What this book covers

Chapter 1, The Evolution and Pitfalls of AI, provides an introduction to the fundamentals of AI, its various types, uses, benefits, and limitations, as well as the mechanics of building AI systems.

Chapter 2, The Rise and Fall of Symbolic AI, discusses the concept of symbolic learning and its history, inner mechanics, and limitations.

Chapter 3, The Neural Networks Revolution, introduces neural networks, their types, potential use cases, and limitations.

Chapter 4, The Need for Explainable AI, highlights the motivation for explainable AI (XAI), its importance, and the current state-of-the-art techniques.

Chapter 5, Introducing Neuro-Symbolic AI: The Next Level of AI, introduces the composite AI topic of neuro-symbolic AI, its mechanics, and its emergence as a way forward for AI development.

Chapter 6, A Marriage of Neurons and Symbols: Opportunities and Obstacles, explores the trade-offs between reasoning and learning and the benefits, challenges, and research gaps in neuro-symbolic computing.

Chapter 7, Applications of Neuro-Symbolic AI, showcases different neuro-symbolic AI applications based on different techniques, inspiring creativity in the adoption of this composite technology.

Chapter 8, Neuro-Symbolic Programming in Python, provides a basic programmatic outline to design and implement neuro-symbolic systems in Python.

Chapter 9, The Future of AI, discusses future developments of AI, the rise of artificial general intelligence (AGI), and the ethical issues associated with the creation of singularity.