There are 250 billion micro-controllers in the world today. 28.1 billion units were sold in 2018 alone, and IC Insights forecasts annual shipment volume to grow to 38.2 billion by 2023.
What if they all became smart? How would that change our world?
TinyML broadly encapsulates the field of machine learning technologies capable of performing on-device analytics of sensor data at extremely low power. Between hardware advancements and the TinyML community’s recent innovations in machine learning, it is now possible to run increasingly complex deep learning models (the foundation of most modern artificial intelligence applications) directly on microcontrollers. A quick glance under the hood shows this is fundamentally possible because deep learning models are compute-bound, meaning their efficiency is limited by the time it takes to complete a large number of arithmetic operations. Advancements in TinyML have made it possible to run these models on existing microcontroller hardware.