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1
Introduction
2
Challenges
3
Qualcomm AI Research
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Qualcomm Core Technologies
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Layers of Interest
6
Inference
7
Features
8
Adaptive Rounding
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Autocon
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Training
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Image Model Zoo
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Transformer Quantization
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Snapdragon Gen 2
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GitHub
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Qualcomm Snapdragon 8
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Conditional Compute
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Demo
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the world of AI model efficiency in this guest lecture from Qualcomm AI Research. Dive into the challenges of deploying neural networks on mobile and IoT devices, and discover cutting-edge solutions for efficient machine learning. Learn about Qualcomm's core technologies, adaptive rounding, autocon, and transformer quantization. Gain insights into image model zoos, conditional compute, and the Qualcomm Snapdragon 8 Gen 2. Witness a live demo showcasing the practical applications of these efficiency techniques. Perfect for those interested in TinyML, efficient deep learning computing, and the future of AI on resource-constrained devices.

AI Model Efficiency Toolkit (AIMET) - Lecture 25

MIT HAN Lab
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