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Neuro-Symbolic AI

Neuro-Symbolic AI

By : Alexiei Dingli, David Farrugia
3.7 (6)
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Neuro-Symbolic AI

Neuro-Symbolic AI

3.7 (6)
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)
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Delving into deep neural networks

So far, we’ve scratched the surface of several ANNs, because there are so many variants that it would be very difficult to collate them all in this document, and it would be beyond the scope of this book. The main problem with ANNs was that toward the end of the last century, they hit a brick wall, and advancements were moving at a relatively slow pace.

This changed soon after the turn of the century due to three main reasons:

  • The amount of information available online in digital form provided a fertile ground for data-hungry algorithms such as ANNs. Just consider that up to 90% of the world’s data was created in the past 2 years, and is constantly increasing at an impressive rate of 2.5 quintillion bytes of data per day.
  • The advancement in video game development. Back then, game developers were looking at ways in which they could improve the graphics. Because of this, they needed a more powerful and dedicated processor...

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