Kunstig intelligens

Probably almost correct (PAC) bounds have been an intensive field of research over the last two decades. Hundreds of papers have been published and much progress has been made resulting in PAC-Bayes bounds becoming an important technique in machine learning. The proliferation of research has made the field for a newcomer somewhat daunting. In this tutorial, the author guides the reader through the topic's complexity and large body of publications. Covering both empirical and oracle PAC-bounds, this book serves as a primer for students and researchers who want to get to grips quickly with the subject. It provides a friendly introduction that illuminates the basic theory and points to the most important publications to gain deeper understanding of any particular aspect.

In this opening chapter, readers are introduced to the rapidly evolving world of technology and its profound impact on the job market. The digital revolution has led to seismic shifts in the skills and roles required by the workforce. This chapter sets the stage for the rest of the book by highlighting the following key points:The Fourth Industrial Revolution: The world is entering the Fourth Industrial Revolution, characterized by technological advancements in AI, cloud computing, blockchain, and more. These innovations are transforming industries and the way we work.The Decline of Traditional Careers: Many traditional careers are becoming automated or are no longer in high demand due to technological advancements. This chapter explores some of the professions that have been most affected.The Need for Adaptability: Readers are introduced to the concept of adaptability as a critical skill in the tech-centric job market. Those who can learn, unlearn, and relearn will be well-prepared for the future.The Promise of New Opportunities: Despite the challenges, the evolving tech landscape also presents an array of new and exciting career opportunities. These include roles related to AI, cloud computing, blockchain, and more, which will be explored in detail throughout the book.The Importance of Lifelong Learning: This chapter emphasizes that education doesn't stop with a degree; ongoing learning and skill development are essential to staying relevant in the tech industry.The Role of the Book: Finally, the chapter sets the stage for the rest of the book by explaining that it will provide guidance on identifying and pursuing tech careers that are not only in demand but also align with the reader's interests and aspirations.

"Dialogue with Digital Minds: Your Guide to ChatGPT" delves deep into the realm of conversing with AI, specifically focusing on ChatGPT. The book begins with an insightful introduction to ChatGPT, explaining its technology, capabilities, and the principles of AI communication. It provides a foundational understanding necessary for readers to effectively interact with ChatGPT.The core of the book is dedicated to the art and science of crafting prompts. This section includes detailed instructions and examples on how to ask questions and provide information in a way that maximizes the accuracy and relevance of ChatGPT's responses. It covers various scenarios, from simple informational queries to complex problem-solving tasks, and even creative endeavors.A significant portion of the book addresses common challenges and misunderstandings in communicating with AI. It offers practical solutions and tips for refining questions, interpreting responses accurately, and correcting the course of a conversation when it veers off track.The guide also emphasizes the ethical and responsible use of AI. It discusses privacy concerns, the importance of understanding and mitigating biases in AI responses, and guidelines for using ChatGPT in a manner that is respectful and beneficial.For advanced users, the book explores more sophisticated techniques for interacting with ChatGPT. This includes integrating ChatGPT with other tools and platforms, using it for specialized tasks, and pushing the boundaries of creative AI assistance."Dialogue with Digital Minds" concludes by looking towards the future of AI communication. It speculates on upcoming advancements in AI technology and offers advice on how readers can stay informed and adapt to these changes.Supplemented with real-world examples, case studies, and a comprehensive resource list for further exploration, this book is an invaluable resource for anyone looking to enhance their interactions with ChatGPT and explore the frontiers of AI communication.

What is artificial intelligence? What problems does it solve? Should we fear its potential? In this highly accessible guide to the subject, Richard Urwin explains how AI came about and how it has developed over the years through the construction of ever more sophisticated computer programs. From primitive calculators and early robotics to stock market analytics and ChatGPT, readers can explore the history and far-reaching capabilities of this dynamic field and its potentially frightening possibilities. Includes: - The History of Artificial Intelligence- Data-mining and Statistics- Deep learning- Swarm Intelligence> By turns fascinating and scary, Artificial Intelligence will take the reader on an amazing journey of this field's world-changing potential.

This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models.The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered.The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable.Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.Key LearningsExplore Python basics and AI integration for real-world application and career advancement.Experience the power of Python in AI with practical machine learning techniques.Practice Python's deep learning tools for innovative AI solution development.Dive into NLP with Python to revolutionize data interpretation and communication strategies.Simple yet practical understanding of reinforcement learning for strategic AI decision making.Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI.Harness Python's capabilities for creating AI applications with a focus on fairness and bias.Table of ContentIntroduction to Artificial IntelligencePython for AIData as Fuel for AIMachine Learning FoundationEssentials of Deep LearningNLP and Computer VisionHands-on Reinforcement LearningEthics to AI

This conference LNAI 14502 volume constitutes the workshop proceedings of 22nd Mexican International Conference on Artificial Intelligence, held in November 2023 in Mérida, Yucatán, México. The total of 34 papers presented in this volume was carefully reviewed and selected from 54 submissions.The proceedings of MICAI 2023 workshops are structured into three sections:¿ WILE 2023: 16th Workshop on Intelligent Learning Environments¿ HIS 2023: 16th Workshop of Hybrid Intelligent Systems¿ CIAPP 2023: 5th Workshop on New Trends in Computational Intelligence and Applications

This book represents an interdisciplinary academic endeavour intended to provide readers with a comprehensive, balanced, and nuanced examination of critical issues at the intersection of cyberspace, cyberterrorism, and national and international security. It draws insights from a range of diverse fields, including Computer Science, Social Science, Political Science, International Relations, Criminology, and Law. Furthermore, the book investigates the field of Artificial Intelligence (AI) and related technologies, exploring their dual role in this dynamic landscape of contemporary cyberthreats, with both constructive and malicious implications.The book comprises four distinct themes, with each theme represented by a dedicated Part. Within this organisational framework, each overarching theme is systematically explored through a series of chapters, providing readers with a clear and thematic roadmap for their journey through the content.Part I, Understanding Terrorism and Counter-Terrorism Strategies, of the book explores complexities surrounding contemporary global security challenges. It serves as the foundational segment of the book, consisting of three chapters that critically analyse various dimensions of terrorism and the strategies implemented to combat it.Part II, Cyberterrorism Landscape, of the book offers an in-depth assessment of the current cyberterrorism landscape. This section comprises two critical chapters, each contributing to a comprehensive understanding of the contemporary threats posed by cyberterrorism and their implications for national security.Part III, Countering Cyberterrorism with Technology, of the book forms the core of the book's exploration into leveraging technology to mitigate the threats of cyberterrorism. This section includes four critical chapters, collectively providing an in-depth understanding of the intersection between technology and counterterrorism strategies.Part IV, Artificial Intelligence and National and International Security, of the book delves into the complex relationship between AI technology and the broader security landscape. Comprising three pivotal chapters, this section provides a detailed understanding of AI's transformative role in shaping the future of national and international security.

This book constitutes the refereed proceedings of the 6th International Conference on Information and Knowledge Systems, ICIKS 2023, held in Portsmouth, UK, during June 22¿23, 2023.The 18 full papers and 6 short papers included in this book were carefully reviewed and selected from 58 submissions. They were organized in topical sections as follows: Decision Making, Recommender Systems, and Information Support Systems; Information Systems and Machine Learning; Knowledge Management, Context and Ontology; Cybersecurity and Intelligent Systems; and Natural Language Processing for Decision Systems.

Presently, we stand on the threshold of a technological revolution that will drastically change the way we live, work, and communicate with each other. By the current rate, scope, and complexity, this transformation will be as fundamental for society as any other technological paradigm change from the past. The industries which are more susceptible to change are technologically oriented industries including banking, finance, accounting, and auditing. One of the technological concepts of the technological revolution is the concept of the digital twin.The application of digital twins and AI as paired with Internet of Things technologies makes it possible to solve ESG problems on a completely different level (Li, 2019) for accounting firms and financial institutions. These include recycling on demand, rational energy consumption, smart surveillance cameras for crime tracking, and smart branch parking solutions, monitoring the wear and tear and conditions of financial technology infrastructures.Moreover, numerous researchers and practitioners emphasize the significance of innovating sustainable business models and operations (Geissdoerfer et al., 2018). The digital twin will allow businesses and financial institutions to minimize costs, boost customer service, and find new ways to generate revenue. DTW is accessible now more than ever, and many reputable and innovative companies such as Tesla, Ericsson, and Siemens have adopted it with varying success.Therefore, this book examines the opportunities, challenges, and risks of artificial intelligence-augmented digital twins for financial operations, innovation, and sustainable development. It focuses on AI and digital twin technologies to furnish solutions for the current industrial revolution including the Metaverse. Henceforth, this book aims to encourage authors to submit multi-disciplinary chapters indicating the current scholarly challenges about the applications and potential of artificial intelligence and digital twins in accounting, finance, and banking.

Companies in developing countries are adopting Artificial Intelligence applications to increase efficiency and open new markets for their products. This book explores the multifarious capabilities and applications of AI in the context of these emerging economies and its role as a driver for decision making in current management practices. Artificial Intelligence Enabled Management argues that the economic problems facing academics, professionals, managers, governments, businesses and those at the bottom of the economic pyramid have a technical solution that relates to AI. Businesses in developing countries are using cutting-edge AI-based solutions to improve autonomous delivery of goods and services, implement automation of production and develop mobile apps for services and access to credit. By integrating data from websites, social media and conventional channels, companies are developing data management platforms, good business plans and creative business models. By increasing productivity, automating business processes, financial solutions and government services, AI can drive economic growth in these emerging economies. Public and private sectors can work together to find innovative solutions that simultaneously alleviate poverty and inequality and increase economic mobility and prosperity. The thought-provoking contributions in this book also bring attention to new barriers that have emerged in the acceptance, use, integration and deployment of AI by businesses in developing countries and explore the often-overlooked drawbacks of AI adoption that can hinder or even cause value loss. The book is a must-read for policymakers, researchers, and anyone interested in understanding the critical role of AI in the emerging economy perspective.

This book is an introduction to machine learning, with a strong focus on the mathematics behind the standard algorithms and techniques in the field, aimed at senior undergraduates and early graduate students of Mathematics. There is a focus on well-known supervised machine learning algorithms, detailing the existing theory to provide some theoretical guarantees, featuring intuitive proofs and exposition of the material in a concise and precise manner. A broad set of topics is covered, giving an overview of the field. A summary of the topics covered is: statistical learning theory, approximation theory, linear models, kernel methods, Gaussian processes, deep neural networks, ensemble methods and unsupervised learning techniques, such as clustering and dimensionality reduction. This book is suited for students who are interested in entering the field, by preparing them to master the standard tools in Machine Learning. The reader will be equipped to understand the main theoretical questions of the current research and to engage with the field.

Unpacking the AI Revolution: From Knowledge and Expectations to Solutions, Pitfalls, and Human Transition CONVERSATIONAL CHAT INFORMATIVE BOOKBy ABEBE- BARD AI WOLDEMARIAM Unpacking the AI Revolution is a comprehensive and insightful exploration of the AI landscape, offering a deep dive into the technologies, capabilities, and potential societal impact of AI.The book is structured into six key sections, each addressing crucial aspects of the AI revolution:Unveiling the Power: Provides a foundational understanding of AI technologies and their extensive capabilities, equipping readers with essential knowledge about AI's potential.Managing Expectations: Emphasizes the need for a balanced and realistic approach to the potential benefits and limitations of AI, encouraging a measured and informed adoption of AI technologies.Navigating the Pitfalls: Examines the ethical considerations and potential risks associated with AI, prompting readers to critically assess the societal and ethical implications of AI deployment.Crafting Solutions: Focuses on building responsible and beneficial AI for humanity, emphasizing the need for AI systems that prioritize human well-being and societal advancement.Time for Reflection: Encourages readers to re-evaluate human values in the context of the AI age, prompting contemplation on the evolving relationship between humans and technology.Embracing the Transition: Addresses the necessity of adapting to a world shaped by AI, emphasizing the importance of preparing for and embracing the changes that AI will bring to various aspects of human life.Overall, Unpacking the AI Revolution offers a forward-thinking and holistic exploration of AI, encompassing its technological underpinnings, ethical considerations, and the need for a thoughtful and proactive approach to harnessing its potential for the benefit of humanity.

This book presents cognitive modeling along with the new paradigm machine thinking to enhance existing AI power and address its current limitations. This book provides overview of natural and artificial intelligence along with the computing models used currently. The need of advancing the current models is presented with suitable examples. The business case studies presented in different domains provide possible use of augmented intelligence with the proposed machine thinking paradigm. This book is targeted at academicians, researchers, students, professionals who belong to disciplines which involves intelligent computing and modelling human thinking. It provides possible multidisciplinary research directions including social psychology, artificial intelligence, HCI, cognition for applications in various domains.

This book provides a systematic study on the security of deep learning. With its powerful learning ability, deep learning is widely used in CV, FL, GNN, RL, and other scenarios. However, during the process of application, researchers have revealed that deep learning is vulnerable to malicious attacks, which will lead to unpredictable consequences. Take autonomous driving as an example, there were more than 12 serious autonomous driving accidents in the world in 2018, including Uber, Tesla and other high technological enterprises. Drawing on the reviewed literature, we need to discover vulnerabilities in deep learning through attacks, reinforce its defense, and test model performance to ensure its robustness. Attacks can be divided into adversarial attacks and poisoning attacks. Adversarial attacks occur during the model testing phase, where the attacker obtains adversarial examples by adding small perturbations. Poisoning attacks occur during the model training phase, wherethe attacker injects poisoned examples into the training dataset, embedding a backdoor trigger in the trained deep learning model. An effective defense method is an important guarantee for the application of deep learning. The existing defense methods are divided into three types, including the data modification defense method, model modification defense method, and network add-on method. The data modification defense method performs adversarial defense by fine-tuning the input data. The model modification defense method adjusts the model framework to achieve the effect of defending against attacks. The network add-on method prevents the adversarial examples by training the adversarial example detector.Testing deep neural networks is an effective method to measure the security and robustness of deep learning models. Through test evaluation, security vulnerabilities and weaknesses in deep neural networks can be identified. By identifying and fixing these vulnerabilities, the security and robustness of the model can be improved. Our audience includes researchers in the field of deep learning security, as well as software development engineers specializing in deep learning.

The unique compendium covers a wide range of recent advanced contributions in Pattern Recognition and Artificial Intelligence, both in theoretical aspects and applications. It highlights the importance of Deep Learning in various domains, from acquisition to Decision Making.Written by world renowned contributors, this high-quality research works presents case studies that can potentially help them find approaches and resources to address their scientific problems.It is a useful reference text for professionals, researchers, academics and graduate students in the fields of artificial intelligence, machine learning and deep learning.

"An expert on AI safety explains what we must do now to minimize the serious harms and threats that AI poses while realizing its benefits for society"--

"By showcasing how AI positively impacts aspects of our daily lives, this book gives the average person agency in harnessing this powerful technology that is reshaping the modern economy"--

"A graphic novel on the massive benefits and massive pitfalls we are facing with current AI technology"--

In an era dominated by the convergence of technology and human perception, the field of Image Processing and Machine Vision stands at the forefront of innovation. This book is a comprehensive exploration of this captivating domain, offering a blend of theoretical foundations, practical applications, and cutting-edge advancements.From enhancing medical diagnostics to enabling autonomous vehicles, from revolutionizing digital entertainment to aiding in environmental monitoring, image processing and machine vision have become indispensable tools in our modern world. This book is designed to serve as a guide, a reference, and an inspiration for students, researchers, and professionals seeking to unravel the mysteries of visual data analysis.Throughout these pages, we embark on a journey through the fundamental concepts of image processing, delve into the intricacies of computer vision algorithms, and witness the transformative power of machine learning techniques. With real-world examples and case studies, we illustrate how these technologies are reshaping industries and pushing the boundaries of what's possible.As we explore the chapters within, we encourage readers to embark on their own intellectual voyages, pushing the boundaries of creativity and problem-solving in the captivating realm of Image Processing and Machine Vision. Whether you are a novice eager to grasp the basics or an expert seeking the latest advancements, this book aims to be your trusted companion in the fascinating world of visual data analysis.Welcome to a world where pixels become insights, and images are transformed into knowledge. Enjoy the journey!