No Starch Press releases Embedded AI book on adding machine learning to resource-constrained devices

The announcement introduces a new technical book, "Embedded AI," that consolidates decades of embedded engineering experience into a practical guide for adding AI to edge hardware. The book's scope includes hardware choice, data collection, model deployment, and system integration, addressing the full lifecycle that engineers typically handle in isolation. By publishing the content in September 2026, the author provides a timely resource as demand for on-device intelligence grows. Adopting the book's methodology requires access to common development boards, most projects rely on an Arduino UNO or a Raspberry Pi Pico, with a few using specialized boards. The required software stack is freely available, including Python with TensorFlow, the Arduino IDE, and the Pico SDK, so there are no direct licensing costs. However, engineers must invest time in acquiring the hardware, setting up the toolchain, and working through the hands-on projects to internalize the concepts. The guide explicitly acknowledges the limits of embedded platforms: when a breadboard connection is flaky, sensor data is noisy, or the tensor arena is too small, the designs will fail. These constraints mean th