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AI, specifically deep learning, 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. At Qualcomm Technologies, we’ve been actively researching and developing AI solutions with the goal to make artificial intelligence ubiquitous across devices, machines, vehicles, and things. To this end, Qualcomm Innovation Center (QuIC) has open sourced the AI Model Efficiency Toolkit (AIMET) on GitHub to collaborate with other leading AI researchers and to provide a simple library plugin for AI developers to utilize for state-of-the-art model efficiency performance. The open source project is meant to help migrate the ecosystem toward integer inference because we believe this is an effective way to increase performance per watt.

In this talk, we will discuss why model efficiency is important and the challenges associated with running models on low-precision hardware. And we will introduce AIMET and its features.

Presenter: Tijmen Blankevoort

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