In 1936, Alan Turing, a then young mathematician, published a paper that would fundamentally alter the course of computing and, indeed, human history. The paper, titled On Computable Numbers, with an Application to the Entscheidungs-problem, introduced concepts that would lay the groundwork for modern computer science. Turing's work addressed a critical question posed by David Hilbert: the Entscheidungs-problem, or "decision problem," which asks whether there exists a definitive method that can determine the truth of any given mathematical statement.

In 1965, Gordon E. Moore, co-founder of Intel, penned a pivotal article titled "Cramming More Components onto Integrated Circuits," which appeared in *Electronics Magazine*. This article not only demonstrated keen observation and prediction about the future of computing hardware but also laid the groundwork for what would later be coined as "Moore's Law." In this concise yet influential piece, Moore outlined his observation that the number of transistors on integrated circuits had doubled every year since their invention and predicted that this trend would continue for at least another decade.

In March 1989, Tim Berners-Lee, a software engineer at CERN, the European Organization for Nuclear Research, wrote a relatively modest but profoundly influential document titled "Information Management: A Proposal." This document laid the groundwork for what would eventually become the World Wide Web, a system that has since transformed virtually every aspect of modern life, from communication to commerce, and beyond. Berners-Lee's proposal aimed to address the growing problem of information loss and inefficiency at CERN due to the high turnover of staff and the vast array of incompatible information systems.

In 1998, two Stanford University graduate students, Sergey Brin and Larry Page, authored a groundbreaking research paper titled "The Anatomy of a Large-Scale Hypertextual Web Search Engine." This paper not only introduced the world to the Google search engine but also outlined a novel approach to solving one of the internet’s most challenging problems: finding relevant information quickly and efficiently in an ever-expanding sea of data.

In 1998, a landmark legal document emerged in the annals of U.S. antitrust law: the "Complaint: U.S. v. Microsoft Corp." This complaint, filed by the United States Department of Justice (DOJ) along with 20 U.S. states, marked the beginning of one of the most significant antitrust cases in modern American history. The core of the lawsuit was the accusation that Microsoft had engaged in anti-competitive and exclusionary practices aimed at maintaining its monopoly in the operating system market, particularly concerning its handling of web browser sales tied to its Windows operating system.

In 2008, amidst a global financial crisis that shook trust in traditional banking systems, a pseudonymous individual or group known as Satoshi Nakamoto published a white paper titled "Bitcoin: A Peer-to-Peer Electronic Cash System." This seminal document proposed a revolutionary form of digital currency—Bitcoin—that could operate independently of any central authority. The white paper laid the groundwork for what would become the first decentralized cryptocurrency.

In 2017, a groundbreaking research paper titled "Attention is All You Need" was published by Ashish Vaswani and his team of co-authors. This work introduced the Transformer model, a novel deep learning architecture that significantly deviated from the then-standard recurrent neural networks (RNNs) and convolutional neural networks (CNNs) used in natural language processing (NLP). The Transformer model, by focusing solely on attention mechanisms—specifically, a mechanism called "self-attention"—enabled better handling of dependencies in input data, offering a substantial improvement in processing efficiency and model performance.

A compelling and rigorously detailed examination of the modern antitrust issues posed by Amazon, one of the largest and most influential companies in the world. Published in the Yale Law Journal in 2017, Khan's article challenges the traditional frameworks used in antitrust law, arguing that they fail to recognize or address the type of market power and consumer harm that Amazon could wield.