Quantum-Enhanced Cloud AI:The Next Frontier in Machine Learning and Deep Learning

Satveer Kour, Harvinder Singh, Anupam Bonkra

• Publisher: Bentham Science Publishers
• Year: 2026
• Topic: Computer Science
• eBook ISBN:
  9798898813215
• Subtopic: Computer Science General
• Index: Computer Science

Quantum-Enhanced Cloud AI: The Next Frontier in Machine Learning and Deep Learning presents a scholarly and comprehensive examination of the convergence of quantum computing, cloud infrastructure, and advanced artificial intelligence. As classical computing approaches approach their practical and physical limits, this volume positions quantum-enhanced cloud platforms as a transformative foundation for next-generation machine learning and deep learning systems.

The book systematically introduces core principles of quantum computing, cloud-based quantum architectures, and hybrid quantum–classical models, establishing a strong conceptual foundation before advancing to practical implementations. It critically examines quantum algorithms, error correction challenges, coherence limitations, and architectural considerations that shape the feasibility of Quantum AI. Through detailed case studies and comparative analyses, the book demonstrates how quantum machine learning techniques can outperform classical approaches in domains such as healthcare, bioinformatics, finance, cybersecurity, agriculture, smart cities, and Internet of Vehicles systems. Emerging topics including edge intelligence, quantum-enabled IoT, sustainable supply chains, and secure cloud-based healthcare frameworks are also explored.

Written in a rigorous yet accessible style, this reference work serves graduate students, researchers, and professionals seeking to understand both the theoretical underpinnings and real-world implications of quantum-enhanced AI. It offers valuable insights into the technological, industrial, and societal impact of this rapidly evolving field.



Key Features

· Comprehensive coverage of quantum computing principles and cloud-based AI architectures

· In-depth analysis of hybrid quantum–classical machine learning models and algorithms

· Comparative evaluation of quantum and classical AI approaches across multiple application domains

· Practical insights into implementation challenges, scalability, and security

· Forward-looking perspectives on the future of Quantum AI and intelligent computing systems.

Table of contents

• Welcome
• Table of Contents
• Title
• BENTHAM SCIENCE PUBLISHERS LTD.
• FOREWORD
• Preface
• List of Contributors
• Quantum-Powered AI in the Cloud: Unleashing the Future of Intelligent Computing
• Revolutionize AI: Quantum-Cloud Delves into Integration Strategies, Benefits, and Future Prospects
• Applications of Quantum AI in Healthcare, Finance, and Cybersecurity
• Cloud Quantum Computing for AI: Innovations, Challenges, and Applications
• Quantum Algorithms for Machine Learning
• Quantum-Driven AI: The Intersection of Quantum Computing and Machine Learning Algorithms
• Comparative Analysis for Human Protein Function Prediction through Machine Learning Techniques and Performance Enhancement Using Quantum Machine Learning (QML)
• Quantum AI for Natural Language Processing and Computer Vision
• Edge Computing and Real-time Decision Making with Quantum AI
• A Comparative Study on Unsupervised Machine Learning Techniques for Agricultural Data Analysis
• The Transformative Applications of Quantum Artificial Intelligence in Healthcare, Finance, and Cybersecurity
• Shielding IoT-Driven Healthcare: A Secure and Lightweight Authentication Protocol for Patient Data Protection
• Exploring the Role of Quantum AI in Enhancing the Web Accessibility Evaluation Techniques
• A Quantum Intelligence AI-Driven Secure Framework for IoV: QI-CAI Clustering Architecture with FDS-QI Deep Learning Security Model
• Wireless Sensor Networks in the Age of AI and Quantum Computing