A highly mathematical investigation of the mathematical underpinnings of the attention economy. Valuable reading for anyone interested in the topic, and a revealing glimpse at the level of resources and insight available to governments via organizations like the funder of this project, the Air Force Research Laboratory. The reader should expect to: - Gain valuable insights into the mathematical underpinnings of online attention markets and fair attention allocation, addressing the pressing issue of attention scarcity in an information-rich world. - Understand the novel neural model called Radflow that tackles the challenges of modeling networks of time series, providing valuable insights and predictions in domains like social networks, transportation systems, and financial markets. - Explore the comprehensive analysis of media consumption patterns and political dynamics during the COVID-19 pandemic, shedding light on media influence, political polarization, and the diversity of audience leanings, contributing to a more informed understanding of current public issues. This annotated edition illustrates the capabilities of the AI Lab for Book-Lovers to add context and ease-of-use to manuscripts. It includes several types of abstracts, building from simplest to more complex: TLDR (one word), ELI5, TLDR (vanilla), Scientific Style, and Action Items; essays to increase viewpoint diversity, such as Grounds for Dissent, Red Team Critique, and MAGA Perspective; and Notable Passages and Nutshell Summaries for each page.