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ONE Tech Launches World¡¯s First Edge AI that Embeds and Trains AI Models Directly on MCU¡¯s

AI-driven solution allows users to train a machine learning model directly on billions of limited-compute power devices
´º½ºÀÏÀÚ: 2021-01-15

DALLAS-- January 15, 2021 -- ONE Tech, a global leader in edge AI technology, today announced the launch of the MicroAI™ Atom Software Development Kit (SDK), which is now publicly available through the ONE Tech developer portal. This SDK download allows users to implement ONE Tech’s machine learning platform—MicroAI™ Atom—directly onto microcontroller unit (MCU)-based hardware.

The MicroAI™ Atom SDK brings intelligence to the endpoint—the source of data—which accelerates machine learning model formation and adoption while lowering overall cost of deploying AI-driven solutions.

The MicroAI™ Atom SDK enables uses cases for assets including:

· Connected devices (IoT devices, phones, handheld computers)
· Industrial machinery (robotic arms, welders, material handlers, motors)
· Utility infrastructure (smart meters, transformers, water treatment facilities)
· Household appliances (washers, dryers, refrigerators)
· Automotive (vehicles, heavy equipment)

In a manufacturing use case, for example, there is a critical need to bring intelligence to manufacturing facilities, but existing methods require an overhaul of hardware—an expensive proposition. With the MicroAI™ Atom SDK, these capabilities are available in a low-compute MCU, allowing existing hardware to support machine learning and predictive maintenance to these facilities quickly and cost-effectively.

“This SDK for MicroAI™ Atom is one of a kind, greatly improving time to market with asset performance management and predictive maintenance use cases while lowering the overall cost of deployment via elimination of expensive hardware needed to run and train the model,” said ONE Tech CEO Yasser Khan. “Our team of engineers brought this technology to life and created the framework for developers across the globe to enable intelligence at the asset.”



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