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AI at the Edge: Solving Real-World Problems with Embedded Machine Learning 1st Edition


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From the Preface

Over the past few years, a growing community of engineers and researchers have quietly rewritten the rules for how computers interact with the physical world. The result, a technology known as “edge artificial intelligence,” promises to upend a century of computer history and touch the lives of every human being.

With a tiny software update, edge AI technology can grant cheap, energy-efficient processors—already inside everything from dishwashers to thermostats—the ability to perceive and understand the world. We can empower everyday objects with their own intelligence, no longer dependent on data-hungry centralized servers. And next-generation tools put this magic in reach of everyone, from high school students to conservation researchers.

There are already many edge AI products out there in the world. Here are some that we’ll meet in the pages of this book:

  • Smart devices that help prevent forest fires caused by electricity transmission, by mounting to electricity pylons and predicting when a fault may occur
  • Wearable bands that keep firefighters safe by warning when they’re at risk from heat strain and overexertion
  • Voice user interfaces that provide hands-free control of technology, no internet connection required
  • Smart collars that monitor the movements of wild elephants, helping researchers understand their behavior and protect them from conflict
  • Wildlife cameras that identify specific animal species and help scientists understand their behavior

The technology of edge AI is still fresh and new, and these existing applications are just a glimpse of what is possible. As more people learn how to work with edge AI, they’ll create applications that solve problems across every avenue of human activity.

The goal of this book is to empower you to be one of them. We want to help you create successful edge AI products based on your own unique perspectives.

Editorial Reviews

Review

AI at the Edge introduces the new and fast-growing field of edge AI in a practical, easy-to-follow way. It demystifies jargon and highlights real challenges that you are likely to encounter when building edge AI applications. The book offers an essential guide to going from concept to deployment—a must-read for getting started in the field.
—Wiebke Hutiri, Delft University of Technology
 
I really love the writing style which makes complex technical topics approachable and digestible. I can imagine it being used as a reference book, returning to it time and time again—which I will certainly be doing!
—Fran Baker, Director of Sustainability and Social Impact, Arm
 
What a wonderfully accessible and thorough introduction to the emerging field of edge AI! It covers an impressive breadth of topics, from the core concepts to the latest hardware and software tools, it's full of actionable advice, and includes several end-to-end examples. Anyone joining this exciting new field will benefit from the deep insights and clarity of thought this book provides.
—Aurélien Geron, former lead of YouTube's automatic video classification team and best-selling author
 
This is the guide to creating smarter devices: AI at the Edge provides an excellent introduction on combining modern AI techniques and embedded systems.
—Elecia White, author of Making Embedded Systems and host of the Embedded podcast

About the Author

Daniel Situnayake is Head of Machine Learning at Edge Impulse, where he leads embedded machine learning R&D. He's coauthor of the O'Reilly book TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers, the standard textbook on embedded machine learning, and has delivered guest lectures at Harvard, UC Berkeley, and UNIFEI. Dan previously worked on TensorFlow Lite at Google, and co-founded Tiny Farms, the first US company using automation to produce insect protein at industrial scale. He began his career lecturing in automatic identification and data capture at Birmingham City University.

Jenny Plunkett is a Senior Developer Relations Engineer at Edge Impulse, where she is a technical speaker, developer evangelist, and technical content creator. In addition to maintaining the Edge Impulse documentation, she has also created developer-facing resources for Arm Mbed OS and Pelion IoT. She has presented workshops and tech talks for major tech conferences such as the Grace Hopper Celebration, Edge AI Summit, Embedded Vision Summit, and more. Jenny previously worked as a software engineer and IoT consultant for Arm Mbed and Pelion. She graduated with a B.S. in Electrical Engineering from The University of Texas at Austin.

Product details

  • Publisher ‏ : ‎ O'Reilly Media; 1st edition (February 14, 2023)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 512 pages
  • ISBN-10 ‏ : ‎ 1098120205
  • ISBN-13 ‏ : ‎ 978-1098120207
  • Item Weight ‏ : ‎ 1.79 pounds
  • Dimensions ‏ : ‎ 7 x 1.2 x 9.1 inches

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