“Introduction to Optimizing ML Models for the Edge,” a Presentation from Cisco Systems

Kumaran Ponnambalam, Principal Engineer of AI, Emerging Tech and Incubation at Cisco Systems, presents the “Introduction to Optimizing ML Models for the Edge” tutorial at the May 2023 Embedded Vision Summit.

Edge computing opens up a new world of use cases for deep learning across numerous markets, including manufacturing, transportation, healthcare and retail. Edge deployments also pose new challenges for machine learning, not seen in cloud deployments. Constrained resources, tight latency requirements, limited bandwidth and unreliable networks require us to rethink how we build, deploy and operate deep learning models at the edge.

In this presentation, Ponnambalam introduces proven techniques, patterns and best practices for optimizing computer vision models for the edge. He covers quantization, pruning, low-rank approximation and knowledge distillation, explaining how they work and when to use them. And he touches on how your choice of ML framework and processor affect how you use these optimization techniques.

See here for a PDF of the slides.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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