Debiasing AI
In an era where artificial intelligence drives unprecedented change, Debiasing AI examines the vital intersection of technology, innovation, and sustainability. The book addresses the pressing challenge of bias in AI systems, exploring its far-reaching implications for fairness, trust, and ethical practices. Through a multidisciplinary lens, the author examines how human biases are embedded in large language models, amplified by coded machine learning, and propagated through trained algorithms. Practical strategies are offered to address these issues, paving the way for the development of more equitable and inclusive AI technologies.With actionable insights, empirical case studies, and theoretical frameworks, Debiasing AI offers a roadmap for designing AI technologies that are not only innovative but also ethically sound and equitable. A must-read for scholars, industry leaders, and policymakers, this book inspires a reimagining of AI's role in creating a fairer and more sustainable future.
Garden of Wisdom
Garden of Wisdom: Timeless Teachings in an AI Era is a transformative exploration of the intersection between ancient wisdom and modern technology. This book offers a comprehensive framework for the ethical evolution of artificial intelligence, integrating timeless principles from biblical narratives, ecological systems, and quantum consciousness. The book introduces groundbreaking concepts like Angelic Intelligence (AI), Nature Intelligence (NI), and regenerative design, urging readers to harmonize technological advancements with sustainability and human dignity. It addresses the challenges of the AI era with actionable strategies such as the Kosmic Tree of Life and Circadian AI, fostering a vision of a future guided by ethics and interconnectedness. Garden of Wisdom is not just a guide for AI professionals but a call to humanity to co-create a flourishing, sustainable world.
Applications of Metaverse and Virtual Reality to Creative Education and Industry
Integrated Uncertainty in Knowledge Modelling and Decision Making
Data Mining
Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today's techniques coupled with the methods at the leading edge of contemporary research
Digital Twin and Blockchain for Sensor Networks in Smart Cities
Digital twin, blackchain, and wireless sensor networks can work together to improve services in the smart city. Big data derived from wireless sensor networks can be integrated to accommodate the exchange of real-time data between citizens, governments, and organizations. Blockchain can provide high security for large-scale communications and transactions between many stakeholders. Digital twin uses physical models and historical data to integrate big information under multidiscipline, multiphysical quantities, multiscale, and multiprobability conditions. Digital Twin and Blockchain for Sensor Networks in Smart Cities explores how digital twin and blockchain can be optimized to improve services. This book is divided into three parts. Part 1 focuses on the fundamental concepts of blockchain and digital twin for sensor networks in the smart cities, while Part 2 describes their applications for managing the regular operations and services. Part 3 deals with their applications for safe cities.
Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City
In smart cities, information and communication technologies are integrated to exchange real-time data between citizens, governments, and organizations. Blockchain provides security for communication and transactions between multiple stakeholders. Digital twin refers to a simulation of physical products in a virtual space. This simulation fully utilizes the physical models, wireless sensor networks, and historical data of city operation to integrate big information (digital twin cities) under multidiscipline, multiphysical quantities, multiscale, and multiprobability. Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City explores how digital twins and blockchain can be used in smart cities. Part 1 deals with their promising applications for healthy cities. Part 2 covers other promising applications and current perspectives of blockchain and digital twins for future smart society and smart city mobility. Together with its companion volume, Digital Twin and Blockchain for Sensor Networks in Smart Cities, this book helps to understand the vast amount of data around the city to encourage happy, healthy, safe, and productive lives.
Neural Network Methods for Dynamic Equations on Time Scales
Integrated Uncertainty in Knowledge Modelling and Decision Making
Drug Discovery and Telemedicine
Our proposed book emerges in response to the critical need for an interdisciplinary resource that encapsulates the burgeoning role of artificial intelligence (AI) in reshaping drug discovery and telemedicine. As these sectors witness transformative changes driven by AI technologies, there's a pressing demand for a comprehensive guide that navigates through these advancements, offering insights, methodologies, and practical applications to professionals at the forefront of healthcare and pharmaceutical research. At its core, the book delves into the intricate ways in which AI and machine learning algorithms are being harnessed to streamline the drug development process, from initial discovery through to clinical trials, and how these technologies are concurrently revolutionizing the delivery of healthcare services via telemedicine. Specific focus areas include the application of deep learning in identifying novel drug candidates, AI-driven predictive models for pharmacokinetics and pharmacodynamics, automation in laboratory research, and the integration of AI in diagnostic processes, personalized medicine, and patient monitoring systems. Each chapter not only explores current state-of-the-art methodologies and case studies but also critically examines challenges, such as data privacy, ethical considerations, and the need for robust, interpretable models that can be trusted by healthcare professionals and patients alike. Furthermore, the book places a strong emphasis on the synergistic potential of combining AI with telemedicine, illustrating how these technologies can expand access to healthcare, improve the accuracy of remote diagnoses, and enable continuous, data-driven patient care. By providing a panoramic view of current trends, technological innovations, and future directions, the book aims to serve as a pivotal reference for scientists, researchers, clinicians, and policymakers involved in drug discovery and healthcare delivery. In conclusion, this book stands as an essential compendium for specialists seeking to navigate the complexities and harness the opportunities presented by AI in the pharmaceutical and healthcare industries. It offers a critical, in-depth exploration of the transformative impact of AI technologies, underscoring their relevance and potential to dramatically enhance drug discovery and telemedicine practices. This publication not only equips its target audience with the knowledge to lead innovation in their fields but also engages with the broader ethical, social, and practical implications of AI, making it an invaluable resource for advancing towards more effective, efficient, and accessible healthcare solutions. The book is significant for several reasons: Interdisciplinary Appeal: It serves as a critical resource for professionals and researchers across the fields of computer science, pharmaceutical sciences, and healthcare, facilitating a deeper understanding of AI's potential and fostering interdisciplinary collaborations. Innovation in Drug Discovery: By highlighting novel AI methodologies in drug discovery, the book offers insights into how these technologies can shorten the development timelines, reduce costs, and increase the success rates of new therapies, which is crucial for addressing unmet medical needs. Revolutionizing Telemedicine: The detailed discussion on AI's role in telemedicine illustrates how these advancements can enhance access to healthcare, improve the quality of care, and make healthcare systems more efficient, especially in remote and underserved areas. Ethical and Regulatory Considerations: It likely addresses the ethical, privacy, and regulatory challenges associated with implementing AI in healthcare, offering guidelines for navigating these complexities while maximizing patient benefits. Future Directions: By exploring current trends and future possibilities, the book not only serves as a repository of current knowledge but also
Computational Intelligence for High-Dimensional Machine Learning
Blockchain and Digital Twin for Smart Healthcare
The smart hospital framework involves three main layers: data, insight and access. Medical data is collected real-time from devices and systems in a smart hospitals: the internet of medical things. This data is integrated to provide insight from the analytics or machine learning software using digital twins. Security and transparency are brought through a combination of digital twin and blockchain technologies. Blockchain and Digital Twins for Smart Healthcare describes the role of blockchain and digital twins in smart healthcare. It describes the ecosystem of the Internet of Medical Things, how data can be gathered using a sensor network, which is securely stored, updated and managed with blockchain for efficient and private medical data exchange. The end goal is insight that provides faster, smarter decisions with more efficiency to improve care for the patient.
Fundamentals of Bioinformatics and Computational Biology
This book comprehensively covers all the core bioinformatics topics and includes practical examples completed using the MATLAB bioinformatics and machine learning toolboxes(TM). It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics to enable physical science students to appreciate the challenges in biological data management, sequence analysis, and systems biology. The book is divided into five parts. The first one includes a survey of existing biological databases and tools that have become essential in today's biotechnology research. The second part covers methodologies for retrieving biological information, including fundamental algorithms for sequence comparison, scoring, and determining evolutionary distance. The third part of the book focuses on modeling biological sequences and patterns as Markov chains, covering core principles for analyzing and searching for sequences of significant motifs and biomarkers and developing stochastic ergodic hidden Markov models for biological sequence families. The fourth one is dedicated to systems biology and covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays. In turn, the last part of the book includes an introduction to machine-learning algorithms for bioinformatics and outlines strategies for developing intelligent diagnostic machine-learning applications, RNA sequence data, and deep learning systems for mass spectrometry data. All in all, this book offers a unique hands-on reference guide to bioinformatics and computational biology. This second edition has been updated to cover additional and most recent databases, and machine learning and deep learning applications in RNA sequence and mass-spectrometry data analysis. Moreover, it presents significant enhancements to the chapter dedicated to microarray analysis, and more practical examples, with additional end-of-chapter problems.
Advanced Snowflake
As Snowflake's capabilities expand, staying updated with its latest features and functionalities can be overwhelming. The platform's rapid development gave rise to advanced tools like Snowpark and the Native App Framework, which are crucial for optimizing data operations but may seem complex to navigate. In this essential book, author Muhammad Fasih Ullah offers a detailed guide to understanding these sophisticated tools, ensuring you can leverage the full potential of Snowflake for data processing, application development, and deploying machine learning models at scale. You'll gain actionable insights and structured examples to transform your understanding and skills in handling advanced data scenarios within Snowflake. By the end of this book, you will: Grasp advanced features such as Snowpark, Snowflake Native App Framework, and Iceberg tables Enhance your projects with geospatial functions for comprehensive geospatial analytics Interact with Snowflake using a variety of programming languages through Snowpark Implement and manage machine learning models effectively using Snowpark ML Develop and deploy applications within the Snowflake environment
Genai on AWS
The definitive guide to leveraging AWS for generative AI GenAI on AWS: A Practical Approach to Building Generative AI Applications on AWS is an essential guide for anyone looking to dive into the world of generative AI with the power of Amazon Web Services (AWS). Crafted by a team of experienced cloud and software engineers, this book offers a direct path to developing innovative AI applications. It lays down a hands-on roadmap filled with actionable strategies, enabling you to write secure, efficient, and reliable generative AI applications utilizing the latest AI capabilities on AWS. This comprehensive guide starts with the basics, making it accessible to both novices and seasoned professionals. You'll explore the history of artificial intelligence, understand the fundamentals of machine learning, and get acquainted with deep learning concepts. It also demonstrates how to harness AWS's extensive suite of generative AI tools effectively. Through practical examples and detailed explanations, the book empowers you to bring your generative AI projects to life on the AWS platform. In the book, you'll: Gain invaluable insights from practicing cloud and software engineers on developing cutting-edge generative AI applications using AWS Discover beginner-friendly introductions to AI and machine learning, coupled with advanced techniques for leveraging AWS's AI tools Learn from a resource that's ideal for a broad audience, from technical professionals like cloud engineers and software developers to non-technical business leaders looking to innovate with AI Whether you're a cloud engineer, software developer, business leader, or simply an AI enthusiast, Gen AI on AWS is your gateway to mastering generative AI development on AWS. Seize this opportunity for an enduring competitive advantage in the rapidly evolving field of AI. Embark on your journey to building practical, impactful AI applications by grabbing a copy today.
AI for Beginners
Feeling overwhelmed by AI jargon and endless resources? Wondering how to get hands-on AI experience in this fast-paced field without losing your mind? Many beginners struggle, but with this step-by-step guide, that can change.Here's what you'll uncover: - A 31-day plan to master AI and reshape your tech perspective - Three beginner-friendly projects to apply AI concepts, such as voice assistants and recommendation systems- Navigating AI's ethical and societal impacts - AI's role in healthcare, finance, and marketing- A guide for integrating AI into your career, especially in marketing and data analysis - Debunking common AI misconceptions - A beginner's guide to AI programming languages like Python- Interactive exercises to elevate you from novice to competent AI practitioner...and more! Do you think you can't handle it because you're not tech-savvy? This book simplifies complex ideas into manageable steps. Unlike rapidly outdated guides, it offers ongoing insights into the latest trends and advancements. This is more than a book; it's a reliable ongoing resource.Whether for career growth, personal development, or curiosity, this guide equips you with the tools to succeed.Ready to tackle AI jargon and gain practical experience? Scroll up and click "Add to Cart" now!
Building Personality-Driven Language Models
This book provides an innovative exploration into the realm of artificial intelligence (AI) by developing personalities for large language models (LLMs) using psychological principles. Aimed at making AI interactions feel more human-like, the book guides you through the process of applying psychological assessments to AIs, enabling them to exhibit traits such as extraversion, openness, and emotional stability. Perfect for developers, researchers, and entrepreneurs, this work merges psychology, philosophy, business, and cutting-edge computing to enhance how AIs understand and engage with humans across various industries like gaming and healthcare. The book not only unpacks the theoretical aspects of these advancements but also equips you with practical coding exercises and Python code examples, helping you create AI systems that are both innovative and relatable. Whether you're looking to deepen your understanding of AI personalities or integrate them into commercial applications, this book offers the tools and insights needed to pioneer this exciting frontier.
Design, Learning, and Innovation
This book constitutes the refereed proceedings of the 9th EAI International Conference on Design, Learning, and Innovation, DLI 2024, held virtually, during November 7-8, 2024. The 11 full papers included in this book were carefully reviewed and selected from 29 submissions. They were organized in topical sections as follows: Using Immersive Technologies for Learning, Accessibility, and Technological Innovation; and Engaging Learners through Gamification, Playful Design, and Generative AI.
Futureproofing Engineering Education for Global Responsibility
This book contains papers in the fields of: Virtual and augmented learning. Games in engineering education. Social aspects of digitalization. Technical teacher training. Accessible learning and technologies. Dance of data in educational science and practice. Engineering education for production and service structures of the future. Innovative approaches to STEAM education and music therapy through emerging technologies. We are currently witnessing a significant transformation in the development of education on all levels and especially in post-secondary and higher education. To face these challenges, higher education must find innovative and effective ways to respond in a proper way. Changes have been made in the way we teach and learn, including the massive use of new means of communication, such as videoconferencing and other technological tools.
The Military Metaverse
The Military Metaverse explores the impact that the Metaverse is having today on how the world's militaries procure, maintain, train, plan and fight, and how the Metaverse presents new challenges and opportunities for future conflict.The military were early adopters of Virtual Reality and Augmented Reality technologies and wider simulation systems. Before 2010 they were one of the few sectors that could afford the technology, and millions of military R&D dollars went into developing and understanding these technologies. However, as the democratisation of metaverse technologies has happened over the past decade there is a danger that militaries have been overtaken and caught short, encumbered with expensive legacy systems, sold and maintained by expensive prime contractors, whilst the gaming and consumer market has cheaper and more innovative and agile systems. The book provides a history of the use of metaverse technologies in the military, particularly in the areas of design, maintenance, training, planning and operations. It then examines the current state of the art in these areas and the opportunities that are available from the current generation of consumer-driven approaches. The drivers for, challenges to, and paths towards an enterprise approach to the Military Metaverse are then presented. The book explores the military use of social virtual worlds, of early work done by defence and security organisations in worlds such as Second Life, and how such environments could become important for intelligence as well as influence operations in the future. Finally, the book will consider what war in the Metaverse might look like, both in terms on in-world activities and the impact of cyber-war on the Metaverse itself.It should be of interest to all militaries across the world, the industries that support them, and those in academia and the wider public with an interest in the military and defence.
The Turing Test Argument
This book departs from existing accounts of Alan Turing's imitation game and test by placing Turing's proposal in its historical, social, and cultural context.It reconstructs a controversy in England, 1946-1952, over the intellectual capabilities of digital computers, which led Turing to propose his test. It argues that the Turing test is best understood not as a practical experiment, but as a thought experiment in the modern scientific tradition of Galileo Galilei. The logic of the Turing test argument is reconstructed from the rhetoric of Turing's irony and wit. Turing believed that learning machines should be understood as a new kind of species, and their thinking as different from human thinking and yet capable of imitating it. He thought that the possibilities of the machines he envisioned were not utopian dreams. And yet he hoped that they would rival and surpass chauvinists and intellectuals who sacrifice independent thinking to maintain their power. These would be transformed into ordinary people, as work once considered 'intellectual' would be transformed into non-intellectual, 'mechanical' work.The Turing Test Argument will appeal to scholars and students in the sciences and humanities and all those interested in Turing's vision of the future of intelligent machines in society and nature.
