AI Model Training & Execution Now Possible on MCUs via ONE Tech MicroAI Atom

By Brandon Lewis

Editor-in-Chief

Embedded Computing Design

July 31, 2020

Blog

AI Model Training & Execution Now Possible on MCUs via ONE Tech MicroAI Atom

ONE Tech estimates that MicroAI Atom algorithms, which run recursive analysis and reside directly on target MCUs at the edge, reduce the cost of deploying endpoint intelligence by a minimum of 80%.

ONE Tech has updated its MicroAI Atom multi-dimensional behavioral algorithms to allow AI models to be both trained and executed directly on MCUs. ONE Tech estimates that MicroAI Atom algorithms, which run recursive analysis and reside directly on target machines at the edge, reduce the cost of deploying endpoint intelligence by a minimum of 80 percent.

“AI models have been largely trained in GPU server environments in the cloud. Training and running a model on an MCU has not been seen before in the industry," says Yasser Khan, CEO of ONE Tech. "[MicroAI Atom] allows AI and predictive maintenance to move from MPU-based devices to MCU-based devices, with a small footprint and significantly lower price point."

In addition to cost savings, the ability to perform tasks on MCUs that were previously only available on MPUs allows IoT and industrial OEMs to develop differentiated solutions that include real-time alerts, edge analytics for asset optimization, increased data privacy, and enhanced cyber security.

For more information, visit www.onetech.ai/en/resources/product-docs/atom-product.

Brandon is responsible for guiding content strategy, editorial direction, and community engagement across the Embedded Computing Design ecosystem. A 10-year veteran of the electronics media industry, he enjoys covering topics ranging from development kits to cybersecurity and tech business models. Brandon received a BA in English Literature from Arizona State University, where he graduated cum laude. He can be reached at [email protected].

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