Showing titles in Computer Science

Generative AI: The Insights You Need from Harvard Business Review will help you understand the potential of these new technologies, pick the right Gen AI projects, and reinvent your business for the new age of AI.

Something new entered our world in November 2022—the first general purpose AI that could pass for a human and do the kinds of creative, innovative work that only humans could do previously. Wharton professor Ethan Mollick immediately understood what ChatGPT meant: after millions of years on our own, humans had developed a kind of co-intelligence that could augment, or even replace, human thinking. Through his writing, speaking, and teaching, Mollick has become one of the most prominent and provocative explainers of AI.

ChatGPT Profits: The Blueprint to Becoming a Millionaire Using Artificial Intelligence by Jonathan Green is your ultimate guide to leveraging AI for your benefit. It's a comprehensive resource that takes you from being a beginner to becoming a proficient user of ChatGPT.

We are approaching a critical threshold in the history of our species. Soon you will live surrounded by AIs. They will organize your life, operate your business, and run core government services. You will live in a world of DNA printers and quantum computers, engineered pathogens and autonomous weapons, robot assistants and abundant energy. None of us are prepared. As co-founder of the pioneering AI company DeepMind, Mustafa Suleyman has been at the center of this revolution. The coming decade, he argues, will be defined by this wave of powerful, fast-proliferating new technologies.

Paul Scharre, a Pentagon defense expert and former U.S. Army Ranger, explores what it would mean to give machines authority over the ultimate decision of life or death. Scharre's far-ranging investigation examines the emergence of autonomous weapons, the movement to ban them, and the legal and ethical issues surrounding their use. Through interviews with defense experts, ethicists, psychologists, and activists, Scharre surveys what challenges might face "centaur warfighters" on future battlefields.

Artificial intelligence may be the most transformative technology of our time. As AI’s power grows, so does the need to figure out what—and who—this technology is really for. AI Needs You argues that it is critical for society to take the lead in answering this urgent question and ensuring that AI fulfills its promise.

The Age of Surveillance Capitalism is neither a hand-wringing narrative of danger and decline nor a digital fairy tale. Rather, it offers a deeply reasoned and evocative examination of the contests over the next chapter of capitalism that will decide the meaning of information civilization in the 21st century. The stark issue at hand is whether we will be the masters of information and machines or its slaves.

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: The union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

What does it mean to be smart? To be human? What do we really want from life and the intelligence we have, or might create? With deep and exclusive reporting, across hundreds of interviews, New York Times Silicon Valley journalist Cade Metz brings you into the rooms where these questions are being answered. Where an extraordinarily powerful new artificial intelligence has been built into our biggest companies, our social discourse, and our daily lives, with few of us even noticing.

Will AI lead to the transformation of society as we know it, or bring about its destruction?

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.

Artificial intelligence does the seemingly impossible - driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses map-like structures to build a model of the world - not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

Claude Shannon was a tinkerer, a playful wunderkind, a groundbreaking polymath, and a digital pioneer whose insights made the Information Age possible. He constructed fire-breathing trumpets and customized unicycles, outfoxed Vegas casinos, and built juggling robots, but he also wrote the seminal text of the Digital Revolution. That work allowed scientists to measure and manipulate information as objectively as any physical object. His work gave mathematicians and engineers the tools to bring that world to pass.

A new industrial revolution has begun. Like mechanization or electricity before it, artificial intelligence will touch every aspect of our lives—and cause profound disruptions in the balance of global power, especially among the AI superpowers: China, the United States, and Europe. Autonomous weapons expert Paul Scharre takes listeners inside the fierce competition to develop and implement this game-changing technology and dominate the future.

Science journalist Sally Adee breaks open the field of bioelectricity—the electric currents that run through our bodies and every living thing—its misunderstood history, and why new discoveries will lead to new ways around antibiotic resistance, cleared arteries, and new ways to combat cancer.

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.