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Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
A fascinating look at Artificial Intelligence, from its humble Cold War beginnings to the dazzling future that is just around the corner. When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate. In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible--and possibly terrifying--future that's much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.
Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches. - An evolutionary approach provides a unifying theme - Thorough coverage of important AI ideas, old and new - Frequent use of examples and illustrative diagrams - Extensive coverage of machine learning methods throughout the text - Citations to over 500 references - Comprehensive index
Recent findings about the capabilities of smart animals such as corvids or octopi and novel types of artificial intelligence (AI), from social robots to cognitive assistants, are provoking the demand for new answers for meaningful comparison with other kinds of intelligence. This book fills this need by proposing a universal theory of intelligence which is based on causal learning as the central theme of intelligence. The goal is not just to describe, but mainly to explain queries like why one kind of intelligence is more intelligent than another, whatsoever the intelligence. Shiny terms like "strong AI," "superintelligence," "singularity" or "artificial general intelligence" that have been coined by a Babylonian confusion of tongues are clarified on the way.
The story of the U.S. Department of Defense's extraordinary effort, in the period from 1983 to 1993, to achieve machine intelligence.
What kind of AI? -- The big puzzle -- Knowledge and behavior -- Making it and faking it -- Learning with and without experience -- Book smarts and street smarts -- The long tail and the limits to training -- Symbols and symbol processing -- Knowledge-based systems -- AI technology
Examines the diagnostic process to question how we understand autism as a category and to better recognize its intelligence and uncommon sense. As autism has become a widely prevalent diagnosis, we have grown increasingly desperate to understand it. Whether by placing baseless blame on vaccinations or seeking a genetic cause, Americans have struggled to understand what autism is and where it comes from. In Autistic Intelligence, Douglas Maynard and Jason Turowetz focus on a different origin of autism: the diagnostic process. By looking at how autism is diagnosed, they ask us to question the norms we use to measure autistic behavior against, why we understand autistic behavior as disordered, and how we go about assigning that disorder to particular people. To do so, the authors take a close look at a clinic in which children are assessed for and diagnosed with autism. Their research draws on hours observing assessment evaluations among psychologists, pediatricians, parents, and children in order to make plain the systems, language, and categories that clinicians rely upon when making their assessments. Those diagnostic tools determine the kind of information doctors can gather about children, and indeed, those assessments affect how children act. Autistic Intelligence shows that autism is not a stable category, but the result of an interpretive act, and in the process of diagnosing children with autism, we often miss all of the unique contributions they make to the world around them.
What is Artificial Intelligence (AI)? What can it do and how is it created? In this highly accessible guide to the subject, Richard Urwin bases his assessment of AI on the definition of AI as a tool that is 'constructed to aid or substitute for human thought'. He explains how AI came about, the importance of the development of the computer and then examines how AI has developed over the years through the construction of computer programs and how the language used to construct these programs has become more and more sophisticated, thus allowing AI to become better and better. Along the way, you will discover numerous intriguing examples of how scientists have progressed the development of AI, learn about Fuzzy Logic and the ups and downs of computer programming, as well as finding out how research into brain function is continually influencing the field of AI. By turns fascinating and scary, Artificial Intelligence will take the reader on an amazing journey that covers everything from the habits of ants to the world of the stock market.
In a captivating memoir, an Egyptian American visionary and scientist provides an intimate view of her personal transformation as she follows her calling—to humanize our technology and how we connect with one another. LONGLISTED FOR THE PORCHLIGHT BUSINESS BOOK AWARD • “A vivid coming-of-age story and a call to each of us to be more mindful and compassionate when we interact online.”—Arianna Huffington NAMED ONE OF THE BEST BOOKS OF THE YEAR BY PARADE Rana el Kaliouby is a rarity in both the tech world and her native Middle East: a Muslim woman in charge in a field that is still overwhelmingly white and male. Growing up in Egypt and Kuwait, el Kaliouby was raised by a strict father who valued tradition—yet also had high expectations for his daughters—and a mother who was one of the first female computer programmers in the Middle East. Even before el Kaliouby broke ground as a scientist, she broke the rules of what it meant to be an obedient daughter and, later, an obedient wife to pursue her own daring dream. After earning her PhD at Cambridge, el Kaliouby, now the divorced mother of two, moved to America to pursue her mission to humanize technology before it dehumanizes us. The majority of our communication is conveyed through nonverbal cues: facial expressions, tone of voice, body language. But that communication is lost when we interact with others through our smartphones and devices. The result is an emotion-blind digital universe that impairs the very intelligence and capabilities—including empathy—that distinguish human beings from our machines. To combat our fundamental loss of emotional intelligence online, she cofounded Affectiva, the pioneer in the new field of Emotion AI, allowing our technology to understand humans the way we understand one another. Girl Decoded chronicles el Kaliouby’s journey from being a “nice Egyptian girl” to becoming a woman, carving her own path as she revolutionizes technology. But decoding herself—learning to express and act on her own emotions—would prove to be the biggest challenge of all.