While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at implementing machine learning on severely resource-constrained systems.
Known as TinyML, it’s both a concept and an organization — and it has acquired significant momentum over the last year or two.
“TinyML deployments are powering a huge growth in ML deployment,…