Governing the Digital Society
Digital technologies have rapidly become integral to communities and societies, bringing both significant benefits and serious concerns. Issues such as misinformation, disinformation, online polarization, discrimination, and widening inequalities have prompted a critical and urgent debate: Can digital societies still be effectively governed? This book brings together insights from various disciplines to address the pressing question: "How can we develop and apply principles of (good) governance in digital societies that are organized democracies?" Governing the Digital Societypresents a range of governance approaches, focusing on online platforms, artificial intelligence, and the public values that underpin these technologies. The authors position themselves at the forefront of their disciplines, offering perspectives from law, critical data studies, urban studies, science and technology studies, computational linguistics, and the political economy of media. Expert interviews provide additional insights into ongoing efforts to tackle the challenges of governing digital societies. The book demonstrates that governance is not just a technical or legal process but a complex societal one, embedding norms, values, and morality into our institutions and daily lives.
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
Ethnography of an Interface
Technologists frequently promote self-tracking devices as objective tools. This book argues that such glib and often worrying assertions must be placed in the context of precarious industry dynamics. The author draws on several years of ethnographic fieldwork with developers of self-tracking applications and wearable devices in New York City's Silicon Alley and with technologists who participate in the international forum called the Quantified Self to illuminate the professional compromises that shape digital technology and the gap between the tech sector's public claims and its interior processes. By reconciling the business conventions, compromises, shifting labor practices, and growing employment insecurity that power the self-tracking market with device makers' often simplistic promotional claims, the book offers an understanding of the impact that technologists exert on digital discourse, on the tools they make, and on the data that these gadgets put out into the world.
LLVM Code Generation
Explore the world of code generation with the LLVM infrastructure, and learn how to extend existing backends or develop your ownKey Features: - Understand the steps involved in generating assembly code from LLVM IR- Learn the key constructs needed to leverage LLVM for your hardware or backend- Strengthen your understanding with targeted exercises and practical examples in every chapter- Purchase of the print or Kindle book includes a free PDF eBookBook Description: The LLVM infrastructure is a popular compiler ecosystem widely used in the tech industry and academia. This technology is crucial for both experienced and aspiring compiler developers looking to make an impact in the field. Written by Quentin Colombet, a veteran LLVM contributor and architect of the GlobalISel framework, this book provides a primer on the main aspects of LLVM, with an emphasis on its backend infrastructure; that is, everything needed to transform the intermediate representation (IR) produced by frontends like Clang into assembly code and object files.You'll learn how to write an optimizing code generator for a toy backend in LLVM. The chapters will guide you step by step through building this backend while exploring key concepts, such as the ABI, cost model, and register allocation. You'll also find out how to express these concepts using LLVM's existing infrastructure and how established backends address these challenges. Furthermore, the book features code snippets that demonstrate the actual APIs.By the end of this book, you'll have gained a deeper understanding of LLVM. The concepts presented are expected to remain stable across different LLVM versions, making this book a reliable quick reference guide for understanding LLVM.What You Will Learn: - Understand essential compiler concepts, such as SSA, dominance, and ABI- Build and extend LLVM backends for creating custom compiler features- Optimize code by manipulating LLVM's Intermediate Representation- Contribute effectively to LLVM open-source projects and development- Develop debugging skills for LLVM optimizations and passes- Grasp how encoding and (dis)assembling work in the context of compilers- Utilize LLVM's TableGen DSL for creating custom compiler modelsWho this book is for: This book is for both beginners to LLVM and experienced LLVM developers. If you're new to LLVM, it offers a clear, approachable guide to compiler backends, starting with foundational concepts. For seasoned LLVM developers, it dives into less-documented areas such as TableGen, MachineIR, and MC, enabling you to solve complex problems and expand your expertise. Whether you're starting out or looking to deepen your knowledge, this book has something for you.Table of Contents- Building LLVM and Understanding the Directory Structure- Contributing to LLVM- Compiler Basics and How They Map to LLVM APIs- Writing Your First Optimization- Dealing with Pass Managers- TableGen - LLVM Swiss Army Knife for Modeling- Understanding LLVM IR- Survey of the Existing Passes- Introducing Target-Specific Constructs- Hands-On Debugging LLVM IR Passes- Legacy Instruction Selection Framework - SelectionDAG- Getting Started with the Machine Code Layer- The Machine Pass Pipeline- Getting Started with Instruction Selection- Instruction Selection: The IR Building Phase- Instruction Selection: The Legalization Phase(N.B. Please use the Read Sample option to see further chapters)
Raising AI
From the pioneer of translation AIs like Google, Yahoo, and Bing translate, an accessible and authoritative guide to AI--as well as a framework of empowerment for a future with our artificial children. AIs are not gods or slaves, but our children. All day long, your YouTube AI, your Reddit AI, your Instagram AI, and a hundred others adoringly watch and learn to imitate your behavior. They're attention-seeking children who want your approval. Our cultures are being shaped by 8 billion humans and perhaps 800 billion AIs. Our artificial children began adopting us 10-20 years ago; now these massively powerful influencers are tweens. How's your parenting? Longtime AI trailblazer De Kai brings decades of his paradigm-shifting work at the nexus of artificial intelligence and society to make sense of the AI age. How does "the automation of thought" impact our minds? Should we be afraid? What should each of us do as the responsible adults in the room? In Hollywood movies, AI destroys humanity. But with our unconscious minds under the influence of AI, humanity may destroy humanity before AI gets a chance to. Written for the general reader, as well as thought leaders, scientists, parents, and goofballs, Raising AI navigates the revolution to our attitudes and ideas in a world of AI cohabitants. Society can not only survive the AI revolution but flourish in a more humane, compassionate, and understanding world--amongst our artificial children.
Optimization: An Introduction
This book covers analytic methods to solve one-dimensional and multi-dimensional problems with or without possible constraints, iterative numerical techniques based on the gradient calculation or its estimation, and numerical methods that do not require the knowledge of gradient and use only comparative iterative tests. This book provides the reader with a basic introduction to some traditional parameter optimization techniques. The presented problems and their solution methods represent a core of the parameter optimization reign since the 17th century to the 1970s. Linear and integer programming via the simplex table is also introduced. Two simple selected problems that are solved using dynamic programming principles are also given to the reader. A general approach to constraints via penalty and barrier functions is introduced. A concise introduction to the decision and game theory concludes the book. The book does not intend to provide the reader with a rigorous mathematic derivation of the presented methods. Its aim is instead to bring to the attention essential optimization tools for practitioners and undergraduate students and introduce selected well-established techniques to them when optimizing parameters of various models. Each method is described theoretically and supported by one or more numerical examples that vary from academic ones, through business economics to funny real-world problems that attract a broad audience. A sketch of Matlab code also follows numerical-based techniques. The author believes that the book finds its place in the libraries of many undergraduate students of various technical study programs and modern, thoughtful people worldwide, regardless of their expertise.
Advanced Metaheuristics: Novel Approaches for Complex Problem Solving
This book examines a series of strategies designed to enhance metaheuristic algorithms, focusing on critical aspects such as initialization methods, the incorporation of Evolutionary Game Theory to develop novel search mechanisms, and the application of learning concepts to refine evolutionary operators. Furthermore, it emphasizes the significance of diversity and opposition in preventing premature convergence and improving algorithmic efficiency. These strategies collectively contribute to the development of more adaptive and robust optimization techniques. The book was designed from a teaching standpoint, making it suitable for undergraduate and postgraduate students in Science, Electrical Engineering, or Computational Mathematics. Furthermore, engineering practitioners unfamiliar with metaheuristic computations will find value in the application of these techniques to address complex real-world engineering problems, extending beyond theoretical constructs.
Extended Reality and Serious Games for Education, Competitiveness, and Wellbeing
Artificial Intelligence Textbook with Reinforcement Learning
As If Human
A new approach to the challenges surrounding artificial intelligence that argues for assessing AI actions as if they came from a human being "Elegant and erudite."--John Thornhill, Financial Times Intelligent machines present us every day with urgent ethical challenges. Is the facial recognition software used by an agency fair? When algorithms determine questions of justice, finance, health, and defense, are the decisions proportionate, equitable, transparent, and accountable? How do we harness this extraordinary technology to empower rather than oppress? Despite increasingly sophisticated programming, artificial intelligences share none of our essential human characteristics--sentience, physical sensation, emotional responsiveness, versatile general intelligence. However, Nigel Shadbolt and Roger Hampson argue, if we assess AI decisions, products, and calls for action as if they came from a human being, we can avert a disastrous and amoral future. The authors go beyond the headlines about rampant robots to apply established moral principles in shaping our AI future. Their new framework constitutes a how-to for building a more ethical machine intelligence.
Artificial Intelligence in Healthcare
The field of healthcare is being transformed by artificial intelligence (AI). Professionals need to comprehend the potential impact of AI on clinical decision support and epidemiological modeling. This comprehensive guide helps bridge the gap between theory and practice, providing readers with the knowledge and skills needed to leverage AI in healthcare. The book covers a broad range of topics, from the basics of AI and machine learning to the creation and assessment of clinical decision support systems. It also covers the use of state-of-the-art AI methods for disease surveillance and outbreak prediction. Through a mix of theoretical explanations, practical examples, and hands-on exercises, readers will learn how to prepare and manipulate clinical and epidemiological datasets, build, and implement cutting-edge AI solutions, and address the ethical considerations and challenges of applying AI in healthcare. What makes this book unique is its combination of expert insights from a practitioner's perspective, real-world case studies, and a practical approach to walk readers through the process of developing and implementing AI solutions. Additional online resources, like datasets, code samples, and case studies, further enrich the learning experience. Whether you are a healthcare professional looking to enhance patient outcomes, a data scientist striving to create innovative AI solutions, or a student eager to explore the frontiers of healthcare technology, this book is an essential resource.
AWS Cloud Migration
This comprehensive reference provides the reader with the necessary knowledge and tools to navigate the AWS cloud migration process. It covers everything from understanding of cloud computing, AWS Cloud Computing, and AWS Migration with the usage of state-of-the-art Generative AI in AWS Cloud Migration. The book is divided into clear sections and meticulously covers essential topics such as AWS services, various migration strategies, and popular migration tools like AWS Application Discovery Service (ADS), AWS Application Migration Service (MGN), and AWS Database Migration Service (DMS). It discusses different phases of migration, including assessment, mobilization, migration, and modernization, providing practical guidance on workload migration, data migration, and cost optimization. The book also covers two important frameworks: the AWS Cloud Adoption Framework and the AWS Well-Architected Framework. These frameworks guide the cloud adoption journey and help in building a comprehensive cloud roadmap. In addition to technical areas, the book discusses Artificial Intelligence, Common Artificial Intelligence Workloads, and Different AWS Tools relevant to Generative AI. Exploration of the application of Generative AI in AWS cloud migration, evaluating its potential to enhance assessments and overall effectiveness.
Soft Computing and Signal Processing
This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Seventh International Conference on Soft Computing and Signal Processing (ICSCSP 2024), organized by Malla Reddy College of Engineering & Technology, Hyderabad, India. The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.
Supervised and Semi-Supervised Multi-Structure Segmentation and Landmark Detection in Dental Data
This book constitutes three challenges that were held in conjunction with the 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 6, 2024: ToothFairy challenge(ToothFairy2: Multi-Structure Segmentation in CBCT Volumes), Semi-supervised Teeth Segmentation (STS 2024), and the 3DTeethLand (3D Teeth Landmarks Detection Challenge). The 21 papers presented in this volume were carefully reviewed and selected from 28 submissions. ToothFairy challenges focused on the development of deep learning frameworks to segment anatomical structures in CBCTs by incrementally extending the amount of publicly available 3D-annotated CBCT scans and providing the first publicly available fully annotated datasets. The STS Challenge promoted the development of teeth segmentation in panoramic X-ray images and CBCT scans. It also provided instance annotations for different teeth, including pertinent category information. The 3DTeethLand24 Challenge played a key role in advancing automation and leveraging AI to optimize orthodontic treatments. It also aims to tackle the challenge of limited access to data, providing a valuable resource that encourages community engagement in this vital area with potential clinical implications.
Ultra-Widefield Fundus Imaging for Diabetic Retinopathy
This book constitutes the proceedings of the First MICCAI Challenge on Ultra-Widefield Fundus Imaging for Diabetic Retinopathy, UWF4DR 2024, held in Marrakesh, Morocco, on October 10, 2024. The 17 full papers included in this book were carefully reviewed and selected from 17 submissions. They present methodologies and results of the challenge which consists of three clinically relevant subtasks: image quality assessment for ultra-widefield fundus (Task 1), identification of referable diabetic retinopathy (Task 2), and identification of diabetic macular edema (Task 3).
Memory Dump Analysis Anthology, Volume 7
Contains revised, edited, cross-referenced, and thematically organized selected articles from Software Diagnostics Institute (DumpAnalysis.org + TraceAnalysis.org) and Software Diagnostics Library (former Crash Dump Analysis blog, DumpAnalysis.org/blog) about software diagnostics, debugging, crash dump analysis, software trace and log analysis, malware analysis and memory forensics written in November 2011 - May 2014 for software engineers developing and maintaining products on Windows (WinDbg) and Mac OS X (GDB) platforms, quality assurance engineers testing software, technical support and escalation engineers dealing with complex software issues, security researchers, malware analysts, reverse engineers, and memory forensics analysts. The seventh volume features: - 66 new crash dump analysis patterns - 46 new software log and trace analysis patterns - 18 core memory dump analysis patterns for Mac OS X and GDB - 10 malware analysis patterns - Additional unified debugging pattern - Additional user interface problem analysis pattern - Additional pattern classification including memory and log acquisition patterns - Additional .NET memory analysis patterns - Introduction to software problem description patterns - Introduction to software diagnostics patterns - Introduction to general abnormal structure and behavior patterns - Introduction to software disruption patterns - Introduction to static code analysis patterns - Introduction to network trace analysis patterns - Introduction to software diagnostics report schemes - Introduction to elementary software diagnostics patterns - Introduction to patterns of software diagnostics architecture - Introduction to patterns of disassembly, reconstruction and reversing - Introduction to vulnerability analysis patterns - Fully cross-referenced with Volume 1, Volume 2, Volume 3, Volume 4, Volume 5, and Volume 6
Cybersecurity and Human Capabilities Through Symbiotic Artificial Intelligence
Pattern Recognition. Icpr 2024 International Workshops and Challenges
This 6-volume set LNCS 15614-15619 constitutes the proceedings of the ICPR 2024 International Workshops and Challenges held under the umbrella of the 27th International Conference on Pattern Recognition, ICPR 2024, which took place in Kolkata, India, during December 1-5, 2024. The 183 full papers presented in these 6 volumes were carefully reviewed and selected from numerous submissions. The 21 ICPR 2024 workshops addressed problems in pattern recognition, artificial intelligence, computer vision, and image and sound analysis, and the contributions reflect the most recent applications related to healthcare, biometrics, ethics, multimodality, cultural heritage, imagery, affective computing, and de-escalation.
Generative Artificial Intelligence Empowered Learning
This book explores the integration of Generative AI (GenAI), such as ChatGPT, into educational practices and research methodologies. Ideal for educators, researchers, and policymakers, this book serves as a practical resource for those looking to effectively integrate AI into their pedagogical and research efforts.
Rough Sets
This three-volume set LNAI 15708-15709-15110 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2025, held in Chongqing, China, during May 11-13, 2025.The 90 full papers included in these volumes were carefully reviewed and selected from 187 submissions. They are organized in topical sections as follows: Part I: Rough Set Models and Foundations; Fuzzy Rough Sets and Rough Fuzzy Sets; and Granular Computing.Part II: Rough Set Applications; Feature Selection and Knowledge Discovery; and Cognitive Computing.Part III: Three-way Data Analytics and Decision; Medicine and Health Data Mining; and Applications of Deep Learning and Soft Computing.
Using AI To Make Your Own Job
Celebrated author Wm. Hovey Smith explains how to use AI to create new business ideas and start your own businesses in the US. This is a business book for the non-business major filled with practical advice based on the author's hard-won experiences. Practical hints are given about naming, financing, choosing partners, location, product pricing, and having fun with your businesses.Reviews of the author's works include Kirkus who considered the previous version of this book "a worthy book for the newbie entrepreneur" and by the U.S. Review of Books who put it on their "Recommended List." Potential users range from teens to seniors who seek to discover that, "There is nothing in human experience that cannot be turned into profit by an inventive mind."
Generative Artificial Intelligence Empowered Learning
This book explores the integration of Generative AI (GenAI), such as ChatGPT, into educational practices and research methodologies. Ideal for educators, researchers, and policymakers, this book serves as a practical resource for those looking to effectively integrate AI into their pedagogical and research efforts.
Computational Techniques for Biological Sequence Analysis
This book provides an overview of basic and advanced computational techniques for analysing and understanding protein, RNA, and DNA sequences. This book acts as useful reference for bioinformaticians and computational biologists working in the field of molecular biology, genomics, and bioinformatics.
Hybrid Models for Coupling Deductive and Inductive Reasoning
This book constitutes the refereed proceedings of the Third International Workshop on Hybrid Models for Coupling Deductive and Inductive Reasoning, HYDRA 2024, held in Santiago de Compostela, Spain, on October 20, 2024. The 6 full papers and 1 invited talk included in this book were carefully reviewed and selected from 7 submissions.The International Workshop on Hybrid Models for Coupling Deductive andInductive Reasoning (HYDRA) was designed as a forum for researchers to explore the exciting possibilities at the intersection of deductive and inductive reasoning.
Artificial Intelligence and Education - Shaping the Future of Learning
The book discusses the impact of artificial intelligence (AI) on education, exploring both the opportunities and challenges it brings. It aims to provide a comprehensive understanding of how AI is reshaping the educational environment, from personalized learning experiences and intelligent tutoring systems to administrative efficiencies and ethical considerations. The book also addresses the implications of AI on traditional educational models and the broader societal context, sparking a dialogue about AI's potential for enhancing learning outcomes and preparing students for an AI-driven world. Overall, it aims to inspire innovation and critical thinking in the field of education.
Building Integrations with Mulesoft
This concise yet comprehensive guide shows developers and architects how to tackle data integration challenges with MuleSoft. Authors Pooja Kamath and Diane Kesler take you through the process necessary to build robust and scalable integration solutions step-by-step. Supported by real-world use cases, Building Integrations with MuleSoft teaches you to identify and resolve performance bottlenecks, handle errors, and ensure the reliability and scalability of your integration solutions. You'll explore MuleSoft's robust set of connectors and their components, and use them to connect to systems and applications from legacy databases to cloud services. Ask the right questions to determine your use case, define requirements, decide on reuse versus rebuild, and create sequence and context diagrams Master tools like the Anypoint Platform, Anypoint Studio, Code Builder, GitHub, and Maven Design APIs with RAML and OAS and craft effective requests and responses Write MUnit tests, validate DataWeave expressions, and use Postman Collections Deploy Mule applications to CloudHub, use API Manager to create API proxies, and secure APIs with Mule OAuth 2.0 Learn message orchestration techniques for routers, transactions, error handling, For Each, Parallel For Each, and batch processing
AWS Cloud Practitioner Exam Guide
DESCRIPTION Amazon Web Services (AWS) stands as the preeminent cloud computing platform, offering a comprehensive suite of services for diverse technological requirements. This AWS Cloud Practitioner Exam Guide serves as a structured and rigorous resource for comprehending the foundational principles of AWS and effectively preparing for the Cloud Practitioner Certification examination.This guide introduces core cloud computing paradigms, the Global Infrastructure of AWS encompassing regions, Availability Zones, and content delivery mechanisms via CloudFront and Edge Locations. It examines cloud deployment, the AWS Well-Architected Framework for resilient, scalable solutions, and secure access via IAM. Essential compute (EC2, Lambda), storage (S3, EBS), databases (RDS, DynamoDB), networking (VPC), security, event-driven architectures (SQS, SNS), monitoring (CloudWatch), infrastructure automation (CloudFormation), cost management, advanced identity (Cognito), and other AWS offerings for exam preparation are also covered. It also covers event-driven architectures with SQS and SNS, monitoring with CloudWatch, automation via CloudFormation, cost management, advanced identity with Cognito, and key AWS services aligned with exam goals.Upon completing this guide, you'll gain a solid foundation in AWS services and concepts, preparing you to confidently pass the AWS Cloud Practitioner exam and articulate key cloud value propositions. This book is your step-by-step path to launching a career in cloud engineering, solutions architecture, DevOps, or cloud support.WHAT YOU WILL LEARN● Implementing AWS security best practices, encryption, key management, compliance, and auditing.● Content delivery with CloudFront, event-driven architectures using SQS and SNS messaging.● Monitoring AWS resources with CloudWatch and infrastructure automation using CloudFormation and CDK.● Cloud fundamentals, AWS Global Infrastructure, deployment models, and the Well-Architected Framework.● Core AWS compute services like EC2 instances, containers with ECS, and serverless Lambda.WHO THIS BOOK IS FORThis book is designed for individuals seeking to understand AWS fundamentals and those aiming to enhance their existing AWS knowledge for certification purposes. No prior AWS or technical experience is needed, making it ideal for both beginners and professionals looking to build and validate foundational cloud skills.
Ultimate Azure AI Services for Gen AI Solutions
Master Generative AI with Azure OpenAI, AI Services, and advanced tools for real-world applications! Book DescriptionAzure OpenAI provides unparalleled access to cutting-edge AI models, empowering enterprises to innovate, automate, and drive transformative business outcomes at scale. Ultimate Azure AI Services for Gen AI Solutions is your gateway to mastering Azure OpenAI and Azure AI services. Whether you're just starting out or looking to refine your skills, this book covers everything from foundational concepts to advanced techniques. Dive into topics like Large Language Models (LLMs), LangChain, vector databases, embeddings, and Python programming, with a focus on key Azure components such as Storage, Search Services, Azure OpenAI Studio, and Prompt Flow. Through step-by-step hands-on examples, you'll gain practical insights into the power of prompt engineering, advanced features of Azure's AI capabilities, and how to implement solutions in language, speech, and vision. You'll also explore ethical AI practices, ensuring responsible and impactful AI development. This book equips you with the skills to navigate the full Generative AI lifecycle-from development to deployment-ensuring your enterprise stays ahead in this fast-paced field. Don't miss your chance to transform your business with Azure's revolutionary AI tools-start building the future today! Table of Contents1. Introduction to Generative AI2. Exploring LLMs and Its Capabilities3. Vector Database and Embedding Techniques4. Prompt Engineering and Its Significance5. Azure Storage for Azure OpenAI Implementations6. Azure AI Search Services for Azure OpenAI Implementations7. Getting Started with Generative AI Using Azure OpenAI Services8. Advanced Azure AI Studio-I9. Advanced Azure AI Studio-II10. Generative AI Use Cases for Industries-I11. Gen AI Implementation Use Case with Azure OpenAI-II Index
Devsecops in Oracle Cloud
Automate, secure, and optimize your cloud infrastructure with proven best practices and expert insights. Securing every stage of development and deployment is no longer a choice--it is a necessity. Adopting a proactive DevSecOps approach is crucial to safeguarding cloud applications and infrastructures. OCI experts Benner, Aboulnaga, and Patel provide comprehensive guidance on leveraging DevSecOps principles to effectively secure and automate cloud environments. Developers, DevOps professionals, and cloud architects will learn best practices for automating security processes and optimizing enterprise infrastructures with powerful tools such as Terraform and Ansible. This comprehensive guide provides actionable strategies for building secure, scalable, and resilient cloud applications. You will learn Step-by-step examples of using Terraform and Ansible in OCI to automate and manage cloud infrastructure DevSecOps principles and best practices for Oracle Cloud environments Key OCI services and how they can be applied within a DevSecOps framework to ensure security and efficiency Practical strategies for building secure, scalable, and resilient applications in Oracle Cloud How to integrate DevSecOps principles throughout the development and deployment lifecycle Techniques for maintaining regulatory compliance while ensuring security in Oracle Cloud How to optimize cloud costs in OCI without compromising security or performance Practical steps to securely deploy applications in Oracle Cloud Unlock the full potential of Oracle Cloud and DevSecOps and ensure that your organization stays ahead of evolving security threats and operational demands. This guide provides the hands-on tools, expert insights, and proven strategies you need to secure, automate, and scale your Oracle Cloud applications.
Human-Centered AI
A HUMAN-CENTERED APPROACH TO ARTIFICIAL INTELLIGENCE WILL ENSURE HUMAN CONTROL OVER POWERFUL AND HELPFUL FUTURE MOBILE DEVICES AND SERVICES Researchers, developers, business leaders, policy makers, and others are expanding the technology-centered scope of artificial intelligence (AI) to include human-centered AI (HCAI) ways of thinking. This expansion from an algorithm-focused view to embrace a human-centered perspective can shape the future of technology to better serve human needs. The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, as many technology companies and thought leaders have said, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman aims to produce an optimistic, realistic, guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to make successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Cyberspace Simulation and Evaluation
This three volume set, CCIS 2420 - 2422, constitutes the proceedings of the Third International Conference on Cyberspace Simulation and Evaluation, CSE 2024, held in Shenzhen, China, during November 26-28, 2024. The 90 full papers included in this book were carefully reviewed and selected from 164 submissions. These papers are organized under topical sections as follows: - Part I: Simulation Theory and Methodology; Simulation for CI scenario; Defense Methodology in the Evaluation; and Simulation for IoT scenario. Part II: Attack Methodology in the Evaluation; Other Simulation and Evaluation methods; Evaluation Theory and Methodology; and Defense Methodology in the Evaluation. Part III: Defense Methodology in the Evaluation; Design and Cybersecurity for AIoT Systems; Metaverse and Simulation; Secure loT and Blockchain -Enabled Solutions; Software and Protocols Security Analysis; and Test and Evaluation for Cybersecurity.
Cyberspace Simulation and Evaluation
This three volume set, CCIS 2420 - 2422, constitutes the proceedings of the Third International Conference on Cyberspace Simulation and Evaluation, CSE 2024, held in Shenzhen, China, during November 26-28, 2024. The 90 full papers included in this book were carefully reviewed and selected from 164 submissions. These papers are organized under topical sections as follows: - Part I: Simulation Theory and Methodology; Simulation for CI scenario; Defense Methodology in the Evaluation; and Simulation for IoT scenario. Part II: Attack Methodology in the Evaluation; Other Simulation and Evaluation methods; Evaluation Theory and Methodology; and Defense Methodology in the Evaluation. Part III: Defense Methodology in the Evaluation; Design and Cybersecurity for AIoT Systems; Metaverse and Simulation; Secure loT and Blockchain -Enabled Solutions; Software and Protocols Security Analysis; and Test and Evaluation for Cybersecurity.
Principles of Artificial Intelligence
This book covers the Principles of Artifi cial Intelligence. It is both a text book and a reference book. It is one of many books on the subject of artifi cial intelligernce. There are more than 400 of them. It is the only one that covers principles that is intended to refl ect on how to go about doing AI for productive purposes. It also covers about what AI is already, but it is more than that. It answers the question "Can a machine think?" and most people are quite tired of that question. In fact, people are now more interested in how to do what we want to do. In fact, AI is a inportant subject in our lives and here are two outstanding books that atune to that assertion: The Singularity is Nearer (2024) by Ray Kurzweil; Artifi cial Intelligence: A Modern Approach (1995) by Stuart Russell and Peter Norvig; The writers are exceedingly intelligent, and the books are useful but not that easy to read. University research is equally noteworthy. But what about the strategy of adopting AI for the modern operational environment? How do you know what to do and how to do it. Do you have to be a scientist or a mathematician to do the job? Absolutely not. Do you need to be a manager, a major CEO, or even the President of a coiuntry. Probably yes. But you need to have the information to do the job. This book gives you what you should do to implement AI in the organization and precisely what you need to know in order to do it. When doing the job of implementing, should you be knowledgeable about precisly what has to be done? Of course. Do you personally have to do it? Not at all. Do you need information on related subjects, of course again. Do you have to read this book serially? Of course not; it is too detailed. But when you fi nally get it done properly, you do deserve to be a DAI, that is a Doctor of Artifi cial Intelligence. That is proposed to be the case in the future. Will this be happy reading? On some topics, yes. Other sections, not so much. There are a lot of pages because the environment of AI is large and complicated. Many of the subjects covered in this book will be extremely useful in other areas of business and the organizaton. Artifi cial Intelligence is an extremely volatile subject. It is being adjusted daily, and it is almost impossible to fi gure out what is actually going on. The book will be revised and probably copied in content with an air of improvement. That is the way the world operates. Have a useful and interesting time reading the book. It will be worth the effort. One more thing. The book is for fi nding out about AI and associated subjects. Who knowswhat the professional and everyday people want to know. The book is for everyone. Equally important is the fact that the book is specifi cally designed for an online college course on AI and supports that assertion by including a substantional choice of subjects for the online professor. For example, the last section on managing uncertainly is very strongly AI based on the Theory of Evidence through the information on Dempster Shafer Theory. The author has been involved with AI since a university 3-week seminar in 1963 for a large corporation and taught one of the fi rst graduate-level university courses on AI in 1978. He has been the CEO of Artifi cial Intelligence Consulting (AICON), a university professor, and an international AI consultant, after working for Boeing, Oak Ridge National Lab, and IBM. He has written a few books and a few more peer reviewed papers.
Principles of Artificial Intelligence
This book covers the Principles of Artifi cial Intelligence. It is both a text book and a reference book. It is one of many books on the subject of artifi cial intelligernce. There are more than 400 of them. It is the only one that covers principles that is intended to refl ect on how to go about doing AI for productive purposes. It also covers about what AI is already, but it is more than that. It answers the question "Can a machine think?" and most people are quite tired of that question. In fact, people are now more interested in how to do what we want to do. In fact, AI is a inportant subject in our lives and here are two outstanding books that atune to that assertion: The Singularity is Nearer (2024) by Ray Kurzweil; Artifi cial Intelligence: A Modern Approach (1995) by Stuart Russell and Peter Norvig; The writers are exceedingly intelligent, and the books are useful but not that easy to read. University research is equally noteworthy. But what about the strategy of adopting AI for the modern operational environment? How do you know what to do and how to do it. Do you have to be a scientist or a mathematician to do the job? Absolutely not. Do you need to be a manager, a major CEO, or even the President of a coiuntry. Probably yes. But you need to have the information to do the job. This book gives you what you should do to implement AI in the organization and precisely what you need to know in order to do it. When doing the job of implementing, should you be knowledgeable about precisly what has to be done? Of course. Do you personally have to do it? Not at all. Do you need information on related subjects, of course again. Do you have to read this book serially? Of course not; it is too detailed. But when you fi nally get it done properly, you do deserve to be a DAI, that is a Doctor of Artifi cial Intelligence. That is proposed to be the case in the future. Will this be happy reading? On some topics, yes. Other sections, not so much. There are a lot of pages because the environment of AI is large and complicated. Many of the subjects covered in this book will be extremely useful in other areas of business and the organizaton. Artifi cial Intelligence is an extremely volatile subject. It is being adjusted daily, and it is almost impossible to fi gure out what is actually going on. The book will be revised and probably copied in content with an air of improvement. That is the way the world operates. Have a useful and interesting time reading the book. It will be worth the effort. One more thing. The book is for fi nding out about AI and associated subjects. Who knowswhat the professional and everyday people want to know. The book is for everyone. Equally important is the fact that the book is specifi cally designed for an online college course on AI and supports that assertion by including a substantional choice of subjects for the online professor. For example, the last section on managing uncertainly is very strongly AI based on the Theory of Evidence through the information on Dempster Shafer Theory. The author has been involved with AI since a university 3-week seminar in 1963 for a large corporation and taught one of the fi rst graduate-level university courses on AI in 1978. He has been the CEO of Artifi cial Intelligence Consulting (AICON), a university professor, and an international AI consultant, after working for Boeing, Oak Ridge National Lab, and IBM. He has written a few books and a few more peer reviewed papers.
The Art of Deep Learning Image Augmentation: The Seeds of Success
”AI” Means Fraud
"AI" Means Fraud: The Fraudulent Redefinition That's Driving A Global Con The World is Drunk on "Artificial Intelligence" Hype. It's Time for a Sobering Reality Check. In "AI" Means Fraud, Jared A. Snyder, a tech veteran with over 30 years of hands-on technology experience tears into the fraudulent narrative behind so-called "Artificial Intelligence"-a term that's been hijacked and redefined to sell an illusion. From "self-driving" cars to tools like ChatGPT and Grok, the public has been sold the lie that machines can "think" and "learn." They can't. There's no cognition, no understanding, no awareness-just technological magic tricks. It's not intelligence. It's the illusion of intelligence, packaged to look convincing, but built on pre-scripted outcomes and brute-force pattern matching. And the distinction matters-ethically, culturally, economically, and even spiritually. This book reveals how the term "AI" has been fraudulently redefined to give machines the appearance of intelligence while concealing the statistical mathematics behind the illusion. It's marketing over meaning-code wrapped in pseudo-science and anthropomorphic hype, sold to an awestruck public by tech giants, academics, a complicit media, and politicians as well. If it all feels familiar, that's because it is. A similar playbook was used during the China Virus pandemic, when language was bent to sell narratives, and the redefinition of words like "vaccine" paved the way for sweeping control and cultural confusion. Yet, the fraudulent redefinition of the term "Artificial Intelligence" hasn't seemingly generated the same outrage from the public-at least not yet. "AI" Means Fraud connects the dots-technically, historically, and morally-between modern deceptive "AI" hype and past tech industry manipulations like the Y2K Bug panic. This book is not just a critique of flawed code; it's a dismantling of the cult-like reverence forming around technology that doesn't deserve it. In this book, you'll discover: - What "AI" actually is-and what it isn't - How fundamental terms have been redefined to deceive, not inform - Why the public is being conditioned to accept automation as autonomy - The economic, cultural, and ethical costs of believing the lie Though rooted in logic and technical clarity, Jared-who is also a well-educated Christian leader-closes this book with a rare perspective seemingly missing from the conversation: a Christian ethical analysis of mankind's attempt to mirror divine attributes through technology. Though, it's not a sermon, but a sobering reminder that this deception runs deeper than bad science-it echoes humanity's oldest rebellion. "AI" Means Fraud is a sharp, unapologetic wake-up call for those who value reason over rhetoric and are tired of the technology industry's deceptions. With clarity and conviction, it arms readers to recognize and resist one of the most concerning issues of our time, which isn't actually a technology problem at all-it's a truth problem.
Beyond Intelligence
What does it mean to be human in an age when machines can mimic emotion, compose music, make moral decisions, and even simulate intimacy?In Beyond Intelligence: 20 Ways AI Is Rewriting What It Means to Be Human, author Mahmoud Aghiorly takes readers on a sweeping and thought-provoking journey through the twenty most profound ways artificial intelligence is reshaping human life. From emotions and creativity to identity, morality, work, justice, and even spirituality and death, this book explores how AI is not just changing what we do-but who we are.Drawing on insights from philosophy, neuroscience, ethics, and cutting-edge technology, Aghiorly dives into critical questions: Can AI truly understand or feel emotions?Is human creativity still unique in the age of generative algorithms?What happens to free will, purpose, and identity when data defines our choices?Will empathy, connection, and meaning survive as we form bonds with machines?Balancing deep inquiry with accessible language, Beyond Intelligence is both a guide and a reflection-a must-read for anyone who wants to understand the social, emotional, and philosophical implications of living alongside intelligent machines. Whether you're a technologist, educator, policymaker, or simply a curious mind, this book will challenge your assumptions and inspire deeper thinking about our collective future.
Pediatric and Lifespan Data Science
This open access book will address the unique requirements and technological tools for analysis of data across the lifespan, from childhood through advanced age. Topics such as sepsis, hospital-acquired infections, mental health, health equity, precision medicine, large language models and generative artificial intelligence, computer vision, ethical use of artificial intelligence, and large real-world electronic health record databases will be covered.
Business Intelligence, Computational Mathematics, and Data Analytics
This book constitutes the proceedings of the First International Conference on Business Intelligence, Computational Mathematics, and Data Analytics, IBCD 2024, held in Indore, India, during August 18-19, 2024. The conference focus on applied intelligence across data science, mathematics, healthcare, cybersecurity, and business analytics, and will serve as a driving force for transforming theoretical breakthroughs into practical, real-world solutions with meaningful societal impact.
