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From medieval robots and Boolean algebra to artificial neural networks and adversarial patches, this fascinating illustrated history takes readers from past to present in the world of artificial intelligence. Across 100 illustrated entries on computing, medicine, and mythology, as well as on the threat to humanity should AI grow out of control, award-winning science author Clifford A. Pickover takes readers on a fascinating journey of how "AI" developed, where it's going, and how it's being adopted in popular culture.
A History of the Future that's Happening Right Now Artificial Intelligence: An Illustrated History explores the historic origins and current applications of AI in such diverse fields as computing, medicine, popular culture, mythology, and philosophy. Through more than 100 entries, award-winning author Clifford A. Pickover, offers a granular, yet accessible, glimpse into the world of AI—from medieval robots and Boolean algebra to facial recognition, and artificial neural networks. First released in 2019, this updated paperback edition brings readers up to speed with coverage of technologies such as DALL-E and ChatGPT, and it explores the very real fear that AI will alter the course of humanity—forever.
Every great advance in science has issued from a new audacity of imagination - John Dewey In A History of Science, Mary Cruse takes readers on a fascinating journey through the evolution of this discipline in its many strands. Throughout the centuries, our conception of what constitutes 'science' has developed hugely - from ancient natural philosophers and medieval alchemists to Renaissance scholars and Enlightenment reformers. Modern science evokes images of bubbling test tubes and spotless lab coats, but this limited perception inhibits us in truly understanding the progress of science throughout history. Cruse does not fall into this trap. Learn about the development of agricultural tools, the study of weather patterns, mapmaking, mathematics and modern geology. Delve into the cutting-edge science of the 21st century - genetic engineering, artificial intelligence, sustainable energy projects. Cruse even speculates on which breakthroughs are yet to come...
"The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
“A thrilling, fast-paced excursion through the history of physical discovery . . . from silly putty to string theory” (Dr. Paul Halpern, author of Collider). Following his previous volumes, The Science Book and The Math Book, acclaimed science writer Clifford Pickover returns with a richly illustrated chronology of physics, containing 250 short, entertaining, and thought-provoking entries. In addition to exploring such engaging topics as dark energy, parallel universes, the Doppler effect, the God particle, and Maxwells demon, The Physics Book extends back billions of years to the hypothetical Big Bang and forward trillions of years to a time of “quantum resurrection.” Like the previous titles in this series, The Physics Book offers a lively and accessible account of major concepts without getting bogged down in complex details.
Artificial Intelligence for Autonomous Networks introduces the autonomous network by juxtaposing two unique technologies and communities: Networking and AI. The book reviews the technologies behind AI and software-defined network/network function virtualization, highlighting the exciting opportunities to integrate those two worlds. Outlining the new frontiers for autonomous networks, this book highlights their impact and benefits to consumers and enterprise customers. It also explores the potential of the autonomous network for transforming network operation, cyber security, enterprise services, 5G and IoT, infrastructure monitoring and traffic optimization, and finally, customer experience and care. With contributions from leading experts, this book will provide an invaluable resource for network engineers, software engineers, artificial intelligence, and machine learning researchers.
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.
Can machines really think? Is the mind just a complicated computer program? Half a century of research into Artificial Intelligence has resulted in machines capable of beating the best human chess players and humanoid robots that can walk and interact with us. Yet exactly should we go about building a truly intelligent machine? Introducing Artificial Intelligence focuses on the major issues behind one of the hardest scientific problems ever undertaken.