  PAQ8 is an open source lossless data compression algorithm that currently
achieves the best compression rates on many benchmarks. This report presents a
detailed description of PAQ8 from a statistical machine learning perspective.
It shows that it is possible to understand some of the modules of PAQ8 and use
this understanding to improve the method. However, intuitive statistical
explanations of the behavior of other modules remain elusive. We hope the
description in this report will be a starting point for discussions that will
increase our understanding, lead to improvements to PAQ8, and facilitate a
transfer of knowledge from PAQ8 to other machine learning methods, such a
recurrent neural networks and stochastic memoizers. Finally, the report
presents a broad range of new applications of PAQ to machine learning tasks
including language modeling and adaptive text prediction, adaptive game
playing, classification, and compression using features from the field of deep
learning.
