Posts in category: nVidia AI

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.

How do you train an AI to understand clinical language with less clinical data? Train another AI to synthesize training data.

Artificial intelligence is changing the way medicine is done, and is increasingly being used in all sorts of clinical tasks.

This is fueled by generative AI and models like GatorTronGPT, a generative language model trained on the University of Florida’s HiPerGator AI supercomputer and detailed in a paper published in Nature Digital Medicine Thursday.

GatorTronGPT joins a growing number of large language models (LLMs) trained on clinical data. Researchers trained the model using the GPT-3 framework, also used by ChatGPT.

They used a massive corpus of 277 billion words for this purpose. The training corpora included 82 billion words from de-identified clinical notes and 195 billion words from various English texts.

But there’s a twist: The research team also used GatorTronGPT to generate a synthetic clinical text corpus with over 20 billion words of synthetic clinical text, with carefully prepared prompts. The synthetic clinical text focuses on clinical factors and reads just like real clinical notes written by doctors.

This synthetic data was then used to train a BERT-based model called GatorTron-S.

In a comparative evaluation, GatorTron-S exhibited remarkable performance on clinical natural language understanding tasks like clinical concept extraction and medical relation extraction, beating the records set by the original BERT-based model, GatorTron-OG, which was trained on the 82-billion-word clinical dataset.

More impressively, it was able to do so using less data.

Both GatorTron-OG and GatorTron-S models were trained on 560 NVIDIA A100 Tensor Core GPUs running NVIDIA’s Megatron-LM package on the University of Florida’s HiPerGator supercomputer. Technology from the Megatron LM framework used in the project has since been incorporated with the NVIDIA NeMo framework, which has been central to more recent work on GatorTronGPT.

Using synthetic data created by LLMs addresses several challenges. LLMs require vast amounts of data, and there’s a limited availability of quality medical data.

In addition, synthetic data allows for model training that complies with medical privacy regulations, such as HIPAA.

The work with GatorTronGPT is just the latest example of how LLMs — which exploded onto the scene last year with the rapid adoption of ChatGPT — can be tailored to assist in a growing number of fields.

It’s also an example of the advances made possible by new AI techniques powered by accelerated computing.

The GatorTronGPT effort is the latest result of an ambitious collaboration announced in 2020, when the University of Florida and NVIDIA unveiled plans to erect the world’s fastest AI supercomputer in academia.

This initiative was driven by a $50 million gift, a fusion of contributions from NVIDIA founder Chris Malachowsky and NVIDIA itself.

Using AI to train more AI is just one example of HiPerGator’s impact, with the supercomputer promising to power more innovations in medical sciences and across disciplines throughout the University of Florida system.

Human analysts can no longer effectively defend against the increasing speed and complexity of cybersecurity attacks. The amount of data is simply too large to screen manually.

Generative AI, the most transformative tool of our time, enables a kind of digital jiu jitsu. It lets companies shift the force of data that threatens to overwhelm them into a force that makes their defenses stronger.

Business leaders seem ready for the opportunity at hand. In a recent survey, CEOs said cybersecurity is one of their top three concerns, and they see generative AI as a lead technology that will deliver competitive advantages.

Generative AI brings both risks and benefits. An earlier blog outlined six steps to start the process of securing enterprise AI.

Here are three ways generative AI can bolster cybersecurity.

Begin With Developers

First, give developers a security copilot.

Everyone plays a role in security, but not everyone is a security expert. So, this is one of the most strategic places to begin.

The best place to start bolstering security is on the front end, where developers are writing software. An AI-powered assistant, trained as a security expert, can help them ensure their code follows best practices in security.

The AI software assistant can get smarter every day if it’s fed previously reviewed code. It can learn from prior work to help guide developers on best practices.

To give users a leg up, NVIDIA is creating a workflow for building such co-pilots or chatbots. This particular workflow uses components from NVIDIA NeMo, a framework for building and customizing large language models.

Whether users customize their own models or use a commercial service, a security assistant is just the first step in applying generative AI to cybersecurity.

An Agent to Analyze Vulnerabilities

Second, let generative AI help navigate the sea of known software vulnerabilities.

At any moment, companies must choose among thousands of patches to mitigate known exploits. That’s because every piece of code can have roots in dozens if not thousands of different software branches and open-source projects.

An LLM focused on vulnerability analysis can help prioritize which patches a company should implement first. It’s a particularly powerful security assistant because it reads all the software libraries a company uses as well as its policies on the features and APIs it supports.

To test this concept, NVIDIA built a pipeline to analyze software containers for vulnerabilities. The agent identified areas that needed patching with high accuracy, speeding the work of human analysts up to 4x.

The takeaway is clear. It’s time to enlist generative AI as a first responder in vulnerability analysis.

Fill the Data Gap

Finally, use LLMs to help fill the growing data gap in cybersecurity.

Users rarely share information about data breaches because they’re so sensitive. That makes it difficult to anticipate exploits.

Enter LLMs. Generative AI models can create synthetic data to simulate never-before-seen attack patterns. Such synthetic data can also fill gaps in training data so machine-learning systems learn how to defend against exploits before they happen.

Staging Safe Simulations

Don’t wait for attackers to demonstrate what’s possible. Create safe simulations to learn how they might try to penetrate corporate defenses.

This kind of proactive defense is the hallmark of a strong security program. Adversaries are already using generative AI in their attacks. It’s time users harness this powerful technology for cybersecurity defense.

To show what’s possible, another AI workflow uses generative AI to defend against spear phishing — the carefully targeted bogus emails that cost companies an estimated $2.4 billion in 2021 alone.

This workflow generated synthetic emails to make sure it had plenty of good examples of spear phishing messages. The AI model trained on that data learned to understand the intent of incoming emails through natural language processing capabilities in NVIDIA Morpheus, a framework for AI-powered cybersecurity.

The resulting model caught 21% more spear phishing emails than existing tools. Check out our developer blog or watch the video below to learn more.

Wherever users choose to start this work, automation is crucial, given the shortage of cybersecurity experts and the thousands upon thousands of users and use cases that companies need to protect.

These three tools — software assistants, virtual vulnerability analysts and synthetic data simulations — are great starting points for applying generative AI to a security journey that continues every day.

But this is just the beginning. Companies need to integrate generative AI into all layers of their defenses.

Attend a webinar for more details on how to get started.

Editor’s note: This post is part of Into the Omniverse, a series focused on how artists, developers and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse.

In 3D art and design, efficient workflows are essential for quickly bringing creative visions to life.

Universal Scene Description, aka OpenUSD, is a framework that enhances these workflows by providing a unified, extensible ecosystem for describing, composing, simulating and collaborating within 3D worlds. OpenUSD is a key technology in Autodesk’s suite of products and solutions, across media and entertainment; architecture, engineering and construction; and product design and manufacturing.

Unveiled at the AU 2023 conference this week, the latest OpenUSD updates to Autodesk Maya enable artists and technical professionals to create and manipulate OpenUSD assets with greater control and efficiency, while also ensuring more efficient and accurate 3D workflows.

Bridging the Digital and Real Worlds With Maya and OpenUSD

Many creators are using Maya and OpenUSD to propel their 3D workflows.

Karol Osinski is a 3D artist at S20M, an architectural and design firm that specializes in tackling unique, bold and elegant projects. When it comes to creating architectural visualizations, Osinski says the biggest challenge is matching the digital world to the real one.

Using USD and creative tools such as Maya, SideFX Houdini and Epic Games’ Unreal Engine, Osinski creates high-quality visuals for clients while accelerating his architectural workflows.

Osinski’s panoramic view from the 20th floor terrace in the Upper East Side

“OpenUSD provides the possibility of bridging different tools like never before,” said Osinski. “I love how accessible USD is for first-time users and how it opens opportunities to make designs very complex.”

“Sir Wade” Neistadt, an animator and YouTube creator, aims to make animation and 3D education more accessible through his video tutorials and industry training. The first step of his unique animation workflow is to act out his animations on camera. He then translates them in Maya to begin his animation work before using USD to export them to other 3D software, including Blender, for finishing touches.

The making of Sir Wade’s VFX robot animation

3D artists at NVIDIA are also experiencing the power of Maya and OpenUSD. Technical specialist Lee Fraser led the “Ferret-Tale Project” to showcase character creation and animation workflows enabled by OpenUSD and generative AI.

To create the demo, Fraser and his team collaborated across 3D applications like Blender, Autodesk Maya and Reallusion Character Creator through OpenUSD Connectors. This allowed them to reduce the data prep and import and export time that’s usually required when working with multiple data sources.

“My favorite thing about using OpenUSD is not having to think about where the 3D files I use originated from,” Fraser said. “It was also easy to use USD layers to experiment with applying different animation clips with different characters.”

Members of the creative community joined a recent livestream to share their workflows using Autodesk tools, OpenUSD and NVIDIA Omniverse, a development platform for connecting and building OpenUSD-based tools and applications.

Whether adjusting lighting conditions in an environment or looking at building designs from the street view, designers in architecture, engineering, construction and operations are advancing their work with AI. Learn more by watching the replay:

Shaping the Future of 3D With More Efficient Workflows

AU 2023 attendees experienced how Autodesk is enhancing Maya with its new OpenUSD plug-in to provide additional practical workflows for various production processes. The software’s latest features include:

• Simplified asset sharing: Designers can now use relative paths when creating OpenUSD stages, allowing for easy asset sharing between different systems. This includes support for sublayers, references, payloads and textures.
• Enhanced control: Plug-in developers and technical directors can overwrite the default prim writers in Maya USD to gain complete control over their OpenUSD exports.

Plus, Autodesk introduced impressive capabilities to LookdevX in Maya, a look-development tool that lets users create OpenUSD shade graphs and custom materials in Maya. These new features include:

• Streamlined shader creation: Users can employ a unified shader workflow, replacing the need for multiple shaders. They can select their desired shader type within the parameters panel, with intuitive error messages guiding them to the correct selection.
• Efficient operations: Creators can copy, paste and duplicate shaders and materials using the Outliner and LookdevX tool sets, with the option to include or exclude connections.
• Seamless color management: LookdevX in Maya integrates with color managers in other digital content creation apps to ensure accurate color representation. Color management data is precisely embedded in USD files for accurate reading.
• Advanced graphing: Users can explore advanced graphing options with the integrated component workflow, supporting multichannel Extended Dynamic Range (EXR) workflows within USD, MaterialX or Arnold shading graphs.
• Efficient troubleshooting: Solo nodes enable faster look-development workflows and efficient graph troubleshooting. Users can inspect renders of upstream nodes, supporting both Autodesk Arnold and MaterialX graphs, including materials, shaders and compounds.

Access to default prim options in Maya UI

Get Plugged Into the World of OpenUSD

Anyone can build their own Omniverse extension or Connector to enhance their 3D workflows and tools. Explore the Omniverse ecosystem’s growing catalog of connections, extensions, foundation applications and third-party tools.

Autodesk and NVIDIA are founding members of the Alliance for OpenUSD (AOUSD), together strengthening an open future with USD. To learn more, explore the AOUSD forum and check out resources on OpenUSD.

Share your Autodesk Maya and Omniverse work through November as part of the #SeasonalArtChallenge. Use the hashtag to submit an autumn harvest-themed scene for a chance to be featured on the @NVIDIAStudio and @NVIDIAOmniverse social channels.

Get started with NVIDIA Omniverse by downloading the standard license free, or learn how Omniverse Enterprise can connect your team. 

Developers can check out these Omniverse resources to begin building on the platform. 

Stay up to date on the platform by subscribing to the newsletter and following NVIDIA Omniverse on Instagram, LinkedIn, Medium, Threads and Twitter.

For more, check out our forums, Discord server, Twitch and YouTube channels..

The fastest way to give the gift of cloud gaming starts this GFN Thursday: For a limited time, every six-month GeForce NOW Ultimate membership includes three months of PC Game Pass.

Also, the newest GeForce NOW app update is rolling out to members, including Xbox Game Syncing and more improvements.

Plus, take advantage of a heroic, new members-only Guild Wars 2 reward. It’s all topped off by support for 18 more games in the GeForce NOW library this week.

Give the Gift of Gaming

Unwrap the gift of gaming: For a limited time, gamers who sign up for the six-month GeForce NOW Ultimate membership will also receive three free months of PC Game Pass — a $30 value.

With it, Ultimate members can play a collection of high-quality Xbox PC titles with the power of a GeForce RTX 4080 rig in the cloud. Jump into the action in iconic franchises like Age of Empires, DOOM, Forza and more, with support for more titles added every GFN Thursday.

Seamlessly launch supported favorites across nearly any device at up to 4K and 120 frames per second or at up to 240 fps with NVIDIA Reflex technology in supported titles for lowest-latency streaming.

This special offer is only here for a limited time, so upgrade today.

Sync’d Up

With so many games ready to stream, it might be hard to decide what to play next. The latest GeForce NOW app update, currently rolling out to members, is here to help.

Members can now connect their Xbox accounts to GeForce NOW to sync the games they own to their GeForce NOW library. Game syncing lets members connect their digital game store accounts to GeForce NOW, so all of their supported games are part of their streaming library. Syncing an Xbox account will also add any supported titles a member has access to via PC Game Pass — perfect for members taking advantage of the latest Ultimate bundle.

The new update also adds benefits for Ubisoft+ subscribers. With a linked Ubisoft+ account, members can now launch supported Ubisoft+ games they already own from the GeForce NOW app, and the game will be automatically added to “My Library.” Get more details on Ubisoft account linking.

Version 2.0.58 also includes an expansion of the new game session diagnostic tools to help members ensure they’re streaming at optimal quality. It adds codec information to the in-stream statistics overlay and includes other miscellaneous bug fixes. The update should be available for all members soon.

A Heroic Offering

This week, members can receive Guild Wars 2 “Heroic Edition,” which includes a treasure trove of goodies, such as the base game, Legacy Armor, an 18-slot inventory expansion and four heroic Boosters. It’s the perfect way to jump into ArenaNet’s critically acclaimed, free-to-play, massively multiplayer online role-playing game.

It’s easy to get membership rewards for streaming games on the cloud. Visit the GeForce NOW Rewards portal and update the settings to receive special offers and in-game goodies.

Members can also sign up for the GeForce NOW newsletter, which includes reward notifications, by logging into their NVIDIA account and selecting “Preferences” from the header. Check the “Gaming & Entertainment” box and “GeForce NOW” under topic preferences.

Ready, Set, Go

The first downloadable content for Gearbox’s Remnant 2 arrives in the cloud. The Awakened King brings a new storyline, area, archetype and more to the dark fantasy co-op shooter — stream it today to experience the awakening of the One True King as he seeks revenge against all who oppose him.

Catch even more action with the 18 newly supported games in the cloud:

• Spirittea (New release on Steam, Nov. 13)
• KarmaZoo (New release on Steam, Nov. 14)
• Naheulbeuk’s Dungeon Master (New release on Steam, Nov. 15)
• Warhammer Age of Sigmar: Realms of Ruin (New release on Steam, Nov. 17)
• Arcana of Paradise —The Tower (Steam)
• Blazing Sails: Pirate Battle Royale (Epic Games Store)
• Disney Dreamlight Valley (Xbox, available on PC Game Pass)
• Hello Neighbor 2 (Xbox, available on PC Game Pass)
• Overcooked! 2 (Xbox, available on PC Game Pass)
• RoboCop: Rogue City (New release on Epic Games Store)
• Roboquest (Xbox, available on PC Game Pass)
• Rune Factory 4 Special (Xbox and available on PC Game Pass)
• Settlement Survival (Steam)
• SOULVARS (Steam)
• State of Decay: Year-One Survival Edition (Steam)
• The Wonderful One: After School Hero (Steam)
• Wolfenstein: The New Order (Xbox, available on PC Game Pass)
• Wolfenstein: The Old Blood (Steam, Epic Games Store, Xbox and available on PC Game Pass)

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

h̴e̴r̴e̴’̴s̴ soon’s the deal…

stay tuned

— NVIDIA GeForce NOW (@NVIDIAGFN) November 15, 2023

The telecommunications industry — the backbone of today’s interconnected world — is valued at a staggering $1.7 trillion globally, according to IDC.

It’s a massive operation, as telcos process hundreds of petabytes of data in their networks each day. That magnitude is only increasing, as the total amount of data transacted globally is forecast to grow to more than 180 zettabytes by 2025.

To meet this demand for data processing and analysis, telcos are turning to generative AI, which is improving efficiency and productivity across industries.

NVIDIA announced an AI foundry service — a collection of NVIDIA AI Foundation Models, NVIDIA NeMo framework and tools, and NVIDIA DGX Cloud AI supercomputing and services — that gives enterprises an end-to-end solution for creating and optimizing custom generative AI models.

Using the AI foundry service, Amdocs, a leading provider of software and services for communications and media providers, will optimize enterprise-grade large language models for the telco and media industries to efficiently deploy generative AI use cases across their businesses, from customer experiences to network operations and provisioning. The LLMs will run on NVIDIA accelerated computing as part of the Amdocs amAIz framework.

The collaboration builds on the previously announced Amdocs-Microsoft partnership, enabling service providers to adopt these applications in secure, trusted environments, including on premises and in the cloud.

Custom Models for Custom Results

While preliminary applications of generative AI used broad datasets, enterprises have become increasingly focused on developing custom models to perform specialized, industry-specific skills.

By training models on proprietary data, telcos can deliver tailored solutions that produce more accurate results for their use cases.

To simplify the development, tuning and deployment of such custom models, Amdocs is integrating the new NVIDIA AI foundry service.

Equipped with these new generative AI capabilities — including guardrail features — service providers can enhance performance, optimize resource utilization and flexibly scale to meet future needs.

Amdocs’ Global Telco Ecosystem Footprint

More than 350 of the world’s leading telecom and media companies across 90 countries take advantage of Amdocs services each day, including 27 of the world’s top 30 service providers, according to OMDIA.⁽¹⁾ Powering more than 1.7 billion daily digital journeys, Amdocs platforms impact more than 3 billion people around the world.

NVIDIA and Amdocs are exploring several generative AI use cases to simplify and improve operations by providing secure, cost-effective, and high-performance generative AI capabilities.

Initial use cases span customer care, including accelerating resolution of customer inquiries by drawing information from across company data.

And in network operations, the companies are exploring ways to generate solutions to address configuration, coverage or performance issues as they arise.

⁽¹⁾ Source: OMDIA 2022 revenue estimates, excludes China.

Stay up to date on the latest NVIDIA generative AI news and technologies and Microsoft Azure AI News.

Automotive companies are transforming every phase of their product lifecycle — evolving their primarily physical, manual processes into software-driven, AI-enhanced digital systems.

To help them save costs and reduce lead times, NVIDIA is announcing two new simulation engines on Omniverse Cloud: the virtual factory simulation engine and the autonomous vehicle (AV) simulation engine.

Omniverse Cloud, a platform-as-a-service for developing and deploying applications for industrial digitalization, is hosted on Microsoft Azure. This one-stop shop enables automakers worldwide to unify digitalization across their core product and business processes. It allows enterprises to achieve faster production and more efficient operations, improving time to market and enhancing sustainability initiatives.

For design, engineering and manufacturing teams, digitalization streamlines their work, converting once primarily manual industrial processes into efficient systems for concept and styling; AV development, testing and validation; and factory planning.

Virtual Factory Simulation Engine

The Omniverse Cloud virtual factory simulation engine is a collection of customizable developer applications and services that enable factory planning teams to connect large-scale industrial datasets while collaborating, navigating and reviewing them in real time.

Design teams working with 3D data can assemble virtual factories and share their work with thousands of planners who can view, annotate and update the full-fidelity factory dataset from lightweight devices. By simulating virtual factories on Omniverse Cloud, automakers can increase throughput and production quality while saving years of effort and millions of dollars that would result from making changes once construction is underway.

On Omniverse Cloud, teams can create interoperability between existing software applications such as Autodesk Factory Planning, which supports the entire lifecycle for building, mechanical, electrical, and plumbing and factory lines, as well as Siemens’ NX, Process Simulate and Teamcenter Visualization software and the JT file format. They can share knowledge and data in real time in live, virtual factory reviews across 2D devices or in extended reality.

T-Systems, a leading IT solutions provider for Europe’s largest automotive manufacturers, is building and deploying a custom virtual factory application that its customers can deploy in Omniverse Cloud.

SoftServe, an elite member of the NVIDIA Service Delivery Partner program, is also developing custom factory simulation and visualization solutions on this Omniverse Cloud engine, covering factory design, production planning and control.

AV Simulation Engine

The AV simulation engine is a service that delivers physically based sensor simulation, enabling AV and robotics developers to run autonomous systems in a closed-loop virtual environment.

The next generation of AV architectures will be built on large, unified AI models that combine layers of the vehicle stack, including perception, planning and control. Such new architectures call for an integrated approach to development.

With previous architectures, developers could train and test these layers independently, as they were governed by different models. For example, simulation could be used to develop a vehicle’s planning and control system, which only needs basic information about objects in a scene — such as the speed and distance of surrounding vehicles — while perception networks could be trained and tested on recorded sensor data.

However, using simulation to develop an advanced unified AV architecture requires sensor data as the input. For a simulator to be effective, it must be able to simulate vehicle sensors, such as cameras, radars and lidars, with high fidelity.

To address this challenge, NVIDIA is bringing state-of-the-art sensor simulation pipelines used in DRIVE Sim and Isaac Sim to Omniverse Cloud on Microsoft Azure.

Omniverse Cloud sensor simulation provides AV and robotics workflows with high-fidelity, physically based simulation for cameras, radars, lidars and other types of sensors. It can be connected to existing simulation applications, whether developed in-house or provided by a third party, via Omniverse Cloud application programming interfaces for integration into workflows.

Fast Track to Digitalization

The factory simulation engine is now available to customers via an Omniverse Cloud enterprise private offer through the Azure Marketplace, which provides access to NVIDIA OVX systems and fully managed Omniverse software, reference applications and workflows. The sensor simulation engine is coming soon.

Enterprises can now also deploy Omniverse Enterprise on new optimized Azure virtual machines.

Learn more on NVIDIA’s Microsoft Ignite showcase page.

As NVIDIA continues to collaborate with Microsoft to build state-of-the-art AI infrastructure, Microsoft is introducing additional H100-based virtual machines to Microsoft Azure to accelerate demanding AI workloads.

At its Ignite conference in Seattle today, Microsoft announced its new NC H100 v5 VM series for Azure, the industry’s first cloud instances featuring NVIDIA H100 NVL GPUs.

This offering brings together a pair of PCIe-based H100 GPUs connected via NVIDIA NVLink, with nearly 4 petaflops of AI compute and 188GB of faster HBM3 memory. The NVIDIA H100 NVL GPU can deliver up to 12x higher performance on GPT-3 175B over the previous generation and is ideal for inference and mainstream training workloads.

Additionally, Microsoft announced plans to add the NVIDIA H200 Tensor Core GPU to its Azure fleet next year to support larger model inferencing with no increase in latency. This new offering is purpose-built to accelerate the largest AI workloads, including LLMs and generative AI models.

The H200 GPU brings dramatic increases both in memory capacity and bandwidth using the latest-generation HBM3e memory. Compared to the H100, this new GPU will offer 141GB of HBM3e memory (1.8x more) and 4.8 TB/s of peak memory bandwidth (a 1.4x increase).

Cloud Computing Gets Confidential

Further expanding availability of NVIDIA-accelerated generative AI computing for Azure customers, Microsoft announced another NVIDIA-powered instance: the NCC H100 v5.

These Azure confidential VMs with NVIDIA H100 Tensor Core GPUs allow customers to protect the confidentiality and integrity of their data and applications in use, in memory, while accessing the unsurpassed acceleration of H100 GPUs. These GPU-enhanced confidential VMs will be coming soon to private preview.

To learn more about the new confidential VMs with NVIDIA H100 Tensor Core GPUs, and sign up for the preview, read the blog.

Learn more about NVIDIA-powered Azure instances on the GPU VM information page.

Today’s landscape of free, open-source large language models (LLMs) is like an all-you-can-eat buffet for enterprises. This abundance can be overwhelming for developers building custom generative AI applications, as they need to navigate unique project and business requirements, including compatibility, security and the data used to train the models.

NVIDIA AI Foundation Models — a curated collection of enterprise-grade pretrained models — give developers a running start for bringing custom generative AI to their enterprise applications.

NVIDIA-Optimized Foundation Models Speed Up Innovation 

NVIDIA AI Foundation Models can be experienced through a simple user interface or API, directly from a browser. Additionally, these models can be accessed from NVIDIA AI Foundation Endpoints to test model performance from within their enterprise applications.

Available models include leading community models such as Llama 2, Stable Diffusion XL and Mistral, which are formatted to help developers streamline customization with proprietary data. Additionally, models have been optimized with NVIDIA TensorRT-LLM to deliver the highest throughput and lowest latency and to run at scale on any NVIDIA GPU-accelerated stack. For instance, the Llama 2 model optimized with TensorRT-LLM runs nearly 2x faster on NVIDIA H100.

The new NVIDIA family of Nemotron-3 8B foundation models supports the creation of today’s most advanced enterprise chat and Q&A applications for a broad range of industries, including healthcare, telecommunications and financial services.

The models are a starting point for customers building secure, production-ready generative AI applications, are trained on responsibly sourced datasets and operate at comparable performance to much larger models. This makes them ideal for enterprise deployments.

Multilingual capabilities are a key differentiator of the Nemotron-3 8B models. Out of the box, the models are proficient in over 50 languages, including English, German, Russian, Spanish, French, Japanese, Chinese, Korean, Italian and Dutch.

Fast-Track Customization to Deployment

Enterprises leveraging generative AI across business functions need an AI foundry to customize models for their unique applications. NVIDIA’s AI foundry features three elements — NVIDIA AI Foundation Models, NVIDIA NeMo framework and tools, and NVIDIA DGX Cloud AI supercomputing services. Together, these provide an end-to-end enterprise offering for creating custom generative AI models.

Importantly, enterprises own their customized models and can deploy them virtually anywhere on accelerated computing with enterprise-grade security, stability and support using NVIDIA AI Enterprise software.

NVIDIA AI Foundation Models are freely available to experiment with now on the NVIDIA NGC catalog and Hugging Face, and are also hosted in the Microsoft Azure AI model catalog.