So far, we have seen how autoencoders are able to learn a reduced representation of the input data. It is natural to think that autoencoders can do a good job at generalized data compression. However, that is not the case. Autoencoders are poor at generalized data compression, such as image compression (that is, JPEG) and audio compression (that is, MP3), because the learned latent representation only represents the data on which it was trained. In other words, autoencoders only work well for images similar to those on which it was trained.
Furthermore, autoencoders are a "lossy" form of data compression, which means that the output from autoencoders will have less information when compared to the original input. These characteristics mean that autoencoders are poor at being generalized data compression techniques. Other forms of data...
