Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Neuro-Symbolic AI

You're reading from   Neuro-Symbolic AI Design transparent and trustworthy systems that understand the world as you do

Arrow left icon
Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781804617625
Length 196 pages
Edition 1st Edition
Concepts
Arrow right icon
Authors (2):
Arrow left icon
Alexiei Dingli Alexiei Dingli
Author Profile Icon Alexiei Dingli
Alexiei Dingli
David Farrugia David Farrugia
Author Profile Icon David Farrugia
David Farrugia
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: The Evolution and Pitfalls of AI 2. Chapter 2: The Rise and Fall of Symbolic AI FREE CHAPTER 3. Chapter 3: The Neural Networks Revolution 4. Chapter 4: The Need for Explainable AI 5. Chapter 5: Introducing Neuro-Symbolic AI – the Next Level of AI 6. Chapter 6: A Marriage of Neurons and Symbols – Opportunities and Obstacles 7. Chapter 7: Applications of Neuro-Symbolic AI 8. Chapter 8: Neuro-Symbolic Programming in Python 9. Chapter 9: The Future of AI 10. Index 11. Other Books You May Enjoy

Introducing Neuro-Symbolic AI – the Next Level of AI

Throughout the previous chapters, we discussed how the primary motivation behind artificial intelligence (AI) is to model human intelligence into computer systems. Over the years, we have witnessed the innovation of many algorithms and techniques that improved computer cognitive and logical processing machines. In Chapter 2, we introduced symbolic AI as one of the first research efforts targeted toward achieving this highly desirable accolade. We discussed how symbolic AI has enabled us to embed world-knowledge constructs (logical rules) into our computer systems. However, the symbolic AI process has proven to be rather cumbersome and expensive. Researchers have also discovered that symbolic AI programs tend to lose accuracy as more rules are represented in the program. To circumvent the tedious process of symbolic rule representation, the field shifted its focus to more data-driven techniques.

Neural networks (NNs) and...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime