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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

Research gaps in neuro-symbolic computing

Although the field of NSAI has grown significantly in research interest and popularity, it is still maturing. NSAI is proving to be rather promising and is seeing major financial investment from strong research and technical institutions such as MIT and IBM. In this section, we will briefly highlight the future NSAI research direction and study avenues of interest:

  • Standardized datasets and comprehensibility tests for benchmarking:

Like the existing CLEVR and CLEVRER datasets, the domain of NSAI would benefit from common datasets that can be used to benchmark existing and new techniques. These standardized resources are critical for comparative research.

  • Strategies for NN inference using symbolic propositions.
  • More comparative evaluations on the NSAI paradigm to determine the best NN architecture to use.
  • Context-aware semantics:

Further investigation on how semantics can be constructed and influenced by...

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