Posts in category: nVidia AI

NVIDIA today launched a cloud service for medical imaging AI to further streamline and accelerate the creation of ground-truth data and training of specialized AI models through fully managed, cloud-based application programming interfaces.

NVIDIA MONAI cloud APIs — announced at the annual meeting of RSNA, the Radiological Society of North America, taking place this week in Chicago — provide an expedited path for developers and platform providers to integrate AI into their medical imaging offerings using pretrained foundation models and AI workflows for enterprises. The APIs are built on the open-source MONAI project founded by NVIDIA and King’s College London.

Medical imaging is critical across healthcare, making up approximately 90% of healthcare data. It’s used by radiologists and clinicians to do screening, diagnosis and intervention, by biopharma researchers to evaluate how clinical trial patients respond to new drugs and by medical device makers to provide real-time decision support.

The scale of work across each of these areas requires a medical imaging-specific AI factory — an enterprise-grade platform that delivers large-scale data management, creates ground-truth annotations, accelerates model development and establishes seamless AI application deployment.

With NVIDIA MONAI cloud APIs, solution providers can more easily integrate AI into their medical imaging platforms, enabling them to provide supercharged tools for radiologists, researchers and clinical trial teams to build domain-specialized AI factories. The APIs are available in early access through the NVIDIA DGX Cloud AI supercomputing service.

The NVIDIA MONAI cloud API is integrated into Flywheel, a leading medical imaging data and AI platform that supports end-to-end workflows for AI development. Developers at medical image annotation companies including RedBrick AI and at machine learning operations (MLOps) platform providers including Dataiku are poised to integrate NVIDIA MONAI cloud APIs into their offerings.

Ready-to-Run Annotation and Training for Medical Imaging

Building efficient and cost-effective AI solutions requires a robust, domain-specialized development foundation that includes full-stack optimizations for software, scalable multi-node systems and state-of-the-art research. It also requires high-quality ground-truth data — which can be arduous and time-consuming to gather, particularly for 3D medical images that require a high level of expertise to annotate.

NVIDIA MONAI cloud APIs feature interactive annotation powered by the VISTA-3D (Vision Imaging Segmentation and Annotation) foundation model. It’s purpose-built for continuous learning, a capability that improves AI model performance based on user feedback and new data.

Trained on a dataset of annotated images from 3D CT scans from more than 4,000 patients, spanning various diseases and parts of the body, VISTA-3D accelerates the creation of 3D segmentation masks for medical image analysis. With continuous learning, the AI model’s annotation quality improves over time.

To further accelerate AI training, this release includes APIs that make it seamless to build custom models based on MONAI pretrained models. NVIDIA MONAI cloud APIs also include Auto3DSeg, which automates hyperparameter tuning and AI model selection for a given 3D segmentation task, simplifying the model development process.

NVIDIA researchers recently won four challenges at the MICCAI medical imaging conference using Auto3DSeg. These included AI models to analyze 3D CT scans of the kidneys and heart, brain MRIs and 3D ultrasounds of the heart.

Solutions Providers, Platform Builders Embrace NVIDIA MONAI Cloud APIs

Medical imaging solution providers and machine learning platforms are using NVIDIA MONAI cloud APIs to deliver critically valuable AI insights to accelerate their customers’ work.

Flywheel has integrated MONAI through NVIDIA AI Enterprise and is now offering NVIDIA MONAI cloud APIs to accelerate medical image curation, labeling analysis and training. The Minneapolis-based company’s centralized, cloud-based platform powers biopharma companies, life science organizations, healthcare providers and academic medical centers to identify, curate and train medical imaging data for the development of trustworthy AI.

“NVIDIA MONAI cloud APIs lower the cost of building high-quality AI models for radiology, disease research and the evaluation of clinical trial data,” said Dan Marcus, chief scientific officer at Flywheel. “With the addition of cloud APIs for interactive annotation and automated segmentation, customers of our medical imaging AI platform can accelerate AI model development to more quickly deliver innovative solutions.”

Annotation and viewer solution providers, including Redbrick AI, Radical Imaging, V7 Labs and Centaur Labs, will also use NVIDIA MONAI cloud APIs to bring AI-assisted annotation and training capabilities to market faster, without having to host and manage the AI infrastructure on their own.

RedBrick AI is integrating the VISTA-3D model available through NVIDIA MONAI cloud APIs to deliver interactive cloud annotation for its medical device customers that support distributed teams of clinicians.

“VISTA-3D allows our clients to rapidly build models across different modalities and conditions,” said Shivam Sharma, CEO of RedBrick AI. “The foundation model is generalizable, making it easy to fine-tune for various clinical applications with accurate, reliable segmentation results.”

To streamline enterprise AI model development, MLOps platform builders including Dataiku, ClearML and Weight & Biases are also investigating the use of NVIDIA MONAI cloud APIs.

Dataiku plans to integrate NVIDIA MONAI cloud APIs to further simplify AI model creation for medical imaging applications.

“With NVIDIA MONAI cloud APIs, Dataiku users would be able to easily use Auto3DSeg, a low-code option to accelerate the development of state-of-the-art segmentation models, through Dataiku’s web interface connected to an NVIDIA-hosted, GPU-accelerated service,” said Kelci Miclaus, global head of AI health and life sciences solutions at Dataiku. “This democratizes AI in biomedical imaging by extending the power to create and apply AI-driven workflows to both data and domain experts.”

Join the medical imaging innovators accelerating AI development with NVIDIA MONAI cloud APIs by signing up for early access.

GeForce NOW is bringing 18 new games to the cloud this week, part of a gratitude-filled GFN Thursday.

A collaboration between Chromebook Plus, CD PROJEKT RED and GeForce NOW brought an immersive 3D activation to Times Square over the weekend, containing a hidden Easter egg for Cyberpunk 2077 players.

Plus, this holiday season, give the gift of high-performance cloud gaming with a free, three-month PC Game Pass subscription included with a six-month GeForce NOW Ultimate membership.

Eye Spy

Times Square was transformed into a futuristic dystopia last weekend by a stunning 3D Cyberpunk 2077 activation. The immersive display showcased the power of GeForce NOW on a Chromebook Plus, enabling gamers to stream thousands of titles from popular digital gaming stores from the cloud, right out of the box.

Long-time Cyberpunk 2077 fans were also challenged to try their hand at spotting a code hidden in the activation — the latest hint in a long line of clues needed to solve a riddle that has had players guessing for the past three years.

Chromebook owners with an Ultimate or Priority membership can explore Cyberpunk 2077’s Night City with NVIDIA RTX ON for the most immersive gaming experience, including the “Phantom Liberty” expansion and 2.0 update. Google and NVIDIA are offering all Chromebook owners three free months of a GeForce NOW Priority membership to get gamers started.

And those interested in leveling up to the highest-performing tier can get three free months of a GeForce NOW Ultimate membership with the purchase of a Cloud Gaming Chromebook. Find more details on how to redeem the offer on the Chromebook Perks page.

Grateful for Great Games

Get the weekend started with the new weekly games list:

• Breathedge (Xbox, available on Microsoft Store)
• Bridge Constructor: The Walking Dead (Xbox, available on Microsoft Store)
• Bus Simulator 21 (Xbox, available on Microsoft Store)
• Chivalry 2 (Xbox, available on PC Game Pass)
• Dungeons 4 (Epic Games Store)
• Hexarchy (Steam)
• Hearts of Iron IV (Xbox, available on Microsoft Store)
• I Am Future (Epic Games Store)
• Imagine Earth (Xbox, available on Microsoft Store)
• The Invincible (Epic Games Store)
• Land of the Vikings (Steam)
• Saints Row IV: Re-Elected (Xbox, available on Microsoft Store)
• SHENZHEN I/O (Xbox, available on Microsoft Store)
• Supraland: Six Inches Under (Xbox, available on PC Game Pass)
• The Surge 2 (Xbox, available on Microsoft Store)
• Thymesia (Xbox, available on Microsoft Store)
• Tropico 6 (Xbox, available on Microsoft Store)
• West of Dead (Xbox, available on Microsoft Store)

What are you looking forward to streaming? Let us know on Twitter or in the comments below.

tell us a device you have that you’re grateful for

bonus points for pictures

— NVIDIA GeForce NOW (@NVIDIAGFN) November 22, 2023

A calendar packed with meetings, calls and lab visits may sound like a typical workday for many — but for Luca Lofranco, whose greatest wish was to experience what it’s like to work at NVIDIA, it was a dream come true.

Eighteen-year-old Lofranco recently traveled from his hometown near Toronto, Canada, to spend the day at our Santa Clara campus, supported by Make-A-Wish, a nonprofit that grants life-changing wishes for children with critical illnesses. The wish from Lofranco, who has Hodgkin’s lymphoma, was the fifth NVIDIA has been a part of in the last decade.

The NVIDIA team kept the day’s agenda a secret — surprising Lofranco with tours of the demo room and robotics lab, a chat with the University Recruiting team, a ride in a self-driving car and a video call with NVIDIA founder and CEO Jensen Huang. An aspiring computer science major, Lofranco was stoked for it all because, as his mom Cassandra shared, “NVIDIA is his Disneyland.”

A Long-Time NVIDIA Fan 

After attending his first computer science summer camp when he was eight, Lofranco learned 3D modeling in Autodesk Maya, programming in Python, as well as 3D printing. His budding interest in tech grew and, soon enough, he was building his own gaming rigs.

NVIDIA quickly became Lofranco’s favorite tech company, he said, so much so that he carved the company logo out of a piece of wood using a computer numerical control machine.

For gaming, he enjoys using NVIDIA GeForce RTX 3070 and GeForce GTX 1080 Ti GPUs. But Lofranco’s ultimate draw to NVIDIA wasn’t its products but its culture.

“Everyone is driven to see the same outcome and comes together to make it happen,” he said. “Everything is designed for collaboration.”

A VIP Experience

Ahead of Lofranco’s visit, the NVIDIA team sent him a box of swag — including a hoodie, a hat and a custom NVIDIA badge.

Once he arrived on campus, NVIDIA volunteers welcomed and whisked Lofranco off on a campus tour, followed by a meeting with the solutions architect team, which includes NVIDIANs focused on healthcare, auto, AI, cloud service providers and large language models.

Next, a visit to the robotics lab helped satisfy Lofranco’s “maker” curiosity. He saw an NVIDIA DGX Station as well as test robots for developing the NVIDIA Jetson edge AI platform, and was soon directing a robot arm to stack colored blocks.

After learning that Lofranco’s favorite foods include lobster, tiramisu and Kit Kat candy bars, the café team prepared a special menu for him and all employees in the office that day. Everyone enjoyed a lobster roll pop-up station in the campus park and tiramisu-flavored ice cream with assorted toppings, including Kit Kat pieces.

Innovators

On a visit to the demo room at NVIDIA’s Santa Clara site, Lofranco and his father revealed that they tinker with innovations themselves. They programmed their water heater in the family hot tub to maintain a comfortable temperature and decrease the time needed to warm it — all thanks to Python code and Raspberry Pi experimentation.

With so much to soak in, Lofranco described his wish day at NVIDIA as “unfathomable” — and that was before his video call with Huang, which stretched from a planned quarter hour to 45 minutes.

After a conversation that spanned NVIDIA’s origins, many near failures and innovation, Huang gifted Lofranco a GeForce RTX 4090 Founders Edition GPU and shared some sound advice: “Keep playing video games — but make sure to prioritize your homework.”

Capping a packed day of fun-filled support from nearly 50 NVIDIANs was a visit to the auto lab and a spin in one of NVIDIA’s self-driving test cars.

How was it all? “Breathtaking,” said Lofranco, who learned firsthand from Huang that while NVIDIA has evolved from being the underdog to a leading tech company, it still feels “like a family.”

Learn more about NVIDIA life, culture and careers. 

Talk about going after low-hanging fruit. Afresh is an AI startup that helps grocery stores and retailers reduce food waste by making supply chains more efficient.

In the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with the company’s cofounder and president, Nathan Fenner, about its mission, offerings and the greater challenge of eliminating food waste.

Most supply chain and inventory management offerings targeting grocers and retailers are outdated. Fenner and his team noticed those solutions, built for the nonperishable side of the business, didn’t work as well on the fresh side — creating enormous amounts of food waste and causing billions in lost profits.

The team first sought to solve the store-replenishment challenge by developing a platform to help grocers decide how much fresh produce to order to optimize costs while meeting demand.

They created machine learning and AI models that could effectively use the data generated by fresh produce, which is messier than data generated by nonperishable goods because of factors like time to decay, greater demand fluctuation and unreliability caused by lack of barcodes, leading to incorrect scans at self-checkout registers.

The result was a fully integrated, machine learning-based platform that helps grocers make informed decisions at each node of the operations process.

The company also recently launched inventory management software that allows grocers to save time and increase data accuracy by intelligently tracking inventory. That information can be inputted back into the platform’s ordering solution, further refining the accuracy of inventory data.

It’s all part of Afresh’s greater mission to tackle climate change.

“The most impactful thing we can do is reduce food waste to mitigate climate change,” Fenner said. “It’s really one of the key things that brought me into the business: I think I’ve always had a keen eye to work in the climate space. It’s really motivating for a lot of our team, and it’s a key part of our mission.”

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Genentech, a member of the Roche Group, is pioneering the use of generative AI to discover and develop new therapeutics and deliver treatments to patients more efficiently.

A new collaboration between Genentech, the biotechnology pioneer, and NVIDIA aims to transform the discovery and development of new medicines by bringing together experts from each company to optimize and accelerate Genentech’s proprietary algorithms.

NVIDIA will work with Genentech to accelerate these models on NVIDIA DGX Cloud, which provides dedicated instances of AI supercomputing and software hosted by NVIDIA cloud service provider partners.

Genentech plans to use NVIDIA BioNeMo, which enables biotech companies to customize models at scale, and integrate BioNeMo cloud application programming interfaces directly into computational drug discovery workflows.

BioNeMo, now generally available as a training service, is a domain-specific platform that simplifies, accelerates and scales generative AI applications for computational drug discovery. It allows researchers to pretrain or fine-tune state-of-the-art models on DGX Cloud.

The collaboration will initially focus on optimizing Genentech’s drug discovery AI models in its “lab in a loop” framework. The goal: To allow its researchers to understand complex biomolecular patterns and relationships to truly disrupt drug development and improve the success rate of R&D, and to empower scientists to deliver multiplicative, rather than linear or additive, benefits for patients and the broader healthcare ecosystem.

“Our collaboration with NVIDIA builds on our long history of successfully inventing and deploying technology in ways that were not initially apparent to others,” said Aviv Regev, executive vice president and head of Genentech Research & Early Development (gRED). “We were the first biotech company to leverage molecular biology for drug discovery and development, which changed the world. We pioneered antibody therapeutics that became the paradigm of treatment. And now, we have brought AI, the lab and the clinic together to uncover otherwise inaccessible patterns in vast quantities of data, and to design experiments to test those patterns. Collaborating with NVIDIA, and introducing generative AI, has the power to turbocharge the discovery and design of therapeutics that will improve the lives of patients across the world.”

Streamlining Drug Discovery With Computation  

Drug discovery and development is currently a lengthy, complicated and costly process. Drug targets for novel medicines are difficult to predict, as is successfully developing a molecule as a potential therapeutic. AI can play a transformational role because generative and other AI models can help scientists rapidly identify potential drug molecules and interactions by training on large-scale datasets.

For Genentech, using AI helps bridge the gap between lab experiments and computational algorithms.

The company’s R&D group, gRED, has already done significant work using AI — across multiple modalities — to discover and develop novel therapeutics while learning more about the building blocks of biology and diseases.

Teams from Genentech and NVIDIA will now work together to optimize Genentech’s custom-developed models to shorten this time-consuming process of drug discovery and development and lead to greater success.

Putting AI in a Loop

Genentech’s “lab in a loop” is an iterative framework for generating and exploring molecular designs with predicted properties. It aims to use experimental data to inform generative computational models and better optimize future molecular designs. NVIDIA will help Genentech optimize its framework by accelerating training and inference of Genentech’s drug discovery models.

Through this collaboration, NVIDIA AI experts will gain insights into AI-related challenges in drug discovery and development. NVIDIA plans to use these insights to improve its BioNeMo platform and others to further accommodate the requirements of models used by the biotech industry.

“AI can play a transformational role in accelerating drug discovery and development — as it has across many parts of healthcare and life sciences,” said Kimberly Powell, vice president of healthcare at NVIDIA. “Together, NVIDIA and Genentech are unlocking scientific innovation by developing and implementing AI models and algorithms that enable us to rapidly iterate and unearth insights.”

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Editor’s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. 

It’s the season of gratitude: that time of year to give thanks for the people and small moments that make life so special.

This week’s featured In the NVIDIA Studio artist, Ravissen Carpenen, is serving up a feast of mouthwateringly photorealistic 3D food renders to the dinner table.

His delectable time-lapse videos are featured on his YouTube channel, CG Realism — presented with a side of upbeat music and a pinch of style.

Carpenen was one of several contributors to the food-themed Studio Standout video contest, alongside Roger Roque (@rogerroqueid), Nicole Morena (@nicky.blender), Heloise Cart (@isoheell) and Kris Theroin (@kristheorin).

Finally, livestreamers using OBS Studio — a free, open-source software for video recording and livestreaming — can download the latest update with HDR10 capture support, WHIP and WebRTC output and more. Learn more details.

All About That Baste

Carpenen’s wife, a pastry chef, inspired his photorealistic, food-centered works.

“My aim, one day, is to be able to create ultra-realistic renders that will be used in film and movies,” he said.

His projects begin with online research and reference gathering, mainly on Pinterest and Behance, which he then compiles into mood boards using the stand-alone image tracking program PureRef.

Before any modeling takes place, Carpenen lights the scene — but without textures.

“This is to tell the story of the artwork, as light intends to give artwork an emotional flow, alongside as well as color and materials,” he said.

Carpenen initially sculpts his models in ZBrush using customizable brushes to shape, texture and paint his virtual clay in a real-time environment with instant feedback.

He then browses the Quixel Megascans library for models that can further add realism, such as garlic cloves and rosemary garnishes for his turkey project.

Rare-in for More

Carpenen uses Marmoset Toolbag’s ambient occlusion, curvature, normal and thickness features to bake the ZBrush meshes from high-poly to low-poly models as 32-bit textures.

The process saves memory space, minimizing lag time while allowing greater flexibility in the modeling stage.

Carpenen’s GeForce RTX 3070 GPU-powered system with RTX acceleration instantly optimized his meshes. RTX-accelerated ray tracing and OptiX AI-powered denoising also enabled smoother viewport movement.

Baking a Berry Good Pie

Once the renders are ready, Carpenen imports them into Adobe Substance 3D Painter to apply custom colors and textures.

There, Carpenen uses RTX-accelerated light and ambient occlusion baking — though not in the oven — to optimize his assets, such as this berry pie, in mere seconds.

He also had the option to set up a live link connection between 3D Painter and NVIDIA Omniverse, a development platform for connecting and building Universal Scene Description (OpenUSD)-based tools and applications, via the USD Composer foundation app.

The connection would allow Carpenen’s texture work in Substance 3D Painter to directly translate to USD Composer — eliminating the need for numerous file imports, exports and reformatting.

Donut Hole in One

Carpenen uses Blender to bring his scenes together with advanced model sculpting, animations and further lighting refinement.

RTX GPUs allow smoother movement in the viewport thanks to Blender Cycles’ RTX-accelerated OptiX ray tracing.

And for exporting final files, RTX-accelerated OptiX ray tracing in Blender Cycles delivers the fastest final-frame render.

Thanks to AI, This Work Is Toast

Carpenen uses Adobe Photoshop Lightroom to put the finishing touches on his food scenes.

GPU-accelerated image processing enables dramatically more responsive adjustments on his 4K-resolution display.

Carpenen had even more RTX-accelerated AI tools at his disposal in Lightroom. The “Raw Details” feature refines the fine color details of high-resolution RAW images. And “Super Resolution” uses AI to upscale images with higher quality than traditional methods.

According to Carpenen, putting in the work is key.

“It’s equivalent to practicing football — if you don’t get enough time daily to practice, you can’t hone skills,” he said. “It’s important to know how to tackle obstacles — and that knowledge can only be gained by experience.”

Check out Carpenen’s YouTube channel, CG Realism, and ArtStation to check out more food projects.

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Generative AI is the latest turn in the fast-changing digital landscape. One of the groundbreaking innovations making it possible is a relatively new term: SuperNIC. 

What Is a SuperNIC?

SuperNIC is a new class of network accelerators designed to supercharge hyperscale AI workloads in Ethernet-based clouds. It provides lightning-fast network connectivity for GPU-to-GPU communication, achieving speeds reaching 400Gb/s using remote direct memory access (RDMA) over converged Ethernet (RoCE) technology.  

SuperNICs combine the following unique attributes: 

• High-speed packet reordering to ensure that data packets are received and processed in the same order they were originally transmitted. This maintains the sequential integrity of the data flow. 
• Advanced congestion control using real-time telemetry data and network-aware algorithms to manage and prevent congestion in AI networks. 
• Programmable compute on the input/output (I/O) path to enable customization and extensibility of network infrastructure in AI cloud data centers. 
• Power-efficient, low-profile design to efficiently accommodate AI workloads within constrained power budgets. 
• Full-stack AI optimization, including compute, networking, storage, system software, communication libraries and application frameworks. 

NVIDIA recently unveiled the world’s first SuperNIC tailored for AI computing, based on the BlueField-3 networking platform. It’s a part of the NVIDIA Spectrum-X platform, where it integrates seamlessly with the Spectrum-4 Ethernet switch system.  

Together, the NVIDIA BlueField-3 SuperNIC and Spectrum-4 switch system form the foundation of an accelerated computing fabric specifically designed to optimize AI workloads. Spectrum-X consistently delivers high network efficiency levels, outperforming traditional Ethernet environments. 

“In a world where AI is driving the next wave of technological innovation, the BlueField-3 SuperNIC is a vital cog in the machinery,” said Yael Shenhav, vice president of DPU and NIC products at NVIDIA. “SuperNICs ensure that your AI workloads are executed with efficiency and speed, making them foundational components for enabling the future of AI computing.” 

The Evolving Landscape of AI and Networking 

The AI field is undergoing a seismic shift, thanks to the advent of generative AI and large language models. These powerful technologies have unlocked new possibilities, enabling computers to handle new tasks.  

AI success relies heavily on GPU-accelerated computing to process mountains of data, train large AI models, and enable real-time inference. This new compute power has opened new possibilities, but it has also challenged Ethernet cloud networks. 

Traditional Ethernet, the technology that underpins internet infrastructure, was conceived to offer broad compatibility and connect loosely coupled applications. It wasn’t designed to handle the demanding computational needs of modern AI workloads, which involve tightly coupled parallel processing, rapid data transfers and unique communication patterns — all of which demand optimized network connectivity.  

Foundational network interface cards (NICs) were designed for general-purpose computing, universal data transmission and interoperability. They were never designed to cope with the unique challenges posed by the computational intensity of AI workloads.  

Standard NICs lack the requisite features and capabilities for efficient data transfer, low latency and the deterministic performance crucial for AI tasks. SuperNICs, on the other hand, are purpose-built for modern AI workloads. 

SuperNIC Advantages in AI Computing Environments 

Data processing units (DPUs) deliver a wealth of advanced features, offering high throughput, low-latency network connectivity and more. Since their introduction in 2020, DPUs have gained popularity in the realm of cloud computing, primarily due to their capacity to offload, accelerate and isolate data center infrastructure processing. 

Although DPUs and SuperNICs share a range of features and capabilities, SuperNICs are uniquely optimized for accelerating networks for AI. The chart below shows how they compare: 

Distributed AI training and inference communication flows depend heavily on network bandwidth availability for success. SuperNICs, distinguished by their sleek design, scale more effectively than DPUs, delivering an impressive 400Gb/s of network bandwidth per GPU.  

The 1:1 ratio between GPUs and SuperNICs within a system can significantly enhance AI workload efficiency, leading to greater productivity and superior outcomes for enterprises.  

The sole purpose of SuperNICs is to accelerate networking for AI cloud computing. Consequently, it achieves this goal using less computing power than a DPU, which requires substantial computational resources to offload applications from a host CPU.  

The reduced computing requirements also translate to lower power consumption, which is especially crucial in systems containing up to eight SuperNICs. 

Additional distinguishing features of the SuperNIC include its dedicated AI networking capabilities. When tightly integrated with an AI-optimized NVIDIA Spectrum-4 switch, it offers adaptive routing, out-of-order packet handling and optimized congestion control. These advanced features are instrumental in accelerating Ethernet AI cloud environments. 

Revolutionizing AI Cloud Computing

The NVIDIA BlueField-3 SuperNIC offers several benefits that make it key for AI-ready infrastructure: 

• Peak AI workload efficiency: The BlueField-3 SuperNIC is purpose-built for network-intensive, massively parallel computing, making it ideal for AI workloads. It ensures that AI tasks run efficiently — without bottlenecks. 
• Consistent and predictable performance: In multi-tenant data centers where numerous tasks are processed simultaneously, the BlueField-3 SuperNIC ensures that each job and tenant’s performance is isolated, predictable and unaffected by other network activities. 
• Secure multi-tenant cloud infrastructure: Security is a top priority, especially in data centers handling sensitive information. The BlueField-3 SuperNIC maintains high security levels, enabling multiple tenants to coexist while keeping data and processing isolated. 
• Extensible network infrastructure: The BlueField-3 SuperNIC isn’t limited in scope — it’s highly flexible and adaptable to a myriad of other network infrastructure needs. 
• Broad server manufacturer support: The BlueField-3 SuperNIC fits seamlessly into most enterprise-class servers without excessive power consumption in data centers.

Learn more about NVIDIA BlueField-3 SuperNICs, including how they integrate across NVIDIA’s data center platforms, in the whitepaper: Next-Generation Networking for the Next Wave of AI. 

Good news for car lovers: Two acclaimed auto shows, taking place now through next week, are delighting attendees with displays of next-generation automotive designs powered by AI.

Hundreds of thousands of auto enthusiasts worldwide are expected to visit Guangzhou, China — known as the city of flowers — to attend its auto show, running through Sunday, Nov. 26. The event will feature new developments in electric vehicles (EVs) and automated driving, with 1,100 vehicles on display.

And across the world, in the city of angels, the Los Angeles Auto Show is expected to reach its highest-ever attendee numbers. Also running through Nov. 26, the show will include classic and exotic cars from private collections, as well as a public test track where attendees can get behind the wheel of the latest EVs.

Auto Guangzhou

One of the most anticipated reveals is from Lotus, which is showcasing its new fully electric Emeya Hyper-GT that launched in September. This stunning luxury vehicle with sports-car agility achieves an impressive suite of intelligent features, powered by dual NVIDIA DRIVE Orin processors. The high-performance processing power enables drivers to enjoy the car’s safe and secure driving capabilities and supports future features through over-the-air (OTA) updates.

With an eye on safety, Emeya carries 34 state-of-the-art surround sensors for diverse and redundant sensor data processing in real time — giving drivers added confidence when behind the wheel. With DRIVE Orin embedded in the back of the vehicle, Emeya delivers advanced driver assistance system (ADAS) capabilities and also offers the built-in headroom to support an autonomous future.

Emeya Hyper-GT is built on Lotus’ innovative Electric Premium Architecture, which underpins the Eletre Hyper-SUV as well, also powered by NVIDIA DRIVE Orin.

In addition, Lotus is showcasing its full range of Lotus electric vehicles, including the Evija hypercar, Eletre Hyper-SUV and Type 136, its recently launched electric bike. Emira, Lotus’ final internal combustion engine vehicle, is also on display.

Several other NVIDIA DRIVE ecosystem members are featuring their next-gen EVs at Auto Guangzhou:

• DENZA, a joint venture between BYD and Mercedes-Benz, is highlighting the intelligent-driving features of its N7 model lineup. All N7 models can be equipped with the NVIDIA DRIVE Orin system-on-a-chip. In addition, DENZA is showcasing its next generation of car configurators built on NVIDIA Omniverse Cloud, enabling consumers to customize various aspects, such as colors, materials and more.
• Human Horizons is showcasing the HiPhi Y SUV, which includes a second-generation intelligent door system design, a range of more than 497 miles on a single charge and an autonomous-driving system powered by NVIDIA DRIVE Orin.
• JI YUE, a Geely Holding and Baidu joint venture, is displaying the ROBOCAR JiYue 01, the first model to offer the premium intelligent driving feature ROBO Drive Max, powered by NVIDIA DRIVE Orin.
• NIO is exhibiting eight models equipped with Banyan, NIO’s Smart Digital System, and Adam, an NVIDIA-powered supercomputer. Adam uses NVIDIA DRIVE Orin to enable advanced automated-driving features and allow continuous OTA upgrades.
• XPENG is unveiling and commencing pre-sales for its next-generation, super-intelligent, seven-seater MPV, the XPENG X9. The company is also showcasing the XPENG G6, the XPENG P7i and the XPENG G9, all featuring NVIDIA DRIVE Orin.
• ZEEKR introduces the ZEEKR 007. The electric sedan is ZEEKR’s first sedan and fourth model, powered by NVIDIA DRIVE Orin. The ZEEKR 007 has a sensor suite consisting of one lidar, 12 high-definition cameras and five millimeter-wave radars for advanced smart assist driving functions with multiple redundancy.

In addition, NVIDIA DRIVE ecosystem partner DeepRoute.ai, a smart driving solutions provider, is demonstrating its DeepRoute Driver 3.0, designed to offer a non-geofenced solution for automated vehicles.

Los Angeles Auto Show

At the LA Auto Show, Lucid Motors is showcasing its highly anticipated Gravity SUV, which will begin production in late 2024. Powered by NVIDIA DRIVE, the luxury SUV features supercar levels of performance and an impressive battery range to mitigate range anxiety.

In addition, Lucid is displaying its Lucid Air sedan, including the Air Pure and Air Touring models. All of these vehicles feature the future-ready DreamDrive Pro driver-assistance system, powered by the NVIDIA DRIVE platform.

Learn more about the industry-leading designs and technologies NVIDIA is developing with its automotive partners.

European startups will get a massive boost from a new generation of AI infrastructure, NVIDIA founder and CEO Jensen Huang said Friday in a fireside chat with iliad Group Deputy CEO Aude Durand — and it’s coming just in time.

“We’re now seeing a major second wave,” Huang said of the state of AI during a virtual appearance at Scaleway’s ai-PULSE conference in Paris for an audience of more than 1,000 in-person attendees.

Two elements are propelling this force, Huang explained in a conversation livestreamed from Station F, the world’s largest startup campus, which Huang joined via video conference from NVIDIA’s headquarters in Silicon Valley.

First, “a recognition that every region and every country needs to build their sovereign AI,” Huang said. Second, the “adoption of AI in different industries,” as generative AI spreads throughout the world, Huang explained.

“So the types of breakthroughs that we’re seeing in language I fully expect to see in digital biology and manufacturing and robotics,” Huang said, noting this could create big opportunities for Europe with its rich digital biology and healthcare industries. “And of course, Europe is also home of some of the largest industrial manufacturing companies.”

Praise for France’s AI Leadership

Durand kicked off the conversation by asking Huang about his views on the European AI ecosystem, especially in France, where the government has invested millions of euros in AI research and development.

“Europe has always been rich in AI expertise,” Huang said, noting that NVIDIA works with 4,000 startups in Europe, more than 400 of them in France alone, pointing to Mistral, Qubit Pharmaceuticals and Poolside AI.

“At the same time, you have to really get the computing infrastructure going,” Huang said. “And this is the reason why Scaleway is so important to the advancement of AI in France” and throughout Europe, Huang said.

Highlighting the critical role of data in AI’s regional growth, Huang noted companies’ increasing awareness of the value of training AI with region-specific data. AI systems need to reflect the unique cultural and industrial nuances of each region, an approach gaining traction across Europe and beyond.

NVIDIA and Scaleway: Powering Europe’s AI Revolution

Scaleway, a subsidiary of iliad Group, a major European telecoms player, is doing its part to kick-start that second wave in Europe, offering cloud credits for access to its AI supercomputer cluster, which packs 1,016 NVIDIA H100 Tensor Core GPUs.

As a regional cloud service provider, Scaleway also provides sovereign infrastructure that ensures access and compliance with EU data protection laws, which is critical for businesses with a European footprint.

Regional members of the NVIDIA Inception program, which provides development assistance to startups, will also be able to access NVIDIA AI Enterprise software on Scaleway Marketplace.

The software includes the NVIDIA NeMo framework and pretrained models for building LLMs, NVIDIA RAPIDS for accelerated data science and NVIDIA Triton Inference Server and NVIDIA TensorRT-LLM for boosting inference.

Revolutionizing AI With Supercomputing Prowess

Recapping a month packed with announcements, Huang explained how NVIDIA is rapidly advancing high performance computing and AI worldwide to provide the infrastructure needed to power this second wave.

These systems are, in effect,  “supercomputers,” Huang said, with AI systems now among the world’s most powerful.

They include Scaleway’s newly available Nabuchodonosor supercomputer, or “Nabu,” an NVIDIA DGX SuperPOD with 127 NVIDIA DGX H100 systems, which will help startups in France and across Europe scale up AI workloads.

“As you know the Scaleway system that we brought online, Nabu, is not your normal computer,” Huang said. “In every single way, it’s a supercomputer.”

Such systems are underpinning powerful new services.

Earlier this week, NVIDIA announced an AI Foundry service on Microsoft Azure, aimed at accelerating the development of customized generative AI applications.

Huang highlighted NVIDIA AI foundry’s appeal to a diverse user base, including established enterprises such as Amdocs, Getty Images, SAP and ServiceNow.

Huang noted that JUPITER, to be hosted at the Jülich facility, in Germany, and poised to be Europe’s premier exascale AI supercomputer, will run on 24,000 NVIDIA GH200 Grace Hopper Superchips, offering unparalleled computational capacity for diverse AI tasks and simulations.

Huang touched on NVIDIA’s just-announced HGX H200 AI computing platform, built on NVIDIA’s Hopper architecture and featuring the H200 Tensor Core GPU. Set for release in Q2 of 2024, it promises to redefine industry standards.

He also detailed NVIDIA’s strategy to develop ‘AI factories,’ advanced data centers that power diverse applications across industries, including electric vehicles, robotics, and generative AI services.

Open Source

Finally, Durand asked Huang about the role of open source and open science in AI.

Huang said he’s a “huge fan” of open source. “Let’s acknowledge that without open source, how would AI have made the tremendous progress it has over the last decade,” Huang said.

“And so the ability for open source to energize the vibrancy and pull in the research and pull in the engagement of every startup, every researcher, every industry is really quite vital,” Huang said. “And you’re seeing it play out just presently, now going forward.”

Friday’s fireside conversation was part of Scaleway’s ai-PULSE conference, showcasing the latest AI trends and innovations. To learn more, visit https://www.ai-pulse.eu/.

Europe’s startup ecosystem is getting a boost of accelerated computing for generative AI.

NVIDIA and cloud service provider (CSP) Scaleway are working together to deliver access to GPUs, NVIDIA AI Enterprise software, and services for turbocharging large language models (LLMs) and generative AI development for European startups.

Scaleway, a subsidiary of French telecommunications provider iliad Group, is offering cloud credits for access to its AI supercomputer cluster, which packs 1,016 NVIDIA H100 Tensor Core GPUs. As a regional CSP, Scaleway also provides sovereign infrastructure that ensures access and compliance with EU data protection laws — critical to businesses with a European footprint.

Sovereign Cloud, Generative AI 

Complying with regulations governing how data and metadata can be stored in cloud computing is critical. When doing business in Europe, U.S. companies, for example, need to comply with EU regulations on sovereignty to secure data against access from foreign adversaries or entities. Noncompliance risks data vulnerabilities, financial penalties and legal consequences.

Regional CSPs like Scaleway provide a strategic path forward for companies to do business in Europe with a sovereign infrastructure. iliad Group’s data centers, where Scaleway operates, are fortified by compliance certifications that ensure data security, covering key aspects like healthcare, public safety, governance and public service activities.

Delivering Sovereign Accelerated Computing 

NVIDIA is working with Scaleway to expand access to sovereign accelerated computing in the EU, enabling companies to deploy AI applications and scale up faster.   

Through the NVIDIA Inception program, startups already relying on the sovereign cloud computing capabilities of Scaleway’s NVIDIA-accelerated infrastructure include Hugging Face, with more to come. Inception is a free global program that provides technical guidance, training, discounts and networking opportunities.

Inception member Hugging Face, based in New York and with operations in France, creates tools and resources to help developers build, deploy and train AI models.

“AI is the new way of building technology, and making the fastest AI accelerators accessible within regional clouds is key to democratizing AI across the world, enabling enterprises and startups to build the experiences of tomorrow,” said Jeff Boudier, head of product at Hugging Face. “I’m really excited that selected French startups will be able to access NVIDIA H100 GPUs in Scaleway’s cluster through the new startup program Scaleway and Hugging Face just announced with Meta and Station F.”

H100 and NVIDIA AI to Scale 

Scaleway’s newly available Nabuchodonosor supercomputer, an NVIDIA DGX SuperPOD with 127 NVIDIA DGX H100 systems, will help startups in France and across Europe scale up AI workloads.

Regional Inception members will also be able to access NVIDIA AI Enterprise software on Scaleway Marketplace, including the NVIDIA NeMo framework and pretrained models for building LLMs, NVIDIA RAPIDS for accelerated data science, and NVIDIA Triton Inference Server and NVIDIA TensorRT-LLM for boosting inference.

NVIDIA Inception Services on Tap

NVIDIA Inception has more than 4,000 members across Europe. Member companies of Scaleway’s own startup program are eligible to join Inception for benefits and resources. Scaleway is earmarking companies to fast-track for Inception membership.

Inception members gain access to cloud computing credits, NVIDIA Deep Learning Institute courses, technology experts, preferred pricing on hardware and software, guidance on the latest software development kits and AI frameworks, as well as opportunities for matchmaking with investors.