Explore featured sessions for accelerated computing for edge AI.

Explore how to scale using AI at the edge, connect through high-performance 5G networks, and drive operational efficiencies through real-time IoT analytics. At GTC, experts will show you how to accelerate your path to a smarter infrastructure by tapping into the power of AI at the edge.

GTC KEYNOTE

Jensen Huang | NVIDIA | Founder and CEO

Don’t miss the chance to hear Jensen Huang inform how the company is driving the rapid pace of technology advancements and new offerings to help solve the world's toughest challenges. The live keynote broadcast happens on November 9, at 9:00 a.m. Central European Time with a rebroadcast at 8:00 a.m. PST / 11:00 a.m. EST.

The keynote webcast will be open for everyone to watch (no registration required).

Featured Speakers

Enable the Convergent Telco Edge to Deliver Multiple Edge AI Apps

Karthik Krishna 
Senior Solutions Manager, VMware

AI Life-cycle Management for the Intelligent Edge

Amanda Saunders
Senior Manager, Edge AI Product Marketing, NVIDIA

Delivering Connected Intelligence to Enterprises with a Commercial AI-on-5G Solution

Soma Velayutham
Industry General Manager, AI & 5G, NVIDIA

Case study: Edge AI for Industrial Applications

German Suvorov
Head of Industrial AI, Data Monsters

Sessions By Topics

Edge Computing

  • Rise of the Intelligent Edge: From Enterprise to Device Edge

    • Justin Boitano, VP and GM of Enterprise and Edge Computing, NVIDIA

    Edge computing is transforming the way organizations use the data they collect from stores, factories, and hospitals, turning those data into actionable, intelligent insights. NVIDIA is working with a broad ecosystem to accelerate the edge computing space. Learn about the hardware, AI applications, and management services that make deploying AI at the edge simple and secure.

  • Real-Time AI Processing at the Edge

    • Francis Lam, Datacenter GPU Product Management, NVIDIA
    • Jacob Liberman, Product Manager - Enterprise and Edge Acceleration, NVIDIA

    Bring together the powerful performance of the NVIDIA Ampere architecture with the enhanced security and latency-reduction capabilities of the DPU to accelerate edge computing workloads. We'll deep dive into how these NVIDIA converged cards can be used to create high-performance AI applications, making them optimal platforms to manage precision manufacturing robots, automated guided vehicles, wireless cameras, self-checkout aisles, and more.

  • Exploring Cloud-Native Edge AI

    • Jacob Liberman, Product Manager - Enterprise and Edge Acceleration, NVIDIA

    Every industry will deploy AI servers at the edge to exploit Internet-of-things sensor data in real time—detecting illness, preventing theft, and responding to natural disasters. We'll review the benefits of cloud native for edge AI. We will also demonstrate how to integrate NVIDIA accelerators into cloud-native edge AI platforms.

  • Case study: Edge AI for Industrial Applications

    • German Suvorov, Head of Industrial AI, Data Monsters

    Data Monsters' team, in cooperation with NVIDIA, implements AI quality inspections on a high-speed packaging line of a major beverage company. It's a computer vision solution based on edge self-supervised AI. We'll share the challenges of scaling from proof-of-concept to pilot and production on multiple lines, deploying infrastructure and models on the manufacturing site, and how we implemented edge orchestration with Fleet Command. We’ll also cover development and research on DGX, and what new features of A100 GPU allowed us to implement real-time operation.

5G

  • Enable the Convergent Telco Edge to Deliver Multiple Edge AI Apps

    • Karthik Krishna, Solutions Product Manager, VMware
    • Joao Kluck Gomes, Global Business Development, NVIDIA

    5G and edge computing are enabling new services for multiple verticals. NVIDIA and VMware are working together to enable telcos to offer these new edge applications using NVIDIA application frameworks, the VMware Telco Cloud Platform, and a large ISV ecosystem. We'll showcase edge use cases and demo an ISV application on the NVIDIA and VMware platform.

  • Scaling XR Applications with CloudXR, Edge Computing, and 5G

    • Krasi Nikolov, CEO and Co-founder, QuarkXR

    As an XR developer in many exciting industries like location-based XR (LBXR), manufacturing, or engineering, you’re dealing with a lot of moving parts and a lot of requirements. We'll share our experience of scaling XR applications for LBXR, manufacturing, and robotic teleoperation using CloudXR, edge computing, and 5G, as well as how CloudXR enabled us to simplify deployment.

  • Delivering Connected Intelligence to Enterprises with a Commercial AI-on-5G Solution

    • Soma Velayutham, Industry General Manager, AI & 5G, NVIDIA
    • Kuntal Chowdhury, SVP and GM, AI and Analytics, Mavenir

    Connected intelligence, powered by AI and super-fast connectivity, is a major driver of digital transformation for many industries. The combination of AI and 5G’s enterprise-grade connectivity in the AI-on-5G platform will help accelerate the creation of smart cities, smart manufacturing, smart retail, automated warehouses, and more. But how is this delivered in an enterprise environment? This session, delivered by Mavenir and NVIDIA, will showcase the activities, partnerships, relationships, and ecosystem in the development and deployment of AI-on-5G solution for enterprise customers.

IoT and Smart Infrastructure

  • The Rise of Smart Infrastructure: Automating Smart Spaces with NVIDIA Metropolis and Edge AI

    • Adam Scraba, Director of Product Marketing, NVIDIA

    From retail shops to warehouses to our city streets, every space is becoming smarter thanks to AI-enabled vision applications. Learn how the world’s smartest spaces are leveraging the NVIDIA Metropolis AI application framework. We’ll cover application areas, NVIDIA tools for training, inference, optimization, and dev-ops management, and the rich ecosystem of partners.

  • Enabling City-Scale AI Video Analytics for Smarter Cities

    • Yongsung Kim, Manager, SK Telecom

    The use of Vision AI applications for tackling city-scale problems and building smarter infrastructure, especially in the post-COVID era, has grown immensely. Telcos, in several markets, are part of the ecosystem. We tackle the cost and scale-out issues of existing vision AI systems by using the chained inference of light-weight vision AI models over a novel hybrid architecture.

  • Own the Sky: Real-Time Multi Sensors Augmentation for Air Mobility

    • Leonid Trainer, Software Group Manager, Elbit Systems

    Air mobility has many challenges, such as low visibility, 3D orientation, and obstacle avoidance. But as we've already seen in the autonomous vehicle industry, by using AI and intelligent sensor augmentation, we can significantly improve the pilot's ability to perform those tasks and even "change the game" in terms of flight safety. In this talk, we will explore our approach for safe air navigation by presenting the pilot real-time augmented imagery based on high-fidelity sensors. We’ll also show how NVIDIA edge hardware, such as Jetson Xavier NX, can help to create a fully operational flyable system solution.

  • Autonomous Stores are Becoming a Reality: From Large-Scale AI Networks to High-Performance Computing

    • Daniel Gabay, Chief Technology Officer, Trigo Vision

    For centuries, people associated shopping in stores with the everyday experience of waiting in lines. Recent advancements in deep learning models and edge computing changed this axiom, enabling Trigo to develop a technology that transforms regular stores into seamless shopping areas. Large retailers, like some of our partners in production—Tesco and REWE—can now let their customers leave their stores without having to scan items or wait in lines. Digitizing an analog, offline retail store is an extreme technological and user experience challenge: there are thousands of constantly changing items of produce, endless permutations of human interactions, and dynamic environmental conditions. All of these factors have to function simultaneously and seamlessly in real time for an autonomous store system to work. We’ll delve into the challenges of AI modeling thousands of products and focus on real-time optimizations needed to make it a reality. We'll also cover our high-throughput data processing pipeline starting from our real-time computing, 3D modeling, and large-scale AI networks.

See IoT, 5G, and edge computing session highlights from the previous GTC. Get ready for what’s to come.

Find the complete GTC On-Demand playlist here.

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