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When time is of the essence, AI can power real-time insights at the edge where data is stored. However, challenges persist in the field with reducing large model architectures to run on smaller devices, ensure security, bridge skills gaps and enable orchestration back to a centralized solution for monitoring and retraining as needed. This tech talk walks through a new method to deploying, running, and securing AI models at the edge that allows for faster processing, reduced latency, and increased security.