The Science of Information: From Language to Black Holes

The meaning of information; American mathematician Claude Shannon concludes that information is the ability to distinguish reliably among possible alternatives; the idea is revolutionary; it leads to the concept of the basic unit of information.

Claude Shannon goes to the Massachusetts Institute of Technology; he submits a master's thesis proving that Boolean algebra can simplify analogue computing devices; how to design a simple electronic circuit that performs mathematical calculations.

How information is measured; how it is encoded efficiently; entropy is vital to the science of information; measuring information in terms of entropy sheds light on everything from password security to efficient binary codes; how to design a game.

According to intuition, information is measured by looking at the length of a message; Shannon's information theory starts with something more fundamenta; discovering that entropy provides a measure of the average surprise.

The link between entropy and coding; Shannon's first fundamental theorem; how far information can be squeezed in a binary code; the basis for data compression; Conan Doyle's "The Return of Sherlock Holmes".

How some data can be compressed beyond the minimum amount of information required by the entropy of the source; techniques that reduce the size of a file without significant loss of quality; how this works in different formats.