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See how NVIDIA can help you take on the most challenging workloads with access to experts, insights, and training on the latest NVIDIA technology. Explore sessions hosted by technical experts spanning AI, NVIDIA Omniverse™, accelerated computing, autonomous driving, computer vision, cybersecurity, digital twins, robotics, and more.

Explore AI, Omniverse, and Beyond from Our Latest GTC Keynote

Take a closer look at the transformative technologies that are helping us take on the world’s greatest challenges–together.

Explore AI, Omniverse, and Beyond from Our Latest GTC Keynote

Take a closer look at the transformative technologies that are helping us take on the world’s greatest challenges–together.

Discover proven techniques for developing safer, more efficient transportation. Learn about advancements in autonomous driving, end-to-end vehicle simulation, robotaxis, trucking, mapping, and more.

  • Featured Automotive Sessions

    OEMs including CARIAD, Mercedes-Benz,, and TuSimple, plus Tier 1 suppliers Valeo and  ZF showcase the latest innovations and advancements in autonomous vehicles on a variety of topics including software, architecture, AI compute, sensing, and more.

  • Autonomous Vehicles

    ETH Zürich, Ottonomy, Ouster, and others reveal how they are building intelligent, safer transportation from the ground up, utilizing new advances in perception, high-performance sensing, and more.

  • AI Infrastructure

    BMW, Cruise, Microsoft, Stellantis, Zoox, and more discuss how autonomous vehicles are born in the data center, where high-performance compute solutions develop, train, test, and validate self-driving software.

  • Simulation

    BMW Group, DeepScenario, dSPACE, Luminar, Renault, and others discuss how high-fidelity, cloud-based simulation is accelerating autonomous vehicle deployment in the real world.

  • Design and Manufacturing

    ESI Group, Hexagon, Maya HTT, Volvo Trucks Group Technology, and others showcase innovative ways to use GPUs for high-performance compute and graphics across transportation, manufacturing, and automotive.

Computer Vision and Video Analytics

Supercharge your vision AI app development at NVIDIA GTC. Discover the latest innovations, developer tools, industry best practices, and more.

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Learn how AI is transforming cybersecurity. Get training, insights, and access to experts on the latest innovations in AI and cybersecurity.

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Data Science and AI

See your life’s work realized with AI and data science. Join thousands of other professionals, leaders, and innovators at this GTC to learn AI and data science from the world’s most advanced data teams.

  • Accelerating the End-to-end Data Science Life Cycle Across Tasks and Teams

    > William Benton | Principal Product Architect, NVIDIA

    > Sophie Watson | Technical Product Marketing Manager 

    Savvy practitioners love to dive deep into machine-learning techniques, but they know that even the most elegant technique isn't the whole story. To get business value from AI, you'll need to build a machine-learning system, which means coordinating cross-functional teams, polyglot services, and diverse data sources. Learn how NVIDIA AI Enterprise, NVIDIA EGX, and the RAPIDS Accelerator for Apache Spark provide benefits across an entire machine-learning system: accelerating discovery, model training, and model serving, feeding a feature extraction pipeline tens of times faster by running Apache Spark queries on Ampere GPUs and making all of this power accessible.

  • Building AI-Based Recommender System Using the Power of Deep Learning and GPU

    > Khalifeh AlJadda | Senior Director of Data Science, The Home Depot

    Recommender systems play a crucial role in any ecommerce platform. Therefore, it's very important to build a personalized, scalable, and reliable recommender system that proactively helps shoppers discover products that engage them while on the website, and then re-engage them with products and content that align with their interest after they leave the website via email, social media, or other marketing channels.

    I'll cover our transformation at The Home Depot to an AI-based recommender system leveraging the power of deep learning and GPU. We'll discuss how we train and deploy real-time deep-learning models to enable personalized recommendations at scale.

  • Conversation AI Demystified

    > Sirisha Rella | Product Marketing Manager, NVIDIA

    Conversational AI technologies are becoming ubiquitous, with countless products taking advantage of automatic speech recognition, natural language understanding, and speech synthesis coming to market. Thanks to new tools and technologies, developing conversational AI applications is easier than ever, enabling a much broader range of applications, such as virtual assistants, real-time transcription, and many more. The talk will be composed of two parts. We'll start with an overview of the conversational AI landscape and discuss how any organization can start developing conversational AI applications today. Then we'll demonstrate how to build and deploy end-to-end conversational AI pipelines using NVIDIA Riva.

  • Using NeMo-Megatron to Build Large-scale, Localized Language Models: From Data Preparation to Training and Deployment to Production

    > Miguel Angel Martinez | Senior Deep Learning Solution Architect, NVIDIA

    > Meriem Bendris | Senior Deep Learning Solution Architect, NVIDIA 

    Recent advances in natural language processing demonstrate the capability of large-scale language models (e.g. GPT-3) to solve a variety of NLP problems with zero shots shifting from supervised fine-tuning to prompt engineering/tuning. However, building large language models raises challenges on data preparation, training, and deployment. In addition, while the process is well-established for a few dominant languages such as English, its execution on localized languages remains limited. We'll give an overview of the end-to-end process for building large-scale language models, discuss the challenges of scaling, and describe some existing solutions for efficient data preparation, distributed training, model optimization, and distributed deployment.

  • Fast, Scalable, and Standardized AI Inference Deployment for Multiple Frameworks, Diverse Models on CPUs and GPUs with Open-Source NVIDIA Triton

    > Shankar Chandrasekaran | Product Marketing Manager, NVIDIA

    > Mahan Salehi | Product Manager, NVIDIA

    We'll go over NVIDIA Triton Inference Server software and what's new. Triton is an open-source inference-serving software for fast and scalable AI in applications. Learn how Triton helps deploy models from all popular frameworks—including TensorFlow, PyTorch, ONNX, TensorRT, RAPIDS FIL (for XGBoost, Scikit-learn Random Forest, LightGBM), OpenVINO, Python, and even custom C++ backends. Also learn about the features that help optimize inference for multiple query types—real-time, batch, streaming, and model ensembles.

Game Development

Find out what’s the latest in RTX real-time ray tracing, DLSS, and GeForce NOW during our game development track at GTC.

  • RTX SDKs: The Foundation of Next-gen Lighting for Games

    > Alexey Panteleev | Distinguished DevTech Engineer, NVIDIA

    NVIDIA provides three SDKs for real-time lighting and denoising. RTXDI implements a set of resampling algorithms for computing direct lighting and ray-traced shadows from many lights—up to millions—without baking. RTXGI approximates indirect lighting using grids of dynamically updated, ray-traced light probes. Finally, NRD provides a collection of real-time denoising algorithms in an easy-to-integrate package.

  • Deep Dive: One Click Animation Retargeting in Omniverse

    > Lina Halper | Principal Animation Engineer, NVIDIA

    Animation retargeting has been a challenge for many years while the demand of diverse characters and use cases are increasing tremendously outside of the traditional gaming industry, as in synthetic data generation or digital twin, for example. Downloading animations online is easy to do, and there is much research on generating those animations automatically, but applying them to a custom character can be challenging and requires a huge technical understanding of rig, skeleton, and animation. Also, there are very limited open options in the industry, and the quality ranges from low to high, with many knobs and tweaks required from users. We'll explain how we tackled this in the Omniverse while aiming for an easy-to-use feature.

  • NVIDIA DLSS Overview & Game Integrations

    > Andrew Edelsten | NVIDIA

    NVIDIA Deep Learning Super Sampling (DLSS) uses the power of deep learning and AI to increase game frame rates through the clever use of spatio-temporal upsample and the NVIDIA Tensor Cores. During the session, the speaker will walk through the underlying technology that makes DLSS possible, and also explain how to integrate DLSS into a new game engine. Learn about the engine requirements for DLSS and things to look out for during an integration. Finally, the session covers general DLSS debugging tools and how to fix common issues that may be negatively affecting the image quality of the final frame.

  • The Importance of Digital Humans for Industries

    > Markus Gross | Vice President of Research, Walt Disney Studios

    > Simon Yuen | Director of Graphics and AI, NVIDIA

    > Matt Workman | Developer, Cine Tracer

    > Sarah Bacha | Head of Research and Innovation, Cedrus AI

     > Vladimir Mastilovic | VP of Digital Humans Technology, Epic Games

    Join technical and business luminaries for this panel discussion exploring how digital humans will have a profound impact on industries outside of Media and Entertainment. We’ll explore what leading technology companies are contributing to the space today, and what they see for the future.

  • Acceleration Structures in Ray Traced Open World Games

    > Peter Morley | Senior Developer Technology Engineer, NVIDIA

    Ray tracing is primed to replace rasterization due to advantages in illuminating environments providing more realistic and immersive experiences in games. Open-world, ray-traced games typically employ hybrid graphics renderers that take the best pieces from ray tracing and rasterization. This talk will primarily focus on the performance and scalability of ray tracing when converting a raster-based renderer into a hybrid (rasterization and ray tracing) renderer.  Specifically, we mention acceleration structure building approaches, ray tracing regimes that scale efficiently, and ray tracing workload scheduling to get the best bang for your buck on NVIDIA RTX hardware.

Graphics, Design Collaboration, and Digital Twins

NVIDIA Omniverse is a scalable, multi-GPU real-time reference development platform for 3D simulation and design collaboration, based on Pixar's Universal Scene Description and NVIDIA RTX technology.


Learn about how NVIDIA Isaac and Jetson platforms are leading the latest advancements in robotics, simulation, and reinforcement learning.

  • Leveraging Embedded Computing to Unlock Autonomy in Human Environments

    > Andrea Thomaz | Co-Founder and CEO, Diligent Robotics

    Dr. Andrea Thomaz will discuss the unique challenges in achieving robot autonomy in a dynamic human environment like busy hospitals–from having to maneuver around objects in busy halls to having to navigate to a requested location, all while integrating multiple camera streams that feed into embedded GPUs. View the full Robotics playlist.

  • Object Manipulation Without Explicit Models

    > Dieter Fox | Sr. Director of Robotics Research, NVIDIA

    This in-depth session covers recent work on learning to manipulate unknown objects directly from visual (depth) data and combining pre-trained language and vision models in order to teach a robot to perform manipulation tasks. View the full Robotics playlist.

  • Deep Learning Using NVIDIA Omniverse for Synthetic 3D Point Cloud Generation

    > Robert Banfield | Machine Learning Engineer, Trimble

    > Nyla Worker | Solutions Architect, NVIDIA

    This session explores the generation of deep learning models to achieve state-of-the-art predictive accuracy by combining publicly available and synthetically generated and labeled point clouds. View the full Robotics playlist.

  • Jetson Developer Day

    Jetson Developer Day is a special event open to developers of all levels. Featuring deep-dive sessions with Jetson platform experts, this collection of talks showcases the latest innovations in autonomous machines and edge AI.

  • Developing ROS-based Mobile Robots Using NVIDIA Isaac ROS GEMs

    > Raffaello Bonghi | Developer Relations, NVIDIA

    Get a technical overview of how NVIDIA hardware-accelerated robotics software packages—Isaac ROS GEMs—are used to help a robot's perception, localization, and mapping. View the full Robotics playlist.

High-Performance Computing (HPC)

Optimize your HPC performance by using parallelizable code across platforms and learn about the latest CUDA developments, NVIDIA GPU updates, HPC software releases, and more.

  • CUDA: New Features and Beyond

    > Stephen Jones | NVIDIA

    Learn about the latest additions to the CUDA platform: Language and Toolkit. Presented by one of the architects of CUDA, this engineer-focused session covers all the latest developments for the NVIDIA GPU developer ecosystem, as well as looking ahead to where CUDA will be going over the coming year.

  • C++ Standard Parallelism

    > Bryce Lelbach | NVIDIA

    Imagine writing parallel code that can run on any platform—CPUs, GPUs, DPUs, specialized accelerators, etc.—without any language or vendor extensions, external libraries, or special compilation tools. It's no longer just a dream. You can do it today in Standard C++!

    Parallelism is increasingly common in software, from supercomputer simulations to mobile applications. But writing parallel code is increasingly challenging due to an explosion of diversity in hardware, a trend that's likely to continue. To meet this challenge, the C++ Committee has developed C++ Standard Parallelism, a parallel programming model for Standard C++ that’s portable to all platforms, from your smartwatch to your supercomputer, and delivers reasonable performance and efficiency for most use cases. We'll dive into the roadmap for C++ Standard Parallelism and discuss what we already have today, what's coming down the line, and where the future may lead us.

  • Latest NVIDIA GPUs

    > Cyril Zeller | NVIDIA

    We'll take a deep dive into the NVIDIA latest GPU architecture and look at how applications can benefit from the latest features, and how to optimize your applications.

  • A Deep Dive into the Latest HPC Software

    > Timothy Costa | NVIDIA

    Take a deep dive into the latest developments in NVIDIA software for high-performance computing applications, including a comprehensive look at what’s new in programming models, compilers, libraries, and tools. We'll cover topics of interest to HPC developers, targeting traditional HPC modeling and simulation, quantum computing, HPC+AI, scientific visualization, and high-performance data analytics.

  • Port, Profile, and Tune HPC Applications for Arm-Based Supercomputers

    > John Linford | Arm

    Learn how to reproducibly characterize performance across architectures! NVIDIA GPUs combined with Arm CPUs create a formidable HPC platform that delivers astonishing application performance with excellent energy efficiency. We present a methodology and software tools for porting and tuning HPC applications on any Arm-based HPC system, including NVIDIA Grace, Ampere Altra, AWS Graviton 2, Fujitsu A64FX, SiPearl Rhea, and many more. This approach combines the Spack package manager and the ReFrame testing framework to ease performance characterizations of applications running on Arm-hosted NVIDIA A100 and NVIDIA V100 GPU systems, as well as a diverse range of Arm-based CPUs.  

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