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Gesamtkatalog

Catalogue complet

Artificial Intelligence for Legal System

Jurisprudence in the Digital Age

1. Artificial Intelligence in the Realm of Justice: Revisit to the Jurisprudential Notions of Justice 2. Safeguarding Personal Data and Privacy (PDP) in The Era of Artificial Intelligence (Ai) Through The Human Rights Lens: Exploring Legal Hurdles And Policy Implications 3. Liability in the Age of AI: Perspectives on Criminal and Civil Responsibility for AI-Induced Harm 4. Constitutional Echoes in the Age of Artificial Intelligence: Bridging Literature, Law, and Technology 5. Enhancing Legal Research Engagement with ChatGPT: An AI Tool Perspective 6. Responsible Application of Artificial Intelligence in the State: The Case of Chile 7. Uncover the Potential of Artificial Intelligence in Legal System Flaking Crime Prevention: Breakthrough New Tools for Law Enforcement in the Digital- Futuristic Arena 8. The Watchful Eye: Exploring Artificial Intelligence as the Contemporary Panopticon in the Criminal Justice System 9. A Small But Digital Step in Cross-Border Judicial Cooperation of EU Member States 10. A Few Critical People to Handle the Truth: AI, Hallucinations and the Labour of Law Clerks 11. Algorithmic Democracy: Exploring The Impact Of Artificial Intelligence on Elections in India - A Case Study in Odisha &amp; West Bengal 12. Justice in the Digital Age: Popular Culture and the Rise of AI-Powered Legal Decision-Making 13. The Intersection of Artificial Intelligence and Procedural Laws: Reimagining Justice in the Digital Era 14. Utility and Efficiency of Ai-Driven Legal System: Illustrations Around The Globe

Medical and Technical Analysis and Signal Processing Perspectives

Exploring Infant Cry

Augmented and Virtual Reality in Healthcare

A Path to Sustainable Development Goals

AI and ML Techniques in IoT-based Communication

Depending on who you ask, artificial intelligence is our salvation or our doom; an overhyped, bigoted artist or the ticket to immortality and utopian abundance; just another tech fad or the last invention we need ever make. The AI discourse is confusing, messy, and frustrating. But the technology — and our response to it — will shape the future, whether or not we’re part of the conversation.
Obsolete is&nbsp;for those who are interested in learning more about AI, but unsure of where to start and who to believe. They may feel intimidated by the technical jargon, put off by dry and abstract prose, or skeptical of the loudest voices on the issue (like Elon Musk and Sam Altman). Obsolete will introduce readers to the basics of AI, the idea that it could lead to human extinction, the roiling three-sided debate surrounding extinction fears, and the people and companies trying to build artificial general intelligence (AGI) — that which can outwit humans across the board. The book will grapple with the core arguments animating the AI debates, which are, by turns, uncritically parroted and unduly dismissed. It will also cut through industry hype while seriously entertaining the implications of AGI.
The risk that AGI could result in our extinction is being recognized by a significant and growing number of leading AI researchers, industrialists, and policymakers, along with the wider public. Existential risk from AI has been explored in other books, but Obsolete will be the first to center its analysis on how both capitalist and great power competition make AI more dangerous.
Obsolete will also tackle questions like: Can machines actually outsmart humanity? If so, when could that happen? If AGI is possible, is it inevitable? Why are people trying to build a technology they claim could end the world? Is the idea of AI-driven extinction the product of a big tech conspiracy aiming to hype the technology and control its regulation? Why has the left mostly ignored or dismissed existential risk from AI? Why do some powerful techies welcome human extinction? How could AI enable stable authoritarian regimes? How could killer robots reshape war and the balance of power? What do China and the US want from AI? And why has it become the front line of their brewing Cold War? And finally: What can and should the left do about it?

Power, Profit, And The Race For Machine Superintelligence

Obsolete

Enhancing Reflective Teaching in Higher Education

Redefining Teaching and Learning

GenAI in Higher Education

Up-to-date reference enabling readers to address the full spectrum of AI security challenges while maintaining model utility Generative AI Security: Defense, Threats, and Vulnerabilities delivers a technical framework for securing generative AI systems, building on established standards while focusing specifically on emerging threats to large language models and other generative AI systems. Moving beyond treating AI security as a dual-use technology, this book provides detailed technical analysis of three critical dimensions: implementing AI-powered security tools, defending against AI-enhanced attacks, and protecting AI systems from compromise through attacks like prompt injection, model poisoning, and data extraction. The book provides concrete technical implementations supported by real-world case studies of actual AI system compromises, examining documented cases like the DeepSeek breaches, Llama vulnerabilities, and Google's CaMeL security defenses to demonstrate attack methodologies and defense strategies while emphasizing foundational security principles that remain relevant despite technological shifts. Each chapter progresses from theoreticalfoundations to practical applications. The book also includes an implementation guide and hands-on exercises focusing on specific vulnerabilities in generative AI architectures, security control implementation, and compliance frameworks. Generative AI Security: Defense, Threats, and Vulnerabilities discusses topics including: <ul> <li>Machine learning fundamentals, including supervised, unsupervised, and reinforcement learning and feature engineering and selection</li> <li>Intelligent Security Information and Event Management (SIEM), covering AI-enhanced log analysis, predictive vulnerability assessment, and automated patch generation</li> <li>Deepfakes and synthetic media, covering image and video manipulation, voice cloning, audio deepfakes, and AI's greater impact on information integrity</li> <li>Security attacks on generative AI, including jailbreaking, adversarial, backdoor, and data poisoning attacks</li> <li>Privacy-preserving AI techniques including federated learning and homomorphic encryption</li> </ul> Generative AI Security: Defense, Threats, and Vulnerabilities is an essential resource for cybersecurity professionals and architects, engineers, IT professionals, and organization leaders seeking integrated strategies that address the full spectrum of Generative AI security challenges while maintaining model utility.

Triangulating AI Security

The MIT Press Essential Knowledge series

Auditing AI

Smart Charging Infrastructures

Medical Robots and Devices: New Developments and Advances

AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies. The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

AI and Data Science in Medical Research

Machine Learning For Dummies

Intelligent IoT-based Diagnostic and Assistive Systems for Neurological Disorders

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. The book covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing. Furthermore, it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

Artificial Intelligence for Legal System

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