Quantum AI: Beyond the Bit

How to develop apps using Quantum AI

By: Ajit Singh

Narrated by: Virtual Voice

"Quantum AI: Beyond the Bit" is a comprehensive, application-focused textbook designed to equip computer science students and developers with the practical skills needed to build applications at the intersection of quantum computing and artificial intelligence. This book demystifies Quantum AI by treating it as an engineering discipline. It eschews dense theoretical physics in favor of a clear, step-by-step methodology for designing, coding, and implementing quantum-enhanced machine learning models. We start with a simple question—"How can we use a quantum computer to solve an AI problem?"—and every chapter is dedicated to answering that question in progressively greater detail.


Philosophy

The core philosophy of this book is "Application over Abstraction." While a conceptual understanding of quantum mechanics and AI is necessary, the ultimate goal of an engineer is to build. This book demystifies Quantum AI by treating it as an engineering discipline. It eschews dense theoretical physics in favor of a clear, step-by-step methodology for designing, coding, and implementing quantum-enhanced machine learning models. We will start with a simple question—"How can we use a quantum computer to solve an AI problem?"—and every chapter is dedicated to answering that question in progressively greater detail.



Key Features

1. Strictly Application-Oriented: More than 70% of the content is dedicated to practical implementation, code examples, and application development.

2. Capstone Project: A dedicated final chapter guides the reader through building a complete, working Quantum AI application from scratch, including fully explained code.

3. Beginner to Advanced: The book caters to beginners with no prior quantum experience and provides a solid ramp-up to advanced topics like Quantum Neural Networks and hybrid model integration.

4. Real-World Tooling: Focuses on popular and industry-relevant Python libraries and platforms like Qiskit, and frameworks for hybrid model integration.

5. Clear and Concise: Written in simple, accessible language with numerous diagrams, code blocks, and step-by-step instructions.


Key Takeaways

Upon completing this book, you will be able to:

1. Understand the fundamental concepts of Quantum AI and its practical significance.

2. Set up a complete development environment for building Quantum AI applications.

3. Implement core Quantum Machine Learning algorithms like the Variational Quantum Classifier (VQC).

4. Design and build hybrid quantum-classical AI models.

5. Develop a complete, end-to-end Quantum AI application for a task like image classification.

6. Analyze the current limitations and future scope of Quantum AI.


Disclaimer: Earnest request from the Author.

Kindly go through the table of contents and refer kindle edition for a glance on the related contents.

Thank you for your kind consideration!