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Gesamtkatalog

Catalogue complet

Autonomous Vehicle Safety Solutions

Foundations, Technologies, and Prospects for the Future

Micro & Nano Technologies

The advances in microsystems offer new opportunities and capabilities to develop systems for biomedical applications, such as diagnostics and therapy. In its third edition, Microsystems for Bioelectronics offers a comprehensive treatment of microsystems by thoroughly covering basic physics, chemistry, biology, materials, and engineering concepts, with an emphasis on the performance limits associated with the shrinking scale of microsystems. Microsystems for Bioelectronics: Scaling and Performance Limits considers physical principles and trends in extremely scaled autonomous microsystems such as integrated intelligent sensor systems, with a focus on energy minimization. It explores the implications of energy minimization on device and system architecture. It further details behavior of electronic components and its implications on system-level scaling and performance limits. In particular, fundamental scaling limits for energy sourcing, sensing, memory, computation and communication subsystems are developed and new applications such as optical, magnetic and mechanical sensors are presented. This fully revised and updated edition includes information on DRAM and 3D NAND semiconductor memories, betavoltaic energy conversion, advanced packaging, recent technology trends, and new technology roadmaps. The new edition of this well-proven book with its unique focus and interdisciplinary approach shows the complexities of the next generation of nanoelectronic microsystems in a clear and easy-to-understand manner, and is aimed for a broad audience within several disciplines.

Scaling and Performance Limits

Microsystems for Bioelectronics

Multi-Agent Control Systems

This book is a comprehensive guide that immerses you into the world of building and deploying AI-powered solutions. You are introduced to the core architecture of LLMs and equipped with essential Best Data Practices (BDPs) for utilizing Generative AI responsibly, ensuring ethical and efficient AI deployment.The book starts with the foundational aspects of Generative AI application development. You will learn the nuances of data handling in Generative AI apps, from working with embeddings to managing unstructured and structured data, and handling Personally Identifiable Information (PII) data. The exploration extends to understanding the differences between deterministic and LLM-based data synthesis and integrating Generative AI apps with enterprise data, providing you with practical insights into leveraging data effectively for intelligent applications. A chapter on prompt engineering explains the importance of prompts in AI interactions, covering a spectrum of techniques and pitfalls while offering exercises to enhance prompt engineering skills. As you progress through the book, you take a journey from conceptualization to production and deployment of Generative AI applications. You discover the essentials of Generative AI application development, gain insights into the pathway from ideation to production, and explore the intricacies of LLM selection and fine-tuning.The book equips you with the knowledge and tools necessary to navigate the complex terrain of AI development and deployment, making it an indispensable resource for AI enthusiasts, developers, and business leaders alike.What You Will Learn<ul><li>Know the core architecture of LLMs and how these models have revolutionized AI applications</li><li>Handle various data types, including unstructured, structured, and personally identifiable information (PII) data in Generative AI applications</li><li>Understand prompt engineering and its importance in AI interactions and applications</li><li>Understand modular design of Generative AI apps, essential backend and frontend components, and the unique principles guiding Generative AI app design</li></ul>&nbsp;&nbsp;

Building and Deploying Ethical AI-Powered Solutions

Practical Generative AI: From Concept to Deployment

Six Dimensions of Business Dark Data

Agentic Hyper-Personalized Dimensions

Smart Charging Infrastructures

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

Machine Learning For Dummies

Praise for IRREPLACEABLE "If you think AI is just about robots and algorithms, think again. IRREPLACEABLE will shatter your assumptions and challenge you to reimagine what it means to be human in a machine age." -Dr. Marshall Goldsmith, Thinkers50 #1 Executive Coach and New York Times Bestselling Author of The Earned Life, Triggers, and What Got You Here Won't Get You There "IRREPLACEABLE is addressing the most important question of our time: how do we keep our humanity front and center in an AI-dominated world? I challenge you to find a book more timely and relevant!" -Klaus Schwab, Founder and Executive Chairman of the World Economic Forum "IRREPLACEABLE is a vital guide to thinking differently and working confidently in tandem with AI. Pascal Bornet's insights and strategies are essential to succeed with customers and colleagues, in your community and career." -Ron Kaufman, New York Times Bestselling Author of Uplifting Service "In a world obsessed with the power of AI, IRREPLACEABLE dares to ask the question: what makes us human? The answer may surprise you." -Dr. Luc Julia, Co-Founder of Apple Siri "One of the most important books of our times, Pascal Bornet's IRREPLACEABLE is a must-read guide for navigating the AI revolution, empowering readers to excel personally and professionally in a technology-driven world." -Bernard Marr, Futurist, Internationally Bestselling Author "A very practical guide to strengthening our humanity with AI." -Nir Eyal, Bestselling Author of Hooked and Indistractable "Both a wake-up call and a practical guide to rediscover what makes us truly human in the age of AI." -Gerd Leonhard, Futurist and Humanist "I've always believed that AI will enhance human capabilities rather than replace them. This excellent book provides a roadmap for individuals and organizations to become effective partners with smart machines. Follow its advice, and you'll be well-equipped for the present and the future." -Thomas H. Davenport, Distinguished Professor, Babson College; Author of Only Humans Need Apply, Working with AI, and All In on AI "IRREPLACEABLE challenges us to confront the ultimate dilemmas: who are we, and what is our purpose in a world transformed by AI? The answers may just change your life." -Professor Jochen Wirtz, Vice Dean MBA Programmes, National University of Singapore "IRREPLACEABLE forces us to question our future in an increasingly technologically mediated world and learn to take action!" -Leonard A. Schlesinger, Baker Foundation Professor, Harvard Business School

The Art of Standing Out in the Age of Artificial Intelligence

IRREPLACEABLE

Embedded System and GUI Development using MATLAB for Engineering Applications

Concepts, Challenges and Applications

Platform Engineering

In an era of escalating energy demands and environmental challenges, mastering the complexities of renewable power systems is essential. This open access book delivers a cutting-edge exploration of innovative modeling and control techniques tailored for the unique characteristics of renewable power systems. Designed for engineers, researchers, and sustainability advocates, this book addresses critical issues such as low inertia and high variability, offering a roadmap to ensure safe, stable, and efficient operation. This comprehensive guide introduces the fully actuated system approach, a groundbreaking method that redefines how we tackle the nonlinear dynamics inherent in renewable power systems. By presenting experimentally validated solutions on hardware microgrids, the book bridges the gap between theory and practice, making it an indispensable resource for professionals aiming to enhance system reliability and control efficiency. Key topics include predictive control for DC and AC systems, learning-based optimization, and resilience strategies against cyber threats, with advanced applications like blockchain integration for secure operations. Readers will gain actionable insights into modern control strategies, rigorous modeling techniques, and emerging technologies shaping the future of renewable power systems. Whether you’re developing advanced control technologies or navigating the challenges of modern power systems, this book equips you with the knowledge and tools to lead in the renewable energy revolution.

Autonomous Vehicle Safety Solutions

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