AI at the Edge

About the

Book

Fill out the form below to receive a physical copy of this practical guide to solving industrial, commercial, and scientific problems with edge AI. Designed for engineering professionals—including product managers and technology leaders—this guide provides an end-to-end framework for building real-world edge AI and embedded ML solutions. You’ll explore every stage of the process, from data collection and model optimization to tuning and testing, and learn how to design, deploy, and support edge AI products. As edge AI becomes a standard tool for systems engineers, this high-level roadmap helps you get started with confidence.

Readers will learn

Learn the benefits of edge AI and how to achieve value in less time while lowering operational costs

Build a team that leverages edge AI expertise to solve real-world problems

Understand which use cases are best solved with edge AI

Learn how to optimize ML at the edge and how it complements cloud ML

Design and operationalize data for edge AI applications

Learn an iterative workflow for developing AI systems

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About the authors

Daniel Situnayake

Director of Machine Learning, Edge Impulse

Daniel Situnayake is Director of Machine Learning at Edge Impulse, where he leads embedded machine learning R&D. He's coauthor of the book AI at the Edge: Solving Real-World Problems with Embedded Machine Learning, along with 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

Senior Developer Relations Engineer, Edge Impulse

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.