Interpreting Foundation Models as Compressed Representations of Training Data: Implications for Copyright Law

The training process of foundation models can be interpreted as a form of data compression, where the model's weights represent a compressed version of the training data. This perspective has significant implications for understanding the copyright status of the model weights and the outputs generated by the model.