The Mobility Society
Over the last century and a half, modern life has largely been characterized by stability and predictability, where individuals settled in one place and followed familiar routines. The late 19th century saw the rise of global brands and transportation advancements, making the world smaller in a virtual sense and more accessible in a logistical one. By the 1990s, global brands and easy transport were the norm, yet the patterns of life remained largely unchanged.About three decades ago, the pace of change quickened dramatically. Ties to a fixed location weakened, economic forces shifted, and telecommunications shifted from landlines to cellular and IP services. Norms around employment shifted, giving rise to the gig economy. Companies like Amazon and Uber reshaped expectations, leading to an "anything, anywhere, anytime" culture.The Mobility Society emerged, a constant evolution transcending place and time. This transformation is expertly explored and defined by the insightful mind of Paul Warburton, who has been at the forefront of this movement for over a decade. His "Now - Near - Far" structure has become a powerful tool in planning and understanding the changes that lie ahead.This book weaves together the complex web of technological and societal changes shaping the Mobility Society. For those involved in these transformations, this book offers fascinating insights, while for those in policymaking roles, it is a crucial guide to understanding and preparing for the inevitable evolution.
Algorithms and Subjectivity
In this thought-provoking volume, Eran Fisher interrogates the relationship between algorithms as epistemic devices and modern notions of subjectivity.Over the past few decades, as the instrumentalization of algorithms has created knowledge that informs our decisions, preferences, tastes, and actions, and the very sense of who we are, they have also undercut, and arguably undermined, the Enlightenment-era ideal of the subject. Fisher finds that as algorithms enable a reality in which knowledge is created by circumventing the participation of the self, they also challenge contemporary notions of subjectivity.Through four case-studies, this book provides an empirical and theoretical investigation of this transformation, analyzing how algorithmic knowledge differs from the ideas of critical knowledge which emerged during modernity - Fisher argues that algorithms create a new type of knowledge, which in turn changes our fundamental sense of self and our concept of subjectivity.This book will make a timely contribution to the social study of algorithms and will prove especially valuable for scholars working at the intersections of media and communication studies, internet studies, information studies, the sociology of technology, the philosophy of technology, and science and technology studies.
Elements of Dimensionality Reduction and Manifold Learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and manifold learning. Three main aspects of dimensionality reduction are covered: spectral dimensionality reduction, probabilistic dimensionality reduction, and neural network-based dimensionality reduction, which have geometric, probabilistic, and information-theoretic points of view to dimensionality reduction, respectively. The necessary background and preliminaries on linear algebra, optimization, and kernels are also explained to ensure a comprehensive understanding of the algorithms.The tools introduced in this book can be applied to various applications involving feature extraction, image processing, computer vision, and signal processing. This book is applicable to a wide audience who would like to acquire a deep understanding of the various ways to extract, transform, and understand the structure of data. The intended audiences are academics, students, and industry professionals. Academic researchers and students can use this book as a textbook for machine learning and dimensionality reduction. Data scientists, machine learning scientists, computer vision scientists, and computer scientists can use this book as a reference. It can also be helpful to statisticians in the field of statistical learning and applied mathematicians in the fields of manifolds and subspace analysis. Industry professionals, including applied engineers, data engineers, and engineers in various fields of science dealing with machine learning, can use this as a guidebook for feature extraction from their data, as the raw data in industry often require preprocessing.The book is grounded in theory but provides thorough explanations and diverseexamples to improve the reader's comprehension of the advanced topics. Advanced methods are explained in a step-by-step manner so that readers of all levels can follow the reasoning and come to a deep understanding of the concepts. This book does not assume advanced theoretical background in machine learning and provides necessary background, although an undergraduate-level background in linear algebra and calculus is recommended.
AI in Wireless for Beyond 5g Networks
Artificial intelligence (AI) is a game changer in many domains, and wireless communication networks are no exception. With the advent of 5G networks, we have witnessed rapid growth in wireless connectivity, which has led to unprecedented opportunities for innovation and new use cases. However, as we move beyond 5G (B5G), the challenges and opportunities are set to become even more significant, offering new, previously unimaginable services.AI in Wireless for Beyond 5G Networks provides a comprehensive overview of the use of AI in wireless communication for B5G networks. The authors draw on their expertise in the field to explore the latest developments in AI technologies and their applications in B5G wireless communication systems. The book discusses a wide range of topics, including enabling AI technologies, architecture, and applications of AI from smartphones, radio access networks (RANs), edge and core networks, and application service providers. It also discusses the trends in on-device AI for B5G networks.This book is written in an accessible style, making it an ideal resource for academics, researchers, and industry professionals in wireless communication. It provides valuable insights into the latest field trends and developments and practical possibilities for implementing AI technologies in wireless communication systems.Above all, this book is a testament to the power of collaboration and innovation in wireless communication. The authors' dedication and expertise have produced a valuable resource for anyone interested in the latest AI and wireless communication developments. This book will inspire and inform readers, and we highly recommend it to scholars interested in the future of AI in wireless communication.
Smart Vr/Ar/MR Systems for Professionals
Smart VR/AR/MR Systems for Professionals is a comprehensive guide that explores the ground-breaking applications of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in various industries. This book aims to equip practicing professionals with the knowledge and insights they need to harness the full potential of these immersive technologies in their respective fields.Through this book, the authors aim to explore the experimental breakthroughs and cutting-edge methodologies that have emerged in the realm of VR/AR/MR. The book delves deeper into the profound impact these technologies have had on the design process, computer-aided design, healthcare product development, manufacturing, human-robot collaboration, medical imaging, rehabilitation, and even phobia therapy.In each chapter of this book, we delve into specific topics, uncovering the principles, methodologies, and best practices that professionals can adopt. Examples of these topics range from empowering design processes with virtual reality to revolutionizing computer-aided design, and from exploring AR/VR/MR technologies in healthcare to transforming manufacturing with digital twins and metrology in VR.The book aims to provide practitioners with valuable insights, real-world examples, and practical guidance to navigate the ever-evolving landscape of VR/AR/MR systems.
Quantum Artificial Intelligence with Qiskit
Quantum Artificial Intelligence (QAI) is a new interdisciplinary research field that combines quantum computing with Artificial Intelligence (AI), aiming to use the unique properties of quantum computers to enhance the capabilities of AI systems. Quantum Artificial Intelligence with Qiskit provides a cohesive overview of the field of QAI, providing the tools for readers to create and manipulate quantum programs on devices as accessible as a laptop computer.Introducing symbolical quantum algorithms, sub-symbolical quantum algorithms, and quantum Machine Learning (ML) algorithms, this book explains each process step by step with associated Qiskit listings. All examples are additionally available for download at https: //github.com/andrzejwichert/qai.Allowing readers to learn the basic concepts of quantum computing on their home computers, this book is accessible to both the general readership as well as students and instructors of courses relating to computer science and AI.
The Ethics of Virtual and Augmented Reality
This book offers new ways of thinking about and assessing the impact of virtual reality on its users. It argues that we must go beyond traditional psychological concepts of VR "presence" to better understand the many varieties of virtual experiences.
Machine Learning and Data Mining for Sports Analytics
This book constitutes the refereed proceedings of the 10th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2023, held in Turin, Italy, in September 2023.The 16 full papers included in this book were carefully reviewed and selected from 31 submissions. They were organized in topical sections as follows: Football/Soccer, Basketball, Other team sports, Individual sports.
Intelligent Human Computer Interaction
This book constitutes the refereed proceedings of the 15th International Conference on Intelligent Human Computer Interaction, IHCI 2023, held in Daegu, South Korea, during November 8-10, 2023.The 55 full papers and 16 short papers included in this book were carefully reviewed and selected from 139 submissions. They were organized in topical sections as follows: Volume I: Natural Language and Dialouge Systems, Affective Computing and Human Factors, Human Centred AI, Human-Robot Interaction and Intelligent Interfaces and User Centred Design.Volume II: AI and Big Data, Deep Learning, Intelligent Systems, Mobile Computing and Ubiquitous Interactions and Social Computing and Interactive Elements.
Music Intelligence
This book constitutes the refereed proceedings of the Second Summit on Music Intelligence, SOMI 2023, held in Beijing, China, during October 28-30, 2023.The 10 full papers included in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections as follows: Music, Neural Science and Music Therapy, Multimodality in Music and Music Generation.
Intelligent Human Computer Interaction
This book constitutes the refereed proceedings of the 15th International Conference on Intelligent Human Computer Interaction, IHCI 2023, held in Daegu, South Korea, during November 8-10, 2023.The 55 full papers and 16 short papers included in this book were carefully reviewed and selected from 139 submissions. They were organized in topical sections as follows: Volume I: Natural Language and Dialouge Systems, Affective Computing and Human Factors, Human Centred AI, Human-Robot Interaction and Intelligent Interfaces and User Centred Design.Volume II: AI and Big Data, Deep Learning, Intelligent Systems, Mobile Computing and Ubiquitous Interactions and Social Computing and Interactive Elements.
Mastering Mlops Architecture: From Code to Deployment
MLOps, a combination of DevOps, data engineering, and machine learning, is crucial for delivering high-quality machine learning results due to the dynamic nature of machine learning data. This book delves into MLOps, covering its core concepts, components, and architecture, demonstrating how MLOps fosters robust and continuously improving machine learning systems. By covering the end-to-end machine learning pipeline from data to deployment, the book helps readers implement MLOps workflows. It discusses techniques like feature engineering, model development, A/B testing, and canary deployments. The book equips readers with knowledge of MLOps tools and infrastructure for tasks like model tracking, model governance, metadata management, and pipeline orchestration. Monitoring and maintenance processes to detect model degradation are covered in depth.
The Potential of Generative AI
The Potential of Generative AI invites you for a captivating journey into the revolutionary technology, where machines become co-creators and the line between imagination and reality blurs. You will learn how AI helps doctors, engineers, and scientists solve real-world problems. Next, you will explore use cases where ChatGPT can boost productivity and enhance creativity. The book explores the journey from the origins of this revolutionary technology to its cutting-edge applications. Discover how generative models like GANs and VAEs work, and familiarize yourself with the impact they are making in fields like healthcare, finance, and art. Through real-world case studies and engaging examples, you will witness AI generating life-saving drugs, composing music, and even designing innovative products.
Mastering Cloud Storage
In today's data-driven world, cloud storage has emerged as an indispensable tool for businesses and individuals alike. With its ability to store and manage vast amounts of data seamlessly, cloud storage has revolutionized the way we handle information. However, navigating the complexities of cloud storage can be a daunting task. This is where this book steps in. Commence on a comprehensive journey through cloud computing fundamentals, exploring evolution, service models, and deployment strategies. Uncover diverse cloud storage technologies, including object, block, and file storage, and look into Amazon S3, Azure Blob Storage, and Google Cloud Storage. Learn to configure storage effectively, implement scalable solutions, and seamlessly integrate with applications. Master disaster recovery, data migration, and hybrid cloud architectures for optimal resource utilization.
Nexus
#1 NEW YORK TIMES BESTSELLER - From the author of Sapiens comes the groundbreaking story of how information networks have made, and unmade, our world. "Striking original . . . A historian whose arguments operate on the scale of millennia has managed to capture the zeitgeist perfectly."--The Economist "This deeply important book comes at a critical time as we all think through the implications of AI and automated content production. . . . Masterful and provocative."--Mustafa Suleyman, author of The Coming Wave For the last 100,000 years, we Sapiens have accumulated enormous power. But despite all our discoveries, inventions, and conquests, we now find ourselves in an existential crisis. The world is on the verge of ecological collapse. Misinformation abounds. And we are rushing headlong into the age of AI--a new information network that threatens to annihilate us. For all that we have accomplished, why are we so self-destructive? Nexus looks through the long lens of human history to consider how the flow of information has shaped us, and our world. Taking us from the Stone Age, through the canonization of the Bible, early modern witch-hunts, Stalinism, Nazism, and the resurgence of populism today, Yuval Noah Harari asks us to consider the complex relationship between information and truth, bureaucracy and mythology, wisdom and power. He explores how different societies and political systems throughout history have wielded information to achieve their goals, for good and ill. And he addresses the urgent choices we face as non-human intelligence threatens our very existence. Information is not the raw material of truth; neither is it a mere weapon. Nexus explores the hopeful middle ground between these extremes, and in doing so, rediscovers our shared humanity.
When Machines Learn
Discover the Dawn of a New Era: The Ties Between Artificial Intelligence and Our FutureImagine a world where every aspect of life is enhanced by artificial intelligence-our jobs, our ethical decisions, and even the way we interact with one another. "When Machines Learn: AI and the Transformation of Society" is a gripping exploration of this not-so-distant future, where AI is not only a tool but a transformative force reshaping every facet of human existence.Dive into the heart of innovation with the pioneering journey through the evolution of artificial intelligence. Unravel the mysteries of its fundamentals and witness history unfold, as AI advances from primitive concepts to sophisticated systems that seamlessly integrate into our daily lives. Take a front-seat tour of the most groundbreaking applications that are setting the stage for a revolution.With humanity at a critical crossroads, explore the intricate dance between AI and its impact on the workforce. Jobs will evolve, industries will be reborn, and a new skilled labor market will rise from the ashes of automation. This book peels back layers of fear and uncertainty, revealing the silver lining of opportunities that lie ahead.Yet, this brave new world comes with its moral dilemmas. Delve into the heart of AI's ethical considerations, addressing the challenging questions of bias, equality, and the importance of transparent and accountable systems. What are the implications for privacy in a data-driven world? How do we navigate the tightrope between technological advancement and the protection of individual rights?Discover how AI will shape the future of humanity, not just through technological prowess but by redefining the core of societal values. Human-AI collaboration paints a vivid picture of enhanced human capabilities, while case studies of AI-driven innovation showcase the explosive potential at our fingertips.The book casts a gaze upon the global stage, examining international policies and the geopolitical race for AI supremacy. It shows us how artificial intelligence can redefine the way we live our daily lives, from personalized experiences to groundbreaking strides in health, education, and transportation.Prepare yourself with knowledge to face the imminent AI future. If you're curious about how AI will disrupt, reconstruct, and innovate the world as we know it, this book is your essential guide to understanding and embracing the AI revolution. Step into the pages of "When Machines Learn" and navigate the boundless possibilities of tomorrow.
AI and ML for Coders
Are you ready to unlock the transformative power of Artificial Intelligence (AI) and Machine Learning (ML) in your coding projects? "AI and ML for Coders" is the essential guide for coders who want to leap into the future of technology.This book is tailored for programmers, developers, and tech enthusiasts eager to integrate AI and ML into their work. Whether you're a seasoned coder or just starting, you'll find invaluable insights and practical knowledge to elevate your craft.Here's what you'll gain from "AI and ML for Coders" A comprehensive understanding of AI and ML evolution, from historical milestones to cutting-edge techniques.A deep dive into the core concepts, terminology, and ethical considerations that every coder must know.Hands-on guidance on choosing the right tools, libraries, and programming languages for your AI and ML projects.Expert strategies for data preparation, preprocessing, and selecting the most effective algorithms for different tasks.Real-world applications and case studies demonstrate AI and ML's power in coding.Key features include: Clear explanations of supervised, unsupervised, and reinforcement learning.Exploration of neural networks, deep learning, natural language processing, and computer vision.Practical advice on navigating the ethical landscape of AI to develop responsible and trustworthy applications.Authored by a seasoned expert in the field, "AI and ML for Coders" is your roadmap to mastering AI and ML. It's not just a book; it's an investment in your future as a coder in an AI-driven world.Take advantage of the opportunity to be at the forefront of the AI revolution. Take the next step and add "AI and ML for Coders" to your library today. Your journey into the realm of AI and ML starts here!
Neural Network Computer Vision with OpenCV 5
Neural Network Computer Vision with OpenCV equips you with professional skills and knowledge to build intelligent vision systems using OpenCV. It creates a sequential pathway for understanding morphological operations, edge and corner detection, object localization, image classification, segmentation, and advanced applications like face detection and recognition, and optical character recognition. This book offers a practical roadmap to explore the nuances of image processing with detailed discussions on each topic, supported by hands-on Python code examples. The readers will learn the basics of neural networks, deep learning and CNNs by using deep learning frameworks like Keras, Tensorflow, PyTorch, Caffe etc. They will be able to utilize OpenCV DNN module to classify images by using models like Inception V3, Resnet 101, Mobilenet V2. Moreover, the book will help to successfully Implement object detection using YOLOv3, SSD and R-CNN models.
DevOps Design Pattern
DevOps design patterns encompass a set of best practices aimed at revolutionizing the software development lifecycle. It introduces a collaborative and streamlined approach to bring together different aspects of development, testing, deployment, and operations. At its core, DevOps seeks to break down traditional silos between these functions, fostering a culture of cooperation and continuous communication among teams. This interconnectivity enables faster, higher-quality software delivery by eliminating bottlenecks. DevOps best practices offer significant benefits to DevOps engineers, enhancing their effectiveness and efficiency. Examine best practices for version control and dynamic environments closely, learn how to "build once, deploy many," and master the art of continuous integration and delivery (CI/CD), reducing manual intervention and minimizing errors. Each chapter equips you with actionable insights, guiding you through automated testing, robust monitoring, and effective rollback strategies.
Synthetic Data
The book concentrates on the impact of digitalization and digital transformation technologies on the Industry 4.0 and smart factories, how the factory of tomorrow can be designed, built, and run virtually as a digital twin likeness of its real-world counterpart, before the physical structure is actually erected.It highlights the main digitalization technologies that have stimulated the Industry 4.0, how these technologies work and integrate with each other, and how they are shaping the industry of the future.It examines how multimedia data and digital images in particular are being leveraged to create fully virtualized worlds in the form of digital twin factories and fully virtualized industrial assets. It uses BMW Group's latest SORDI dataset (Synthetic Object Recognition Dataset for Industry), i.e., the largest industrial images dataset to-date and its applications at BMW Group and Idealworks, as one of the main explanatory scenarios throughout the book.It discusses the need of synthetic data to train advanced deep learning computer vision models, and how such datasets will help create the "robot gym" of the future: training robots on synthetic images to prepare them to function in the real world.
Emerging Topics in Pattern Recognition and Artificial Intelligence
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.
Digital Transformation in Policing: The Promise, Perils and Solutions
This book shares essential insights into how the social sciences and technology could foster new advances in managing the complexity inherent to the criminal and digital policing landscape. Said landscape is both dynamic and intricate, emanating as it does from crimes that are both persistent and transnational. Globalization, human and drug trafficking, cybercrime, terrorism, and other forms of transnational crime can have significant impacts on societies around the world. This necessitates a reassessment of what crime, national security and policing mean. Recent global events such as human and drug trafficking, the COVID-19 pandemic, violent protests, cyber threats and terrorist activities underscore the vulnerabilities of our current security and digital policing posture.This book presents concepts, theories and digital policing applications, offering a comprehensive analysis of current and emerging trends in digital policing. Pursuing an evidence-based approach, itoffers an extraordinarily perceptive and detailed view of issues and solutions regarding the crime and digital policing landscape. To this end, it highlights current technological and methodological solutions as well as advances concerning integrated computational and analytical solutions deployed in digital policing. It also provides a comprehensive analysis of the technical, ethical, legal, privacy and civil liberty challenges stemming from the aforementioned advances in the field of digital policing; and accordingly, offers detailed recommendations supporting the design and implementation of best practices including technical, ethical and legal approaches when conducting digital policing. The research gathered here fits well into the larger body of work on various aspects of AI, cybersecurity, national security, digital forensics, cyberterrorism, ethics, human rights, cybercrime and law. It provides a valuable reference for law enforcement, policymakers, cybersecurity experts, digital forensic practitioners, researchers, graduates and advanced undergraduates, and other stakeholders with an interest in counter-terrorism. In addition to this target audience, it offers a valuable tool for lawyers, criminologist and technology enthusiasts.
Generative AI For Business Leaders
Byte-sized Learning AI series by Now Next Later AI: Practical guides providing senior decision-makers with a clear, accessible roadmap for harnessing the power of generative AI, enhancing innovation, and boosting business outcomes.Save by buying the entire 3 book series in one single collection: Generative AI Transformation Blueprint Drawing on insights from leading consultancies and input from both established and rising leaders in the AI field, it presents a validated strategic approach. This blueprint not only outlines best practices but also showcases pioneering use cases, integrating them into a cohesive framework for practical implementation.Spanning across areas from strategic alignment and talent development to ethical governance and sustaining competitive edge amid relentless underlying progress, it delivers clarity for charting an optimal generative AI roadmap.Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and HypeShortlisted for the 2023 HARVEY CHUTE Book Awards recognizing emerging talent and outstanding works in the genre of Business and Enterprise Non-Fiction.Explore the transformative potential of technologies like GPT-4 and Claude 2. These large language models (LLMs) promise to reshape how businesses operate. Aimed at non-technical business leaders, this guide offers a pragmatic approach to leveraging LLMs for tangible benefits, while ensuring ethical considerations aren't sidelined.LLMs can refine processes in marketing, software development, HR, R&D, customer service, and even legal operations. But it's essential to approach them with a balanced view. In this guide, you'll: Learn about the rapid advancements of LLMs.Understand complex concepts in simple terms.Discover practical business applications.Get strategies for smooth integration.Assess potential impacts on your team.Delve into the ethics of deploying LLMs.With a clear aim to inform rather than influence, this book is your roadmap to adopting LLMs thoughtfully, maximizing benefits, and minimizing risks. Let's move beyond the noise and understand how LLMs can genuinely benefit your business.Artificial Intelligence Fundamentals for Business Leaders: Up to Date With Generative AIThe perfect guide to help non-technical business leaders understand the power of AI.More Than a CollectionBy purchasing this series, you will also be granted access to the AI Academy platform. There you can test your knowledge through end-of-chapter quizzes and engage in discussion with other readers.You will also receive 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion.AI Academy by Now Next Later AIWe are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically.
Open-Set Text Recognition
In real-world applications, new data, patterns, and categories that were not covered by the training data can frequently emerge, necessitating the capability to detect and adapt to novel characters incrementally. Researchers refer to these challenges as the Open-Set Text Recognition (OSTR) task, which has, in recent years, emerged as one of the prominent issues in the field of text recognition. This book begins by providing an introduction to the background of the OSTR task, covering essential aspects such as open-set identification and recognition, conventional OCR methods, and their applications. Subsequently, the concept and definition of the OSTR task are presented encompassing its objectives, use cases, performance metrics, datasets, and protocols. A general framework for OSTR is then detailed, composed of four key components: The Aligned Represented Space, the Label-to-Representation Mapping, the Sample-to-Representation Mapping, and the Open-set Predictor. In addition, possible implementations of each module within the framework are discussed. Following this, two specific open-set text recognition methods, OSOCR and OpenCCD, are introduced. The book concludes by delving into applications and future directions of Open-set text recognition tasks.This book presents a comprehensive overview of the open-set text recognition task, including concepts, framework, and algorithms. It is suitable for graduated students and young researchers who are majoring in pattern recognition and computer science, especially interdisciplinary research.
The Rise of Artificial Intelligence Impact on Industries and Society
The excursion through "The Ascent of Man-made consciousness: Effect on Enterprises and Society" is an enrapturing investigation that navigates the scenes of mechanical development, cultural change, and moral contemplations. This far reaching investigation unfurls across a progression of sections, each digging into unmistakable features of Man-made reasoning (simulated intelligence) that on the whole shape the story of our mechanical future. Beginning with the essential sections on the advancement and meanings of computer based intelligence, the account spreads out the verifiable embroidery of this groundbreaking innovation. From its conceptualization to contemporary forward leaps in AI and profound learning, the parts enlighten the unique exchange of logical request, mechanical headways, and the cultural effect of man-made intelligence. As the story advances, key ideas and wording act as the etymological framework, offering perusers a common language to explore the complexities of computer based intelligence - from directed figuring out how to brain organizations. The underpinnings of simulated intelligence are divulged in lovely detail, explaining the collaboration between information, calculations, and computational power. The parts on AI and profound learning arise as powerful motors impelling simulated intelligence's groundbreaking potential, exhibiting its flexibility and viability in tending to complex difficulties. The investigation of brain organizations and calculations digs into the complicated components that support simulated intelligence direction, disentangling the refinement that characterizes the innovation's abilities. The story then consistently changes into the advantageous connection between information, enormous information, and simulated intelligence. Here, the combination of computer based intelligence with sweeping datasets becomes the overwhelming focus, impelling progressions that reclassify how associations gather experiences, make expectations, and enhance tasks in the time of data overflow. The parts committed to computer based intelligence in different businesses, like medical care, money, assembling, and farming, feature the innovation's extraordinary touch, reshaping processes, improving productivity, and driving advancement across assorted areas. In imagining a human-driven man-made intelligence future, the finishing up sections welcome perusers to ponder a worldview where computer based intelligence isn't just a device however a compassionate partner. This future-situated investigation stresses inclusivity, straightforwardness, and personalization, preparing for an agreeable mix of man-made intelligence into the structure holding the system together. The source of inspiration reverberations all through the story, encouraging policymakers, industry pioneers, scientists, the labor force, promotion gatherings, teachers, and people in general to effectively partake in forming a future where man-made intelligence adjusts consistently with human qualities. Basically, this investigation remains as a demonstration of the groundbreaking capability of simulated intelligence, approaching partners from different domains to on the whole explore the moral aspects, cultural ramifications, and open doors introduced by this significant innovative development. The story fills in as a compass, directing perusers through the complicated landscape of artificial intelligence, encouraging comprehension, and rousing a common obligation to capable and moral artificial intelligence improvement.
Responsible AI
AI systems are solving real-world challenges and transforming industries, but there are serious concerns about how responsibly they operate on behalf of the humans that rely on them. Many ethical principles and guidelines have been proposed for AI systems, but they're often too 'high-level' to be translated into practice. Conversely, AI/ML researchers often focus on algorithmic solutions that are too 'low-level' to adequately address ethics and responsibility. In this timely, practical guide, pioneering AI practitioners bridge these gaps. The authors illuminate issues of AI responsibility across the entire system lifecycle and all system components, offer concrete and actionable guidance for addressing them, and demonstrate these approaches in three detailed case studies. Writing for technologists, decision-makers, students, users, and other stake-holders, the topics cover: Governance mechanisms at industry, organisation, and team levels Development process perspectives, including software engineering best practices for AI System perspectives, including quality attributes, architecture styles, and patterns Techniques for connecting code with data and models, including key tradeoffs Principle-specific techniques for fairness, privacy, and explainability A preview of the future of responsible AI
Artificial Intelligence
In a world where technology is advancing at an astounding rate, artificial intelligence (AI), machine learning (ML), and deep learning (DL) are leading the way in bringing about previously unheard-of changes to almost every aspect of our lives. Artificial intelligence (AI) has become ingrained in modern life, from smart homes anticipating our needs to modern medical diagnostics, demonstrating its indispensable role as a partner in human progress rather than merely an aid.With its title, "Artificial Intelligence: Harnessing the Power of Machine Learning and Deep Learning," the e-book seeks to serve as your introduction to this fascinating and ever-evolving world, where the limits of human capabilities are continually being pushed to the limit. Whether you are an experienced practitioner looking to expand your knowledge or a curious mind exploring this field for the first time, this thorough guide aims to provide insightful information.We will go on an insightful journey together in the upcoming chapters as we examine the complex web of ideas, advancements, and technologies that make up the field of artificial intelligence. We will discuss the algorithms that enable machines to learn from and forecast data as we delve deeply into machine learning principles. As we continue, we will delve deeper and deeper into the fascinating field of deep learning, a subset of machine learning that is described by neural networks that can remarkably mimic the functioning of the human brain
Learn LLVM 17 - Second Edition
Learn how to build and use the complete spectrum of real-world compilers, including the frontend, optimization pipeline, and a new backend by leveraging the power of LLVM core librariesKey Features- Get to grips with using LLVM libraries step by step- Understand the high-level design of LLVM compilers and apply these principles to your own compiler- Add a new backend to target an unsupported CPU architecture- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionLLVM was built to bridge the gap between the theoretical knowledge found in compiler textbooks and the practical demands of compiler development. With a modular codebase and advanced tools, LLVM empowers developers to build compilers with ease. This book serves as a practical introduction to LLVM, guiding you progressively through complex scenarios and ensuring that you navigate the challenges of building and working with compilers like a pro.The book starts by showing you how to configure, build, and install LLVM libraries, tools, and external projects. You'll then be introduced to LLVM's design, unraveling its applications in each compiler stage: frontend, optimizer, and backend. Using a real programming language subset, you'll build a frontend, generate LLVM IR, optimize it through the pipeline, and generate machine code. Advanced chapters extend your expertise, covering topics such as extending LLVM with a new pass, using LLVM tools for debugging, and enhancing the quality of your code. You'll also focus on just-in-time compilation issues and the current state of JIT-compilation support with LLVM. Finally, you'll develop a new backend for LLVM, gaining insights into target description and how instruction selection works.By the end of this book, you'll have hands-on experience with the LLVM compiler development framework through real-world examples and source code snippets.What you will learn- Configure, compile, and install the LLVM framework- Understand how the LLVM source is organized- Discover what you need to do to use LLVM in your own projects- Explore how a compiler is structured, and implement a tiny compiler- Generate LLVM IR for common source language constructs- Set up an optimization pipeline and tailor it for your own needs- Extend LLVM with transformation passes and clang tooling- Add new machine instructions and a complete backendWho this book is forThis book is for compiler developers, enthusiasts, and engineers new to LLVM. C++ software engineers looking to use compiler-based tools for code analysis and improvement, as well as casual users of LLVM libraries who want to gain more knowledge of LLVM essentials will also find this book useful. Intermediate-level experience with C++ programming is necessary to understand the concepts covered in this book.Table of Contents- Installing LLVM- The Structure of a Compiler- Turning the Source File into an Abstract Syntax Tree- Basics of IR Code Generation- IR Generation for High-Level Language Constructs- Advanced IR Generation- Optimizing IR- The TableGen Language- JIT Compilation- Debugging Using LLVM Tools- The Target Description- Instruction Selection- Beyond Instruction Selection
Machine Learning for Decision Makers
This new and updated edition takes you through the details of machine learning to give you an understanding of cognitive computing, IoT, big data, AI, quantum computing, and more. The book explains how machine learning techniques are used to solve fundamental and complex societal and industry problems. This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in machine learning. A new chapter on quantum computers and machine learning is included to prepare you for future challenges. Insights for decision makers will help you understand machine learning and associated technologies and make efficient, reliable, smart, and efficient business decisions. All aspects of machine learning are covered, ranging from algorithms to industry applications. Wherever possible, required practical guidelines and best practices related to machine learning and associated technologies are discussed. Also covered in this edition are hot-button topics such as ChatGPT, superposition, quantum machine learning, and reinforcement learning from human feedback (RLHF) technology. Upon completing this book, you will understand machine learning, IoT, and cognitive computing and be prepared to cope with future challenges related to machine learning. What You Will LearnMaster the essentials of machine learning, AI, cloud, and the cognitive computing technology stackUnderstand business and enterprise decision-making using machine learningBecome familiar with machine learning best practicesGain knowledge of quantum computing and quantum machine learningWho This Book Is ForManagers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them
Segmentation of the Aorta. Towards the Automatic Segmentation, Modeling, and Meshing of the Aortic Vessel Tree from Multicenter Acquisition
This book constitutes the First Segmentation of the Aorta Challenge, SEG.A. 2023, which was held in conjunction with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, on October 8, 2023. The 8 full and 3 short papers presented have been carefully reviewed and selected for inclusion in the book. They focus specifically on robustness, visual quality and meshing of automatically generated segmentations of aortic vessel trees from CT imaging. The challenge was organized as a "container submission" challenge, where participants had to upload their algorithms to Grand Challenge in the form of Docker containers. Three tasks were created for SEG.A. 2023.
The Definitive Guide to Google Vertex AI
Implement machine learning pipelines with Google Cloud Vertex AIKey Features: Understand the role of an AI platform and MLOps practices in machine learning projectsGet acquainted with Google Vertex AI tools and offerings that help accelerate the creation of end-to-end ML solutionsImplement Vision, NLP, and recommendation-based real-world ML models on Google Cloud PlatformPurchase of the print or Kindle book includes a free PDF eBookBook Description: While AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google's unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management.This book is a comprehensive guide that lets you explore Google Vertex AI's easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you'll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You'll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows.By the end of this book, you'll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.What You Will Learn: Understand the ML lifecycle, challenges, and importance of MLOpsGet started with ML model development quickly using Google Vertex AIManage datasets, artifacts, and experimentsDevelop no-code, low-code, and custom AI solution on Google CloudImplement advanced model optimization techniques and toolingUnderstand pre-built and turnkey AI solution offerings from GoogleBuild and deploy custom ML models for real-world applicationsExplore the latest generative AI tools within Vertex AIWho this book is for: If you are a machine learning practitioner who wants to learn end-to-end ML solution development on Google Cloud Platform using MLOps best practices and tools offered by Google Vertex AI, this is the book for you.
Recent Trends in Image Processing and Pattern Recognition
This book constitutes the refereed proceedings of the 6th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2023, held in Derby, UK, during December 2023, in collaboration with the Applied AI Research Lab at the University of South Dakota.The 62 full papers included in this book were carefully reviewed and selected from 216 submissions. The papers are organized in the following topical sections: Volume I: Artificial intelligence and applied machine learning; applied image processing and pattern recognition; and biometrics and applications. Volume II: Healthcare informatics; pattern recognition in blockchain, IOT, cyber plus network security, and cryptography.
Optimization, Learning Algorithms and Applications
This two-volume set CCIS 1981 and 1982 constitutes the refereed post-conference proceedings of the Third International Conference on Optimization, Learning Algorithms and Applications, OL2A 2023, held in Ponta Delgada, Portugal, in September 2023.The 66 revised full papers presented in these proceedings were carefully reviewed and selected from 162 submissions. The papers are organized in the following topical sections: Volume I: Machine learning; learning algorithms in engineering education; machine learning and data analysis in internet of things; optimization; optimization in the SDG context.Volume II: Computer vision based on learning algorithms; machine learning and AI in robotics; optimization in control systems design.
Optimization, Learning Algorithms and Applications
This two-volume set CCIS 1981 and 1982 constitutes the refereed post-conference proceedings of the Third International Conference on Optimization, Learning Algorithms and Applications, OL2A 2023, held in Ponta Delgada, Portugal, in September 2023.The 66 revised full papers presented in these proceedings were carefully reviewed and selected from 162 submissions. The papers are organized in the following topical sections: Volume I: Machine learning; learning algorithms in engineering education; machine learning and data analysis in internet of things; optimization; optimization in the SDG context.Volume II: Computer vision based on learning algorithms; machine learning and AI in robotics; optimization in control systems design.
Comptia Security＋ Certification Kit
Everything you need to prepare for and take the Security+ exam! The CompTIA Security+ Certification Kit includes CompTIA Security+ Study Guide: Exam SY0-701, 9th Edition, and the CompTIA Security+ Practice Tests: Exam SY0-701, 3rd Edition. Together, both books provide comprehensive review for the CompTIA Security+ SY0-701 certification exam. The Kit covers: Assessing the security posture of an enterprise environment, and recommending and implementing appropriate security solutions Monitoring and securing hybrid environments, including cloud, mobile, and IoT Operating with an awareness of applicable laws and policies, including principles of governance, risk, and compliance Identifying, analyzing, and responding to security events and incidents The Study Guide has been completely revised to align with the latest version of the exam objectives. The Practice Tests includes hundreds of domain-by-domain questions plus practice exams to test your knowledge of the topics. Receive one year of FREE access after activation to the Sybex online interactive learning environment, to help you prepare with superior study tools, hundreds of practice questions, and flashcards that allow you to gauge your readiness and avoid surprises on exam day. And save 10% when you purchase your CompTIA exam voucher with our exclusive WILEY10 coupon code.
Computer-Human Interaction Research and Applications
These 2 volumes constitute the selected papers of the 7th International Conference, CHIRA 2023, held Rome, Italy, during November 16-17, 2023.The 14 full papers and the 29 short papers presented in these books were carefully reviewed and selected from 69 submissions. The papers selected contribute to the advancement of research and practical applications of human-technology and human-computer interaction. Different aspects of Computer-Human Interaction were covered in four parallel tracks: human factors for interactive systems, research, and applications; interactive devices; interaction design; and adaptive and intelligent systems.
Computer-Human Interaction Research and Applications
These 2 volumes constitute the selected papers of the 7th International Conference, CHIRA 2023, held Rome, Italy, during November 16-17, 2023.The 14 full papers and the 29 short papers presented in these books were carefully reviewed and selected from 69 submissions. The papers selected contribute to the advancement of research and practical applications of human-technology and human-computer interaction. Different aspects of Computer-Human Interaction were covered in four parallel tracks: human factors for interactive systems, research, and applications; interactive devices; interaction design; and adaptive and intelligent systems.
Visualization of Time-Oriented Data
This is an open access book.Time is an exceptional dimension with high relevance in medicine, engineering, business, science, biography, history, planning, or project management. Understanding time-oriented data via visual representations enables us to learn from the past in order to predict, plan, and build the future. This second edition builds upon the great success of the first edition. It maintains a brief introduction to visualization and a review of historical time-oriented visual representations. At its core, the book develops a systematic view of the visualization of time-oriented data. Separate chapters discuss interaction techniques and computational methods for supporting the visual data analysis. Many examples and figures illustrate the introduced concepts and techniques. So, what is new for the second edition? First of all, the second edition is now published as an open-access book so that anyone interested in the visualization of time and time-oriented data can read it. Second, the entire content has been revised and expanded to represent state-of-the-art knowledge. The chapter on interaction support now includes advanced methods for interacting with visual representations of time-oriented data. The second edition also covers the topics of data quality as well as segmentation and labeling. The comprehensive survey of classic and contemporary visualization techniques now provides more than 150 self-contained descriptions accompanied by illustrations and corresponding references. A completely new chapter describes how the structured survey can be used for the guided selection of suitable visualization techniques. For the second edition, our TimeViz Browser, the digital pendant to the survey of visualization techniques, received a major upgrade. It includes the same set of techniques as the book, but comes with additional filter and search facilities allowing scientists and practitioners to find exactly the solutions they are interested in.
Developing Kaggle Notebooks
Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impactLeverage the power of Generative AI with Kaggle ModelsPurchase of the print or Kindle book includes a free PDF eBookKey Features: Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline modelsWork robustly with any type, modality, and size of data, be it tabular, text, image, video, or soundImprove the style and readability of your Notebooks, making them more impactful and compellingBook Description: Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this field and rise to the top in the Kaggle Notebooks tier. The book is structured as a seven-step data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.For each topic, we provide one or more Notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature introduced progressively, initially as part of a Notebook, and later extracted for use across future Notebooks to enhance code reusability on Kaggle. It aims to make the Notebooks' code more structured, easy to maintain, and readable.Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualification to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refine your model and prepare for a submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.What You Will Learn: Approach a dataset or competition to perform data analysis via a notebookLearn data ingestion and address issues arising with the ingested dataStructure your code using reusable componentsAnalyze in-depth both small and large datasets of various typesDistinguish yourself from the crowd with the content of your analysisEnhance your notebook style with a color scheme and other visual effectsCaptivate your audience with data and compelling storytelling techniquesWho this book is for: This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to: Beginners on Kaggle from any backgroundSeasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualizationExpert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankingsProfessionals who already use Kaggle for learning and competing
Waic and Wbic with Python Stan
Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include: A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!
Designing and Prototyping Interfaces with Figma - Second Edition
Explore the latest Figma features with this newly updated 2nd edition, including Variables and Conditional Prototyping. Learn cutting-edge design principles and create captivating interfaces with this full-color guide.Key FeaturesExplore Figma's latest features, including Variables and Conditional Prototyping, to create dynamic and responsive interfacesIntegrate AI capabilities and optimize your workflow with the latest Figma pluginsCreate engaging, interactive prototypes that captivate your users and stakeholdersPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAre you a UI/UX designer eager to learn the art of creating compelling interfaces using Figma? Look no further! The highly anticipated new edition is here to transform your creative journey.Explore Figma's latest features and delve into the power of variables and conditional Prototyping. Get ready to transform your static designs into dynamic, interactive prototypes, offering users and stakeholders an immersive experience. Stay at the forefront of design innovation with insights into integrating AI capabilities and optimizing your workflow with the latest Figma plugins. With user-centric design at its core, this book guides you through mastering design thinking, enabling you to tackle complex design challenges with ease. One unique aspect of this edition is its focus on effective communication. Learn how to convey your design vision clearly to both technical and non-technical audiences. In the rapidly changing world of UI/UX design, iteration is key. This book will teach you how to gather user feedback and iterate on your designs by creating interactive prototypes.Whether you're new to Figma or a seasoned pro, this comprehensive guide equips you with the skills to create captivating interfaces, fosters creativity and problem-solving, and makes you an indispensable, forward-thinking designer.What you will learnCreate high-quality designs that cater to your users' needs, providing an outstanding experienceMastering mobile-first design and responsive design conceptsIntegrate AI capabilities into your design workflow to boost productivity and explore design innovationCraft immersive prototypes with conditional prototyping and variablesCommunicate effectively to technical and non-technical audiencesDevelop creative solutions for complex design challengesGather and apply user feedback through interactive prototypesWho this book is forThis book is for aspiring UX/UI designers who want to get started with Figma as well as established designers who want to migrate to Figma from other design tools. This guide will provide you a walkthrough of the entire process of creating a full-fledged prototype for a responsive interface using all the tools and features that Figma has to offer. As a result, this book is suitable for both UX and UI designers, product and graphic designers, as well as anyone who wants to explore the complete design process from scratch.Table of ContentsExploring Figma and Transitioning from Other ToolsStructuring Moodboards, Personas, and User Flows within FigJamGetting to Know Your Design EnvironmentWireframing a Mobile-First Experience Using Vector ShapesDesigning Consistently Using Grids, Colors, and TypographyCreating a Responsive Mobile Interface Using Auto LayoutBuilding Components and Variants in a Collaborative WorkspaceUser Interface Design on Tablet, Desktop, and the WebPrototyping with Transitions, Smart Animate, and Interactive Components(N.B. Please use the Look Inside option to see further chapters)
Inductive Logic Programming
This book constitutes the refereed proceedings of the 32nd International Conference on Inductive Logic Programming, ILP 2023, held in Bari, Italy, during November 13-15, 2023.The 11 full papers and 1 short paper included in this book were carefully reviewed and selected from 18 submissions. They cover all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.
Introduction to Digital Humanism
This open access textbook introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights. The book is organized in three parts: Part I "Background" provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II "Digital Humanism - a System's View" focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III "Critical and Societal Issues of Digital Systems" delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy. This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency.
Introduction to Digital Humanism
This open access textbook introduces and defines digital humanism from a diverse range of disciplines. Following the 2019 Vienna Manifesto, the book calls for a digital humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights. The book is organized in three parts: Part I "Background" provides the multidisciplinary background needed to understand digital humanism in its philosophical, cultural, technological, historical, social, and economic dimensions. The goal is to present the necessary knowledge upon which an effective interdisciplinary discourse on digital humanism can be founded. Part II "Digital Humanism - a System's View" focuses on an in-depth presentation and discussion of the main digital humanism concerns arising in current digital systems. The goal of this part is to make readers aware and sensitive to these issues, including e.g. the control and autonomy of AI systems, privacy and security, and the role of governance. Part III "Critical and Societal Issues of Digital Systems" delves into critical societal issues raised by advances of digital technologies. While the public debate in the past has often focused on them separately, especially when they became visible through sensational events the aim here is to shed light on the entire landscape and show their interconnected relationships. This includes issues such as AI and ethics, fairness and bias, privacy and surveillance, platform power and democracy. This textbook is intended for students, teachers, and policy makers interested in digital humanism. It is designed for stand-alone and for complementary courses in computer science, or curricula in science, engineering, humanities and social sciences. Each chapter includes questions for students and an annotated reading list to dive deeper into the associated chapter material. The book aims to provide readers with as wide an exposure as possible to digital advances and their consequences for humanity. It includes constructive ideas and approaches that seek to ensure that our collective digital future is determined through human agency.
Microsoft 365 Administrator MS-102 Exam Guide
A comprehensive MS-102 exam guide offering practical insights, from provisioning Microsoft 365 to mastering Defender components, ensuring not just exam success but true expertisePurchase of the book unlocks access to web-based exam prep resources like mock exams, flashcards, exam tips, and a free eBook PDF.Key Features: Navigate exam topics easily with well-structured and informative contentAccess online practice tools to enhance exam readinessBoost exam confidence through expert tips and real-world insightsPurchase of the book unlocks access to web-based exam prep resources like mock exams, flashcards, exam tips, and a free eBook PDFBook Description: The MS-102: Microsoft 365 Administrator Exam Guide is meticulously crafted to empower readers with practical insights, starting with the essentials of provisioning a Microsoft 365 tenant, configuring identity synchronization and secure access, and deploying key Microsoft 365 Defender components.The book's purpose is clear-to guide professionals through the complexities of the MS-102 exam, ensuring not just exam success but mastery of the subject matter. This comprehensive exam guide comes with lifetime access to supplementary resources on an online platform, including flashcards, mock exams, and exam tips from experts. With unlimited access to the website, you'll have the flexibility to practice as many times as you desire, maximizing your exam readiness.As you progress through each chapter, the book unveils the layers of Microsoft 365 workloads, equipping you with the skills to manage role-based administration, deploy identity synchronization using Entra ID Connect, implement modern authentication methods, manage secure access through Conditional Access policies, and analyze security threats using Microsoft 365 Defender.By the end of this book, you'll have the proficiency to implement data loss prevention, configure information and data protection features, and approach the MS-102 exam with confidence.What You Will Learn: Implement and manage Microsoft 365 tenantsAdminister users, groups, and contacts in Entra IDConfigure and manage roles across Microsoft 365 servicesTroubleshoot identity synchronization issuesDeploy modern authentication methods to enhance securityAnalyze and respond to security incidents using Microsoft 365 DefenderImplement retention policies and sensitivity labelsEstablish data loss prevention for enhanced information protectionWho this book is for: If you're looking to validate your skills in planning, deploying, and managing Microsoft 365 identity and security workloads, this book is for you. Ideal for IT professionals seeking the MS-102 certification, this book ensures success with clear guidance, practical insights, and hands-on exercises. Although not a pre-requisite, prior knowledge of configuring DNS records, experience of administering a Microsoft 365 tenant, and a high-level understanding of information protection concepts will be beneficial.
Manifold Learning
This Open Access book reviews recent theoretical and numerical developments in nonlinear model order reduction in continuum mechanics, being addressed to Master and PhD students, as well as to researchers, lecturers and instructors. The aim of the authors is to provide tools for a better understanding and implement reduced order models by using: physics-based models, synthetic data forecast by these models, experimental data and deep learning algorithms. The book involves a survey of key methods of model order reduction applied to model-based engineering and digital twining, by learning linear or nonlinear latent spaces.Projection-based reduced order models are the projection of mechanical equations on a latent space that have been learnt from both synthetic data and experimental data. Various descriptions and representations of structured data for model reduction are presented in the applications and survey chapters. Image-based digital twins are developed in a reduced setting. Reduced order models of as-manufactured components predict the mechanical effects of shape variations. A similar workflow is extended to multiphysics or coupled problems, with high dimensional input fields. Practical techniques are proposed for data augmentation and also for hyper-reduction, which is a key point to speed up projection-based model order reduction of finite element models. The book gives access to python libraries available on gitlab.com, which have been developed as part of the research program [FUI-25] MORDICUS funded by the French government. Similarly to deep learning for computer vision, deep learning for model order reduction circumvents the need to design parametric problems prior reducing models. Such an approach is highly relevant for image-base modelling or multiphysics modelling.
Reinforcement Learning for Reconfigurable Intelligent Surfaces
This book presents the intersection of two dynamic fields: Reinforcement Learning (RL) and RIS- Assisted Wireless Communications. With an emphasis on both discrete and continuous problems, it introduces a comprehensive overview of RL techniques and their applications in the evolving world of RIS-assisted wireless communications. Chapter 1 introduces the fundamentals of RL and deep RL (DRL), providing a solid foundation for understanding subsequent chapters. It also presents the Q-learning, deep Q-learning, and deep deterministic policy gradient algorithms. Chapter 2 provides a holistic overview of RIS-assisted systems and details several use cases in wireless communications. Then, Chapters 3 and 4 present various applications of the discrete and continuous DRL to RIS-assisted wireless communications. From maximizing the sum-rate to minimizing, the system resources and maximizing the energy efficiency. These chapters showcase the versatility of the DRL algorithms in tackling arange of challenges. This book concludes with Chapter 5, which introduces the challenges and future directions in this field. It explores the particulars of hyperparameter tuning, problem design, and complexity analysis, while also highlighting the potential of hybrid DRL, multi-agent DRL, and transfer learning techniques for advancing wireless communication systems. Optimizing RIS-Assisted Wireless Systems requires powerful algorithms to cope with the dynamic propagation environment. DRL is envisioned as one of the key enabling techniques to exploit the full potential of RIS-Assisted Wireless Communication Systems. It empowers these systems to intelligently adapt to dynamic wireless environments, maximize performance metrics, and adjusts their configurations to accommodate diverse use cases efficiently. This book serves as a valuable resource, shedding light on the potential of DRL to optimize RIS-Assisted Wireless Communication, enabling researchers, engineers, advanced level students in computer science and electrical engineering and enthusiasts to grasp the intricacies of this topic. It offers a comprehensive understanding of the principles, applications, and challenges, making it a reference to recognize the full potential of the RIS technology in modern wireless communication systems.
Critical Theory of AI
We live in an age of artificial intelligence. Machines think and act in ever more complex ways, making suggestions and decisions on our behalf. While AI might be seen as practical and profitable, issues of data surveillance, algorithmic control, and sexist and racist bias persist. In this rapidly changing landscape, social analysis of AI risks getting scaled down to issues of 'ethics', 'responsibility', and 'fairness'. While these are important issues, they must be addressed not from an 'AI first' perspective, but more thoroughly in terms of power and contention. Approaching artificial intelligence from the often overlooked perspective of critical social theory, this book provides a much-needed intervention on how both old and new theories conceptualize the social consequences of AI. Questions are posed about the ideologies driving AI, the mythologies surrounding AI, and the complex relationship between AI and power. Simon Lindgren provides a way of defining AI as an object of social and political critique, and guides the reader through a set of contentious areas where AI and politics intersect. In relation to these topics, critical theories are drawn upon, both as an argument for and an illustration of how AI can be critiqued. Given the opportunities and challenges of AI, this book is a must-read for students and scholars in the humanities, social sciences, and STEM disciplines.
