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Creating Machine Learning models for deployment on constrained devices requires a considerable number of manual tweaks. Developers need to take into account the size and compute constraints of the target platform to adjust...
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While the advent of Large Language Models has brought significant leaps in many areas including text analysis and computer vision, translating to benefits across a variety of industries, the size of the models can be a limitation...
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For complex ML systems involving many sensors (e.g. cameras, depth sensors, accelerometers), interconnected algorithms and a sophisticated control flow, system performance monitoring is a challenging problem. To architect these...
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Neural networks are a powerful tool for processing noisy and unstructured sensor data like camera frames, accelerometer or biometric readings, which makes them perfect for preprocessing or decision making on edge devices, where...
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Today at the RISC-V Summit in Santa Clara, we’re pleased to participate in Google’s announcement of the open source release of project Open Se Cura. The announcement crowns a many-year collaboration towards developing a secure...
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With a rapid increase in interest in adding edge Machine Learning capabilities to consumer-facing as well as industrial devices - brought about by the rapid advances in deep learning and now also LLMs, the increasing compute...
