About This Session
Cloud inference provides unparalleled scale and capability, but mission-critical operations in disconnected environments - like factory floors or remote field sites often require immediate, localized intelligence. As enterprises move beyond chat interfaces into real-time, autonomous actions, building a hybrid architecture that seamlessly bridges the cloud and the edge becomes essential. This session tackles the engineering realities of deploying localized AI. We will explore how to architect systems that run Small Language Models (SLMs) and specialized reasoning engines directly at the edge, integrating seamlessly with local IoT telemetry and industrial systems. Attendees will learn how to balance localized reasoning for immediate, privacy-safe decision-making with asynchronous cloud syncs for heavy processing. You will walk away with practical patterns for overcoming hardware constraints, managing offline-first AI deployments, and building intelligence that works reliably everywhere.
Topics
- AWS
- Automation
- Autonomous Systems
- Edge AI
- Internet of Things (IoT)
- Privacy