Books like Internet dreams by Mark J. Stefik

Kurzweil explores the coming fusion of human minds with advanced machines, predicting that integrated intelligence will surpass current human capacity, shaping future society.

Brian McCullough chronicles the birth and explosive growth of the Internet, tracing its early 1993 origins in an Illinois basement to the rise of iconic innovators like Marc Andreessen and Mark Zuckerberg.

Pedro Domingos unveils the quest for a universal learning algorithm that could extract any knowledge from data, exploring how such a machine—the Master Algorithm—might reshape business, science, and society.

Ray Kurzweil surveys the rise of artificial intelligence, from philosophical roots to contemporary breakthroughs and future implications for science, society, and economy.

A practical handbook for today’s information‑churned consumers, teaching how to manage, filter, and effectively use digital data in the age of the internet and the information superhighway.

Exploring the physical infrastructure of the Internet and its historical figures and keepers of data.

This book is an eagle's eye view of the Internet edge. It is about the experiences of those who encountered similar issues as they built precursors to the Net such as videotext, teletext, and the Source.

How deep learning-from Google Translate to driverless cars to personal cognitive assistants-is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

Author Klaus Schwab explores how the fourth industrial revolution—a convergence of AI, biotechnology, nanotechnology and digital networks—will reshape society, economy and identity, urging a future where technology serves humanity within ethical bounds.