vice president of healthcare. In her talk, Powell discussed the industry collaborations and announced new resources for healthcare and life sciences developers.

These include an NVIDIA NIM microservice for GenMol, a generative AI model for controlled, high-performance molecular generation — and an NVIDIA BioNeMo Blueprint for protein binder design, part of the NVIDIA Blueprints collection of enterprise-grade reference workflows for agentic and generative AI use cases.

For more from NVIDIA at the J.P. Morgan Healthcare Conference, listen to the audio recording of Powell’s session.

Subscribe to NVIDIA healthcare news.

Main image above features, from left to right, Illumina’s Jacob Thaysen, Mayo Clinic’s Christina Zorn, Arc Institute’s Patrick Collison, IQVIA’s Ari Bousbib and NVIDIA’s Jensen Huang. 

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IQVIA, the world’s leading provider of clinical research services, commercial insights and healthcare intelligence, is working with NVIDIA to build custom foundation models and agentic AI workflows that can accelerate research, clinical development and access to new treatments.

AI applications trained on the organization’s vast healthcare-specific information and guided by its deep domain expertise will help the industry boost the efficiency of clinical trials and optimize planning for the launch of therapies and medical devices — ultimately improving patient outcomes.

Operating in over 100 countries, IQVIA has built the largest global healthcare network and is uniquely connected to the ecosystem with the most comprehensive and granular set of information, analytics and technologies in the industry.

Announced today at the J.P. Morgan Conference in San Francisco, IQVIA’s collection of models, AI agents and reference workflows will be developed with the NVIDIA AI Foundry platform for building custom models, allowing IQVIA’s thousands of pharmaceutical, biotech and medical device customers to benefit from NVIDIA’s agentic AI capabilities and IQVIA’s technologies, life sciences information and expertise.

Enabling Industry Applications in Clinical Trials

The healthcare and life sciences industry generates more information than any other industry in the world, making up 30% of the world’s data volume.

IQVIA plans to use its unparalleled information assets, analytics and domain expertise —  known as IQVIA Connected Intelligence — with the NVIDIA AI Foundry service to build language and multimodal foundational models that will power a collection of customized IQVIA AI agents.

These agents are anticipated to be available in predefined workflows, or blueprints, that would accomplish a specific task. This partnership aims to accelerate the innovation cycle of IQVIA Healthcare-grade AI. IQVIA has been leading in the responsible use of AI, ensuring that its AI-powered capabilities are grounded in privacy, regulatory compliance and patient safety. IQVIA Healthcare-grade AI represents the company’s commitment to these principles.

One key opportunity area is in clinical development, when clinical trials are conducted for new drugs. The overall process takes about 11 years, on average, and each trial has a multitude of workflows that could be supported by AI agents. For example, just starting a clinical trial involves site selection, participant recruitment, regulatory submissions and tight communication between study sites and their sponsors.

NVIDIA AI Foundry Streamlines Custom Model Development

To streamline the development of these AI agents, IQVIA is using tools within NVIDIA AI Foundry and the NVIDIA AI Enterprise software platform, including NVIDIA NIM microservices, especially the Llama Nemotron and Cosmos Nemotron model families; NVIDIA AI Blueprint reference workflows; the NVIDIA NeMo platform for developing custom generative AI; and dedicated capacity on NVIDIA DGX Cloud.

The NVIDIA AI Blueprint for multimodal PDF data extraction can help IQVIA unlock the immense amount of healthcare text, graphs, charts and tables stored in PDF files, bringing previously inaccessible information to train AI models and agents for domain-specific and even customer-specific applications. NVIDIA RAPIDS data science libraries then accelerate the construction of knowledge graphs.

Additional AI agents could automate complex, time-consuming tasks, like document generation and patient recruitment, allowing healthcare professionals to focus on strategic decision-making and human interaction.

Learn more about NVIDIA technologies and their impact on healthcare and life sciences.

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For decades, leadership in computing and software ecosystems has been a cornerstone of American strength and influence worldwide. The federal government has wisely refrained from dictating the design, marketing and sale of mainstream computers and software — key drivers of innovation and economic growth.

The first Trump Administration laid the foundation for America’s current strength and success in AI, fostering an environment where U.S. industry could compete and win on merit without compromising national security. As a result, mainstream AI has become an integral part of every new application, driving economic growth, promoting U.S. interests and ensuring American leadership in cutting-edge technology.

Today, companies, startups and universities around the world are tapping mainstream AI to advance healthcare, agriculture, manufacturing, education and countless other fields, driving economic growth and unlocking the potential of nations. Built on American technology, the adoption of AI around the world fuels growth and opportunity for industries at home and abroad.

That global progress is now in jeopardy. The Biden Administration now seeks to restrict access to mainstream computing applications with its unprecedented and misguided “AI Diffusion” rule, which threatens to derail innovation and economic growth worldwide.

In its last days in office, the Biden Administration seeks to undermine America’s leadership with a 200+ page regulatory morass, drafted in secret and without proper legislative review. This sweeping overreach would impose bureaucratic control over how America’s leading semiconductors, computers, systems and even software are designed and marketed globally. And by attempting to rig market outcomes and stifle competition — the lifeblood of innovation — the Biden Administration’s new rule threatens to squander America’s hard-won technological advantage.

While cloaked in the guise of an “anti-China” measure, these rules would do nothing to enhance U.S. security.  The new rules would control technology worldwide, including technology that is already widely available in mainstream gaming PCs and consumer hardware. Rather than mitigate any threat, the new Biden rules would only weaken America’s global competitiveness, undermining the innovation that has kept the U.S. ahead.

Although the rule is not enforceable for 120 days, it is already undercutting U.S. interests. As the first Trump Administration demonstrated, America wins through innovation, competition and by sharing our technologies with the world — not by retreating behind a wall of government overreach. We look forward to a return to policies that strengthen American leadership, bolster our economy and preserve our competitive edge in AI and beyond.

Ned Finkle is vice president of government affairs at NVIDIA.

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