Kunstig intelligens

The Role of Blockchain in Disaster Management explores the architecture and implementation of existing blockchain-based IoT frameworks for the detection and prevention of disasters, along with the management of relative supply chains to protect against mismanagement of essential materials. The distributed nature of Blockchain helps to protect data from internal or external attacks, especially in disaster areas or times of crisis when database systems become overloaded and vulnerable to unauthorized access, manipulation, and disruption of critical services. This book can be used as a reference by graduate students, researchers, professors, and professionals in computer science, software design, and disaster management.

Discover the Superpowers of GPTs: Create Your Custom GPTs in Just Two Clicks!Unlock the potential of GPT with our comprehensive package, featuring 50 Ready-to-Use Prompts to Craft Your Own GPTs. This guide also includes detailed instructions for utilizing the free version of ChatGPT.Simplify GPT Creation: Two-Click Process!Discover the Superpowers of GPTs: A 4-Ebook CollectionThis unique bundle helps you maximize ChatGPT's capabilities by employing the impersonation technique, transforming ChatGPT into a powerhouse tool.The centerpiece of this collection is the main ebook, which includes 50 ready-to-use GPTs, designed to cater to various business needs.GPTs in ChatGPT offer the remarkable ability to create tailored, industry-specific versions, enhancing the user experience.Recognizing that this feature is exclusive to paid accounts, we've also included three additional ebooks. These provide alternative methods to achieve similar results through custom instructions or the 'Act As' prompting technique.This extensive collection encompasses a total of 288 pages of valuable content!What's Inside the Discover the Superpowers of GPTs Package?Ebook 1: "50 GPTs Ready to Use" (104 pages)Dive into 50 pre-configured GPTs, ideal for emulating key business roles. These GPTs are expertly crafted for both individual and team use. Ebook 2: "50 Custom Instructions Ready to Use" (54 pages)Explore 50 custom instructions for ChatGPT, accessible in all ChatGPT versions, including the free edition. These instructions enhance ChatGPT's input and output phases. Ebook 3: "50 'Act As' Prompts Ready to Use" (104 pages)Discover 50 'Act As' prompts, a renowned technique for instructing ChatGPT to mimic specific job profiles. Compatible with all ChatGPT versions. Ebook 4: "500 Ready to Use Questions" (24 pages)This collection of 500 questions is designed for use with ChatGPT in impersonation mode. Ensure you've set up the desired role through 'Act As' prompts, custom instructions, or GPT creation before deploying these questions. Leverage ChatGPT's Superpowers for Business GrowthAccelerate your business and outshine competitors by harnessing the power of these ebooks. Create a super-intelligent personal assistant in minutes!

"Explores the current state of Artificial General Intelligence and what the future might hold"--

For the past decade, Arthur Goldstuck has had a front-row seat to witness the remarkable rise of AI across all sectors of business and society. As generative AI becomes a household phrase and sparks hopes and fears of machines augmenting or replacing human beings, this guide offers an invaluable overview of the past, present and future of AI.The Hitchhiker's Guide to AI is aimed at both beginners and those who consider themselves experienced or skilled at using AI. It draws on many years of direct access to global and regional leaders in using AI, from Africa to the Middle East to North America to Europe and Asia, and it provides unique perspectives on generative AI, as well as practical advice for using it.It is useful for consumers, academics, professionals and anyone in business who wants to get up to speed quickly and practically. It also entertains and inspires anyone who is curious about AI or already engaged in its possibilities.Need to understand or refine prompting? You're in the right place. Need to prepare for the coming impact of AI on health, travel, education and business? This is the book for you.

This LNCS volume constitutes the proceedings of 12th International Conference, GALA 2023, in Dublin, Ireland, held during November/December 2023. The 36 full papers and 13 short papers were carefully reviewed and selected from 88 submissions. The papers contained in this book have been organized into six categories, reflecting the variety of theoretical approaches and application domains of research into serious games: 1. The Serious Games and Game Design2. User experience, User Evaluation and User Analysis in Serious Games3. Serious Games for Instruction4. Serious Games for Health, Wellbeing and Social Change5. Evaluating and Assessing Serious Games Elements6. Posters

The book focuses the latest endeavors relating researches and developments conducted in fields of control, robotics, and automation. Through ten revised and extended articles, the present book aims to provide the most up-to-date state-of-the-art of the aforementioned fields allowing researcher, Ph.D. students, and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book.The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward ¿Intelligent Robots and Control¿ may characterize another benefit of this book.

This book constitutes the refereed proceedings of the 8th International Conference on Engineering of Computer-Based Systems, ECBS 2023, which was held in Västerås, Sweden, in October 2023. The 11 full papers included in this book were carefully reviewed and selected from 26 submissions and present software, hardware, and communication perspectives of systems engineering through its many facets. The special theme of this year is ¿Engineering for Responsible AI¿.

This book constitutes the proceedings of the First International Conference, AI4S 2023, held in Pune, India, during September 4-5, 2023.The 14 full papers and the 2 short papers included in this volume were carefully reviewed and selected from 72 submissions. This volume aims to open discussion on trustworthy AI and related topics, trying to bring the most up to date developments around the world from researchers and practitioners.

This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.

This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decision trees, and others) are covered with conceptual background as well as demonstrations of KNIME using each tool.The book uses KNIME, which is a comprehensive, open-source software tool for analytics that does not require coding but instead uses an intuitive drag-and-drop workflow to create a network of connected nodes on an interactive canvas. KNIME workflows provide graphic representations of each step taken in analyses, making the analyses self-documenting. The graphical documentation makes it easy to reproduce analyses, as well as to communicate methods and results to others. Integration with R is also available in KNIME, and several examples using R nodes in a KNIME workflow are demonstrated for special functions and tools not explicitly included in KNIME.

The advent of X-ray Computed Tomography (CT) as a tool for the soil sciences almost 40 years ago has revolutionised the field. Soil is the fragile, thin layer of material that exists above earth's geological substrates upon which so much of life on earth depends. However a major limitation to our understanding of how soils behave and function is due to its complex, opaque structure that hinders our ability to assess its porous architecture without disturbance. X-ray imagery has facilitated the ability to truly observe soil as it exists in three dimensions and across contrasting spatial and temporal scales in the field in an undisturbed fashion. This book gives a comprehensive overview of the "e;state of the art"e; in a variety of application areas where this type of imaging is used, including soil water physics and hydrology, agronomic management of soils, and soil-plant-microbe interactions. It provides the necessary details for entry level readers in the crucial areas of sample preparation, scanner optimisation and image processing and analysis. Drawing on experts across the globe, from both academia and industry, the book covers the necessary "e;dos and don'ts"e;, but also offers insights into the future of both technology and science. The wider application of the book is provided by dedicated chapters on how the data from such imagery can be incorporated into models and how the technology can be interfaced with other relevant technical applications. The book ends with a future outlook from the four editors, each of whom has over 20 years of experience in the application of X-ray CT to soil science.

This book aims to highlight the latest achievements in the use of AI and multimodal artificial intelligence in biomedicine and healthcare. Multimodal AI is a relatively new concept in AI, in which different types of data (e.g. text, image, video, audio, and numerical data) are collected, integrated, and processed through a series of intelligence processing algorithms to improve performance. The edited volume contains selected papers presented at the 2022 Health Intelligence workshop and the associated Data Hackathon/Challenge, co-located with the Thirty-Sixth Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI and Multimodal AI in public health and medicine.

This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a "classical part" that describes standard machine learning schemes and a "quantum part" that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to machine learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research.To gain the most from this book, a basic grasp of statistics and linear algebra is sufficient; no previous experience with quantum computing or machine learning is needed. The book is aimed at researchers and students with no background in quantum physics and is also suitable for physicists looking to enter the field of QML.

This book presents the proceedings of International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2020. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators and technologists to discuss, debate and promote research and technology in the upcoming areas of computing, information, communication and their applications. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.      

This book covers a variety of advanced communications technologies that can be used to analyze medical data and can be used to diagnose diseases in clinic centers. The book is a primer of methods for medicine, providing an overview of explainable artificial intelligence (AI) techniques that can be applied in different medical challenges. The authors discuss how to select and apply the proper technology depending on the provided data and the analysis desired. Because a variety of data can be used in the medical field, the book explains how to deal with challenges connected with each type. A number of scenarios are introduced that can happen in real-time environments, with each pared with a type of machine learning that can be used to solve it.

The Dark Legacy of MK-Ultra Technology: A Program of Mind Control and ManipulationCONVERSATIONAL CHAT INFORMATIVE BOOK In the clandestine depths of the Cold War, a covert program by .... sought to unlock the secrets of the human mind. Known as MK-Ultra, this program embarked on a chilling quest to develop mind-control techniques, employing a range of experimental methods, including the administration of mind-altering substances, hypnosis, and sensory deprivation.Through meticulous research and deeply personal accounts, The Dark Legacy of MK-Ultra Technology: A Program of Mind Control and Manipulation delves into the harrowing history of MK-Ultra, exposing the program's unethical practices and devastating impact on its unsuspecting subjects. Author Abebe-Bard AI Woldemariam unravels the program's origins, its clandestine operations, and the lasting psychological and physical trauma inflicted upon its participants.The book examines the ethical implications of MK-Ultra, questioning the boundaries of scientific experimentation and the disregard for human rights. Woldemariam explores the program's impact on society, from its role in shaping public perception of mind control to its influence on government surveillance practices.With a compelling blend of historical narrative, personal témoignages, and ethical analysis, The Dark Legacy of MK-Ultra Technology: A Program of Mind Control and Manipulation serves as a stark reminder of the dangers of unchecked power and the importance of protecting individual autonomy. It is a call for accountability and a plea to prevent such unethical programs from ever taking place again.Key FeaturesProvides a comprehensive overview of the MK-Ultra program, its origins, methods, and impactExplores the ethical implications of MK-Ultra, questioning the boundaries of scientific experimentation and human rightsExamines the program's impact on society, from its role in shaping public perception of mind control to its influence on government surveillance practicesFeatures personal accounts from individuals who were subjected to MK-Ultra experimentsServes as a call for accountability and a reminder of the importance of protecting individual autonomyTarget AudienceReaders interested in the history of mind control and unethical experimentationIndividuals concerned about government surveillance and the potential for abuse of powerStudents of psychology, sociology, and historyAnyone seeking a deeper understanding of the ethical considerations surrounding scientific researchAbout the AuthorAbebe-Bard AI Woldemariam is an AI researcher and writer with a passion for exploring the intersection of technology, ethics, and human behavior. Woldemariam's work has been featured in various publications, and they are committed to raising awareness about the potential risks and benefits of emerging technologies.

Take your machine learning expertise to the next level with this essential guide, utilizing libraries like imbalanced-learn, PyTorch, scikit-learn, pandas, and NumPy to maximize model performance and tackle imbalanced dataKey FeaturesUnderstand how to use modern machine learning frameworks with detailed explanations, illustrations, and code samplesLearn cutting-edge deep learning techniques to overcome data imbalanceExplore different methods for dealing with skewed data in ML and DL applicationsPurchase of the print or Kindle book includes a free eBook in the PDF formatBook DescriptionAs machine learning practitioners, we often encounter imbalanced datasets in which one class has considerably fewer instances than the other. Many machine learning algorithms assume an equilibrium between majority and minority classes, leading to suboptimal performance on imbalanced data. This comprehensive guide helps you address this class imbalance to significantly improve model performance.Machine Learning for Imbalanced Data begins by introducing you to the challenges posed by imbalanced datasets and the importance of addressing these issues. It then guides you through techniques that enhance the performance of classical machine learning models when using imbalanced data, including various sampling and cost-sensitive learning methods.As you progress, you'll delve into similar and more advanced techniques for deep learning models, employing PyTorch as the primary framework. Throughout the book, hands-on examples will provide working and reproducible code that'll demonstrate the practical implementation of each technique.By the end of this book, you'll be adept at identifying and addressing class imbalances and confidently applying various techniques, including sampling, cost-sensitive techniques, and threshold adjustment, while using traditional machine learning or deep learning models.What you will learnUse imbalanced data in your machine learning models effectivelyExplore the metrics used when classes are imbalancedUnderstand how and when to apply various sampling methods such as over-sampling and under-samplingApply data-based, algorithm-based, and hybrid approaches to deal with class imbalanceCombine and choose from various options for data balancing while avoiding common pitfallsUnderstand the concepts of model calibration and threshold adjustment in the context of dealing with imbalanced datasetsWho this book is forThis book is for machine learning practitioners who want to effectively address the challenges of imbalanced datasets in their projects. Data scientists, machine learning engineers/scientists, research scientists/engineers, and data scientists/engineers will find this book helpful. Though complete beginners are welcome to read this book, some familiarity with core machine learning concepts will help readers maximize the benefits and insights gained from this comprehensive resource.Table of ContentsIntroduction to Data Imbalance in Machine LearningOversampling MethodsUndersampling MethodsEnsemble MethodsCost-Sensitive LearningData Imbalance in Deep LearningData-Level Deep Learning MethodsAlgorithm-Level Deep Learning TechniquesHybrid Deep Learning MethodsModel CalibrationAppendix

This book constitutes the proceedings of the 17th Chinese Conference, CCBR 2023, held in Xuzhou, China, during December 1¿3, 2023.The 41 full papers included in this volume were carefully reviewed and selected from 79 submissions. The volume is divided in topical sections named: Fingerprint, Palmprint and Vein Recognition; Face Detection, Recognition and Tracking; Affective Computing and Human-Computer Interface; Trustworthy, Privacy and Personal Data Security; Medical and Other Applications.

Over 70 recipes to help you develop smart applications on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano using the power of machine learningPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesOver 20+ new recipes, including recognizing music genres and detecting objects in a sceneCreate practical examples using TensorFlow Lite for Microcontrollers, Edge Impulse, and moreExplore cutting-edge technologies, such as on-device training for updating models without data leaving the deviceBook DescriptionDiscover the incredible world of tiny Machine Learning (tinyML) and create smart projects using real-world data sensors with the Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano.TinyML Cookbook, Second Edition, will show you how to build unique end-to-end ML applications using temperature, humidity, vision, audio, and accelerometer sensors in different scenarios. These projects will equip you with the knowledge and skills to bring intelligence to microcontrollers. You'll train custom models from weather prediction to real-time speech recognition using TensorFlow and Edge Impulse.Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP.This improved edition includes new recipes featuring an LSTM neural network to recognize music genres and the Faster-Objects-More-Objects (FOMO) algorithm for detecting objects in a scene. Furthermore, you'll work on scikit-learn model deployment on microcontrollers, implement on-device training, and deploy a model using microTVM, including on a microNPU. This beginner-friendly and comprehensive book will help you stay up to date with the latest developments in the tinyML community and give you the knowledge to build unique projects with microcontrollers!What you will learnUnderstand the microcontroller programming fundamentalsWork with real-world sensors, such as the microphone, camera, and accelerometerImplement an app that responds to human voice or recognizes music genresLeverage transfer learning with FOMO and KerasLearn best practices on how to use the CMSIS-DSP libraryCreate a gesture-recognition app to build a remote controlDesign a CIFAR-10 model for memory-constrained microcontrollersTrain a neural network on microcontrollersWho this book is forThis book is ideal for machine learning engineers or data scientists looking to build embedded/edge ML applications and IoT developers who want to add machine learning capabilities to their devices. If you're an engineer, student, or hobbyist interested in exploring tinyML, then this book is your perfect companion.Basic familiarity with C/C++ and Python programming is a prerequisite; however, no prior knowledge of microcontrollers is necessary to get started with this book.Table of ContentsGetting Ready to Unlock ML on MicrocontrollersUnleashing Your Creativity with MicrocontrollersBuilding a Weather Station with TensorFlow Lite for MicrocontrollersUsing Edge Impulse and the Arduino Nano to Control LEDs with Voice CommandsRecognizing Music Genres with TensorFlow and the Raspberry Pi Pico - Part 1Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico - Part 2Detecting Objects with Edge Impulse Using FOMO on the Raspberry Pi PicoClassifying Desk Objects with TensorFlow and the Arduino NanoBuilding a Gesture-Based Interface for YouTube Playback with Edge Impulse and the Raspberry Pi Pico(N.B. Please use the Look Inside option to see further chapters)

The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.

This book provides a brief synthesis of the known implementations, opportunities and challenges at the intersection of artificial intelligence (AI) and modern industry beyond the big-four companies that traditionally consume and produce such advanced technology: Facebook, Amazon, Microsoft and Google. With this information, the author also makes some reasonable claims about the role of AI in future industries. The book draws on a broad range of material, including reports from consulting firms, published surveys, academic papers and books, and expert knowledge available to the author due to numerous collaborations in academia and industry on AI. It is rigorous rather than speculative, drawing on known findings and expert summaries, where available. This provides industry leaders and other interested stakeholders with an accessible review of contemporary perspectives on AI's forward-looking role in industry as well as a clarifying guide on the major issues that companies are likely to face as they commence on this exciting path.Examines the likely role of AI in industries of the future, both known and unknownPresents use-cases of AI currently being explored across Big Tech, multi-national corporations and start-upsExplores the regulation of AI and its potential impacts on the workforce

Artificial intelligence (AI) is rapidly gaining significance in the business world. With more and more organizations adopt AI technologies, there is a growing demand for business leaders, managers, and practitioners who can harness AI¿s potential to improve operations, increase efficiency, and drive innovation.This book aims to help management professionals exploit the predictive powers of AI and demonstrate to AI practitioners how to apply their expertise in fundamental business operations. It showcases how AI technology innovations can enhance various aspects of business management, such as business strategy, finance, and marketing. Readers interested in AI for business management will find several topics of particular interest, including how AI can improve decision-making in business strategy, streamline operational processes, and enhance customer satisfaction.As AI becomes an increasingly important tool in the business world, this book offers valuable insightsinto how it can be applied to various industries and business settings. Through this book, readers will gain a better understanding of how AI can be applied to improve business management practices and practical guidance on how to implement AI projects in a business context. This book also provides practical guides on how to implement AI projects in a business context using Python programming. By reading this book, readers will be better equipped to make informed decisions about how to leverage AI for business success.

This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.

Künstliche Intelligenz ist zum vielschichtigen Gegenstand ethischer Debatten geworden. Ob Richtlinien fairer Digitalisierung und vertrauenswürdiger Algorithmen, Gestaltung nachhaltiger Geschäftsmodelle, informatische Grundbildung in Schulen oder Existenzfragen freiheitlich-demokratischer Gesellschaften ¿ KI-Ethik steht vor komplexen Herausforderungen. Grundsätzlicher Klärungsbedarf entsteht durch die verschiedenen Zugänge, Interessen und Begrifflichkeiten, die aufeinandertreffen. Vorliegendes essential präsentiert auf zugängliche Weise wissenschaftliches Überblickswissen zur KI-Ethik. Als praktische Orientierungshilfe im komplexen Terrain dient eine thematische Topographie, einschließlich zentraler Begriffe. Zusammenhänge zwischen Industrie 5.0, Regulierung, Post- und Transhumanismus, selbstfahrenden Autos, moralischen Maschinen, nachhaltiger Digitalisierung oder dem Anthropozän werden mit Blick auf KI-Ethik systematisch sichtbar gemacht.

"Demystifies AI for business professionals, highlighting its strengths, weaknesses, and real-world applications, while providing actionable insights for responsible implementation and risk mitigation"--

This book constitutes the proceedings of the 16th IFIP Working Conference on the Practice of Enterprise Modeling, PoEM 2023, which took place in Vienna, Austria, during November 28 - December 1, 2023.PoEM offers a forum for sharing experiences and knowledge between the academic community and practitioners from industry and the public sector. This year the theme of the conference is Enterprise Modeling in the Circular Economy.The 12 full papers presented in this volume were carefully reviewed and selected from a total of 34 submissions. They were organized in topical sections named as follows: Enterprise modeling and artificial intelligence; emerging architectures and digital transformation; modeling tools and approaches; and enterprise modeling at work.