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What would you do with 7 teraOPS of compute available for running your machine learning models on a mobile device?
That would really open up your options in robotics, edge computing, connected cameras and always-on applications, wouldn't it? Hardware acceleration can speed up neural network execution by orders of magnitude in use cases like image classification, object detection, face detection and speech recognition. It can pave the way for new, real-time use cases that otherwise wouldn't be possible, like live video enhancements and fast body tracking for games.
[Editor’s note: DigitalTrends.com is a comprehensive source of information about consumer electronics and technology. Its “Tech for Change” series of content shines a spotlight on technical innovations that make a meaningful impact. A recent article featured eSight Corp, whose electronic eyeglasses combine computer vision and augmented reality (AR) to help people see in spite of central vision loss.]
Qualcomm Developer Network September Developer of the Month is Claude Dareau from Framestore. Claude is a lead programmer at Framestore and his work centers around the development of rendering solutions for AR, VR, and XR applications.
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