Why TinyML Is Such A Big Deal


Why TinyML Is Such A Big Deal

Why TinyML Is Such A Big Deal

“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, greatly accelerating the use of ML in all manner of devices and making those devices better, smarter, and more responsive to human interaction,” said Steve Roddy, vice president of product marketing for Arm‘s Machine Learning Group.

Only so many applications can be realized on systems with little memory and limited computing power, some of which will be battery-powered. But for those applications, there is a dedicated version of TensorFlow Lite and an ongoing stream of new ideas for implementing complex logic with a light footprint.

Based on the incredible attention being paid to complex edge inference platforms and raw power in the data center, it may seem like folly to try to do that same work in a meager platform. And yet a growing number of people are doing just that. So is TinyML a new hardware platform? A software tool? A completely new AI methodology? It’s none of the above, and some of each…”

Source: semiengineering.com/why-tinyml-is-such-a-big-deal/

September 3, 2021
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