-PDF Download- An Intuitive Exploration Of Artificial Intelligence EBOOK

An Intuitive Exploration of Artificial Intelligence

Author: Simant Dube

Publisher: Springer Nature

Published: 2021-06-21

Total Pages: 355

ISBN-13: 3030686248

This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.

Artificial Intuition

Author: Carlos Perez

Publisher: Createspace Independent Publishing Platform

Published: 2018-01-15

Total Pages: 394

ISBN-13: 9781983895647

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I challenge you to find a field as interesting and exciting as Deep Learning. This book is a spin-off from my previous book "The Deep Learning AI Playbook." The Playbook was meant for a professional audience. This is targeted to a much wider audience. There are two kinds of audiences, those looking to explore and those looking to optimize. There are two ways to learn, learning by exploration and learning by exploitation. This book is about exploration into the emerging field of Deep Learning. It's more like a popular science book and less of a business book. It's not going to provide any practical advice of how to use or deploy Deep Learning. However, it's a book that will explore this new field in many more perspectives. So at the very least, you'll walk away with the ability to hold a very informative and impressive conversation about this unique subject. It's my hope that having less constraints on what I can express can lead to a more insightful and novel book. There are plenty of ideas that are either too general or too speculative to fit within a business oriented book. With a business book, you always want to manage expectations. Artificial Intelligence is one of those topics that you want to keep speaking in a conservative manner. That's one reason I felt the need for this book. Perhaps the freedom to be more liberal can give readers more ideas as where this field is heading. Also, it's not just business that needs to understand Deep Learning. We are all going to be profoundly impacted by this new kind of Artificial Intelligence and it is critical we all develop at least a good intuition of how it will change the world.The images in the front cover are all generated using Deep Learning technology.

Practical Deep Learning for Cloud, Mobile, and Edge

Author: Anirudh Koul

Publisher: "O'Reilly Media, Inc."

Published: 2019-10-14

Total Pages: 585

ISBN-13: 1492034819

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Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Exploring Artificial Intelligence in the New Millennium

Author: Gerhard Lakemeyer

Publisher: Morgan Kaufmann

Published: 2003

Total Pages: 424

ISBN-13: 9781558608115

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This guide is a unique presentation of the spectrum of ongoing research in Artificial Intelligence. An ideal collection for personal reference or for use in introductory courses in AI and its subfields, "Exploring Artificial Intelligence in the New Millennium" is essential reading for anyone interested in the intellectual and technological challenges of AI.

Exploring Artificial Intelligence

Author: Howard E. Shrobe

Publisher: Morgan Kaufmann

Published: 1988

Total Pages: 728

ISBN-13:

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"Exploring Artificial Intelligence" is a unique presentation of the spectrum of research in Artificial Intelligence. Each self-contained chapter is based on a survey talk given at the National Conferences on Artificial Intelligence (AAAI 1986 & 1987). The original speakers, all leading researchers in their fields, have updated and revised their talks especially for this publication. Selected and edited to be accessible to students and nonspecialists, "Exploring Artificial Intelligence" preserves the informal character of the talks while presenting authoritative overviews of current research in critical subareas of AI. Individually, each lecture provides a penetrating exploration of a key area. Taken together, they offer a panorama of the field as a whole: its core issues, progress, and future directions. An ideal collection for personal reference or for use in introductory courses in AI and its subfields, "Exploring Artificial Intelligence" is essential reading for anyone interested in the intellectual and technological challenges of Artificial Intelligence.

Becoming Artificial

Author: Danial Sonik

Publisher: Andrews UK Limited

Published: 2020-11-24

Total Pages: 142

ISBN-13: 1788360524

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Becoming Artificial is a collection of essays about the nature of humanity, technology, artifice, and the irreducible connections between them. Artificial Intelligence (AI) was once the stuff of pure fantasy. Ideas about machines that could think seemed as plausible as space travel or inexpensive communication technology. The last two decades have introduced a number of game-changing innovations that make discussion of AI no longer a mere armchair speculation, but rather a serious topic of debate for everyone who will be affected, from policy makers to an increasingly displaced workforce. The growth in power of AI algorithms and systems has sparked many thought-provoking questions: Is there something fundamental to being human or are humans simply biological computers? Will AI continue to assist us or eventually enslave us? Can self-driving cars be legally responsible for their actions? And most importantly, how can we chart a path for AI that ensures a humane and beneficial future for society?

Can We Trust AI?

Author: Rama Chellappa

Publisher: JHU Press

Published: 2022-11-15

Total Pages: 224

ISBN-13: 142144531X

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Artificial intelligence is part of our daily lives. How can we address its limitations and guide its use for the benefit of communities worldwide? Artificial intelligence (AI) has evolved from an experimental computer algorithm used by academic researchers to a commercially reliable method of sifting through large sets of data that detect patterns not readily apparent through more rudimentary search tools. As a result, AI-based programs are helping doctors make more informed decisions about patient care, city planners align roads and highways to reduce traffic congestion with better efficiency, and merchants scan financial transactions to quickly flag suspicious purchases. But as AI applications grow, concerns have increased, too, including worries about applications that amplify existing biases in business practices and about the safety of self-driving vehicles. In Can We Trust AI?, Dr. Rama Chellappa, a researcher and innovator with 40 years in the field, recounts the evolution of AI, its current uses, and how it will drive industries and shape lives in the future. Leading AI researchers, thought leaders, and entrepreneurs contribute their expertise as well on how AI works, what we can expect from it, and how it can be harnessed to make our lives not only safer and more convenient but also more equitable. Can We Trust AI? is essential reading for anyone who wants to understand the potential—and pitfalls—of artificial intelligence. The book features: • an exploration of AI's origins during the post–World War II era through the computer revolution of the 1960s and 1970s, and its explosion among technology firms since 2012; • highlights of innovative ways that AI can diagnose medical conditions more quickly and accurately; • explanations of how the combination of AI and robotics is changing how we drive; and • interviews with leading AI researchers who are pushing the boundaries of AI for the world's benefit and working to make its applications safer and more just. Johns Hopkins Wavelengths In classrooms, field stations, and laboratories in Baltimore and around the world, the Bloomberg Distinguished Professors of Johns Hopkins University are opening the boundaries of our understanding of many of the world's most complex challenges. The Johns Hopkins Wavelengths book series brings readers inside their stories, illustrating how their pioneering discoveries and innovations benefit people in their neighborhoods and across the globe in artificial intelligence, cancer research, food systems' environmental impacts, health equity, planetary science, science diplomacy, and other critical arenas of study. Through these compelling narratives, their insights will spark conversations from dorm rooms to dining rooms to boardrooms.

Artificial Intelligence and Quantum Computing for Advanced Wireless Networks

Author: Savo G. Glisic

Publisher: John Wiley & Sons

Published: 2022-04-13

Total Pages: 884

ISBN-13: 111979031X

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ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.

Exploring Artificial Intelligence as a Field of Study

Author: Frye Dawn Henry

Publisher: Duchess Marketing Agency LLC

Published: 2024-06-08

Total Pages: 30

ISBN-13:

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Dive into the fascinating world of artificial intelligence (AI) with "Exploring Artificial Intelligence as a Field of Study." This book is perfect for beginners and enthusiasts looking to understand the basics of AI and its incredible potential. From the history and evolution of AI to its various types and applications, this book breaks down complex concepts into easy-to-understand language. Learn how AI works, and explore machine learning, neural networks, and natural language processing. Discover how AI is transforming industries, enhancing everyday life, and what ethical considerations come into play. Whether you're a student, a professional, or just curious about AI, this book provides valuable insights to help you get started in or consider the exciting field of artificial intelligence. Embark on your AI journey today with this informative and engaging book!

The Myth of Artificial Intelligence

Author: Erik J. Larson

Publisher: Harvard University Press

Published: 2021-04-06

Total Pages: 321

ISBN-13: 0674259920

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“Exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it.” —John Horgan “If you want to know about AI, read this book...It shows how a supposedly futuristic reverence for Artificial Intelligence retards progress when it denigrates our most irreplaceable resource for any future progress: our own human intelligence.” —Peter Thiel Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. A computer scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to reveal why this is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don’t correlate data sets. We make conjectures, informed by context and experience. And we haven’t a clue how to program that kind of intuitive reasoning, which lies at the heart of common sense. Futurists insist AI will soon eclipse the capacities of the most gifted mind, but Larson shows how far we are from superintelligence—and what it would take to get there. “Larson worries that we’re making two mistakes at once, defining human intelligence down while overestimating what AI is likely to achieve...Another concern is learned passivity: our tendency to assume that AI will solve problems and our failure, as a result, to cultivate human ingenuity.” —David A. Shaywitz, Wall Street Journal “A convincing case that artificial general intelligence—machine-based intelligence that matches our own—is beyond the capacity of algorithmic machine learning because there is a mismatch between how humans and machines know what they know.” —Sue Halpern, New York Review of Books