Alexiei Dingli

The book presents a unique study on the Artificial Intelligence (AI) readiness of public administrations focusing on the Maltese public administration as a case study. This was conducted following the launch of the Malta AI National Strategy in 2019. Since the Maltese public administration is the driving force behind the integration of AI solutions nationwide, the research is deemed necessary to understand whether the public workforce itself is ready to face the oncoming AI revolution. The researchers applied a mixed-methods approach to gain insight and a broader perspective of the status quo concerning AI adoption. Important considerations that stem from this study include the need for increased AI knowledge among public administrators since the majority of respondents reported a lack of awareness of AI technologies and their deployment. Understanding AI-related advantages must be accompanied by a robust instructional effort at all levels of education. It was unanimously agreed that the early inclusion of AI-related courses in the Maltese educational system will aid in developing a future AI-savvy workforce. Furthermore, upskilling and reskilling the public officers will facilitate knowledgeable human capital and proficiencies required to effectively integrate AI solutions within society. The study concludes by recommending several critical reforms within governments that will improve the AI-readiness factor of any Public Administration.

Explore the inner workings of AI along with its limitations and future developments and create your first transparent and trustworthy neuro-symbolic AI system Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand symbolic and statistical techniques through examples and detailed explanations Explore the potential of neuro-symbolic AI for future developments using case studies Discover the benefits of combining symbolic AI with modern neural networks to build transparent and high-performance AI solutions Book DescriptionNeuro-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. What you will learn Gain an understanding of the intuition behind neuro-symbolic AI Determine the correct uses that can benefit from neuro-symbolic AI Differentiate between types of explainable AI techniques Think about, design, and implement neuro-symbolic AI solutions Create and fine-tune your first neuro-symbolic AI system Explore the advantages of fusing symbolic AI with modern neural networks in neuro-symbolic AI systems Who this book is forThis book is ideal for data scientists, machine learning engineers, and AI enthusiasts who want to explore the emerging field of neuro-symbolic AI and discover how to build transparent and trustworthy AI solutions. A basic understanding of AI concepts and familiarity with Python programming are needed to make the most of this book.

The book presents a unique study on the Artificial Intelligence (AI) readiness of public administrations focusing on the Maltese public administration as a case study. This was conducted following the launch of the Malta AI National Strategy in 2019. Since the Maltese public administration is the driving force behind the integration of AI solutions nationwide, the research is deemed necessary to understand whether the public workforce itself is ready to face the oncoming AI revolution. The researchers applied a mixed-methods approach to gain insight and a broader perspective of the status quo concerning AI adoption. Important considerations that stem from this study include the need for increased AI knowledge among public administrators since the majority of respondents reported a lack of awareness of AI technologies and their deployment. Understanding AI-related advantages must be accompanied by a robust instructional effort at all levels of education. It was unanimously agreed that the early inclusion of AI-related courses in the Maltese educational system will aid in developing a future AI-savvy workforce. Furthermore, upskilling and reskilling the public officers will facilitate knowledgeable human capital and proficiencies required to effectively integrate AI solutions within society. The study concludes by recommending several critical reforms within governments that will improve the AI-readiness factor of any Public Administration.

Did you ever read something on a book, felt the need to comment, took up a pencil and scribbled something on the books’ text’? If you did, you just annotated a book. But that process has now become something fundamental and revolutionary in these days of computing. Annotation is all about adding further information to text, pictures, movies and even to physical objects. In practice, anything which can be identified either virtually or physically can be annotated. In this book, we will delve into what makes annotations, and analyse their significance for the future evolutions of the web. We will explain why it was thought to be unreasonable to annotate documents manually and how Web 2.0 is making us rethink our beliefs. We will have a look at tools which make use of Artificial Intelligence techniques to support people in the annotation task. Behind these tools, there exists an important property of the web known as redundancy; we will explain what it is and show how it can be exploited. Finally we will gaze into the crystal ball and see what we might expect to see in the future. Until people understand what the web is all about and its grounding in annotation, people cannot start appreciating it. And until they do so, they cannot start creating the web of the future.

Did you ever read something on a book, felt the need to comment, took up a pencil and scribbled something on the books’ text’? If you did, you just annotated a book. But that process has now become something fundamental and revolutionary in these days of computing. Annotation is all about adding further information to text, pictures, movies and even to physical objects. In practice, anything which can be identified either virtually or physically can be annotated. In this book, we will delve into what makes annotations, and analyse their significance for the future evolutions of the web. We will explain why it was thought to be unreasonable to annotate documents manually and how Web 2.0 is making us rethink our beliefs. We will have a look at tools which make use of Artificial Intelligence techniques to support people in the annotation task. Behind these tools, there exists an important property of the web known as redundancy; we will explain what it is and show how it can be exploited. Finally we will gaze into the crystal ball and see what we might expect to see in the future. Until people understand what the web is all about and its grounding in annotation, people cannot start appreciating it. And until they do so, they cannot start creating the web of the future.