2 min read

Almost after a week of Microsoft’s announcement about its plan to develop a computer vision develop kit for edge computing, Intel smartly introduced its latest offering, called OpenVINO in the domain of Internet of Things (IoT) and Artificial Intelligence (AI). This toolkit is a comprehensive computer vision solution, that brings computer vision and deep learning capabilities to the edge devices smoothly.

OpenVINO (Open Visual Inference and Neural Network Optimization) toolkit supports popular open source frameworks like OpenCV, Caffe and TensorFlow. It supports and works with Intel’s traditional CPUs, AI chips, field programmable gate array (FPGA) chips and Movidius vision processing unit (VPU).

The toolkit presumes the potential to address a wide number of challenges faced by developers in delivering distributed and end-to-end intelligence. With OpenVINO, developers can simply streamline their deep learning inferences and deploy high-performance computer vision solutions across a wide range of use-cases. Computer vision limitations related to bandwidth, latency and storage are expected to be resolved to an extent. This toolkit would also help developers in optimizing AI-integrated computer vision applications and scaling distributed vision applications which generally needs a complete redesign of solution.

Until now, edge computing has been more of a prospect for an IoT market. With OpenVINO, Intel stands as the the only industry leader in delivering IoT solutions from the edges, providing an unparalleled solution to meet AI needs of businesses. OpenVINO is already being used by companies like GE Healthcare, Dahua, Amazon Web Services and Honeywell across their Digital Imaging and IoT Solutions.

To explore more information on its capabilities and performance, visit Intel’s official OpenVINO product documentation.

A gentle note to readers: OpenVINO  is not to be confused with Openvino, an open-source winery and wine-backed cryptoasset, Openvino.

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Category Manager and tech enthusiast. Previously worked on global market research and lead generation assignments. Keeps a constant eye on Artificial Intelligence.


  1. Can I use my converted trained model using open vino to raspberry pi3 intel nuc?
    Will I get any problems if I start inferencing on pi. Can you please give procedure on how to inference on pi using openvino and intel nuc


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