mathematical theory from the field of probability theory and statistics
Information theory is a branch of mathematics that uses probability and statistics to measure and understand how much information is contained in messages, data, or signals. It matters because it provides precise tools for figuring out how efficiently information can be communicated, stored, or processed—which is fundamental to everything from computer science to telecommunications.
AI-generated from the Wikipedia summary — may contain errors.
Information theory is the mathematical study of the quantification, storage, and communication of a particular type of mathematically defined information. The field was established and formalized by Claude Shannon in the 1940s, though early contributions were made in the 1920s through the works of Harry Nyquist and Ralph Hartley.
Information theory was initially formed in the context of telecommunication but soon found a wide range of other applications. It is now at the intersection of mathematics, statistics and computer science, and has applications in diverse fields ranging from electrical engineering and physics to neurobiology.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).