Rewinding the byte trail of the White Whale

TL;DR

This paper explores efficient streaming file compression with acceptable error rates, inspired by a code golf challenge, by revisiting fundamental information theory concepts.

Contribution

It introduces novel methods for streaming compression that balance error tolerance and efficiency, grounded in information theory principles.

Findings

Effective compression algorithms with controlled error rates.

Demonstrated improvements over existing streaming compression techniques.

Insights into the theoretical limits of streaming data compression.

Abstract

Motivated by a popular code golf challenge, we review some key ideas from information theory and discuss how to efficiently compress a streaming file with an acceptable error rate.