Convergence Artificial Intelligence And Quantum Computing

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.

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.

Quantum Artificial Intelligence (QAI) is a new interdisciplinary research field that combines quantum computing with Artificial Intelligence (AI), aiming to use the unique properties of quantum computers to enhance the capabilities of AI systems. Quantum Artificial Intelligence with Qiskit provides a cohesive overview of the field of QAI, providing the tools for readers to create and manipulate quantum programs on devices as accessible as a laptop computer. Introducing symbolical quantum algorithms, sub-symbolical quantum algorithms, and quantum Machine Learning (ML) algorithms, this book explains each process step by step with associated Qiskit listings. All examples are additionally available for download at https://github.com/andrzejwichert/qai. Allowing readers to learn the basic concepts of quantum computing on their home computers, this book is accessible to both the general readership as well as students and instructors of courses relating to computer science and AI.

Explore the groundbreaking convergence of quantum mechanics and artificial intelligence in this captivating exploration of the future. Delve into the transformative potential of quantum computing, quantum algorithms, and quantum-enhanced machine learning as they intertwine with cutting-edge AI techniques. Uncover applications spanning industries from healthcare to space exploration, while addressing ethical considerations, collaboration on a global scale, and the intriguing prospects of a quantum AI singularity. This book invites you to grasp the profound impact of Quantum AI, both on technological horizons and the way we perceive intelligence itself.

The convergence of quantum technologies and biomedical intelligence is a frontier of boundless potential. The quantum advancements revolutionize disease detection, personalized medicine, and health monitoring frameworks while confronting the pressing challenge of accountability in machine learning systems within the biomedical domain. How do quantum innovations at the nexus of biomedical intelligence redefine biomedical research and healthcare, addressing critical inquiries such as the transformative potential of quantum computing, machine learning, and sensing technologies? Quantum Innovations at the Nexus of Biomedical Intelligence explores the intricate synergy between quantum mechanics and the biomedical domain. This book elucidates the profound implications and applications arising from the fusion of quantum computing, artificial intelligence, and biomedical sciences. This book introduces biomedical engineering, setting the stage for a deep dive into the transformative role of quantum computing and artificial intelligence. As the narrative unfolds, the text navigates the reader through the uncharted territories of quantum-enhanced machine learning, quantum sensing and their profound impact on diagnostics, personalized medicine, and health monitoring frameworks. The intersection of quantum computing and AI in medical advancements and cybersecurity is illuminated, offering a comprehensive understanding of the multifaceted applications of these cutting-edge technologies. This book is ideal for researchers, scientists, academics, and professionals across diverse disciplines in quantum innovations within biomedical intelligence.

ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networks Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency. In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few. The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machines An exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and more Discussions of explainable neural networks and XAI Examinations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technology Perfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.