H. Peter Alesso – författare

"In their fascinating analysis of the recent history of information technology, H. Peter Alesso and Craig F. Smith reveal the patterns in discovery and innovation that have brought us to the present tipping point. . . . A generation from now, every individual will have personally tailored access to the whole of knowledge . . . the sooner we all begin to think about how we got here, and where we're going, the better. This exciting book is an essentialfirst step."—From the Foreword by James BurkeMany people envision scientists as dispassionate characters who slavishly repeat experiments until "eureka"—something unexpected happens. Actually, there is a great deal more to the story of scientific discovery, but seeing "the big picture" is not easy. Connections: Patterns of Discovery uses the primary tools of forecasting and three archetypal patterns of discovery—Serendipity, Proof of Principle, and 1% Inspiration and 99% Perspiration—to discern relationships of past developments and synthesize a cohesive and compelling vision for the future. It challenges readers to think of the consequences of extrapolating trends, such as Moore's Law, to either reach real machine intelligence or retrench in the face of physical limitations. From this perspective,the book draws "the big picture" for the Information Revolution's innovations in chips, devices, software, and networks.With a Foreword by James Burke and bursting with fascinating detail throughout, Connections: Patterns of Discovery is a must-read for computer scientists, technologists, programmers, hardware and software developers, students, and anyone with an interest in tech-savvy topics.

What Is Thinking? What is Turing's Test? What is Gödel's Undecidability Theorem? How is Berners-Lee's Semantic Web logic going to overcome paradoxes and complexity to produce machine processing on the Web?Thinking on the Web draws from the contributions of Tim Berners-Lee (What is solvable on the Web?), Kurt Gödel (What is decidable?), and Alan Turing (What is machine intelligence?) to evaluate how much "intelligence" can be projected onto the Web.The authors offer both abstract and practical perspectives to delineate the opportunities and challenges of a "smarter" Web through a threaded series of vignettes and a thorough review of Semantic Web development.