Today the terms Internet of Things (IoT), 5G, and edge computing are everywhere. With the explosive growth in IoT devices, the emergence of true 5G capable networks, and the growth in AI, organizations are trying to figure out how to use these trends to help them get ahead.

As the leader in AI, NVIDIA is bringing these topics to the forefront of our annual NVIDIA GTC, taking place November 8-11. We will show organizations how they can accelerate their path to a smarter infrastructure by tapping into the power of AI at the edge. Here is a preview of some of the top sessions in our edge AI track including topics such as edge computing, IoT, AI-on-5G.

Edge Computing

Promotional image of Justin Boitano, speaker of the "Rise of the Intelligent Edge: Enterprise to Device Edge" GTC session. — *Figure 1. Edge Computing Session by Justin Boitano, VP and GM of Enterprise and Edge Computing, NVIDIA*

Rise of the Intelligent Edge – from Enterprise to Device Edge: AI at the edge is turning data collected from sensors and devices into actionable insights. Edge computing is a key business differentiator for every industry, but many are just getting started. We will look at the edge computing ecosystem and help organizations bring edge AI to reality. Learn the hardware, applications, and management services that make deploying AI at the edge simple and secure.

Exploring Cloud-native Edge AI: Edge computing is turning the AI data center of the future on its head. Rather than 10,000 servers in one location, edge AI will be deployed one or more servers in 10,000 locations. The complexity of maintaining a fleet of distributed servers can erode the business value. We will review the benefits of cloud native for edge AI and demonstrate how to integrate NVIDIA accelerators into cloud-native edge AI platforms.

How Cities, Stadiums, and Factories are Leveraging Edge AI and Metropolis: You may not think city management, stadium operations, and complex manufacturing processes have a lot in common. But they are all streamlining the operation of their most valuable spaces and reducing management costs thanks to AIcomputer vision. In this panel, experts from Shell; the City of Raleigh, North Carolina; and Gillette Stadium will share best practices to guide other smart spaces on their journey.

Figure 2. Edge implementers panel talks about the challenges and benefits of AI powered computer vision

AI-on-5G

Delivering Connected Intelligence to Enterprises with a Commercial AI-on-5G Solution: Connected intelligence is a major driver of digital transformation. The combination of AI and 5G’s enterprise-grade connectivity 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 joint-session from Mavenir and NVIDIA will showcase all that is involved in the development and deployment of AI-on-5G solution for enterprise.

Enable the Convergent Telco Edge to Deliver Multiple Edge AI Apps: 5G and edge computing are enabling telcos to offer new business services across many industries. NVIDIA and VMware are working together to enable telcos to offer new edge applications. We will showcase edge use cases from AI applications using NVIDIA application frameworks, VMware Telco Cloud Platform, and a large partner ecosystem.

IoT, Computer Vision, and Smart Infrastructure

Image shows how computer vision could be used to identify people in cities. — *Figure 4. NVIDIA Metropolis simplifies smart infrastructure*

The Rise of Smart Infrastructure: Automating Smart Spaces with NVIDIA Metropolis and Edge AI: The world’s smartest spaces are leveraging NVIDIA Metropolis to accelerate time to impact, from development to deployment and management. In this session, we will look at application areas; the breadth of NVIDIA tools for training, inference, optimization; and dev-ops management. Learn how NVIDIA Metropolis simplifies solution integration by bringing together an entire rich ecosystem.

Enabling City-scale AI Video Analytics for Smarter Cities: The use of vision AI for tackling city-scale problems and building smarter infrastructure has grown, especially in the post-COVID era. When it comes to city-scale, it is important that vision AI inference engines can be easily scaled-out and cost-effective for large-scale service deployment. We will look at the cost and scale-out issues of existing vision AI systems by using a hybrid architecture of DeepStream and NVIDIA Triton.

Join Us at GTC

With over 500 sessions covering the latest breakthroughs in AI and deep learning, GTC is the best place to learn from experts, practitioners, and leaders in their field. The virtual event kicks off on November 9, with a keynote presentation from NVIDIA CEO and Co-Founder, Jensen Huang.

Do not miss all of the amazing sessions, labs, and more! Register for free today.