What is TinyML, and why does it matter?
Learn the basic concept, the benefits, and where to start in this tiny revolution.
Tiny Machine Learning (or TinyML) is a machine learning technique that integrates reduced and optimized machine learning applications that require "full-stack" (hardware, system, software, and applications) solutions, including machine learning architectures, techniques, tools, and approaches capable of performing on-device analytics at the very edge of the cloud.
TinyML can be implemented in low-energy systems, such as sensors or microcontrollers to perform automated tasks.
With TinyML, we can do more with less. The technique is still ML, but with less energy and costs and without an internet connection.
A small device for a tremendous impact.
This could summarize Tiny Machine Learning (or TinyML), emerging breakthroughs within artificial intelligence, without exaggeration.
If we consider that, according to a forecast by ABI Research, by 2030, it is likely that around 2.5 billion devices will reach the market through…
