tinyMLSummit2021 Qualcomm Tutorial: Advanced network quantization and compression through the AIMET

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tinyml Summit 2021 https://www.tinyml.org/event/summit-2021
Tutorial: Advanced network quantization and compression through the AI Model Efficiency Toolkit (AIMET)
Abhijit KHOBARE, Director of Software Engineering, Qualcomm Technologies, Inc. (QTI)
Chirag PATEL, Principal Engr./Mgr. in Corp. R&D AI Research team, Qualcomm Technologies, Inc. (QTI)

AI is revolutionizing industries, products, and core capabilities by delivering dramatically enhanced experiences. However, the deep neural networks of today use too much memory, compute, and energy. To make AI truly ubiquitous, it needs to run on the end device within a tight power and thermal budget. Quantization and compression help address these issues. In this tutorial, we’ll discuss:

The existing quantization and compression challenges
Our research in novel quantization and compression techniques to overcome these challenges
How developers and researchers can implement these techniques through the AI Model Efficiency Toolkit

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