Here's another look at the competing 'camps' in machine learning, this time depicted by Jason Eisner as three in number, and based on real work in the field: classical, Baysean, and deep learning. Also interesting in this article is the brief account of the history of dividing fields of study into distinct 'cultures', as well as the division of progress into 'stages' or 'steps'. The two are often related: "Jason presents his intellectual simplex in an a-historical frame, but of course there has been a temporal sequence, as the term 'classical' suggests."

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