26min chapter

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Scaling Large ML Models to Small Devices with Atila Orhon

Software Engineering Daily

CHAPTER

Deploying Large Machine Learning Models on Small Devices

The chapter explores the challenges of deploying large machine learning models on small devices, emphasizing the importance of real-time applications and data privacy. It discusses model compression techniques, focusing on the development of the on-device WISPR kit for translation transcription applications. The conversation highlights optimizations for performance and compression, balancing generic tools and bespoke techniques for efficient deployment.

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