How to choose the right Edge AI framework for your project

There are several open-source AI frameworks on the market. Their capabilities and characteristics vary considerably with performance, coding language, pre-trained models, commercial support, licensing terms etc.

For some application use-cases, it may be necessary to concurrently support more than one AI framework with interoperability solutions such as Open Neural Network Exchange (ONNX). ONNX supports framework interoperability with shared models and operators.

The solutions range from discrete semiconductor devices to off-the-shelf modular development platforms.

The most popular AI frameworks presently on the market include Keras, MixNet, PyTorch (inc. Caffe 2) and TensorFlow (inc. TensorFlow Lite).

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