MIT Sloan AI Adoption Certificate — From Proof-of-Concept to Practice
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Explore the practical considerations and challenges of implementing computer vision in battery-powered IoT devices through this tinyML Talks webcast. Delve into the complexities of processing vast amounts of visual data, the necessity of hardware accelerators, and clever algorithms that leverage data locality and sparsity. Gain insights into real-world issues such as indoor/outdoor location, orientation, optics, and sensor selection. Learn about firmware, AI, power management, and communications in tinyCV systems. Discover typical use cases, view a demonstration, and understand power consumption metrics. Engage with discussions on motion detection and participate in a Q&A session to deepen your understanding of low-power computer vision applications in IoT.
Syllabus
Introduction
About TinyVision
Firmware
AI
Optics
Power
Questions
Communications
Data Sheet
Dual Scope
Typical Use Case
Demonstration
Power consumption
QA
Motion detection
Sponsors
Taught by
tinyML