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

July 30, 2020 Brandon Lewis

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.

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About the Author

Brandon Lewis

Brandon Lewis, Editor-in-Chief of Embedded Computing Design, is responsible for guiding the property's content strategy, editorial direction, and engineering community engagement, which includes IoT Design, Automotive Embedded Systems, the Power Page, Industrial AI & Machine Learning, and other publications. As an experienced technical journalist, editor, and reporter with an aptitude for identifying key technologies, products, and market trends in the embedded technology sector, he enjoys covering topics that range from development kits and tools to cyber security and technology business models. Brandon received a BA in English Literature from Arizona State University, where he graduated cum laude. He can be reached by email at

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