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Edge AI in Future Computing

AI-Driven IoT Systems for Industry 4.0

Studies in National Governance and Emerging Technologies

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp;
 
 Raluca Csernatoni is a Research Fellow at Carnegie Europe, where she works on the nexus between European defence and emerging technologies. She is also Guest Professor at the Centre for Security, Diplomacy and Strategy (CSDS), Vrije Universiteit Brussel, Belgium, and Visiting Faculty in the Department of International Relations, Central European University, Austria.

This book examines how artificial intelligence systems and their applications in security and defence are entangled with governance and policy processes in the EU. Combining concepts and insights from (critical) security studies and science and technology studies, it argues that behind the various AI-related policy initiatives in the EU are particular narratives on security and defence based on European fears of technological innovation and strategic gaps. In this respect, the book casts light on how such beliefs have become increasingly instrumentalized in the European governance dynamics, and subsequently embedded in successive policy initiatives and security and defence research programmes. It challenges conventional understandings of AI technologies as mere security and defence-enabling instruments, by providing a conceptually driven analysis of how certain visions of AI help govern and control one of the most dynamic emergent socio-technical fields. The book will appeal to all those interested in artificial intelligence, security studies, technology and European governance.&nbsp;

Artificial Security and the Politics of Hype in the EU

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

This open access book critically analyses a wide range of consumer law issues generated or exacerbated by the Internet of Things. The Internet of Things challenges many of the dichotomies which have shaped current laws: goods-services, hardware-software, tangible-intangible, online-offline. The book focuses on 4 specific challenges: things-as-service, liability, bricking of physical devices through software control, and the potential for enhanced personalisation, especially for digital assistants. The chapters analyse specific applications such as smart homes, connected cars, and consumer wearables with a view to providing innovative solutions to the new challenges posed by the Internet of Things, and to steer the development of the Internet of Things in a fairer direction. As well as offering an important analysis of the potential for smart consumer laws in the Internet of Things, the book also provides important insights into the growing divergence between Germany's and the UK's consumer laws since Brexit. The ebook editions of this book are available open access under a CC BY 4.0 licence on bloomsburycollections.com. Open access was funded by UKRI (Arts and Humanities Research Council) and the German Research Foundation (DFG).

Lessons from Germany and the United Kingdom

From Smart Technologies to Smart Consumer Law

'Book of the Year' as chosen by The Conversation'Disconcerting . . . a disturbing and important book' NEW SCIENTIST'Smart and wonderfully readable' NEW YORK TIMESThe bad science and sinister ideas behind Silicon Valley's foolish obsession with immortality, AI paradise and limitless growth.Tech billionaires have decided that they should determine our futures for us. According to Elon Musk, Jeff Bezos, Sam Altman and more, the only good future for humanity is one powered by technology: trillions of humans living in space, functionally immortal, served by superintelligent AIs.In More Everything Forever, scientist and writer Adam Becker investigates these wildly implausible and often profoundly immoral visions of tomorrow to reveal why, in reality, there is no good evidence that they will, or should, come to pass. The giants of Silicon Valley claim that their ideas are based on science, but the truth is darker: they come from a jumbled mix of shallow futurism and racist pseudoscience. And behind these fanciful visions of space colonies and digital immortality is a cynical power grab, at the expense of essential work spent on solving real problems like the climate crisis.More Everything Forever exposes the powerful myths that dominate Silicon Valley, challenging us to see how foolish, and dangerous, these visions of the future are.

AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity

More Everything Forever

The purpose of this book is to explain the concept of portfolio, program, and project investment management and to provide the knowledge and the necessary understanding to effectively undertake the process. It begins by explaining how to understand the business problem the organization is trying to resolve with its strategy objectives. It then looks at financial management, particularly how to calculate the whole-of-life program and project capital and operational costs used to measure value for money from the investment. This information is used to inform program and project business case options analysis, investment appraisal of the initiative, and portfolio prioritization through the entire corporate portfolio management process. This book details the investment management process and how it integrates with an adapted corporate portfolio management process and benefits management process that focuses on a clear line of sight - an industry technique that ensures the achievement of strategy objectives through benefits realization. In addition, it explores specific cognitive bias that impacts and unduly influences the investment decision-making process. Finally, it describes several leading-edge techniques to make it easier to implement and sustain the discipline of portfolio, program, and project investment management.

How to Achieve Strategic Objectives through Benefits Realization

Portfolio, Program, and Project Investment Management

<div><div>Das erste Lexikon im Fintech-Bereich stellt mit über 800 Stichworten einschlägiges Know-how zur "Financial Technology" bereit und hilft damit bei der Klärung aktueller Begrifflichkeiten. Dem interdisziplinären Charakter der Fintech-Entwicklung zufolge sind die Begriffe an der Schnittstelle von (Wirtschafts-)Informatik, Finanzwissenschaft und Innovationsmanagement verortet. Die Fintech-Terminologie richtet sich dabei mit ihren konzise beschriebenen und mit anschaulichen Grafiken ergänzten Inhalten gleichermaßen an Studierende sowie Interessierte aus Wissenschaft und Praxis.</div><div> </div><div>Die Autoren</div><div>Prof. Dr. Rainer Alt ist Professor für Wirtschaftsinformatik an der Universität Leipzig und Autor zahlreicher Publikationen im Fintech-Bereich.&nbsp;</div><div>Dr. Stefan Huch ist Senior Director bei Capgemini Invent und vertritt die Professur Digitalisierung von Unternehmensprozessen an der Hochschule Merseburg.</div><div> </div><div>Würdigungen</div><div>"Aus meiner Sicht als Führungskraft einer global agierenden Bank ist das Fintech-Lexikon ein sehr gelungenes Nachschlagewerk, das alle relevanten Begrifflichkeiten in einer sehr verständlichen Art strukturiert darstellt und erläutert- eine gute Stütze, um in der Praxis die relevanten Begrifflichkeiten der Fintech-Szene im Überblick zu haben." Achim Lebeau, COO, DB Privat- und Firmenkunden AG</div><div>"Selbst gründen bedeutet in vielen Bereichen ins kalte Wasser geworfen zu werden. Man muss in kürzester Zeit zum Allround-Experten werden: im Sales, im Marketing, im Finance oder im Fundraising. Hier eine strukturierte Übersicht aller Begrifflichkeiten der Startup-Welt an der Hand zu haben, ist eine enorme Hilfe." Jenny Saft, Geschäftsführung und Co-Founderin, Oviavo GmbH</div><div>"Dieses Fintech-Lexikon bietet einen hervorragenden Orientierungsrahmen, indem es alle relevanten Begrifflichkeiten im Kontext der digitalisierten Finanzwelt aufgreift. Diese sind konsequent strukturiert und inverständlichen Worten definiert. Ein wertvoller Beitrag für die Praxis." Thomas Zerndt, CEO, Business Engineering Institute St. Gallen AG</div>
</div>

Dieses Buch hilft dem Leser im Umfeld der Digitalisierung bei der Begriffsklärung und stellt einschlägiges Know-how zur Verfügung.&nbsp;Was bedeutet 42? Was ist eine Subchain? Was ist der Unterschied zwischen Robotics und Artificial Intelligence? Der Schwerpunkt liegt dabei auf den Entwicklungen, die seit 2010 mit der Digitalisierung unter dem Namen "Financial Technology" eine zunehmende Verbreitung erlebt haben. Die Begrifflichkeiten umfassen grundlegende Begriffe, die Eingang in die allgemeine Sprache gefunden haben, wie etwa Artificial Intelligence oder Blockchain, aber auch fachspezifische Termini, die für das Verständnis der einzelnen Technologien notwendig sind (zum Beispiel 42, Nonce). Die Fintech-Terminologie bietet dem Leser einen konzisen und gleichzeitig anschaulich dargestellten alphabetisch geordneten Überblick mit den darin enthaltenen praxisorientierten Antworten.

Begriffe für die digitalisierte Finanzwelt

Fintech-Lexikon

Aviation Human Factors: Theory, Research, and Applications for Advanced Aviation Systems is a postgraduate textbook designed to address the unprecedented challenges facing contemporary aviation that existing texts fail to cover adequately. The progressive integration of artificial intelligence into flight-critical systems, the emergence of advanced air mobility platforms without established regulatory frameworks, the shift toward single-pilot and reduced-crew operations, and the digital transformation of air traffic management all raise critical questions about human performance that demand rigorous, up-to-date educational resources.This textbook offers operationally grounded coverage of how operators interact with automated systems, maintain situational awareness, preserve manual skills that high automation erodes, and exercise authority over increasingly autonomous technologies. It is built on a fundamental insight that transformed the field: accidents are not primarily the result of individual failure, but of the way systems around individuals are designed, organized, and managed. This realization demanded intellectual courage from investigators and institutional honesty from regulators, particularly in an industry built on professional standards and certification. Over decades, the field has developed the tools and evidence to demonstrate that system design lies at the heart of safety performance rather than human inadequacy.The textbook gives readers the theoretical frameworks, empirical knowledge, and critical thinking skills needed to address the defining human factors questions of next-generation aviation practice, ultimately helping them to understand and improve the conditions under which people can perform safely, sustainably, and with professional dignity. It is for postgraduate students in aviation human factors, aviation safety, aerospace human systems, and related disciplines. It is equally relevant to aviation professionals seeking to deepen their understanding of contemporary human factors challenges.This book will feature instructor PowerPoint slides, chapter summary sheets, case study teaching notes and a research methods resource guide.

Theory, Research, and Applications for Advanced Aviation Systems

Aviation Human Factors

Das moderne Recht wirft viele grundsätzliche Fragen auf: Ist Recht mit Gerechtigkeit notwendig verbunden? Was ist überhaupt Recht und was Gerechtigkeit? Wie verhalten sich Recht und Moral zueinander? Warum und unter welchen Bedingungen ist Recht verbindlich?
Diesen und zahlreichen anderen Fragen zu Recht, Ethik und ihrer Bedeutung für Staat und Gesellschaft geht Mahlmann in seinem Lehrbuch anhand von vielen Beispielen nach - von der Folter über die neuen Herausforderungen Künstlicher Intelligenz für das Recht bis hin zu Perspektiven einer internationalen Friedensordnung in einer Epoche neuer Kriege. Dabei schlägt er einen Bogen von der Antike bis in die Gegenwart und entwickelt vor diesem historischen Hintergrund Antworten auf zentrale systematische Fragen der Rechtsphilosophie und Rechtstheorie.

Das moderne Recht wirft viele grundsätzliche Fragen auf: Ist Recht mit Gerechtigkeit notwendig verbunden? Was ist überhaupt Recht und was Gerechtigkeit? Wie verhalten sich Recht und Moral zueinander? Warum und unter welchen Bedingungen ist Recht verbindlich?
Diesen und zahlreichen anderen Fragen zu Recht, Ethik und ihrer Bedeutung für Staat und Gesellschaft geht Mahlmann in seinem Lehrbuch anhand von vielen Beispielen nach – von der Folter über die neuen Herausforderungen Künstlicher Intelligenz für das Recht bis hin zu Perspektiven einer internationalen Friedensordnung in einer Epoche neuer Kriege. Dabei schlägt er einen Bogen von der Antike bis in die Gegenwart und entwickelt vor diesem historischen Hintergrund Antworten auf zentrale systematische Fragen der Rechtsphilosophie und Rechtstheorie.

Rechtsphilosophie und Rechtstheorie

A step-by-step guide to AI-native analytics systems for BI practitioners Building Business Intelligence Apps with AI provides a step-by-step guide for data analysts, data engineers, and BI developers who need to integrate AI into their analytics workflows. Written by Ryan Dolley, a data industry veteran with fifteen years of experience across BI development, consulting, and data vendor roles, this book shows how to partner with AI to deliver better data models, dashboards, and business queries while building AI-native experiences for end users. The book addresses data foundations, outsourcing repetitive tasks to AI, and scaling autonomous analytics systems that maintain accuracy and data governance. Readers learn practical steps for increasing individual and team effectiveness using AI while avoiding common pitfalls such as hallucination, data inaccuracy, and user abandonment. It delivers operating models that data departments need, covering everything from data blending and dashboard creation to personalization and responsiveness. Readers will also find: <ul> <li>Practical techniques for partnering with LLMs to accelerate data modeling, querying, and dashboard development across BI workflows</li> <li>Strategies to outsource repetitive analytics tasks to AI while maintaining rigorous data governance and accuracy standards</li> <li>Operating models for individuals and data departments to scale AI-native analytics systems that end users adopt</li> <li>Methods for building autonomous, personalized analytics experiences that address user expectations for speed and responsiveness</li> <li>Guidance on avoiding AI pitfalls including hallucination, data inaccuracy, and user abandonment in production analytics environments</li> </ul> Data analysts, data engineers, BI developers, and their managers will find in this book the specific skills and operating models needed to integrate AI into daily analytics work. It equips practitioners to build accurate, autonomous analytics systems while strengthening data governance and accelerating delivery across their teams.

Building Business Intelligence Apps with AI

Leveraging Data Science and Machine Learning

Predictive Intelligence for Transforming Healthcare Insurance

AI-Driven IoT Systems for Industry 4.0

Weitere Titel zum Thema