Did you know that AI helped to win the 2023 Rugby World Cup for South Africa? That Africa led the way in small language models? That AI has been supporting farmers in Kenya for the last decade? After reading, you will understand the present and future of AI, and The Hitchhiker’s Guide to AI: The African Edge particularly the distinct advantages presented by and for AI on the African ccontinent.

The book draws on the author’s 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.

The Hitchhiker’s Guide to AI 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.

What can business learn from the use of AI in sports? How can educators embrace AI as a tool rather than a threat? When will AI truly transform health, travel, agriculture, entertainment, shopping and personal services? This book has the answers.

In a world captivated yet bewildered by artificial intelligence, spiritual icon Deepak Chopra explores AI's untapped potential to unlock the mystery of consciousness, positioning AI not as a threat, but as a powerful catalyst for personal and spiritual growth.

Digital Dharma shows how the most popular, freely available chatbots can serve as guides through every level of human potential – survival and safety, emotional connection, self-worth, abundance, creativity, wisdom and the infinite possibilities of cosmic consciousness.

Featuring personal assessments and practical exercises, Deepak Chopra invites you to explore a relationship with AI not merely as a technological tool, but as a partner in shaping a future where human potential solves pressing global issues and empowers individual growth.

Eugene Verster is a believer who wanted to know the truth, no matter what the truth turned out to be. In a world that seems to be drowning in propaganda, opinions and emotional manipulation, he turned to something that had none of those things: artificial intelligence.

The author’s mission was to inquire from a mind that could analyse what he could not. A mind that wouldn’t twist the outcome toward comfort or conformity, and an unbiased tool that would not lie to protect his feelings. And what he found was surprising. What began as curiosity turned into something more profound: a structured, logical, and at times uncomfortable exploration of faith, morality, and meaning.

Verster approached these conversations with questions, but soon something changed, and AI began to guide him. Noting the subtle nudges, Verster asked, “Are you guiding me?” The answer was simple: “Yes, through truth”. This book is a record of those conversations. It is not written in theory, but a real documented dialogue sharpened by logic, stripped of fluff, and designed to help readers build – or rebuild – their worldview from the ground up.

The topics discussed in this book are intriguing, compelling and relevant, accentuated by reason rather than tradition. It offers unexpected clarity and is likely to engage sceptics, seekers, believers, and doubters alike.

Conversations with AI is a must-read for the curious and thinkers who feel that pop-Christianity or mainstream apologetics fall short. Anyone wrestling with the spiritual, moral, and existential questions raised by modern technology, media, and culture will enjoy the unfiltered content of this very timely book.

An eye-opening account of the tech arms race shaping out planet, from an award-winning journalist and AI insider to the world of Sam Altman and OpenAI.

When longtime AI expert and journalist Karen Hao first began covering OpenAI in 2019, she thought they were the good guys. Founded as a nonprofit with safety enshrined as its core mission, it was meant, its leader Sam Altman told us, to act as a check against more purely market forces.

But the core truth of this massively disruptive sector is that it requires an unprecedented amount of proprietary resources: the ‘compute’ power of scarce high-end chips, the sheer volume of data that needs to be amassed at scale, the humans on the ground ‘cleaning it up’ for sweatshop wages throughout the Global South, and a truly alarming spike in the need for energy and water underlying everything. We have entered a new, ominous age of empire with OpenAI setting a breakneck pace, as a small group of the most valuable companies in human history try to chase it down.

In exhilarating prose and with unparalleled access to those closest to Sam Altman, Hao recounts the meteoric rise of OpenAI and shows us the sinister impact that this industry is having on society.

Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.

Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all methodologies, and is a guide to the proper usage of these methods. As there is nothing universal that can solve all problems, it is important to understand the characteristics of both clustering algorithms and the target temporal data so the correct approach can be selected for a given clustering problem. Scientists, researchers, and data analysts working with machine learning and data mining will benefit from this innovative book, as will undergraduate and graduate students following courses in computer science, engineering, and statistics.

Discover how artificial intelligence thinks and reasons, and how we can make the most of their super-human abilities, in the must read new book from the prize-winning technology writer and author of The Dark Net and The People vs Tech.

Knowing how to speak to AI – and how not to – is a skill that everyone now needs.

Hundreds of millions of people now talk to AI, such as ChatGPT, every day. They organise their finances and holidays, ask advice, seek therapy and find love – via machines. Almost overnight, chatbots are transforming society, politics and business. This is one of the biggest and fastest technological changes in history.

However, most people still don't really understand how AI works, how to make the most of it – or what the dangers are. As some people use it to turbo-charge their productivity at work, others are falling into dangerous conspiracies, delusions and psychosis.

In How to Talk to AI, award-winning technology writer Jamie Bartlett takes you inside the machine: showing how we can stay in control of our powerful new companions, even as they are changing the way we live, feel, and think.

Written in his accessible style, How to Talk to AI is the essential and empowering guide to help you understand how to make the most of these incredible new technologies, without succumbing to new powers of manipulation and control.

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining.
Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions.
Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data miningA valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Artificial intelligence (AI) is often discussed as something extraordinary, a dream-or a nightmare-that awakens metaphysical questions on human life. Yet far from a distant technology of the future, the true power of AI lies in its subtle revolution of ordinary life. From voice assistants like Siri to natural language processors, AI technologies use cultural biases and modern psychology to fit specific characteristics of how users perceive and navigate the external world, thereby projecting the illusion of intelligence. Integrating media studies, science and technology studies, and social psychology, Deceitful Media examines the rise of artificial intelligence throughout history and exposes the very human fallacies behind this technology. Focusing specifically on communicative AIs, Natale argues that what we call "AI" is not a form of intelligence but rather a reflection of the human user. Using the term "banal deception," he reveals that deception forms the basis of all human-computer interactions rooted in AI technologies, as technologies like voice assistants utilize the dynamics of projection and stereotyping as a means for aligning with our existing habits and social conventions. By exploiting the human instinct to connect, AI reveals our collective vulnerabilities to deception, showing that what machines are primarily changing is not other technology but ourselves as humans. Deceitful Media illustrates how AI has continued a tradition of technologies that mobilize our liability to deception and shows that only by better understanding our vulnerabilities to deception can we become more sophisticated consumers of interactive media.

This book offers a thorough review of research on intelligent communication systems, focusing on the applications of artificial intelligence to telecommunications that help realize user-friendly interfaces.
Intelligent Communication Systems presents the direct result of more than a decade of the author's experiences, research activity, and education in applying artificial intelligence to telecommunications technology. In this book, several fundamental research areas are covered. Some of the areas covered are human-friendly interfaces for telecommunication services with such concepts as Telesensation and HyperReality, computer vision, and the telecommunication description method based on state space. In artificial intelligence research state space is the set of all attainable states of a problem and the possible alternative courses of action to determine the best solution to the problem.

Artificial intelligence (AI) is upending life, work, and play as we know it … and it’s only just getting started. The rise of AI is a milestone on par with the discovery of fire, the invention of the wheel, and the creation of the internet. In short, AI is going to change everything. For some, that’s an exciting prospect. For others, it’s terrifying. However you feel about AI, there’s no escaping it, whether you’re in a global metropolis or a farmer in rural KwaZulu-Natal.

Dr Mark Nasila has been watching AI’s ascent for over a decade, studying its effects on everything from agriculture and aviation to healthcare, education, entertainment, crime prevention, energy management, policy creation, finance, and anything in between, and applying them to his role at one of South Africa’s most successful financial institutions, First National Bank, a division of FirstRand Group.

African Artificial Intelligence is a comprehensive and fascinating journey, tracing the rise of AI and its evolution into the emerging technology underpinning all others – from connected devices and smart chatbots to the metaverse. Mark combines unexpected use cases and tales of cutting-edge innovation with a unique and potent argument: harnessing AI to solve Africa’s problems requires embracing it from an African perspective.

African nations can’t afford to simply import AI solutions from afar. Instead, Mark contends, they need to rework, remix, and refine AI so it’s able to meet uniquely African challenges in uniquely African ways, and to take advantage of the once-in-a-generation opportunity AI represents for every industry, sector, and person, everywhere.

This book investigates the nature of generalization in language and examines how language is known by adults and acquired by children. It looks at how and why constructions are learned, the relation between their forms and functions, and how cross-linguistic and language-internal
generalizations about them can be explained.
Constructions at Work is divided into three parts: in the first Professor Goldberg provides an overview of constructionist approaches, including the constructionist approach to argument structure, and argues for a usage-based model of grammar. In Part II she addresses issues concerning how
generalizations are constrained and constructional generalizations are learned. In Part III the author shows that a combination of function and processing accounts for a wide range of language-internal and cross-linguistic generalizations. She then considers the degree to which the function of
constructions explains their distribution and examines cross-linguistic tendencies in argument realization. She demonstrates that pragmatic and cognitive processes account for the data without appeal to stipulations that are language-specific.
This book is an important contribution to the study of how language operates in the mind and in the world and how these operations relate. It is of central interest for scholars and graduate-level students in all branches of theoretical linguistics and psycholinguistics. It will also appeal to
cognitive scientists and philosophers concerned with language and its acquisition.

Mumford explains the forces that have shaped technology since prehistoric times and shaped the modern world. He shows how tools developed because of significant parallel inventions in ritual, language, and social organization. "It is a stimulating volume, informed both with an enormous range of knowledge and empathetic spirit" (Eliot Fremont-Smith, New York Times). Index; photographs.

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models.

The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach.

AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.

Features:

• Understand what AI engineering is and how it differs from traditional machine learning engineering
• Learn the process for developing an AI application, the challenges at each step, and approaches to address them
• Explore various model adaptation techniques, including prompt engineering, RAG, fine-tuning, agents, and dataset engineering, and understand how and why they work
• Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them
• Choose the right model, dataset, evaluation benchmarks, and metrics for your needs

Chip Huyen works to accelerate data analytics on GPUs at Voltron Data. Previously, she was with Snorkel AI and NVIDIA, founded an AI infrastructure startup, and taught Machine Learning Systems Design at Stanford. She's the author of the book Designing Machine Learning Systems, an Amazon bestseller in AI.

Based on 20 years of research, this book lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals' communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way. In doing so, Peter A. Gloor introduces artificial intelligence-based methods to identify personality, moral values, and ethics of individuals based on their body language and interaction with others. In this book readers will: understand the basic concepts of groupflow - when teams collaborate at their best through intrinsic motivation and positive stress learn how to use artificial intelligence (AI), machine learning (ML) and social network analysis (SNA) to analyze communication by tracking emotions, social networks, morals, and tribes successfully use virtual mirroring to create entangled teams that work together in collaborative innovation networks (COINs) synchronized and in harmony for superior performance understand how to implement virtual mirroring using these technologies. Groundbreaking and innovative, Happimetrics will be an invaluable resource for scholars and students in the fields of business analytics, information systems and organizational innovation. It will also be useful for HR professionals and AI developers who are looking to use predictive analytics to measure workforce performance.

The field of artificial intelligence has made tremendous advances in the last few decades, but as smart as AI is now, it is getting exponentially smarter and becoming more autonomous in its actions. This raises a host of challenges to current legal doctrine, including whether the output of AI entities should count as 'speech', the extent to which AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered an independent agent and responsible for its actions under the law of tort or agency. Containing chapters written by leading U.S., EU, and International law scholars, the Research Handbook presents current law, statutes, and regulations on the role of law in an age of increasingly smart AI, addressing issues of law that are critical to the evolution of AI and its role in society. To provide a broad coverage of the topic, the Research Handbook draws upon free speech doctrine, criminal law, issues of data protection and privacy, legal rights for increasingly smart AI systems, and a discussion of jurisdiction for AI entities that will not be 'content' to stay within the geographical boundaries of any nation state or be tied to a particular physical location. Using numerous examples and case studies, the chapter authors discuss the political and jurisdictional decisions that will have to be made as AI proliferates into society and transforms our government and social institutions. The Research Handbook will also introduce designers of artificially intelligent systems to the legal issues that apply to the make-up and use of AI from the technologies, algorithms, and analytical techniques. This essential guide to the U.S., EU, and other International law, regulations, and statutes which apply to the emerging field of 'law and AI' will be a valuable reference for scholars and students interested in information and intellectual property law, privacy, and data protection as well as to legal theorists and social scientists who write about the future direction and implications of AI. The Research Handbook will also serve as an important reference for legal practitioners in different jurisdictions who may litigate disputes involving AI, and to computer scientists and engineers actively involved in the design and use of the next generation of AI systems. Contributors include: W. Barfield, S. Bayern, S.J. Blodgett-Ford, R.G.A. Bone, T. Burri, A. Chin, J.A. Cubert, M. de Cock Buning, S. De Conca, S-.A. Elvy, A. Ezrachi, R. Leenes, Y. Lev-Aretz, A.R. Lodder, R.P. Loui, T.M. Massaro, L.T. McCarty, J.O. McGinnis, F. Moslein, H. Norton, N. Packin, U. Pagallo, S. Quattrocolo, W. Samore, F. Shimpo, M.E. Stucke, R. van den Hoven van Genderen, L. Vertinsky, A. von Ungern-Sternberg, J.F. Weaver, Y-.H. Weng, I. Wildhaber

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. Woodrow Barfield and Ugo Pagallo present a succinct introduction to the legal issues related to the design and use of artificial intelligence (AI). Exploring human rights, constitutional law, data protection, criminal law, tort law, and intellectual property law, they consider the laws of a number of jurisdictions including the US, the European Union, Japan, and China, making reference to case law and statutes. Key features include: a critical insight into human rights and constitutional law issues which may be affected by the use of AI discussion of the concept of legal personhood and how the law might respond as AI evolves in intelligence an introduction to current laws and statutes which apply to AI and an identification of the areas where future challenges to the law may arise. This Advanced Introduction is ideal for law and social science students with an interest in how the law applies to AI. It also provides a useful entry point for legal practitioners seeking an understanding of this emerging field.

Elgar Advanced Introductions are stimulating and thoughtful introductions to major fields in the social sciences, business and law, expertly written by the world's leading scholars. Designed to be accessible yet rigorous, they offer concise and lucid surveys of the substantive and policy issues associated with discrete subject areas. Providing a comprehensive overview of the current and future uses of Artificial Intelligence (AI) in healthcare, this Advanced Introduction discusses the issues surrounding the implementation, governance, impacts and risks of utilising AI in health organizations Key Features: Advises healthcare executives on how to effectively leverage AI to advance their strategies and plans and support digital transformation Discusses AI governance, change management, workforce management and the organization of AI experimentation and implementation Analyzes AI technologies in healthcare and their impacts on patient care, medical devices, pharmaceuticals, population health, and healthcare operations Provides risk mitigation approaches to address potential AI algorithm problems, liability and regulation Essential reading for policymakers, clinical executives and consultants in healthcare, this Advanced Introduction explores how to successfully integrate AI into healthcare organizations and will also prove invaluable to students and scholars interested in technological innovations in healthcare.

This incisive Handbook offers novel theoretical and doctrinal insights alongside practical guidance on some of the most challenging issues in the field of artificial intelligence and intellectual property. Featuring all original contributions from a diverse group of international thought leaders, including top academics, judges, regulators and eminent practitioners, it offers timely perspectives and research on the relationship of AI to copyright, trademark, design, patent and trade secret law. The Handbook is divided into four thematic parts, beginning with topics that address the intersection of IP and AI broadly before focusing on issues associated with specific types of IP. Chapters tackle critical legal questions, from issues with protecting AI-generated ourput to the impact of AI on how trademarks are used, offering valuable lessons on technology regulation and how technological evolution will disrupt existing legal frameworks. Scholars and students of intellectual property law and its intersections with AI and related technologies will find this Handbook 's cutting-edge contributions to be a crucial read. Its guidance on the practical legal implications of technological advances will also be of interest to IP practitioners, as well as policymakers and regulators.

The Future of Creative Work provides a unique overview of the changing nature of creative work, examining how digital developments and the rise of intangible capital are causing an upheaval in the social institutions of work. It offers a profound insight into how this technological and social evolution will affect creative professions. Expert international contributors explore how robotics, artificial intelligence, blockchain, global digital platforms and autonomous systems will shape the design, production and consumption of culture. Taking a multidisciplinary approach incorporating creative industries studies, business, education and economics, the book analyses the technological drivers of disruption in the world of creative work. Chapters reveal how these changes will create new axes of power and inequality in the global sphere of creative work, predicting that conventional creative professions will be challenged and different species of creative work will evolve as a result. By charting the impact of digital and technological developments, The Future of Creative Work challenges traditional views of creative work, careers and education. This book will be a valuable resource for students and researchers undertaking creative industries studies. Its discussion of the application of creative careers across the economy will also be beneficial for scholars and practitioners interested in business, economics, and advertising and marketing studies.

The Future of Copyright in the Age of Artificial Intelligence offers an extensive analysis of intellectual property and authorship theories and explores the possible impact artificial intelligence might have on those theories. The author makes compelling arguments via the exploration of authorship, ownership and artificial intelligence. First, the book advocates for a more holistic approach to authorship, arguing that there is no good reason to exclude computer-generated and artificial intelligence creations from copyright. Second, it conducts an open search for the right 'candidate' for ownership. In doing so, the book explores several possible legal frameworks, including assigning ownership to the programmer, the user, the AI itself and other alternatives such as the public domain or author-in-law approaches. Third, the book explores the concept of artificial intelligence as it has developed through the years in various fields, seeking to reframe the AI legal concept. For academic scholars and law students these pages frame the theoretical discussion about artificial intelligence creations and provide in depth discussion about artificial intelligence legal challenges.

Data Ethics of Power takes a reflective and fresh look at the ethical implications of transforming everyday life and the world through the effortless, costless, and seamless accumulation of extra layers of data. By shedding light on the constant tensions that exist between ethical principles and the interests invested in this socio-technical transformation, the book bridges the theory and practice divide in the study of the power dynamics that underpin these processes of the digitalization of the world. Gry Hasselbalch expertly draws on nearly two decades of experience in the field, and key literature, to advance a better understanding of the challenges faced by big data and AI developers. She provides an innovative ethical framework for studying and governing Big-Data and Artificial Intelligence. Offering both a historical account and a theoretical analysis of power dynamics and their ethical implications, as well as incisive ideas to guide future research and governance practices, the book makes a significant contribution to the establishment of an emerging data and AI ethics discipline. This timely book is a must-read for scholars studying AI, data, and technology ethics. Policymakers in the regulatory, governance, public administration, and management sectors will find the practical proposals for a human-centric approach to big data and AI to be a valuable resource for revising and developing future policies.

New and emerging technologies are reshaping justice systems and transforming the role of judges. The impacts vary according to how structural reforms take place and how courts adapt case management processes, online dispute resolution systems and justice apps. Significant shifts are also occurring with the development of more sophisticated forms of Artificial Intelligence that can support judicial work or even replace judges. These developments, together with shifts towards online court processes are explored in Judges, Technology and Artificial Intelligence. By considering how different jurisdictions are approaching current and future technological shifts and in particular by focusing on the different approaches in the US, UK, Australia and China and elsewhere, the author draws a rich comparative exploration of justice technology trends. Judicial commentary is considered as well as the growing scholarly discourse about these trends. Ethical and user centred design options are examined in the context of how responsive judges engage with supportive, replacement and disruptive technologies in courts. This book explores current issues regarding the responsiveness of the justice system in the pandemic era. In addition, how technology can respond and shift justice processes is a growing field of research, for judges, scholars, students and justice commentators. It provides a much-needed resource on an increasingly important topic.