<div class="raw-html-embed"><a href="https://staempflirecht.ch/studium">JUS-Studium? Das Fachwissen von Expertinnen und Experten des Schweizer Rechts – griffbereit!</a></div>

Über uns

À propos de nous

Nachhaltigkeit

Durabilité

Open Access

Karriere

Carrière

Aboverträge Kündigen

Résiliation d’abonnement

Vertrag widerrufen

Résiliation de contrat 

Datenschutz

Protection des données

Impressum

Mentions légales

Barrierefreiheit

Accessibilité

Zahlung und Lieferung

Paiement et livraison

Libra

Was ist Libra?

C'est quoi Libra ?

Kostenlos testen

Tester gratuitement

LEXIA

LEXIA Arbeitsrecht

Was ist LEXIA?

C'est quoi LEXIA ?

LEXIA Familienrecht

Zeitschriften

Revues

recht

Pflegerecht

ZBJV

forumpoenale

ZStrR

Anwaltsrevue

Revue de l'avocat

RSAS

FamPra.ch

ASYL

Life Science Recht

BlAR

Sachbuch

Livres spécialisés

LOKI

Semaphor

Fokusthemen

Focus

Thema

Recht studieren

Arbeitsrecht

Droit du travail

Studium

Études

Familienrecht

Droit de la famille

Sozialversicherungsrecht

Droit des assurances sociales

Strafrecht

Droit pénal

Aktienrecht

Droit des sociétés anonymes

Publikationen

Publications

Literatur

Digitales Angebot

Bücher

Livres

Buchreihen

Collections

Onlinemodule LEXIA

Modules en ligne LEXIA

recht.ch

Studienliteratur

Littérature pour les études

Swisslex

Dienstleistungen

Services

Dienstleistungen für

Corporate Books

Publishing Lösungen

Aktuelles

Geschäftskunden

Professionnels

Corporate Publishing

Content solutions

Buchhandlungen

Librairies

Veranstaltungen

Événements

Presse

Dozierende

Enseignants

Studierende

Étudiants

Inserierende

Annonceurs

Newsletter

Blog

Autorinnen/Autoren

Auteurs

Unsere Schreibenden

Hilfe

Unsere Autorinnen und Autoren

Liste

Autorenlounge

Espace des auteurs

Bei uns publizieren

Publier chez nous

Open Access Policy

Verlag

Éditions

Themen

Mehr wissen

Mitarbeitende

Collaborateurs

Geschichte

Histoire

Unser Magazin

Notre magazine

Vision und Mission

Vision et mission

Partner

Partenaires

Unternehmenskultur

Culture d'entreprise

Kontakt

Contact

Shop

Schweizer Recht

Ausländisches Recht

Über unseren Shop

Neuerscheinungen

Nouveautés

Sortiment & Suche

Catalogue & Recherche

Vorankündigungen

À paraître

Nach Rechtsgebiet

Par domaine juridique

Kommentare

Commentaires

Gesamtkatalog

Catalogue complet

Fachkatalog Recht

Catalogue de droit

Nelson H: AI Powered Digital Twins

AI Powered Digital Twins

A Guide for Humans, Engineers, and Enterprises

Preface xxi Part 1 AI-native Digital Twins 1 Chapter 1 Digital Twins and Humans 3 Chapter 2 When AI Powers Digital Twins 19 Chapter 3 AI Agents Within Digital Twins 45 Part 2 Infrastructure and Security Requirements 87 Chapter 4 AI Data Centers 91 Chapter 5 Energy Infrastructure for AI at Scale 101 Chapter 6 A Standard of Care for AI-powered Digital Twins 109 Chapter 7 Cybersecurity 123 Part 3 Engineering 141 Chapter 8 AI Engineering 143 Chapter 9 Hardware Layer and Supply Chain 171 Chapter 10 Communication Networks and Graphs 185 Chapter 11 Data Engineering 197 Chapter 12 System Design 221 Chapter 13 Mathematical Modeling and Computation 235 Chapter 14 Engineering for Longevity 257 Chapter 15 The Quantum Realm, Computation, and Consciousness 269 Part 4 Humans, Purpose, and Business 283 Chapter 16 AI and Data Strategy 285 Chapter 17 Business, Bubbles, and Human-centered Philosophy 291 Appendix: Full Engineering Architecture Expanded 303 Resources and Influences 311 About the Author 315 Index 317

Mastering Business Analytics

Data Analytics for Strategic Decisions explores how businesses can harness the power of data, technology, and analytics to make strategic decisions that drive growth and innovation. It provides a comprehensive guide to integrating business strategy with data-driven methodologies, offering practical tools and insights for modern organizations.Readers will gain a deep understanding of how to transform data into actionable insights, improving decision-making across marketing, finance, operations, and strategy. The book combines theoretical foundations with real-world applications, including case studies, datasets, and practical exercises. It also addresses emerging topics like AI, predictive analytics, and data governance, ensuring readers are equipped with cutting-edge knowledge and skills.This book is designed for undergraduate and master's students in Business Administration, Business Analytics, and Digital Transformation, as well as professionals seeking to enhance their data-driven decision-making capabilities. It is ideal for courses in Business Analytics, Data Analytics for Business, Business Intelligence, and Digital Transformation.The book includes supplementary materials such as datasets for practical exercises, case studies, and discussion questions, making it suitable for both classroom and online learning environments.

Fundamentals of Business Technology and AI Integration

Data Analytics for Strategic Decisions

Innovations in Intelligent Internet of Everything IoE

Biomedical Applications of AI and IoMT in Smart Healthcare

Wiley Finance

The handbook to unleash the power of AI in Finance with guidance to pragmatically managing AI Risk Are you ready to harness the transformative potential of artificial intelligence and machine learning in finance while effectively managing the associated risks? "AI and Risk Management in Finance: A Practitioner's Handbook" by Sri Krishnamurthy, CFA, is your indispensable guide. Tailored for financial professionals, this comprehensive handbook delivers practical insights, case studies, and frameworks to navigate the complex landscape of AI and ML in the financial sector. This pragmatic handbook, developed primarily for professionals involved in designing, developing, and deploying AI models in the financial industry explores cutting-edge technologies, regulatory landscapes, and pragmatic frameworks. From generative AI to robust risk management strategies, this handbook equips you with the tools you need to validate models, ensure compliance, and operationalize AI risk management effectively. Leveraging lessons from QuantUniversity's AI and Machine Learning Risk Management program offered in 18 countries, this book focuses on enabling practitioners apply the state-of-the-art AI and machine learning techniques factoring unique risks specific to the financial services domain. Whether you're a seasoned professional or a newcomer, this book offers invaluable insights for harnessing the power of AI responsibly in the financial industry. Highlights of the Book: <ul> <li>Machine Learning and AI in Financial Services: Dive into the fundamentals of ML and AI, exploring various applications within the financial industry through real-world case studies.</li> <li>Generative AI and LLMs in Finance: Understand the emerging landscape, key players, and advanced concepts like prompt engineering and fine-tuning with practical examples.</li> <li>Risk Management for AI/ML Applications: Learn about current and emerging regulatory landscapes, AI risk management frameworks, and legislative efforts shaping the field.</li> <li>Data Governance Issues: Address critical aspects of data quality, privacy, security, and governance, with actionable frameworks and illustrative case studies.</li> <li>Model and System Governance: Gain insights into validating machine learning models, quantifying model risk, and ensuring robust system governance with MLOps and model monitoring.</li> <li>Key Risk Assessment Facets: Focus on documentation, explainability, fairness, security, and reliability with detailed case studies.</li> <li>Verification and Validation: Distinguish between verification and validation and learn frameworks for effective AI application validation.</li> <li>Algorithmic Auditing: Conduct comprehensive algorithmic audits with detailed processes and real-world examples.</li> <li>Operationalizing AI Risk Management: Discover ten essential strategies for implementing AI risk management practices effectively in your organization.</li> </ul> Prepare for the future of finance with expert advice and actionable strategies. Don't miss out on this comprehensive guide-your roadmap to navigating AI and risk management in the financial sector.

A Practitioner�s Guide to Machine Learning, Generative AI, Agentic Systems, and Responsible Deployment

AI and Risk Management in Finance

Research in Creative Writing

Writing Human in the Age of AI

This book offers an alternate trajectory for EU copyright law. Building on cultural norms in creative communities to reuse, recreate and share, the book proposes a more holistic approach to reconcile conflicting copyright interests. Drawing upon Niklas Luhmann's system theory, John Dewey's theory of art and feminist data theory, it advocates access to, and care within, creative communicative spaces, such as social media platforms or artificial intelligence (AI) data infrastructures, to safeguard creativity and cultural production online. Following a comprehensive assessment of current EU copyright law and related regulation, it proposes a rebuttable presumption of artistic communication to account for the nature of communication between authors, users and the public that safeguards creative reuse. The book isolates the question of remuneration, particularly in AI context, as one of collective socio-cultural value to address wider harms through a cultural commons existing on the border of the EU copyright system. Reflecting on traditional copyright concepts such as authorship, consent and remuneration alongside more novel legal structures like a right of collective informational self-determination, Reshaping EU Copyright Law to Support Creativity Online provides a foundation to reshape how the EU copyright system and its regulatory neighbours adequately respond to new forms of creativity, dissemination, and its use.

Offers an alternate trajectory for EU copyright law to adequately respond to new forms of creativity

Creative Reuse

Reshaping EU Copyright Law to Support Creativity Online

Artificial intelligence has crossed the liability Rubicon. It is no longer a backend IT experiment governed by soft ethics, voluntary frameworks, and vague policy statements; it is a material financial asset driving enterprise revenue and unprecedented legal exposure. As we transition into Industry 5.0, algorithms are making autonomous, consequential decisions at machine speed. Yet, corporate boards and risk committees are attempting to govern these gigahertz systems using static compliance checklists designed for a slower, simpler era. The result is a looming crisis of algorithmic discrimination, regulatory friction, and catastrophic reputational decay. When an opaque, black-box model hallucinates financial advice or leaks proprietary trade secrets, the ensuing failure cascade can destroy billions in market capitalization overnight.AI Governance and Risk Management provides the definitive, boardroom-ready blueprint for surviving the fragmented global regulatory dragnet. This book dismantles the illusion of traditional "Human-in-the-Loop" oversight, proving that true algorithmic safety requires hard, architectural constraints. Drawing on decades of technology operations and academic leadership, the text translates classical financial auditing principles into executable machine logic. The author brings unparalleled practical experience-from supporting six Silicon Valley startups in client-facing roles to develop computer vision use cases, to leading over 30 continuous improvement projects for Cisco Systems. Having authored foundational texts on Segregation of Duties (SOD) and Hierarchical SOD two decades ago, and backed by 15 years of teaching financial risk management, this expertise culminates in the AI Integrity Framework (AIIF). This Hamiltonian approach empowers organizations to embed continuous improvement cycles and strict SOD directly into their deployment pipelines.Readers will discover how to engineer automated "Build Breaks," architect deterministic kill switches, and secure the unstructured data supply chain against copyright contamination and intellectual property theft. By shifting from reactive public relations to proactive "Governance as Code," Chief Risk Officers, legal counsel, and audit committees can mathematically prove fiduciary control to regulators across overlapping jurisdictions, from California to the European Union.Authored by a veteran industry practitioner, creator of five previous Wiley &amp; Sons texts, and current developer of the Industry 5.0 and AI curriculum at Santa Clara University, this release is not a theoretical ethics manual. It is an uncompromising operational survival guide. It provides the exact structural tools necessary to transform artificial intelligence from an unquantified off-balance-sheet liability into a fully auditable, legally defensible, and highly profitable enterprise asset.

The AI Integrity Framework (AIIF) for Enterprise Control and Regulatory Compliance

Auditable AI Governance and Risk Management

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated learning and healthcare.Federated learning, a decentralized machine learning approach that enables model training across multiple devices or institutions without centralized data sharing, holds immense promise for revolutionizing healthcare by facilitating collaboration, preserving patient privacy, and improving healthcare outcomes. This book aims to unravel the complexities of federated learning and demonstrate its transformative potential in various healthcare applications. Through a combination of theoretical insights, practical guidelines, case studies, and real-world examples, the book aims to empower readers to harness the potential of federated learning to address pressing healthcare challenges effectively.Whether readers are healthcare professionals seeking to leverage data-driven approaches to improve patient care, researchers exploring innovative solutions at the intersection of machine learning and healthcare, policymakers grappling with regulatory and ethical considerations, or technologists developing cutting-edge healthcare solutions, this book serves as a valuable resource for understanding, implementing, and advancing federated learning in healthcare.

Empowering Wellness

Federated Learning Applications in Healthcare

The Promise and Peril of Navigating Our Agentic AI Future

When Machines Act

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact. Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments. You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behavior Featuring real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance. Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

'Book of the Year' as chosen by The Conversation 'Disconcerting . . . a disturbing and important book' NEW SCIENTIST 'Smart and wonderfully readable' NEW YORK TIMES The 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

Put AI to work to achieve your marketing goals An estimated 88% of marketers already use AI daily, and they're seeing real results in content creation, brand awareness, and sales. Marketing with AI For Dummies gives you the skills to simplify your workload, automate tasks, and make smarter marketing decisions. You'll learn to create personalized marketing, generate emails, and develop creative assets in record time -- all with AI doing the heavy lifting. This edition answers your questions to Agentic AI workflows, answer engine optimization, large language models, and synthetic personas. You'll also get guidance on AI ethics and current regulations, plus platform-specific AI features and the modern SEO landscape. Whether you're generating content or building personalized customer experiences, this book has you covered. Inside this book: <ul> <li>Learn how Agentic AI reshapes campaign execution and customer engagement through autonomous workflows</li> <li>Discover answer engine optimization and how to stay visible in AI-generated search results</li> <li>Explore large language models, including embeddings, fine-tuning, and retrieval-augmented generation for marketing</li> <li>Build synthetic personas for research, creative testing, and targeted message development</li> <li>Get up to speed on AI-mediated commerce and how AI influences recommendations and purchasing</li> </ul> Whether you're a seasoned marketer looking to level up your AI skills or someone who handles marketing as part of a bigger role, this Dummies guide makes it easy to get started. From content creation to predictive analytics, you'll find friendly, practical advice you can use to put AI to work for you right now.

Marketing with AI For Dummies

AI Powered Digital Twins

Weitere Titel zum Thema