Deploy Industrial Machine Vision with Embedded AI at the Edge

As industrial environments demand smarter, faster, and more reliable automation, machine vision powered by AI is rapidly becoming a cornerstone technology for quality control, anomaly detection, and operational efficiency. Yet deploying AI at the Edge in industrial settings comes with unique challenges: strict latency requirements, bandwidth constraints, data privacy regulations, and the need for robust, reliable systems that can operate at scale.
 
This presentation explores how a new generation of embedded compute architectures—designed specifically for Edge AI—are transforming machine vision capabilities in industrial applications. Attendees will learn about both the hardware and the vast software ecosystem through real world examples of how an open, flexible development approach—combined with scalable, AI-native hardware—empowers manufacturers to bring real-time vision inference, multimodal sensing, and context-aware decision-making directly to the Edge.

This session is part of our “AI in 2025: Shifting the discussion to the Edge” webinar series. Registration/event page here.

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