Book Image

Neuro-Symbolic AI

By : Alexiei Dingli, David Farrugia
Book Image

Neuro-Symbolic AI

By: Alexiei Dingli, David Farrugia

Overview of this book

Neuro-symbolic AI offers the potential to create intelligent systems that possess both the reasoning capabilities of symbolic AI along with the learning capabilities of neural networks. This book provides an overview of AI and its inner mechanics, covering both symbolic and neural network approaches. You’ll begin by exploring the decline of symbolic AI and the recent neural network revolution, as well as their limitations. The book then delves into the importance of building trustworthy and transparent AI solutions using explainable AI techniques. As you advance, you’ll explore the emerging field of neuro-symbolic AI, which combines symbolic AI and modern neural networks to improve performance and transparency. You’ll also learn how to get started with neuro-symbolic AI using Python with the help of practical examples. In addition, the book covers the most promising technologies in the field, providing insights into the future of AI. Upon completing this book, you will acquire a profound comprehension of neuro-symbolic AI and its practical implications. Additionally, you will cultivate the essential abilities to conceptualize, design, and execute neuro-symbolic AI solutions.
Table of Contents (12 chapters)

The pitfalls of AI

Sometimes, it is easy to get caught up in the AI hype, and we can get the impression that AI can solve all the problems of the world. It is essential to analyze AI pitfalls because they can help us understand what’s real and what’s not, and what works and what doesn’t.

Is AI limitless?

When we look at different AI applications, many are simply amazing: self-driving cars, pizza delivery drones, machine-brain interfacing, and so many others. But have we ever stopped and asked ourselves whether they are ready for use or whether they’re just a concept? Because unfortunately, many of these amazing applications are created in a lab but they’re not commercialized, yet people make a lot of hype about them. So, there’s a thin line between what is production-ready and what isn’t. When looking at different applications, you have to do some due diligence, speak with experts, and try to understand the current state of the...