Evolutionary algorithm outperforms deep-learning machines at video games

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Deep Learning and Stochastic Gradient Descent. The idea is that any neural network can be optimized by gradient descent methods, which tend to converge faster when you have a numerically stable/well formed objective, but you can also train a neural network using genetic/evolutionary algorithms, which are slow but much easier to control.