Prepare for the coming convergence of AI and quantum computing A collection of essays from 20 renowned, international authors working in industry, academia, and government, Convergence: Artificial Intelligence and Quantum Computing explains the impending convergence of artificial intelligence and quantum computing. A diversity of viewpoints is presented, each offering their view of this coming watershed event. In the book, you’ll discover that we’re on the cusp of seeing the stuff of science fiction become reality, with huge implications for ripping up the existing social fabric, global economy, and current geopolitical order. Along with an incisive foreword by Hugo- and Nebula-award winning author David Brin, you’ll also find: Explorations of the increasing pace of technological development Explanations of why seemingly unusual and surprising breakthroughs might be just around the corner Maps to navigate the potential minefields that await us as AI and quantum computing come together A fascinating and thought-provoking compilation of insights from some of the leading technological voices in the world, Convergence convincingly argues that we should prepare for a world in which very little will remain the same and shows us how to get ready.

The integration of artificial intelligence (AI), quantum computing, and semiconductor technology offers improved innovation to redefine computational power and capabilities. As AI drives advances in machine learning and data processing, quantum computing revolutionizes problem-solving with its ability to handle complex calculations at improved speeds. Advancements in semiconductor technology push the limits of processing efficiency and miniaturization. Continued exploration on this convergence may accelerate breakthroughs in various fields such as cryptography, material science, and healthcare. Integration of AI, Quantum Computing, and Semiconductor Technology explores the intersection of artificial intelligence (AI) and semiconductor technology within the context of quantum computing. It offers a comprehensive analysis of the current advancements, challenges, and potential applications resulting from this convergence. This book covers topics such as cyber security, healthcare monitoring, and machine learning, and is a useful resource for computer engineers, energy scientists, business owners, healthcare administrators, environmental scientists, academicians, and researchers.

Artificial Intelligence, Blockchain and quantum computing are emerging technologies that are redefining various aspects of our daily lives. These technologies have the potential to revolutionize industry, optimize efficiency and address complex problems that were previously unimaginable. Over the years, there has been a significant increase in research and development in these fields, leading to remarkable discoveries and breakthroughs. These technologies are interconnected in many ways, and each complements and enhances the others. The book delves into the current status and future prospects of these technologies, their impact on different sectors and the challenges they present. AI, for example, has been a topic of interest for decades, but recent advances have taken its development to a new level, enabling machines to mimic human cognitive processes. Blockchain, on the other hand, popularized by cryptocurrencies such as Bitcoin, goes beyond digital currency, offering transparency and security in transactions. Quantum computing, although in its early stages, promises to perform complex calculations at astonishing speeds. However, along with their benefits, these technologies also pose ethical and technical challenges. The book highlights the importance of interdisciplinary collaboration and continued research to fully unlock the transformative potential of AI, Blockchain and quantum computing.

Picture a world where autonomous systems operate continuously and intelligently, utilizing real-time data to make informed decisions. Such systems have the potential to revolutionize agriculture, urban infrastructure, and industrial automation. This transformation, often termed the Internet of Self-Sustaining Systems (IoSS), is a pivotal topic that demands academic attention and exploration. Addressing this critical issue head-on is The Convergence of Self-Sustaining Systems With AI and IoT, which offers an in-depth examination of this transformative convergence. It serves as a guiding light for academic scholars seeking to unravel the vast potential of self-sustaining systems coupled with AI and IoT. Inside its pages, readers will delve into AI-driven autonomous agriculture, eco-friendly transportation solutions, and intelligent energy management. Moreover, the book explores emerging technologies, security concerns, ethical considerations, and governance frameworks. Join us on this intellectual journey and position yourself at the forefront of the AI and IoT revolution that promises a sustainable, autonomous future.

Blockchain (BC) and artificial intelligence (AI) are currently two of the hottest computer science topics and their future seems bright. However, their convergence is not straightforward, and more research is needed in both fields. Thus, this book presents some of the latest advances in the convergence of BC and AI, gives useful guidelines for future researchers on how BC can help AI and how AI can become smarter, thanks to the use of BC. This book specifically analyzes the past of BC through the history of Bitcoin and then looks into the future: from massive internet-of-things (IoT) deployments, to the so-called metaverse, and to the next generation of AI-powered BC-based cyber secured applications.

Smart Cities and Artificial Intelligence offers a comprehensive view of how cities are evolving as smart ecosystems through the convergence of technologies incorporating machine learning and neural network capabilities, geospatial intelligence, data analytics and visualization, sensors, and smart connected objects. These recent advances in AI move us closer to developing urban operating systems that simulate human, machine, and environmental patterns from transportation infrastructure to communication networks. Exploring cities as real-time, living, dynamic systems, and providing tools and formats including generative design and living lab models that support cities to become self-regulating, this book provides readers with a conceptual and practical knowledge base to grasp and apply the key principles required in the planning, design, and operations of smart cities. Smart Cities and Artificial Intelligence brings a multidisciplinary, integrated approach, examining how the digital and physical worlds are converging, and how a new combination of human and machine intelligence is transforming the experience of the urban environment. It presents a fresh holistic understanding of smart cities through an interconnected stream of theory, planning and design methodologies, system architecture, and the application of smart city functions, with the ultimate purpose of making cities more liveable, sustainable, and self-sufficient.

This book provides a comprehensive account of Chinese AI in its various facets, based on primary Chinese-language sources. China’s rise as an AI power is an event of importance to the world and a potential challenge to liberal democracies. Filling a gap in the literature, this volume is fully documented, data-driven, and presented in a scholarly format suitable for citation and for supporting downstream research, while also remaining accessible to laypersons. It brings together 15 recognized international experts to present a full treatment of Chinese artificial intelligence. The volume contains chapters on state, commercial, and foreign sources of China’s AI power; China’s AI talent, scholarship, and global standing; the impact of AI on China’s development of cutting-edge disciplines; China’s use of AI in military, cyber, and surveillance applications; AI safety, threat mitigation, and the technology’s likely trajectory. The book ends with recommendations drawn from the authors’ interactions with policymakers and specialists worldwide, aimed at encouraging AI’s healthy development in China and preparing the rest of the world to engage with it. This book will be of much interest to students of Chinese politics, science and technology studies, security studies and international relations.

Today's supply chains are becoming more complex and interconnected. As a result, traditional optimization engines struggle to cope with the increasing demands for real-time order fulfillment and inventory management. With the expansion and diversification of supply chain networks, these engines require additional support to handle the growing complexity effectively. This poses a significant challenge for supply chain professionals who must find efficient and cost-effective solutions to streamline their operations and promptly meet customer demands. Quantum Computing and Supply Chain Management: A New Era of Optimization offers a transformative solution to these challenges. By harnessing the power of quantum computing, this book explores how supply chain planners can overcome the limitations of traditional optimization engines. Quantum computing's ability to process vast amounts of data from IoT sensors in real time can revolutionize inventory management, resource allocation, and logistics within the supply chain. It provides a theoretical framework and practical examples to illustrate how quantum algorithms can enhance transparency, optimize dynamic inventory allocation, and improve supply chain resilience.

Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary to provide perspective on the implications as one continuous stream of technology. It then discusses scalable and adaptive deep learning algorithms, which work in modern machine learning systems where there is a deluge of data. These algorithms sufficiently prepare AI technologies to face the challenges of increasing data as well as expansion of computational capabilities. Chapter three is Federated learning for Edge AI further makes privacy / personalization and security stronger. The amalgamation of blockchain emphasizes the robust and distributed nature of edge intelligence in modern IoT ecosystems. One of the most pressing issues in today's ethical landscape is that of Explainable Artificial Intelligence (XAI), and so the fourth chapter deals with some recent advances in explaining black-box models, providing a way to better understand -and thus potentially trust- AI-driven decision-making processes. This study explores the application of Automated Machine Learning (AutoML) in the contexts of Industry 4.0 and Society 5.0 giving insights on how automation can bring efficiency and innovation in different sectors. It also presents information on the challenges and opportunities that AutoML faces. In conclusion, the book discusses Artificial General Intelligence (AGI), which is a new topic that presents an ambitious view of what AI may be capable of in the future and some points to digest over how the concept might relate to our understanding on what industry may look like in the next stage of human evolution. Individually, these chapters offer a slice of the overall picture of where AI technologies are headed to keep pace with an advancing world.