Navigating Probabilistic Modeling and Online Learning

This chapter explores the nuances of probabilistic modeling, focusing on the differences between static and streaming data. It emphasizes online models that adapt in real-time, discusses the role of feature selection, and highlights the challenges of integrating new information. Additionally, it covers the limitations of automated solutions and the complexities involved in scaling expert systems toward artificial general intelligence.