What is TinyML?
TL;DR
Machine learning that runs on ultra-small devices like microcontrollers. Essential for IoT and wearable applications.
TinyML: Definition & Explanation
TinyML (Tiny Machine Learning) is a technology that enables machine learning models to run on ultra-small, low-power devices such as microcontrollers (MCUs). It can perform inference with just kilobytes to megabytes of memory, consuming sub-milliwatt power levels. Representing the extreme edge of edge AI, TinyML enables real-time inference without an internet connection. Frameworks such as TensorFlow Lite for Microcontrollers, Edge Impulse, and Arduino ML are commonly used. Applications are expanding in power- and size-constrained environments including health monitoring on wearable devices, voice recognition in smart home devices, anomaly detection in agricultural IoT sensors, and predictive maintenance in factory equipment.