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Efficient Deployment of Models at the Edge // Krishna Sridhar // #284

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Innovations in Edge Computing and On-Device AI

This chapter explores the transformative landscape of edge computing and the deployment of machine learning models, specifically focusing on Apple's CoreML. It discusses the importance of running models locally for practices like face recognition and mobile photography, balancing fast performance with user privacy. Additionally, it highlights the challenges of integrating evolving AI frameworks into hardware while emphasizing the advancements made in on-device AI capabilities.

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