TinyML is Breathing Life into Billions of Devices

Until now, building machine learning (ML) algorithms for hardware meant complex mathematical modes based on sample data, known as training data, to make predictions or decisions without being explicitly programmed to do so. And this is as complex and expensive to build as it sounds. On top of that, ML-related tasks were traditionally translated to the cloud; creating latency, consuming scarce power, and putting machines at the mercy of connection speeds. 

Combined, these constraints made computing slower, more expensive, and less predictable. Tiny Machine Learning (TinyML) is the latest embedded software technology that moves hardware into an almost magical realm, where machines can automatically learn and grow through use, like a primitive human brain.