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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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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

Artificial neural networks modeling the human brain

As we’ve just seen, large interconnected neural networks help us process information and model the world around us. In simple terms, as can be seen in Figure 3.1, a neuron gathers information from others using the dendrites, sums up all the inputs, and if the resultant value is beyond a certain threshold, it fires. This signal is then sent to connecting neurons through the axon. So, the dendrites are our input, the nucleus inside the neuron is where the processing happens, and the axon is our output.

Figure 3.1: The neuron (Designed by brgfx/Freepik)

Figure 3.1: The neuron (Designed by brgfx/Freepik)

If we were to translate the concepts behind the neuron as illustrated in Figure 3.1 to a computer, we would have a structure similar to the diagram in Figure 3.2. Essentially the dendrites are represented by the input nodes and there can be various inputs (X1, X2, X3, …, and Xn). Since each physical dendrite might have different strength, this...

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