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ONNX Runtime: It’s an open-supply inference motor for working machine learning models on various platforms. This consists of embedded devices. It’s optimized for performance and efficiency, making it perfect for embedded AI applications.
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Real-time data processing: Embedded systems should be able to capture, review, and react to expanding volumes of data in real-time
Pinterest: Pinterest employs fancy tech from NVIDIA to make its search and recommendations superior. They made use of NVIDIA’s TensorRT software to make their recommendations occur faster, ML on embedded chips like 40% faster!
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Model complexity: Embedded devices frequently have restricted assets. So it could be tough to train intricate models on these devices.
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