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Amazon Open Sources SageMaker Neo to Run Machine Learning Models at the Edge


Abstract art.

Amazon's new Neo-AI is an open source project aiming to optimize the performance of machine learning models for numerous platforms.

Credit: Pixabay

Amazon has launched Neo-AI, a new open source project that aims to optimize the performance of machine learning (ML) models for numerous platforms.

Amazon SageMaker Neo was announced as an extension of Amazon SageMaker, an ML platform as a service. 

SageMaker initially targeted the training phase of ML models, and SageMaker Neo takes on the biggest challenge of optimizing ML models for diverse target environments, effectively closing the loop between the training and inference phases of ML models.

SageMaker Neo can compile ML models built using Apache MXNet, TensorFlow, and PyTorch, among others, needing only a fully-trained model and target platform as input parameters to generate a native, fully-optimized model ready for inference.

Currently, SageMaker Neo supports NVIDIA Jetson TX1, NVIDIA Jetson TX2, Raspberry Pi 3, and AWS DeepLens as target deployments, with support for Xilinx, Cadence, and Qualcomm coming soon.

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