In previous Radars, we've written about TinyML — the practice of running trained models on small devices with onboard sensors to make decisions or extract features without a roundtrip to the cloud. Edge Impulse has made the process of collecting sensor data and then training and deploying a model as simple as possible. Edge Impulse is an end-to-end hosted platform for developing models optimized to run on small edge devices such as microcontrollers. The platform guides the developer through the entire pipeline, including the task of collecting and labeling training data. They've made it easy to get started using your mobile phone for both data collection and running the classifier while the model training and refining happens in the more powerful, cloud-hosted environment. The resulting recognition algorithms can also be optimized, compiled and uploaded to a wide range of microcontroller architectures. Although Edge Impulse is a commercial venture, the platform is free for developers and makes the entire process fun and engaging even for those who are new to machine learning. The low barrier of entry to creating a working application means that we'll be seeing more edge devices with smart decisioning built in.