Why a restricted Boltzman machine (RBM) tends to learn very similar weights?
A restricted Boltzmann machine (RBM) learns a lossy compression of the original inputs or in other words, a probability distribution.

Those are 4 different weight matrices are all reduced dimension representations of the original face inputs. If you visualized the weights as a probability distribution, the distributions value would be different but they would have the same amount of loss from the original image reconstruction.