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Artificial Intelligence (Studies in Systems, Decision and Control #488)
by Bahaaeddin A. M. Alareeni Islam ElgedawyArtificial intelligence (AI) has the potential to significantly improve efficiency, reduce costs, and increase the speed and accuracy of financial decision-making, making it an increasingly important tool for financial professionals. One way that AI can improve efficiency in finance is by automating tasks and processes that are time-consuming and repetitive for humans. For example, AI algorithms can be used to analyze and process large amounts of data, such as financial statements and market data, in a fraction of the time that it would take a human to do so. This can allow financial professionals to focus on higher-value tasks, such as interpreting data and making strategic decisions, rather than being bogged down by mundane tasks. AI can also reduce costs in finance by increasing automation and eliminating the need for certain tasks to be performed manually. This can result in cost savings for financial institutions, which can then be passed on to customers in the form of lower fees or better services. AI can be used to identify unusual patterns of activity that may indicate fraudulent behavior. This can help financial institutions reduce losses from fraud and improve customer security. AI-powered chatbots and virtual assistants can help financial institutions provide faster, more efficient customer service, particularly when it comes to answering common questions and handling routine tasks. Some financial institutions are using AI to analyze market data and make trades in real-time. AI-powered trading algorithms can potentially make faster and more accurate trading decisions than humans. In terms of speed and accuracy, AI algorithms can analyze data and make decisions much faster than humans, and can do so with a high degree of accuracy. This can be particularly useful in fast-moving financial markets, where quick and accurate decision-making can be the difference between success and failure.This book highlights how AI in finance can improve efficiency, reduce costs, and increase the speed and accuracy of financial decision-making. Moreover, the book also focuses on how to ensure the responsible and ethical use of AI in finance.This book is a valuable resource for students, scholars, academicians, researchers, professionals, executives, government agencies, and policymakers interested in exploring the role of artificial intelligence (AI) in finance. Its goal is to provide a comprehensive overview of the latest research and knowledge in this area, and to stimulate further inquiry and exploration.
Artificial Intelligence: 30th Benelux Conference, BNAIC 2018, ‘s-Hertogenbosch, The Netherlands, November 8–9, 2018, Revised Selected Papers (Communications in Computer and Information Science #1021)
by Martin Atzmueller Wouter DuivesteijnThis book contains a selection of the best papers of the 30th Benelux Conference on Artificial Intelligence, BNAIC 2018, held in ‘s-Hertogenbosch, The Netherlands, in November 2018. The 9 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 31 submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
Artificial Intelligence: Fundamentals and Applications
by Cherry Bhargava Pradeep Kumar SharmaThis comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.
ARTificial Intelligence
by David BiedrzyckiEver since he was a little chip, Robot knew he was ART-ificially different. A funny and heartfelt picture book exploring AI, art, and creativity.Try as he might, Robot can't keep up with the other robots at the warehouse. But when he's sent off for reprogramming, he takes a wrong turn and ends up encountering music, dancing, and ART! He tries to share his discovery, only to find that art is hard to explain—and even harder to do. Will Robot learn to express himself and transform the warehouse . . . or will he be recycled?
Artificial Intelligence: The Case Against (Routledge Library Editions: Artificial Intelligence #3)
by Rainer BornThe purpose of this book, originally published in 1987, was to contribute to the advance of artificial intelligence (AI) by clarifying and removing the major sources of philosophical confusion at the time which continued to preoccupy scientists and thereby impede research. Unlike the vast majority of philosophical critiques of AI, however, each of the authors in this volume has made a serious attempt to come to terms with the scientific theories that have been developed, rather than attacking superficial ‘straw men’ which bear scant resemblance to the complex theories that have been developed. For each is convinced that the philosopher’s responsibility is to contribute from his own special intellectual point of view to the progress of such an important field, rather than sitting in lofty judgement dismissing the efforts of their scientific peers. The aim of this book is thus to correct some of the common misunderstandings of its subject. The technical term Artificial Intelligence has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike.
Artificial Intelligence: An Introduction to the Big Ideas and their Development (Chapman & Hall/CRC Mathematics and Artificial Intelligence Series)
by Robert H. Chen Chelsea ChenArtificial Intelligence: An Introduction to Big Ideas and their Development, Second Edition guides readers through the history and development of artificial intelligence (AI), from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence, including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of the mathematics and computer science of AI. As the book proceeds, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus. Accessible to anyone with an interest in AI and its mathematics and computer science. Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence. New to the Second Edition Fully revised and corrected throughout to bring the material up-to-date. Greater technical detail and exploration of basic mathematical concepts, while retaining the simplicity of explanation of the first edition. Entirely new chapters on large language models (LLMs), ChatGPT, and quantum computing.
Artificial Intelligence: An Introduction for the Inquisitive Reader
by Robert H. Chen Chelsea C. ChenArtificial Intelligence: An Introduction for the Inquisitive Reader guides readers through the history and development of AI, from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence including Deep Blue, AlphaGo and even Texas Hold’em, followed by their historical background, so that AI can be seen as a natural development of mathematics and computer science. As the book moves forward, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today. Features Only mathematical prerequisite is an elementary knowledge of calculus Accessible to anyone with an interest in AI and its mathematics and computer science Suitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence.
Artificial Intelligence: A Philosophical Introduction
by Jack CopelandPresupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer.
Artificial Intelligence: A Philosophical Introduction
by Jack CopelandPresupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding. There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer.
Artificial Intelligence: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings (Lecture Notes in Computer Science #9883)
by Christo Dichev Gennady AgreThis book constitutes the refereed proceedings of the 17th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2016, held in Varna, Bulgaria in September 2015. The 32 revised full papers 6 poster papers presented were carefully reviewed and selected from 86 submissions. They cover a wide range of topics in AI: from machine learning to natural language systems, from information extraction to text mining, from knowledge representation to soft computing; from theoretical issues to real-world applications.
Artificial Intelligence: The Psi-Organ in a Nutshell (SpringerBriefs in Computer Science)
by Dietmar DietrichTo be able to merge the psyche with the neural system has been a long-sought goal. There is much scientific literature on results from research on this topic, but the goal of this “booklet” is to present the subject in a nutshell and to attract a wider audience to this highly complex topic. Scientists often need years to grasp the scope and implications of merging the psyche with the neural system. Does that really have to be the case? What does the simulated model look like? What are the underlying philosophies? Can it be understood without mathematical formalism? Uniting the psyche and neurology in one model, on the one hand, allows psychological and social theories to be tested on a scientific basis using simulation experiments. On the other hand, a model developed according to the functional structures of the human brain, let us call it the Psi-Organ, which comprises neurology and psyche as one unit, can serve as a basis for AI systems. These can be systems with cognitive capabilities that save human lives, save energy, ensure safety at airports, provide support in caring for the elderly and much more. In other words, systems that can simplify our lives in the most relevant ways and on a broad basis. This model, the Psi-Organ, goes far beyond today's primarily behavior-based AI methods. The manuscript can serve as an excellent introduction to the problem of understanding and modelling the human mind, and to the problem of achieving artificial “intelligence” in general, increasing awareness and understanding for the associated challenges. In that regard, it is a valuable supplementary text for advanced students or researchers in the field, notably not only in AI, but also (and perhaps primarily) in the medical fields.
Artificial Intelligence: First CAAI International Conference, CICAI 2021, Hangzhou, China, June 5–6, 2021, Proceedings, Part II (Lecture Notes in Computer Science #13070)
by Lu Fang Yiran Chen Guangtao Zhai Jane Wang Ruiping Wang Weisheng DongThis two-volume set LNCS 13069-13070 constitutes selected papers presented at the First CAAI International Conference on Artificial Intelligence, held in Hangzhou, China, in June 2021. Due to the COVID-19 pandemic the conference was partially held online. The 105 papers were thoroughly reviewed and selected from 307 qualified submissions. The papers are organized in topical sections on applications of AI; computer vision; data mining; explainability, understandability, and verifiability of AI; machine learning; natural language processing; robotics; and other AI related topics.
Artificial Intelligence: Third CAAI International Conference, CICAI 2023, Fuzhou, China, July 22–23, 2023, Revised Selected Papers, Part II (Lecture Notes in Computer Science #14474)
by Lu Fang Jian Pei Guangtao Zhai Ruiping WangThis two-volume set LNAI 14473-14474 constitutes revised selected papers presented at the Third CAAI International Conference, CICAI 2023, in Fuzhou, China, in July 2023. CICAI is a summit forum in the field of artificial intelligence and the 2023 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 100 papers were thoroughly reviewed and selected from 376 submissions. CICAI 2023 conference covers a wide range of of AI generated content, computer vision, machine learning, nature language processing, application of AI, and data mining, amongst others.
Artificial Intelligence: Third CAAI International Conference, CICAI 2023, Fuzhou, China, July 22–23, 2023, Revised Selected Papers, Part I (Lecture Notes in Computer Science #14473)
by Lu Fang Jian Pei Guangtao Zhai Ruiping WangThis two-volume set LNAI 14473-14474 constitutes revised selected papers presented at the Third CAAI International Conference, CICAI 2023, in Fuzhou, China, in July 2023. CICAI is a summit forum in the field of artificial intelligence and the 2023 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 100 papers were thoroughly reviewed and selected from 376 submissions. CICAI 2023 conference covers a wide range of of AI generated content, computer vision, machine learning, nature language processing, application of AI, and data mining, amongst others.
Artificial Intelligence: Second CAAI International Conference, CICAI 2022, Beijing, China, August 27–28, 2022, Revised Selected Papers, Part I (Lecture Notes in Computer Science #13604)
by Lu Fang Daniel Povey Guangtao Zhai Tao Mei Ruiping WangThis three-volume set LNCS 13604-13606 constitutes revised selected papers presented at the Second CAAI International Conference on Artificial Intelligence, held in Beijing, China, in August 2022. CICAI is a summit forum in the field of artificial intelligence and the 2022 forum was hosted by Chinese Association for Artificial Intelligence (CAAI).The 164 papers were thoroughly reviewed and selected from 521 submissions. CICAI aims to establish a global platform for international academic exchange, promote advanced research in AI and its affiliated disciplines such as machine learning, computer vision, natural language, processing, and data mining, amongst others.
Artificial Intelligence: Second CAAI International Conference, CICAI 2022, Beijing, China, August 27–28, 2022, Revised Selected Papers, Part III (Lecture Notes in Computer Science #13606)
by Lu Fang Daniel Povey Guangtao Zhai Tao Mei Ruiping WangThis three-volume set LNCS 13604-13606 constitutes revised selected papers presented at the Second CAAI International Conference on Artificial Intelligence, held in Beijing, China, in August 2022. CICAI is a summit forum in the field of artificial intelligence and the 2022 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 164 papers were thoroughly reviewed and selected from 521 submissions. CICAI aims to establish a global platform for international academic exchange, promote advanced research in AI and its affiliated disciplines such as machine learning, computer vision, natural language, processing, and data mining, amongst others.
Artificial Intelligence: Second CAAI International Conference, CICAI 2022, Beijing, China, August 27–28, 2022, Revised Selected Papers, Part II (Lecture Notes in Computer Science #13605)
by Lu Fang Daniel Povey Guangtao Zhai Tao Mei Ruiping WangThis three-volume set LNCS 13604-13606 constitutes revised selected papers presented at the Second CAAI International Conference on Artificial Intelligence, held in Beijing, China, in August 2022. CICAI is a summit forum in the field of artificial intelligence and the 2022 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 164 papers were thoroughly reviewed and selected from 521 submissions. CICAI aims to establish a global platform for international academic exchange, promote advanced research in AI and its affiliated disciplines such as machine learning, computer vision, natural language, processing, and data mining, amongst others.
Artificial Intelligence: An Introduction (Psychology Revivals)
by Alan GarnhamFirst published in 1987, this book provides a stimulating introduction to artificial intelligence (AI) - the science of thinking machines. After a general introduction to AI, including its history, tools, research methods, and its relation to psychology, Garnham gives an account of AI research in five major areas: knowledge representation, vision, thinking and reasoning, language, and learning. He then describes the more important applications of AI and discusses the broader philosophical issues raised by the possibility of thinking machines. In the final chapter, he speculates about future research in AI, and more generally in cognitive science. Suitable for psychology students, the book also provides useful background reading for courses on vision, thinking and reasoning, language and learning.
Artificial Intelligence: Its Philosophy and Neural Context (Routledge Library Editions: Artificial Intelligence)
by F. H. GeorgeOriginally published in 1986, in order to probe, dispute and analyse the role of artificial intelligence in cybernetic thought and information science, the author pursues this topic within its philosophical, behavioral and neurophysiological contexts, while drawing attention to cognitive issues. By elucidating the problems and potential associated with knowledge-based systems, the book emphasized the need to examine artificial intelligence in its own right.
Artificial Intelligence (Forensic Science in Focus)
by Zeno Geradts Katrin FrankeARTIFICIAL INTELLIGENCE (AI) IN FORENSIC SCIENCES Foundational text for teaching and learning within the field of Artificial Intelligence (AI) as it applies to forensic science Artificial Intelligence (AI) in Forensic Sciences presents an overview of the state-of-the-art applications of Artificial Intelligence within Forensic Science, covering issues with validation and new crimes that use AI; issues with triage, preselection, identification, argumentation and explain ability; demonstrating uses of AI in forensic science; and providing discussions on bias when using AI. The text discusses the challenges for the legal presentation of AI data and interpretation and offers solutions to this problem while addressing broader practical and emerging issues in a growing area of interest in forensics. It builds on key developing areas of focus in academic and government research, providing an authoritative and well-researched perspective. Compiled by two highly qualified editors with significant experience in the field, and part of the Wiley — AAFS series ‘Forensic Science in Focus’, Artificial Intelligence (AI) in Forensic Sciences includes information on: Cyber IoT, fundamentals on AI in forensic science, speaker and facial comparison, and deepfake detection Digital-based evidence creation, 3D and AI, interoperability of standards, and forensic audio and speech analysis Text analysis, video and multimedia analytics, reliability, privacy, network forensics, intelligence operations, argumentation support in court, and case applications Identification of genetic markers, current state and federal legislation with regards to AI, and forensics and fingerprint analysis Providing comprehensive coverage of the subject, Artificial Intelligence (AI) in Forensic Sciences is an essential advanced text for final year undergraduates and master’s students in forensic science, as well as universities teaching forensics (police, IT security, digital science and engineering), forensic product vendors and governmental and cyber security agencies.
Artificial Intelligence: A Driver of Inclusive Development and Shared Prosperity for the Global South
by Arthur G.O. MutambaraThis book presents contextualised and detailed research on Artificial Intelligence (AI) and the Global South. It examines the key challenges of these emerging and least industrialised countries while proffering holistic and comprehensive solutions. The book then explains how AI, as part of these broad interventions, can drive Global South economies to achieve inclusive development and shared prosperity. The book outlines how countries can swiftly prepare to adopt and develop AI across all sectors. It presents novel national, regional, and continental AI adoption, development, and implementation frameworks.Features: Broad non-AI interventions and prescriptions to address Global South challenges A comprehensive but accessible introduction to AI concepts, technology, infrastructure, systems, and innovations such as AlphaFold, ChatGPT-4, and DeepSeek-R1 An overview of AI-related technologies such as quantum computing, battery energy storage systems, 3D printing, nanotechnology, IoT, and blockchain How to prepare emerging economies to unlock the benefits of AI while mitigating the risks Discussion of specific AI applications in 11 critical Global South sectors Details of 11 sector case studies of AI adoption in the Global South and Global North Ten country case studies: Sharing emergent AI experiences in the Global South AI adoption framework: vision, strategy, policy, governance, legislation/regulation, and implementation matrix A framework for democratising and decolonising AI The value proposition for AI research, development, and ownership in the Global South A case for the participation of the Global South in the AI semiconductor industry This book is aimed at policymakers, business leaders, graduate students, academics, researchers, strategic thinkers, and world leaders seeking to understand and leverage the transformative role of AI-based systems in achieving inclusive development, economic transformation, and shared prosperity.
Artificial Intelligence (Studies in Systems, Decision and Control #517)
by Reem Khamis Hamdan Amina BuallayThe impact of artificial intelligence (AI) on business and society has been significant, with the incorporation of AI technologies such as robots, facial recognition, algorithms, and natural language processing into business leading to both corporate benefits and potential challenges for stakeholders. The question of how to engage in responsible business practices in the era of AI is an important one, and there is a need for more research on the relationship between AI and corporate social responsibility (CSR). As AI becomes more prevalent, there is a growing focus on the ethical implications of AI and the potential for AI to perpetuate biases or to displace human workers. CSR initiatives can include considerations of ethical AI in the development and use of AI systems. AI has the potential to solve many global challenges and improve people's lives, but it can also have negative consequences if not developed and used responsibly. CSR initiatives can focus on the social impact of AI,including efforts to ensure that the benefits of AI are distributed fairly and that AI is used for the common good. CSR initiatives often involve engaging with stakeholders, including employees, customers, and communities, to understand their needs and concerns and to ensure that their interests are taken into account. This can include engaging with stakeholders about the use of AI in the organization and its potential impactsThe adoption of AI in business is changing many aspects of doing business in a socially responsible manner, and there is a need to examine the potential unethical behaviors and novel ways of engaging in CSR that may arise. This book aims to focus on AI and CSR, and to advance our understanding of the role of AI in organizations and the literature on CSR by assembling high-quality papers with a strong connection between theory and practice.
Artificial Intelligence: Second International Conference, SLAAI-ICAI 2018, Moratuwa, Sri Lanka, December 20, 2018, Revised Selected Papers (Communications in Computer and Information Science #890)
by Jude Hemanth Thushari Silva Asoka KarunanandaThis book constitutes the refereed proceedings of the Second International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri Lanka, in December 2018.The 32 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: intelligence systems; neural networks; game theory; ontology engineering; natural language processing; agent based system; signal and image processing.
Artificial Intelligence: What Everyone Needs to Know
by Jerry KaplanOver the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you.