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[D] Neuroevolution and Deep Learning Comparison

Does anyone have a benchmark/comparison of a neuroevolution algorithm for machine learning such as NEAT and a more traditional deep learning approach? Preferably an interactive one that features many different kinds of tasks and tracks the performance of different sizes of models as they train. I have done some experiments with genetic algorithms in the past and would like to see if they provide any long-term advantages over gradient-descent based methods at any type of problem. Any help would be appreciated. (Repost because forgot to tag post the first time.)

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.