In many of my previous posts I stressed, efficiency and local perspectives. Such emphasis can be traced back to faith in machines which reflects the faith of theoretical computer science community that polynomial amount of resources is efficient while exponential is not.
I love studying machines as the results can so much help understand ourselves (modulo communicable understanding). Computer Science provides a nice unified way for studying machine characteristics. This reminds me I have to finish one of my posts on language of thoughts :) It has a rough precursor which I posted about 2 years ago.
Practical and efficient statistics relies on Bayesian and Markovian principles which allow principled way of working by understanding limits of machines. It's amazing to know that lot of lower bound results in complexity theory and almost entire applied statistics can be traced back to the contributions of Markov brothers! All the extensions are non-trivial but behind the non-trivial efforts of later generations was the motivation based on faith in practicality or in more crisp words, machines.