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Steve Steele, Director of Platforms in the Machine Learning Group at Arm, presents the “Project Trillium: A New Suite of Machine Learning IP from Arm” tutorial at the May 2018 Embedded Vision Summit.

Machine learning processing engines today tend to focus on specific device classes or the needs of individual sectors. Arm’s Project Trillium changes that by offering ultimate scalability. While the initial launch focuses on mobile processors, future Arm ML products will deliver the ability to move up or down the performance curve–from sensors and smart speakers, to mobile, home entertainment and beyond.

Project Trillium comprises a suite of Arm IP including ML and object detection processors and Arm NN, a SW stack supporting ML across a wide range of Arm and other hardware IP. The Arm ML processor is built specifically for machine learning, based on a highly scalable architecture that can target ML across a wide range of performance points. The Arm OD processor efficiently identifies people and other objects with virtually unlimited detections per frame. And Arm NN serves as a bridge between neural network frameworks and the underlying hardware by leveraging a library of highly optimized NN primitives.

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