Posts in category: nVidia AI

NVIDIA is bringing OpenUSD-based Omniverse enterprise digital twins to the Apple Vision Pro.

Announced today at NVIDIA GTC, a new software framework built on Omniverse Cloud APIs, or application programming interfaces, lets developers easily send their Universal Scene Description (OpenUSD) industrial scenes from their content creation applications to the NVIDIA Graphics Delivery Network (GDN), a global network of graphics-ready data centers that can stream advanced 3D experiences to Apple Vision Pro.

In a demo unveiled at the global AI conference, NVIDIA presented an interactive, physically accurate digital twin of a car streamed in full fidelity to Apple Vision Pro’s high-resolution displays.

The demo featured a designer wearing the Vision Pro, using a car configurator application developed by CGI studio Katana on the Omniverse platform. The designer toggles through paint and trim options and even enters the vehicle — leveraging the power of spatial computing by blending 3D photorealistic environments with the physical world.

Bringing the Power of RTX Enterprise Cloud Rendering to Spatial Computing

Spatial computing has emerged as a powerful technology for delivering immersive experiences and seamless interactions between people, products, processes and physical spaces. Industrial enterprise use cases require incredibly high-resolution displays and powerful sensors operating at high frame rates to make manufacturing experiences true to reality.

This new Omniverse-based workflow combines Apple Vision Pro groundbreaking high-resolution displays with NVIDIA’s powerful RTX cloud rendering to deliver spatial computing experiences with just the device and an internet connection.

This cloud-based approach allows real-time physically based renderings to be streamed seamlessly to Apple Vision Pro, delivering high-fidelity visuals without compromising details of the massive, engineering fidelity datasets.

“The breakthrough ultra-high-resolution displays of Apple Vision Pro, combined with photorealistic rendering of OpenUSD content streamed from NVIDIA accelerated computing, unlocks an incredible opportunity for the advancement of immersive experiences,” said Mike Rockwell, vice president of the Vision Products Group at Apple. “Spatial computing will redefine how designers and developers build captivating digital content, driving a new era of creativity and engagement.”

“Apple Vision Pro is the first untethered device which allows for enterprise customers to realize their work without compromise,” said Rev Lebaredian, vice president of simulation at NVIDIA. “We look forward to our customers having access to these amazing tools.”

The workflow also introduces hybrid rendering, a groundbreaking technique that combines local and remote rendering on the device. Users can render fully interactive experiences in a single application from Apple’s native SwiftUI and Reality Kit with the Omniverse RTX Renderer streaming from GDN.

NVIDIA GDN, available in over 130 countries, taps NVIDIA’s global cloud-to-edge streaming infrastructure to deliver smooth, high-fidelity, interactive experiences. By moving heavy compute tasks to GDN, users can tackle the most demanding rendering use cases, no matter the size or complexity of the dataset.

Enhancing Spatial Computing Workloads Across Use Cases

The Omniverse-based workflow showed potential for a wide range of use cases. For example, designers could use the technology to see their 3D data in full fidelity, with no loss in quality or model decimation. This means designers can interact with trustworthy simulations that look and behave like the real physical product. This also opens new channels and opportunities for e-commerce experiences.

In industrial settings, factory planners can view and interact with their full engineering factory datasets, letting them optimize their workflows and identify potential bottlenecks.

For developers and independent software vendors, NVIDIA is building the capabilities that would allow them to use the native tools on Apple Vision Pro to seamlessly interact with existing data in their applications.

Learn more about NVIDIA Omniverse and GDN.

Generative AI and digital twins are changing the way companies in multiple industries design, manufacture and operate their products.

Siemens, a leading technology company for automation, digitalization and sustainability, announced today at NVIDIA GTC that it is expanding its partnership with NVIDIA by adopting new NVIDIA Omniverse Cloud APIs, or application programming interfaces, with its Siemens Xcelerator platform applications, starting with Teamcenter X. Teamcenter X is Siemens’ industry-leading cloud-based product lifecycle management (PLM) software.

NVIDIA Omniverse is a platform of APIs and services based on Universal Scene Description (OpenUSD) that enables developers to build generative AI-powered tools, applications and services for industrial digital twins and automation.

Enterprises of all sizes depend on Teamcenter software, part of the Siemens Xcelerator platform, to develop and deliver products at scale. By connecting NVIDIA Omniverse with Teamcenter X, Siemens will be able to provide engineering teams with the ability to make their physics-based digital twins more immersive and photorealistic, helping eliminate workflow waste and reduce errors.

Through the use of Omniverse APIs, workflows such as applying materials, lighting environments and other supporting scenery assets in physically based renderings will be dramatically accelerated using generative AI.

AI integrations will also allow engineering data to be contextualized as it would appear in the real world, allowing other stakeholders — from sales and marketing teams to decision-makers and customers — to benefit from deeper insight and understanding of real-world product appearance.

Unifying and Visualizing Complex Industrial Datasets

Traditionally, companies have relied heavily on physical prototypes and costly modifications to complete large-scale industrial projects and build complex, connected products. That approach is expensive and error-prone, limits innovation and slows time to market.

By connecting Omniverse Cloud APIs to the Xcelerator platform, Siemens will enable its customers to enhance their digital twins with physically based rendering, helping supercharge industrial-scale design and manufacturing projects. With the ability to connect generative AI APIs or agents, users can effortlessly generate 3D objects or high-dynamic range image backgrounds to view their assets in context.

This means that companies like HD Hyundai, a leader in sustainable ship manufacturing, can unify and visualize complex engineering projects directly within Teamcenter X. At NVIDIA GTC, Siemens and NVIDIA demonstrated how HD Hyundai could use the software to visualize digital twins of liquified natural gas carriers, which can comprise over 7 million discrete parts, helping validate their product before moving to production.

Interoperable, photoreal and physics-based digital twins like these accelerate engineering collaboration and allow customers to minimize workflow waste, save time and costs, and reduce risk of manufacturing defects.

Combining Digital and Physical Worlds With Omniverse APIs

Omniverse Cloud APIs enable data interoperability and physically based rendering for industrial-scale design and manufacturing projects in Teamcenter X. This starts with a real-time, embedded, photoreal viewport powered by the USD Render and USD Write APIs, which engineers can use to interactively navigate, edit and iterate on a shared model of their live data.

The USD Query API lets Teamcenter X users navigate and interact with physically accurate scenes, while the USD Notify API automatically provides real-time design and scene updates. To facilitate cloud-based collaboration and data exchange, Teamcenter X will leverage the Omniverse Channel API to establish a secure connection between multiple users across devices.

In the future, Siemens plans to bring NVIDIA accelerated computing, generative AI and Omniverse to more of its Siemens Xcelerator portfolio.

Learn more about NVIDIA Omniverse, Siemens Xcelerator and the partnership.

Get started with NVIDIA Omniverse, access OpenUSD resources, and learn how Omniverse Enterprise can connect your team. Stay up to date on Instagram, Medium and Twitter. For more, join the Omniverse community on the  forums, Discord server, Twitch and YouTube channels.

While simulation is critical for training, testing and deploying autonomy,  achieving real-world fidelity is incredibly challenging.

It requires accurate modeling of the physics and behavior of an autonomous system’s sensors and surroundings.

Designed to address this challenge by delivering large-scale, high-fidelity sensor simulation, Omniverse Cloud APIs, announced today at NVIDIA GTC, are poised to accelerate the path to autonomy. They bring together a rich ecosystem of simulation tools, applications and sensors.

The application programming interfaces address the critical need for high-fidelity sensor simulations to safely explore the myriad real-world scenarios autonomous systems will encounter.

In addition, the Omniverse Cloud platform offers application developers access to a range of powerful Universal Scene Description (OpenUSD), RTX and generative AI-enabled service-level cloud APIs to bring interoperability and physically based rendering to next-generation tools.

Simulation Key to Unlocking New Levels of Safety

As demand increases for robots, AVs, and other AI systems, developers are seeking to accelerate their workflows. Sensor data powers these systems’ perception capabilities, enabling them to comprehend their environment and make informed decisions in real time.

Traditionally, developers have used real-world data for training, testing and validation.

However, these methods are limited in covering rare scenarios or data that can’t be captured in the real world. Sensor simulation provides a seamless way to effectively test countless “what if” scenarios and diverse environmental conditions.

With Omniverse Cloud APIs, developers can enhance the workflows they’re already using with high-fidelity sensor simulation to tackle the challenge of developing full-stack autonomy.

This not only streamlines the development process but also lowers the barriers to entry for companies of virtually all sizes developing autonomous machines.

The Ecosystem Advantage

By bringing together an expansive ecosystem of simulators, verification and validation (V&V) tools, content and sensor developers, the Omniverse Cloud APIs enable a universal environment for AI system development.

Developers and software vendors such as CARLA, MathWorks, MITRE, Foretellix and Voxel51 underscore the broad appeal of these APIs in autonomous vehicles.

CARLA is an open-source AV simulator used by more than 100,000 developers. With Omniverse Cloud APIs, CARLA users can enhance their existing workflows with high-fidelity sensor simulation.

Similarly, MITRE, a nonprofit that operates federally funded R&D centers and is dedicated to improving safety in technology, is building a Digital Proving Ground for the AV industry to validate self-driving solutions. The DPG will use the Omniverse APIs to enable core sensor simulation capabilities for their developers.

MathWorks and Foretellix provide critical simulation tools for authoring, executing, monitoring, and debugging of testing scenarios. As the GTC demo showed, combining such simulation and test automation tools with the APIs forms a powerful test environment for AV development. On the showfloor, Foretellix is showing an in-depth look at this solution in Booth 630.

And, by integrating the APIs with Voxel51’s FiftyOne platform, developers can easily visualize and organize ground-truth data generated in simulation for streamlined training and testing.

Leading industrial-sensor solution provider SICK AG is working on integrating these APIs in its sensor development process to reduce the number of physical prototypes, iterate quickly on design modifications and validate the eventual performance. These validated sensor models can eventually be used by autonomous systems developers in their applications.

Developers will also have access to sensor models from a variety of manufacturers, including lidar makers Hesai, Innoviz Technologies, Luminar, MicroVision, Robosense, and Seyond, visual sensor suppliers OMNIVISION, onsemi, and Sony Semiconductor Solutions, and Continental, FORVIA HELLA, and Arbe for radar.

Additionally, AI/ML developers can call on these APIs to generate large and diverse sets of synthetic data — critical input for training and validating perception models that power these autonomous systems.

Empowering Developers and Accelerating Innovation

By reducing the traditional barriers to high-fidelity sensor simulation, NVIDIA Omniverse Cloud APIs empower developers to address complex AI problems without significant infrastructure overhauls.

This democratization of access to advanced simulation tools promises to accelerate innovation, allowing developers to quickly adapt to and integrate the latest technological advancements into their testing and development processes.

Apply here for early access to Omniverse Cloud APIs.

Get started with NVIDIA Omniverse, access OpenUSD resources, and learn how Omniverse Enterprise can connect your team. Stay up to date on Instagram, Medium and Twitter. For more, join the Omniverse community on the  forums, Discord server, Twitch and YouTube channels.

Real-time AI is helping with the heavy lifting in manufacturing, factory logistics and robotics.

In such industries — often involving bulky products, expensive equipment, cobot environments and logistically complex facilities — a simulation-first approach is ushering in the next phase of automation.

NVIDIA founder and CEO Jensen Huang today demonstrated in his GTC keynote how developers can use digital twins to develop, test and refine their large-scale, real-time AIs entirely in simulation before rolling them out in industrial infrastructure, saving significant time and cost.

NVIDIA Omniverse, Metropolis, Isaac and cuOpt interact in AI gyms where developers can train AI agents to help robots and humans navigate unpredictable or complex events.

In the demo, a digital twin of a 100,000-square-foot warehouse — built using the NVIDIA Omniverse platform for developing and connecting OpenUSD applications — operates as a simulation environment for dozens of digital workers and multiple autonomous mobile robots (AMRs), vision AI agents and sensors.

Each AMR, running the NVIDIA Isaac Perceptor multi-sensor stack, processes visual information from six sensors, all simulated in the digital twin.

At the same time, the NVIDIA Metropolis platform for vision AI creates a single centralized map of worker activity across the entire warehouse, fusing together data from 100 simulated ceiling-mounted camera streams with multi-camera tracking. This centralized occupancy map helps inform optimal AMR routes calculated by the NVIDIA cuOpt engine for solving complex routing problems.

cuOpt, a record-breaking optimization AI microservice, solves complex routing problems with multiple constraints using GPU-accelerated evolutionary algorithms.

All of this happens in real time, while Isaac Mission Control coordinates the entire fleet using map data and route graphs from cuOpt to send and execute AMR commands.

An AI Gym for Industrial Digitalization

AI agents can assist in large-scale industrial environments by, for example, managing fleets of robots in a factory or identifying streamlined configurations for human-robot collaboration in supply chain distribution centers. To build these complex agents, developers need digital twins that function as AI gyms — physically accurate environments for AI evaluation, simulation and training.

Such software-in-the-loop AI testing enables AI agents and AMRs to adapt to real-world unpredictability.

In the demo, an incident occurs along an AMR’s planned route, blocking the path and preventing it from picking up a pallet. NVIDIA Metropolis updates an occupancy grid, mapping all humans, robots and objects in a single view. cuOpt then plans an optimal route, and the AMR responds accordingly to minimize downtime.

With Metropolis vision foundation models powering the NVIDIA Visual Insight Agent (VIA) framework, AI agents can be built to help operations teams answer questions like, “What situation occurred in aisle three of the factory?” And the generative AI-powered agent offers immediate insights such as, “Boxes fell from the shelves at 3:30 p.m., blocking the aisle.”

Developers can use the VIA framework to build AI agents capable of processing large amounts of live or archived videos and images with vision-language models — whether deployed at the edge or in the cloud. This new generation of visual AI agents will help nearly every industry summarize, search and extract actionable insights from video using natural language.

All of these AI functions can be enhanced through continuous, simulation-based training and are deployed as modular NVIDIA NIM inference microservices.

Learn more about the latest advancements in generative AI and industrial digitalization at NVIDIA GTC, a global AI conference running through Thursday, March 21, at the San Jose Convention Center and online.

NVIDIA’s AI platform is available to any forward-thinking business — and it’s easier to use than ever.

Launched today, NVIDIA AI Enterprise 5.0 includes NVIDIA microservices, downloadable software containers for deploying generative AI applications and accelerated computing. It’s available from leading cloud service providers, system builders and software vendors — and it’s in use at customers such as Uber.

“Our adoption of NVIDIA AI Enterprise inference software is important for meeting the high performance our users expect,” said Albert Greenberg, vice president of platform engineering at Uber. “Uber prides itself on being at the forefront of adopting and using the latest, most advanced AI innovations to deliver a customer service platform that sets the industry standard for effectiveness and excellence.”

Microservices Speed App Development

Developers are turning to microservices as an efficient way to build modern enterprise applications at a global scale. Working from a browser, they use cloud APIs, or application programming interfaces, to compose apps that can run on systems and serve users worldwide.

NVIDIA AI Enterprise 5.0 now includes a wide range of microservices — NVIDIA NIM for deploying AI models in production and the  NVIDIA CUDA-X collection of microservices which includes NVIDIA cuOpt.

NIM microservices optimize inference for dozens of popular AI models from NVIDIA and its partner ecosystem.

Powered by NVIDIA inference software — including Triton Inference Server, TensorRT, and TensorRT-LLM — NIM slashes deployment times from weeks to minutes. It provides security and manageability based on industry standards as well as compatibility with enterprise-grade management tools.

NVIDIA cuOpt is a GPU-accelerated AI microservice that’s set world records for route optimization and can empower dynamic decision-making that reduces cost, time and carbon footprint. It’s one of the CUDA-X microservices that help industries put AI into production.

More capabilities are in the works. For example, NVIDIA RAG LLM operator — now in early access and described in more detail here — will move co-pilots and other generative AI applications that use retrieval-augmented generation from pilot to production without rewriting any code.

NVIDIA microservices are being adopted by leading application and cybersecurity platform providers including CrowdStrike, SAP and ServiceNow.

More Tools and Features

Three other updates in version 5.0 are worth noting.

The platform now packs NVIDIA AI Workbench, a developer toolkit for quickly downloading, customizing, and running generative AI projects. The software is now generally available and supported with an NVIDIA AI Enterprise license.

Version 5.0 also now supports Red Hat OpenStack Platform, the environment most Fortune 500 companies use for creating private and public cloud services. Maintained by Red Hat, it provides developers a familiar option for building virtual computing environments. IBM Consulting will help customers deploy these new capabilities.

In addition, version 5.0 expands support to cover a wide range of the latest NVIDIA GPUs, networking hardware and virtualization software.

Available to Run Anywhere

The enhanced NVIDIA AI platform is easier to access than ever.

NIM and CUDA-X microservices and all the 5.0 features will be available soon on the AWS, Google Cloud, Microsoft Azure and Oracle Cloud marketplaces.

For those who prefer to run code in their own data centers, VMware Private AI Foundation with NVIDIA will support the software, so it can be deployed in the virtualized data centers of Broadcom’s customers.

Companies have the option of running NVIDIA AI Enterprise on Red Hat OpenShift, allowing them to deploy on bare-metal or virtualized environments. It’s also supported on Canonical’s Charmed Kubernetes as well as Ubuntu.

In addition, the AI platform will be part of the software available on HPE ProLiant servers from Hewlett Packard Enterprise (HPE). HPE’s enterprise computing solution for generative AI handles inference and model fine-tuning using NVIDIA AI Enterprise.

In addition, Anyscale, Dataiku and DataRobot — three leading providers of the software for managing machine learning operations — will support NIM on their platforms. They join an NVIDIA ecosystem of hundreds of MLOps partners, including Microsoft Azure Machine Learning, Dataloop AI, Domino Data Lab and Weights & Biases.

However they access it, NVIDIA AI Enterprise 5.0 users can benefit from software that’s secure, production-ready and optimized for performance. It can be flexibly deployed for applications in the data center, the cloud, on workstations or at the network’s edge.

NVIDIA AI Enterprise is available through leading system providers, including Cisco, Dell Technologies, HP, HPE, Lenovo and Supermicro.

Hear Success Stories at GTC

Users will share their experiences with the software at NVIDIA GTC, a global AI conference, running March 18-21 at the San Jose Convention Center.

For example, ServiceNow chief digital information officer Chris Bedi will speak on a panel about harnessing generative AI’s potential. In a separate talk, ServiceNow vice president of AI Products Jeremy Barnes will share on using NVIDIA AI Enterprise to achieve maximum developer productivity.

Executives from BlackRock, Medtronic, SAP and Uber will discuss their work in finance, healthcare, enterprise software, and business operations using the NVIDIA AI platform.

In addition, executives from ControlExpert, a global application provider for  car insurance companies based in Germany, will share how they developed an AI-powered claims management solution using NVIDIA AI Enterprise software.

They’re among a growing set of companies that benefit from NVIDIA’s work evaluating hundreds of internal and external generative AI projects — all integrated into a single package that’s been tested for stability and security.

And get the full picture from NVIDIA CEO and founder Jensen Huang in his GTC keynote.

See notice regarding software product information. 

The stars align this GFN Thursday as more top titles from Ubisoft and Square Enix join the cloud.

Star Wars Outlaws will be coming to the GeForce NOW library at launch later this year, while STAR OCEAN THE SECOND STORY R and PARANORMASIGHT: The Seven Mysteries of Honjo are part of eight new titles joining this week.

Additionally, four other games are getting NVIDIA RTX enhancements, all arriving at next week’s Game Developers Conference.

NARAKA: BLADEPOINT and Portal with RTX are adding full ray tracing and NVIDIA DLSS 3.5 Ray Reconstruction capabilities. This month’s Diablo IV update will add ray tracing. And Sengoku Dynasty — available to stream today — was recently updated with DLSS 3 Frame Generation.

Coming Soon

GeForce NOW members will be able to stream Star Wars Outlaws, the first open-world Star Wars game from Ubisoft, when it comes to the cloud at launch later this year.

Set between the events of The Empire Strikes Back and Return of the Jedi, explore distinct planets across the galaxy, both iconic and new. Risk it all as Kay Vess, a scoundrel seeking freedom and a fresh new start. Members will fight, steal and outwit their way through the galaxy’s crime syndicates to become the galaxy’s most wanted.

The game will launch with DLSS 3 and ray-traced effects, as well as NVIDIA RTX Direct Illumination (RTXDI) and ray-traced global illumination lighting, taking visuals to the next level. Turn RTX ON, available to Ultimate and Priority members as well as Day Pass users. And both Ultimate members and Day Pass users get the added benefit of NVIDIA DLSS 3 and NVIDIA Reflex for a streaming experience nearly indistinguishable from playing locally.

Adventure Awaits

With GeForce NOW, there’s always something new to play. This week, Japan-based publisher Square Enix brings two of its latest role-playing adventures to the cloud.

Witness an awakened destiny in STAR OCEAN THE SECOND STORY R, the highly acclaimed remake of the STAR OCEAN series’ second installment. Brought to life with a unique 2.5D aesthetic, which fuses 2D pixel characters and 3D environments, the remake includes all the iconic aspects of the original release while adding fresh elements. Experience new battle mechanics, full Japanese and English voice-overs, original and rearranged music, fast-travel and more. Discover the modernized, classic Japanese role-playing game perfect for newcomers and long-time fans alike.

Members can also try STAR OCEAN THE SECOND STORY R – DEMO this week before purchasing the full game.

Plus, solve an century-old mystery in PARANORMASIGHT: The Seven Mysteries of Honjo, a horror-adventure visual novel surrounding a Japanese tale, in which a mysterious “Rite of Resurrection” leads to conflict between those who have the power to curse others. Players conduct investigations throughout immersive, ambient, 360-degree environments to unravel the mysteries of Honjo, including by conversing with many interesting — and suspicious — characters.

Ultimate members can stream these games at up to 4K resolution for amazing visual quality across nearly any device and access NVIDIA GeForce RTX 4080 servers for extended session lengths. Upgrade today.

Shine Bright Like a New Game

Members can look for the following new games this week:

• Hellbreach: Vegas (New release on Steam, March 11)
• Deus Ex: Mankind Divided (New release on Epic Games Store, Free March 14)
• Outcast – A New Beginning (New release on Steam, March 15)
• Balatro (Steam)
• PARANORMASIGHT: The Seven Mysteries of Honjo (Steam)
• Space Engineers (Xbox, available on PC Game Pass)
• STAR OCEAN THE SECOND STORY R (Steam)
• STAR OCEAN THE SECOND STORY R – DEMO (Steam)
• Warhammer 40,000: Boltgun (Xbox, available on PC Game Pass)

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

How would your life look without video games?

— NVIDIA GeForce NOW (@NVIDIAGFN) March 13, 2024

NVIDIA’s GTC 2024 AI conference will set the stage for another leap forward in AI.

At the heart of this highly anticipated event: the opening keynote by Jensen Huang, NVIDIA’s visionary founder and CEO, who speaks on Monday, March 18, at 1 p.m. Pacific, at the SAP Center in San Jose, Calif.

Planning Your GTC Experience

There are two ways to watch.

Register to attend GTC in person to secure a spot for an immersive experience at the SAP Center. The center is a short walk from the San Jose Convention Center, where the rest of the conference takes place. Doors open at 11 a.m., and badge pickup starts at 10:30 a.m.

The keynote will also be livestreamed at www.nvidia.com/gtc/keynote/.

Whether attending in person or virtually, commit to joining us all week. GTC is more than just a conference. It’s a gateway to the next wave of AI innovations.

• Transforming AI: Hear more from Huang as he discusses the origins and impact of transformer neural network architecture with its creators and industry pioneers. He’ll host a panel with all eight authors of the legendary 2017 paper that introduced the concept of transformers: Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin.Wed., March 20, 11-11:50 a.m. Pacific.
• Join Visionaries Transforming Our World: Hear from leaders such as xAI cofounder Igor Babuschkin; Microsoft Vice President of GenAI Sebastian Bubeck, Stanford University’s Fei-Fei Li,  Meta Vice President of AI Research Joelle Pineau; OpenAI Chief Operating Officer Brad LightCap; Adept AI founder and CEO David Luan; Waabi founder and CEO Raquel Urtasun; Mistral CEO Arthur Mensch; and many others at the forefront of AI across various industries.
• Be Part of What Comes Next: Engage from March 17-21 in workshops and peer networking and connect with the experts. This year’s session catalog is packed with topics covering everything from robotics to generative AI, showcasing real-world applications and the latest in AI innovation.
• Stay Connected: Tune in online to engage with the event and fellow attendees using #GTC24 on social media.

With visionary speakers and a comprehensive program covering the essentials of AI and computing, GTC promises to be an enlightening experience for all.

Don’t miss your chance to be at the forefront of AI’s evolution. Register now.

Editor’s note: This post is part of our AI Decoded series, which aims to demystify AI by making the technology more accessible, while showcasing new hardware, software, tools and accelerations for RTX PC and workstation users.

If AI is having its iPhone moment, then chatbots are one of its first popular apps.

They’re made possible thanks to large language models, deep learning algorithms pretrained on massive datasets — as expansive as the internet itself — that can recognize, summarize, translate, predict and generate text and other forms of content. They can run locally on PCs and workstations powered by NVIDIA GeForce and RTX GPUs.

LLMs excel at summarizing large volumes of text, classifying and mining data for insights, and generating new text in a user-specified style, tone or format. They can facilitate communication in any language, even beyond ones spoken by humans, such as computer code or protein and genetic sequences.

While the first LLMs dealt solely with text, later iterations were trained on other types of data. These multimodal LLMs can recognize and generate images, audio, videos and other content forms.

Chatbots like ChatGPT were among the first to bring LLMs to a consumer audience, with a familiar interface built to converse with and respond to natural-language prompts. LLMs have since been used to help developers write code and scientists to drive drug discovery and vaccine development.

But the AI models that power those functions are computationally intensive. Combining advanced optimization techniques and algorithms like quantization with RTX GPUs, which are purpose-built for AI, helps make LLMs compact enough and PCs powerful enough to run locally — no internet connection required. And a new breed of lightweight LLMs like Mistral — one of the LLMs powering Chat with RTX — sets the stage for state-of-the-art performance with lower power and storage demands.

Why Do LLMs Matter?

LLMs can be adapted for a wide range of use cases, industries and workflows. This versatility, combined with their high-speed performance, offers performance and efficiency gains across virtually all language-based tasks.

LLMs are widely used in language translation apps such as DeepL, which uses AI and machine learning to provide accurate outputs.

Medical researchers are training LLMs on textbooks and other medical data to enhance patient care. Retailers are leveraging LLM-powered chatbots to deliver stellar customer support experiences. Financial analysts are tapping LLMs to transcribe and summarize earning calls and other important meetings. And that’s just the tip of the iceberg.

Chatbots — like Chat with RTX — and writing assistants built atop LLMs are making their mark on every facet of knowledge work, from content marketing and copywriting to legal operations. Coding assistants were among the first LLM-powered applications to point toward the AI-assisted future of software development. Now, projects like ChatDev are combining LLMs with AI agents — smart bots that act autonomously to help answer questions or perform digital tasks — to spin up an on-demand, virtual software company. Just tell the system what kind of app is needed and watch it get to work.

Learn more about LLM agents on the NVIDIA developer blog.

Easy as Striking Up a Conversation 

Many people’s first encounter with generative AI came by way of a chatbot such as ChatGPT, which simplifies the use of LLMs through natural language, making user action as simple as telling the model what to do.

LLM-powered chatbots can help generate a draft of marketing copy, offer ideas for a vacation, craft an email to customer service and even spin up original poetry.

Advances in image generation and multimodal LLMs have extended the chatbot’s realm to include analyzing and generating imagery — all while maintaining the wonderfully simple user experience. Just describe an image to the bot or upload a photo and ask the system to analyze it. It’s chatting, but now with visual aids.

Future advancements will help LLMs expand their capacity for logic, reasoning, math and more, giving them the ability to break complex requests into smaller subtasks.

Progress is also being made on AI agents, applications capable of taking a complex prompt, breaking it into smaller ones, and engaging autonomously with LLMs and other AI systems to complete them. ChatDev is an example of an AI agent framework, but agents aren’t limited to technical tasks.

For example, users could ask a personal AI travel agent to book a family vacation abroad. The agent would break that task into subtasks — itinerary planning, booking travel and lodging, creating packing lists, finding a dog walker — and independently execute them in order.

Unlock Personal Data With RAG

As powerful as LLMs and chatbots are for general use, they can become even more helpful when combined with an individual user’s data. By doing so, they can help analyze email inboxes to uncover trends, comb through dense user manuals to find the answer to a technical question about some hardware, or summarize years of bank and credit card statements.

Retrieval-augmented generation, or RAG, is one of the easiest and most effective ways to hone LLMs for a particular dataset.

RAG enhances the accuracy and reliability of generative AI models with facts fetched from external sources. By connecting an LLM with practically any external resource, RAG lets users chat with data repositories while also giving the LLM the ability to cite its sources. The user experience is as simple as pointing the chatbot toward a file or directory.

For example, a standard LLM will have general knowledge about content strategy best practices, marketing tactics and basic insights into a particular industry or customer base. But connecting it via RAG to marketing assets supporting a product launch would allow it to analyze the content and help plan a tailored strategy.

RAG works with any LLM, as the application supports it. NVIDIA’s Chat with RTX tech demo is an example of RAG connecting an LLM to a personal dataset. It runs locally on systems with a GeForce RTX or NVIDIA RTX professional GPU.

To learn more about RAG and how it compares to fine-tuning an LLM, read the tech blog, RAG 101: Retrieval-Augmented Generation Questions Answered.

Experience the Speed and Privacy of Chat with RTX

Chat with RTX is a local, personalized chatbot demo that’s easy to use and free to download. It’s built with RAG functionality and TensorRT-LLM and RTX acceleration. It supports multiple open-source LLMs, including Meta’s Llama 2 and Mistral’s Mistral. Support for Google’s Gemma is coming in a future update.

Users can easily connect local files on a PC to a supported LLM simply by dropping files into a folder and pointing the demo to that location. Doing so enables it to answer queries with quick, contextually relevant answers.

Since Chat with RTX runs locally on Windows with GeForce RTX PCs and NVIDIA RTX workstations, results are fast — and the user’s data stays on the device. Rather than relying on cloud-based services, Chat with RTX lets users process sensitive data on a local PC without the need to share it with a third party or have an internet connection.

To learn more about how AI is shaping the future, tune in to NVIDIA GTC, a global AI developer conference running March 18-21 in San Jose, Calif., and online.

AI-driven change is in the air, as are concerns about the technology’s environmental impact. In this episode of NVIDIA’s AI Podcast, Daniel Castro, vice president of the Information Technology and Innovation Foundation and director of its Center for Data Innovation, speaks with host Noah Kravitz about the motivation behind his AI energy use report, which addresses misconceptions about the technology’s energy consumption. Castro also touches on the need for policies and frameworks that encourage the development of energy-efficient technology. Tune in to discover the crucial role of GPU acceleration in enhancing sustainability and how AI can help address climate change challenges.

Register for NVIDIA GTC, a global AI developer conference running March 18-21 in San Jose, Calif., to explore sessions on energy-efficient computing and using AI to combat climate change.

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Show Notes

1:41: Context on and findings from the AI energy use report
10:36: How GPU acceleration has transformed the energy efficiency of AI, particularly in weather and climate forecasting
12:31: Examples of how GPU acceleration has improved the energy efficiency of AI operations
15:51: Castro’s insights on sustainability and AI
20:01: Policies and frameworks to encourage energy-efficient AI
26:43: Castro’s outlook on the interplay among advancing AI technology, energy sustainability and climate change

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For students, researchers and educators eager to delve into AI, GTC — NVIDIA’s conference on AI and accelerated computing — is in a class of its own.

Taking place from March 18-21 at the San Jose Convention Center, GTC features over 900 talks presented by world-renowned experts in fields such as generative AI, high performance computing, healthcare, energy and environment and robotics.

See some of the top sessions for attendees in higher education below. And don’t miss NVIDIA founder and CEO Jensen Huang’s GTC keynote on how AI is transforming industries, on Monday, March 18, at 1 p.m. PT.

For Researchers 

• Transforming AI is a panel featuring Huang and the eight authors of “Attention Is All You Need,” a groundbreaking paper that introduced the transformer neural network architecture.
• Fireside Chat With Fei-Fei Li and Bill Dally: The High-Speed Revolution in AI and Managing the Impact on Humanity, featuring Dally, chief scientist and senior vice president of research at NVIDIA, and Li, Sequoia Professor of computer science at Stanford University.
• Fireside Chat With Christian Szegedy and Bojan Tunguz: Automated Reasoning for More Advanced Software Synthesis and Verification, featuring Szegedy, research scientist and founder of xAI, and Tunguz, data scientist at NVIDIA.

See more sessions for researchers.

For Educators

• Priming Researchers and Students for AI and Accelerated Computing Breakthroughs With Self-Sustaining Training Programs, featuring Israel Chaparro-Cruz, lecturer and co-investigator from Universidad Nacional Jorge Basadre Grohmann; Mohammad Mostafanejad, lead software scientist at the Molecular Sciences Software Institute at Virginia Tech; and Joe Bungo, Deep Learning Institute program manager at NVIDIA.
• Learn How Educators Are Integrating Generative AI, Simulation and Design Into Their Curricula, featuring Deepak Chetty, area head for virtual production and assistant professor of practice at the University of Texas, Austin; Barbara Mones, teaching professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington; and Laura Scholl, senior content developer for the NVIDIA Deep Learning Institute.
• Omniverse Educator Summit, an opportunity for educators to explore the NVIDIA Omniverse platform, connect with peers and discover practical resources for classrooms from NVIDIA, including the Deep Learning Institute’s Teaching Kits and University Ambassador Program. Register to attend.

Find more sessions for educators.

For Students

• AI Secrets I Wish I Knew, featuring speakers from Stanford University, NVIDIA and education journalism initiative EdSurge.
• NVIDIA Graduate Fellowship Fast Forward Talks, featuring Dally and fellowship recipients from Caltech, Cornell University, Stanford University and UC Berkeley.
• Bridging the AI Divide: Expanding Access and Training to Nontraditional Talents and Underserved Communities, featuring speakers from Black Women In Artificial Intelligence, Create Labs, Cortex Innovation District and NVIDIA.

Discover more sessions for students and apply to join the NVIDIA Student Network.

To gain hands-on experience, check out training labs and full-day technical workshops at GTC.