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Neuro-Symbolic AI

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

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781804617625
Length 196 pages
Edition 1st Edition
Concepts
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Authors (2):
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Alexiei Dingli Alexiei Dingli
Author Profile Icon Alexiei Dingli
Alexiei Dingli
David Farrugia David Farrugia
Author Profile Icon David Farrugia
David Farrugia
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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

Subfields of AI

Now that we’ve explored the origins of AI and understood how it evolved over the years, let’s look at the different subfields that constitute this vast field of study. At this stage, it’s important to note that there isn’t a single subdivision acceptable to everyone. There might be other ways of dividing these areas, and some might also overlap. However, this is an attempt at logically organizing the subfields of AI.

Figure 1.2 – Subfields of AI

Figure 1.2 – Subfields of AI

ML

ML tries to create algorithms capable of learning. It typically starts by using data found in a training set and then generates predictions out of that data. DL is one of the various subfields of ML, which tries to create learning algorithms while gaining inspiration from the brain’s inner workings. Today, this subfield is considered the superstar of AI, and in fact, it is used in almost all the other subfields. ML has various applications such as...

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