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Introduction
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Title
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Outline
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What is tinyML
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Constraints
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Defining tinyML
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Why we are excited about tinyML
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Opportunities in all verticals
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Animal Foundation
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Community Events
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How tinyML is implemented
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Is tinyML good enough
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The future of tinyML
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Alwayson voice
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MEMS sensors
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Environmental sensing
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Time use and edge measurement
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Alwayson Vision
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Applications
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Examples
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Face Detection
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Image Quality
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System Approach
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Summary
Description:
Explore recent advancements in tinyML technologies and always-on machine capabilities in this 47-minute keynote presentation from the IEEE Computer Society Annual Symposium on VLSI 2020. Delivered by Evgeni Gousev of Qualcomm AI Research, the talk covers the definition and constraints of tinyML, its exciting potential across various industries, and implementation strategies. Delve into the future of tinyML, focusing on always-on voice and vision applications, MEMS sensors, environmental sensing, and edge measurement. Gain insights into specific examples such as face detection and image quality improvements, and understand the system approach required for successful tinyML implementation. Discover how tinyML is revolutionizing machine learning on resource-constrained devices and opening up new possibilities in the field of artificial intelligence.

Recent Progress on TinyML Technologies and Always-On Machine Opportunities

tinyML
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