Correct me if I&#x27;m wrong but I get the impression is that Convolutional Neural Networks (cnn) are the constructs that have demonstrated a unique effectiveness for deep neural networks and have done this primarily through pattern recognition.<p>Recurrent NNs are a different beast, predicting sequential processes and so operating in an area closer to hidden Markov chain that have some successes but their operations and direction don&#x27;t seem as convnets.<p>Note that since the game of go is a sequence of moves, one might training a RNN to play go. However, AlphaGo (very roughly) used a Convnet to tell a Monte Carlo Tree structure which final positions looked good.<p>I&#x27;m going partly from: <a href="http:&#x2F;&#x2F;neuralnetworksanddeeplearning.com&#x2F;chap6.html#other_approaches_to_deep_neural_nets" rel="nofollow">http:&#x2F;&#x2F;neuralnetworksanddeeplearning.com&#x2F;chap6.html#other_ap...</a>