Data Science, Machine Learning, AI, Data, Autoencoder.
28x28 image, the image is shrunk down into a 512-dimensional vector, then again into a two-dimensional vector by the encoder. The decoder takes the output of the encoder and attempts to recreate the original 28x28 image. Reducing the dimensionality of input like this can be extremely useful.