Scaling of Information in Natural Language - 2004

Explore the intriguing relationship between semantic accuracy and communication efficiency in natural language through a novel technique presented in this lecture. Delve into the application of Shannon's information theory to analyze large linguistic corpora, uncovering a scaling relation that quantifies how words are semantically refined in human language. Learn about the information bottleneck method and its role in hierarchical clustering of words to capture semantic representation complexity. Discover potential implications for understanding human cognition across various complex modalities such as music and mathematics. Gain insights from Dr. Naftali Tishby, an expert in the intersection of computer science, statistical physics, and computational biology, as he discusses his research on the foundations of biological information processing and introduces conceptual frameworks for data representation and learning algorithms based on information theory.