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Books > Computing & IT > Applications of computing > Artificial intelligence
This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.
This book develops an original theoretical framework for understanding human-technology relations. The author's approach, which he calls technoanalysis, analyzes artificial intelligence based on Freudian psychoanalysis, biosemiotics, and Latour's actor-network theory. How can we communicate with AI to determine shared values and objectives? And what, ultimately, do we want from machines? These are crucial questions in our world, where the influence of AI-based technologies is rapidly growing. Unconscious dynamics influence AI and digital technology and understanding them is essential to better controlling AI systems. This book's unique methodology- which combines psychoanalysis, biosemiotics, and actor-network theory-reveals a radical reformulation of the problem of the human mind. Technoanalysis views the mind as a hybrid network of humans and nonhuman actants in constant interaction with one another. The author argues that human unconscious dynamics influence and shape technology, just as technology influences and shapes human unconscious dynamics. He proceeds to show how this conception of the relationship between the unconscious and technology can be applied to social robotics and AI. Unconscious Networks will appeal to scholars and advanced students interested in philosophy of technology, philosophy of artificial intelligence, psychoanalysis, and science and technology studies.
Novel perspectives on machine behaviour as it relates to behavioural science. A framework of terminology to empower discussion of AI within behavioural science. A compelling definition of hypernudging developed from AI and behavioural science principles.
Underwater robots play a significant role in ocean exploration. This book provides full coverage of the theoretical and practical aspects of bionic gliding underwater robots, including system design, modeling control, and motion planning. To overcome the inherent shortcomings of traditional underwater robots that can simultaneously lack maneuverability and endurance, a new type of robot, the bionic gliding underwater robot, has attracted much attention from scientists and engineers. On the one hand, by imitating the appearance and swimming mechanisms of natural creatures, bionic gliding underwater robots achieve high maneuverability, swimming efficiency, and strong concealment. On the other hand, borrowing from the buoyancy adjustment systems of underwater gliders, bionic gliding underwater robots can obtain strong endurance, which is significant in practical applications. Taking gliding robotic dolphin and fish as examples, the designed prototypes and proposed methods are discussed, offering valuable insights into the development of next-generation underwater robots that are well suited for various oceanic applications. This book will be of great interest to students and professionals alike in the field of robotics or intelligent control. It will also be a great reference for engineers or technicians who deal with the development of underwater robots.
Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence's adoption in higher education and the challenges to building sustainable instead of dystopic schooling. As AI becomes integral to both pedagogy and profitability in today's colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression. This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability. Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns.
Introduces the main philosophical ideas concerning mind and freedom Explains the basic principles of computer science, artificial intelligence of brain research, quantum physics, and quantum artificial intelligence Provides an essential compilation of knowledge in philosophy, computer science, biology, and quantum physics
SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems. Features: The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems Different use cases covered include smart health care, smart city, internet of drones, etc This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.
The proposed title intends to provide a comprehensive view of emerging paradigms of computer science. The initial chapters will introduce various emerging paradigms and discuss research challenges related to them. Then some of the chapters will focus on the research solutions to address the identified challenges. The last few chapters will provide a discussion on future research directions.
Highlights the importance and applications of Swarm Intelligence and Machine learning in Healthcare industry. Elaborates Swarm Intelligence and Machine Learning for Cancer Detection. Focuses on applying Swarm Intelligence and Machine Learning for Heart Disease detection and diagnosis. Explores of the concepts of machine learning along with swarm intelligence techniques, along with recent research developments in healthcare sectors. Investigates how healthcare companies can leverage the tapestry of big data to discover new business values. Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms.
Showcases the state-of-the-art research in the area of AI with specific consideration to engineering, management and safety of civil construction. Offers detailed insights towards applying AI into design, construction and maintenance of infrastructure Leverages the various sub-disciplines of AI to arrive at modern, smart, and safe infrastructure as well as achieve a synergy between users/commuters and such structures. Covers practical case studies of primary interest to students, researchers, engineers, social scientists and government officials.
Provides strong and accessible theoretical bases to swarm intelligence algorithms, from particle optimization to bioinspired and meta-heuristic algorithms Presents emerging meta-heuristic algorithms and applications Provides overviews on Python and R based computing libraries for swarm intelligence and meta-heuristic algorithms Presenting real-world applications, especially on Industry, Medicine and Biology.
* International approach, with examples and cases from the US, Europe and Africa * Each chapter contains objectives, case studies, discussion questions and further reading suggestions. * PPT slides and data sets available as digital supplements
This book brings together history and theory in art and media to examine the effects of artificial intelligence and machine learning in culture, and reflects on the implications of delegating parts of the creative process to AI. In order to understand the complexity of authorship and originality in relation to creativity in contemporary times, Navas combines historical and theoretical premises from different areas of research in the arts, humanities, and social sciences to provide a rich historical and theoretical context that critically reflects on and questions the implications of artificial intelligence and machine learning as an integral part of creative production. As part of this, the book considers how much of postproduction and remix aesthetics in art and media preceded the current rise of metacreativity in relation to artificial intelligence and machine learning, and explores contemporary questions on aesthetics. The book also provides a thorough evaluation of the creative application of systematic approaches to art and media production, and how this in effect percolates across disciplines including art, design, communication, as well as other fields in the humanities and social sciences. An essential read for students and scholars interested in understanding the increasing role of AI and machine learning in contemporary art and media, and their wider role in creative production across culture and society.
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0. Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 discusses how to develop adaptive, robust, scalable, and reliable applications that can be used in solutions for day-to-day problems. It focuses on the two frontiers - Big Data and Cloud Computing - and reviews the advantages and consequences of utilizing Cloud Computing to tackle Big Data issues within the manufacturing and production sector as part of Industry 4.0. The book unites some of the top Big Data experts throughout the world who contribute their knowledge and expertise on the different aspects, approaches, and concepts related to new technologies and novel findings. Based on the latest technologies, the book offers case studies and covers the major challenges, issues, and advances in Big Data and Cloud Computing for Industry 4.0. By exploring the basic and high-level concepts, this book serves as a guide for those in the industry, while also helping beginners and more advanced learners understand both basic and more complex aspects of the synergy between Big Data and Cloud Computing.
Nanetti outlines a methodology for deploying artificial intelligence and machine learning to enhance historical research. Historical events are the treasure of human experiences, the heritage that societies have used to remain resilient and express their identities. Nanetti has created and developed an interdisciplinary methodology supported by practice-based research that serves as a pathway between historical and computer sciences to design and build computational structures that analyse how societies create narratives about historical events. This consilience pathway aims to make historical memory machine-understandable. It turns history into a computational discipline through an interdisciplinary blend of philological accuracy, historical scholarship, history-based media projects, and computational tools. Nanetti presents the theory behind this methodology from a humanities perspective and discusses its practical application in user interface and experience. An essential read for historians and scholars working in the digital humanities.
Blockchain: Principles and Applications in IoT covers all the aspects of Blockchain and its application in IOT. The book focuses on Blockchain, its features, and the core technologies that are used to build the Blockchain network. The gradual flow of chapters traces the history of blockchain from cryptocurrencies to blockchain technology platforms and applications that are adopted by mainstream financial and industrial domains worldwide due to their ease of use, increased security and transparency. * Focuses on application of Blockchain on IoT domain * Focuses on Blockchain as a data repository * Most books on Blockchain cover bitcoins and crypto currency. This book will also cover blockchain in other areas like healthcare, supply chain management, etc * Covers consensus algorithms like PAROX, RAFT etc. and its applications This book is primarily aimed at graduates and researchers in computer science and IT.
Uses the two programming languages officially supported in ROS2 (C++, mainly, and Python). Approaches ROS2 from three different but complementary dimensions; the Community, Computation Graph, and the Workspace. Includes a complete simulated robot, development and testing strategies, Behavior Trees, and Nav2 description, setup and use. A GitHub repository with code to assist readers.
Artificial intelligence (AI) has driven businesses to adopt new business practices rapidly, enhance product development and services, has helped to power AI-based market intelligence and customer insights, and improve customer relationship management. This timely book addresses the use of AI in marketing. This book also explores the dark side of AI in marketing management and discusses ethics and transparency of automated decision-making in AI applications, data privacy, cyber security issues, and biases in various facets of marketing. Emerging applications of AI such as DeepFakes which use deep learning technology could increase risks of manipulation and deception. Hence, apart from leveraging AI capabilities and advantages, the book cautions the need for prevention strategies to deal with potential issues that could arise from the adoption of AI in marketing management. This book will provide practical insights into the role of AI in marketing management. It will be a useful reference for those researching marketing and marketing professionals.
* Provides simple, conceptual descriptions of everyday technologies * Includes clear examples and diagrams that demonstrate the principles and techniques, not just a "how-to" punch list * Covers advanced topics for readers who want to dive into the deep end of the technology pool * Avoids jargon-where terminology does appear, the text will provide clear, concise definitions
Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.
Ambient intelligence (AmI) was established in the late 1990s as a recent paradigm for electronic environments for the timeframe of 2010-2020. AmI is essentially an elabo- tion of Mark Weiser's vision of ubiquitous computing. Weiser was aiming at a novel mobile computing infrastructure integrated into the networked environment of people. AmI is the idea of a technology that will become invisibly embedded in our natural s- roundings, present whenever we need it, enabled by simple and effortless interaction, attuned to all our senses, adaptive to users, context-sensitive, and autonomous. AmI refers to smart electronic environments that are sensitive and responsive to the presence of people. Since its adoption the vision has grown and fully developed, bec- ing quite influential in the development of novel ideas for information processing and new concepts for multi-disciplinary fields including electrical engineering, computer science, industrial design, user interfaces, and cognitive sciences. The AmI system - fords a basis for new paradigms of technological innovation within a multi-dimensional society. The added value of the AmI vision is the fact that the large-scale integration of electronics into the environment allows the actors, i. e. , people and objects, to collaborate with their surroundings in a natural measure. This is directly related to the increasing societal demand for communication and the exchange of information.
Helps readers to transition from traditional statistics to modern data science Reviews the pros and cons of open source and commercial software packages, and their proper applications in specific situations. Explores data using dynamic methods rather than counting on dichotomous thinking. Considers alternate models using ensemble models and model comparison rather than fixing a preconceived hypothesis/model on a single method. Shows how to find the hidden pattern in the data by dynamic visualization rather than over-relying on numeric results.
A leading artificial intelligence researcher lays out a new approach to AI that will enable us to coexist successfully with increasingly intelligent machines In the popular imagination, superhuman artificial intelligence is an approaching tidal wave that threatens not just jobs and human relationships, but civilization itself. Conflict between humans and machines is seen as inevitable and its outcome all too predictable. In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage. If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.
Why do minds exist? How did mud and stone develop into beings that can experience longing, regret, love and compassion-beings that are aware of their own experience? Until recently, science offered few answers to these existential questions. Journey of the Mind is the first book to offer a unified account of the mind that explains how consciousness, language, the Self and civilisation emerged incrementally out of chaos. The journey begins three billion years ago with the emergence of the simplest possible mind, a nanoscopic archeon, then ascends through amoebas, worms, frogs, birds, monkeys and AI, examining successively smarter ways of thinking. The authors explain the mathematical principles generating conscious experience and show how these principles led cities and democratic nations to develop new forms of consciousness-the self-aware "superminds". Journey of the Mind concludes by contemplating a higher stage of consciousness already emerging-and the ultimate fate of all minds in the universe.
Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security. Key Features: Introduces the latest trends in the fields of machine learning, blockchain and cyber security Discusses the fundamentals, challenges and architectural overviews with concepts Explores recent advancements in machine learning, blockchain, and cyber security Examines recent trends in emerging technologies This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security. |
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