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There is an existence of a loss/reward function for any task that can be evaluated, but this does not mean that function generalizes to any model. In your prompt you mention "human-level performance", this assumes a metric such as accuracy, auc, precision, winning %, etc that humans were evaluated on for some task. Since it is possible to model any ...


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I will give you a few scenarios where matrix factorisation stills works pretty well. Topic Modelling : Given a matrix of Document as Rows and Terms/Words as column you can use Non Negative Matrix factorisation to identify Topics. Number of Topics is defined by user or can be treated as hyperparameter. Image Ref : https://towardsdatascience.com/nmf-a-visual-...


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