Chris McEvilly

Organizations are running AI workloads for model training, fine-tuning, reinforcement learning and inference, across an expanding set of environments, including AWS Regions, AWS Local Zones, AWS Outposts, AWS Dedicated Local Zones, and AWS AI Factories.

As organizations use agentic AI to automate complex infrastructure operations, many have data residency, low latency, and security requirements that depend on running AI closer to their data.

As customers scale generative AI and agentic AI implementations from pilots to production, they need to balance speed of innovation with data sovereignty requirements, low-latency edge processing needs, and space, power, and cost efficiency.

Customers in regulated industries are looking to leverage generative AI with sensitive data that must remain on premises due to data residency requirements. Additionally, some customers with data generated at the edge need to run small language models (SLMs) locally for real-time processing.

In this workshop, learn how to architect, design, build, and deploy applications at the edge using AWS hybrid cloud and edge computing services. Explore architecture best practices for deploying a high-bandwidth media streaming application to AWS Wavelength Zones on a 5G network.

In this chalk talk, consider popular hybrid cloud and edge computing use cases and learn which AWS service or combination of services best fits the use case. This is a highly interactive talk where attendees can share their use case and have AWS experts walk through it to recommend the most appropriate AWS solution and reference architecture.

In this workshop, learn how to architect, build, and deploy applications at the edge using AWS hybrid cloud and edge computing services. Our team of experts will guide you through the steps of extending your workloads to 5G networks and large metro centers using AWS Wavelength and AWS Local Zones.