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Neuro-Symbolic AI

Neuro-Symbolic AI

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

Neuro-Symbolic AI

3.7 (6)
By: Alexiei Dingli, 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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The Future of AI

I’m sure that by now, no one is doubting that artificial intelligence (AI) is one of the most powerful technologies of our time. It has enabled breakthroughs in many domains, including computer vision, natural language processing, speech recognition, self-driving cars, and more. But the million-dollar question is, what does the future hold? How will it impact our society, economy, and environment? What are the opportunities and challenges that lie ahead?

Top experts have different viewpoints on the matter.

Geoffrey Hinton, one of the pioneers of deep learning, believes that we need to go beyond the current paradigm of neural networks and explore new ways of modeling complex phenomena, such as causality, common sense reasoning, and consciousness. Recently, Geoffrey Hinton resigned from his position at Google over growing concerns about the ethical implications of AI.

Yoshua Bengio, another deep learning pioneer, is excited about generative AI models...

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Neuro-Symbolic AI
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