The Descent Of Artificial Intelligence
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The Descent Of Artificial Intelligence
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Author : Kevin Padraic Donnelly
language : en
Publisher: University of Pittsburgh Press
Release Date : 2024-07-15
The Descent Of Artificial Intelligence written by Kevin Padraic Donnelly and has been published by University of Pittsburgh Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-15 with Science categories.
The idea that a new technology could challenge human intelligence is as old as the warning from Socrates and Plato that written language eroded memory. With the emergence of generative artificial intelligence programs, we find ourselves once again debating how a new technology might influence human thought and behavior. Researchers, software developers, and “visionary” tech writers even imagine an AI that will equal or surpass human intelligence, adding to a sense of technological determinism where humanity is inexorably shaped by powerful new machines. But among the hundreds of essays, books, and movies that approach the question of AI, few have asked how exactly scientists and philosophers have codified human thought and behavior. Rather than focusing on technical contributions in machine building, The Descent of Artificial Intelligence explores a more diverse cast of thinkers who helped to imagine the very kind of human being that might be challenged by a machine. Kevin Padraic Donnelly argues that what we often think of as the “goal” of AI has in fact been shaped by forgotten and discredited theories about people and human nature as much as it has been by scientific discoveries, mathematical advances, and novel technologies. By looking at the development of artificial intelligence through the lens of social thought, Donnelly deflates the image of artificial intelligence as a technological monolith and reminds readers that we can control the narratives about ourselves.
The Descent Of Artificial Intelligence
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Author : Kevin Donnelly
language : en
Publisher:
Release Date : 2024-05-21
The Descent Of Artificial Intelligence written by Kevin Donnelly and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-21 with Science categories.
The idea that a new technology could challenge human intelligence is as old as the warning from Socrates and Plato that written language eroded memory. With the emergence of generative artificial intelligence programs, we find ourselves once again debating how a new technology might influence human thought and behavior. Researchers, software developers, and "visionary" tech writers even imagine an AI that will equal or surpass human intelligence, adding to a sense of technological determinism where humanity is inexorably shaped by powerful new machines. But among the hundreds of essays, books, and movies that approach the question of AI, few have asked how exactly scientists and philosophers have codified human thought and behavior. Rather than focusing on technical contributions in machine building, The Descent of Artificial Intelligence explores a more diverse cast of thinkers who helped to imagine the very kind of human being that might be challenged by a machine. Kevin Padraic Donnelly argues that what we often think of as the "goal" of AI has in fact been shaped by forgotten and discredited theories about people and human nature as much as it has been by scientific discoveries, mathematical advances, and novel technologies. By looking at the development of artificial intelligence through the lens of social thought, Donnelly deflates the image of artificial intelligence as a technological monolith and reminds readers that we can control the narratives about ourselves.
Digital Fluency
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Author : Volker Lang
language : en
Publisher:
Release Date : 2021
Digital Fluency written by Volker Lang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
If you are curious about the basics of artificial intelligence, blockchain technology, and quantum computing as key enablers for digital transformation, Digital Fluency is your handy guide. The real-world applications of these cutting-edge technologies are expanding rapidly, and your daily life will continue to be affected by each of them. There is no better time than now to get started and become digitally fluent. You need not have previous knowledge of these technologies, as author Volker Lang will expertly guide you through this digital age. He illustrates key concepts and applications in numerous examples and figures throughout Digital Fluency, and the end of each chapter presents you with a helpful implementation checklist of central lessons before proceeding to the next. This book gets to the heart of digital buzzwords and concepts, and tells you what they truly mean. Breaking down topics such as AI-powered automated driving, blockchain-based cryptocurrencies, quantum optimization of urban traffic, and more is imperative to being ready for what the future of industry holds. Whether your own digital transformation journey takes place within your organization, your studies, or your individual household, Digital Fluency maps out a concrete digital action plan for all of your technology and strategy needs.
Deterministic Artificial Intelligence
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Author : Timothy Sands
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-05-27
Deterministic Artificial Intelligence written by Timothy Sands and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-27 with Computers categories.
Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book.
Artificial Intelligence
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Author : Richard E. Neapolitan
language : en
Publisher: CRC Press
Release Date : 2018-03-12
Artificial Intelligence written by Richard E. Neapolitan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-12 with Computers categories.
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
Artificial Intelligence
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Author : Leonidas Deligiannidis
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-08-05
Artificial Intelligence written by Leonidas Deligiannidis and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Computers categories.
Artificial Intelligence (AI) revolves around creating and utilizing intelligent machines through science and engineering. This book delves into the theory and practical applications of computer science methods that incorporate AI across many domains. It covers techniques such as Machine Learning (ML), Convolutional Neural Networks (CNN), Deep Learning (DL), and Large Language Models (LLM) to tackle complex issues and overcome various challenges.
Artificial Intelligence
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-13
Artificial Intelligence written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Computers categories.
Welcome to the world of Artificial Intelligence (AI)! This book is designed to provide you with a comprehensive introduction to the exciting field of Artificial Intelligence. Whether you are a student, a professional, or simply someone curious about the latest advancements in AI, this book aims to be your go-to resource. Artificial Intelligence has become an integral part of our daily lives, impacting industries such as healthcare, finance, transportation, and entertainment. As AI technologies continue to evolve, the demand for individuals with expertise in AI is on the rise. Whether you are pursuing a degree in computer science, aiming to enhance your career prospects, or simply fascinated by the endless possibilities of AI, this book is here to guide you on your journey.
The Hitchhiker S Guide To Machine Learning Algorithms
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Author : Devin Schumacher
language : en
Publisher: SERP Media
Release Date : 2023-07-26
The Hitchhiker S Guide To Machine Learning Algorithms written by Devin Schumacher and has been published by SERP Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Computers categories.
Hello humans & welcome to the world of machines! Specifically, machine learning & algorithms. We are about to embark on an exciting adventure through the vast and varied landscape of algorithms that power the cutting-edge field of artificial intelligence. Machine learning is changing the world as we know it. From predicting stock market trends and diagnosing diseases to powering the virtual assistants in our smartphones and enabling self-driving cars, and picking up the slack on your online dating conversations. What makes this book unique is its structure and depth. With 100 chapters, each dedicated to a different machine learning concept, this book is designed to be your ultimate guide to the world of machine learning algorithms. Whether you are a student, a data science professional, or someone curious about machine learning, this book aims to provide a comprehensive overview that is both accessible and in-depth. The algorithms covered in this book span various categories including: Classification & Regression: Learn about algorithms like Decision Trees, Random Forests, Support Vector Machines, and Logistic Regression which are used to classify data or predict numerical values. Clustering: Discover algorithms like k-Means, Hierarchical Clustering, and DBSCAN that group data points together based on similarities. Neural Networks & Deep Learning: Dive into algorithms and architectures like Perceptrons, Convolutional Neural Networks (CNN), and Long Short-Term Memory Networks (LSTM). Optimization: Understand algorithms like Gradient Descent, Genetic Algorithms, and Particle Swarm Optimization which find the best possible solutions in different scenarios. Ensemble Methods: Explore algorithms like AdaBoost, Gradient Boosting, and Random Forests which combine the predictions of multiple models for improved accuracy. Dimensionality Reduction: Learn about algorithms like Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) which reduce the number of features in a dataset while retaining important information. Reinforcement Learning: Get to know algorithms like Q-learning, Deep Q-Network (DQN), and Monte Carlo Tree Search which are used in systems that learn from their environment. Each chapter is designed as a standalone introduction to its respective algorithm. This means you can start from any chapter that catches your interest or proceed sequentially. Along with the theory, practical examples, applications, and insights into how these algorithms work under the hood are provided. This book is not just an academic endeavor but a bridge that connects theory with practical real-world applications. It's an invitation to explore, learn, and harness the power of algorithms to solve complex problems and make informed decisions. Fasten your seat belts as we dive into the mesmerizing world of machine learning algorithms. Whether you are looking to expand your knowledge, seeking inspiration, or in pursuit of technical mastery, this book should sit on your coffee table and make you look intelligent in front of all invited (and uninvited) guests.
Artificial Intelligence
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Nature
Release Date : 2021-07-16
Artificial Intelligence written by Charu C. Aggarwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-16 with Computers categories.
This textbook covers the broader field of artificial intelligence. The chapters for this textbook span within three categories: Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5. Inductive Learning Methods: These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters~6 through 11. Integrating Reasoning and Learning: Chapters~11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence. The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.
Artificial Intelligence And Complex Dynamical Systems
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Author : Giorgos Tsironis
language : en
Publisher: Springer Nature
Release Date : 2025-03-13
Artificial Intelligence And Complex Dynamical Systems written by Giorgos Tsironis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Science categories.
This book serves as a comprehensive introduction to nonlinear complex systems through the application of machine learning methods. Artificial intelligence (AI) has affected the foundations of scientific discovery, and can therefore lend itself to developing a better understanding of the unpredictable nature of complex dynamical systems and to predict their future evolution. Utilizing Python code, this book teaches and applies machine learning to topics such as chaotic dynamics and time-series analysis, solitons, breathers, chimeras, nonlinear localization, biomolecular dynamics, and wave propagation in the heart. The consistent integration of methods and models allow for readers to develop a necessary intuition on how to handle complexity through AI. This textbook contains a wealth of expository material, code, and example problems to support and organize academic coursework, allowing the technical nature of these areas of study to become highly accessible. Requiring only a basic background in mathematics and coding in Python, this book is an essential text for a wide array of advanced undergraduate or graduate students in the applied sciences interested in complex systems through the lens of machine learning.