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.

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.

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.

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.

Creativity in Computing and DataFlow Supercomputing, the latest release in the Advances in Computers series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore topics in greater depth and breadth than journal articles typically allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained.

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.

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.

Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is "Disciple," a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.

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.

Over the last 20 years, the role of unmanned aircraft systems in modern warfare has grown at an unprecedented rate. No longer simply used for intelligence, data collection or reconnaissance, drones are routinely used for target acquisition and to strike enemy targets with missiles and bombs. Organized by nationality, Military Drones offers a compact guide to the main unmanned aerial vehicles being flown in combat zones today. These include classics, such as the MQ-1 Predator, primarily used for intelligence gathering; the Black Hornet Nano, a micro UAV that is so small it can fit in the palm of your hand and is used by ground troops for local situational awareness; the Chinese tri-copter Scorpion, which is ideal for the stationary observation and strike role in a built-up area; and the French EADS Talarion, a twinjet long-endurance UAV designed for high-altitude surveillance. Illustrated with more than 100 photographs and artworks, Military Drones provides a detailed insight into the specialist military unmanned aerial vehicles that play a key role in the modern battle space.

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

Special Forces are a key component of every modern army, capable of carrying out clandestine operations, reconnaissance, and incisive attacks behind enemy lines. Units such as the British SAS, US Navy SEALs, the US Army’s Delta Force, Polish GROM and the France’s National Gendarmerie Intervention Group are famous for their bravery and formidable record. Aircraft are a key element of their functionality, without which Special Forces would not be able to move quickly to the combat zone. Arranged into chapters divided by transports, gunships, helicopters, and unmanned aerial vehicles, the book includes the AC-130H gunship, which can be armed with weapons such as the M61 Vulcan rotary cannon and can destroy ground targets from a range of 2,000 metres; the CV-22 Osprey tiltrotor aircraft, which can land large numbers of men and material in tight spaces because of its STOL capabilities; the Eurocopter AS365 Dauphin II, used by the British Joint Special Forces Aviation Wing (JSFAW) for the insertion of small units behind enemy lines; and the Mil Mi- 171Sh Storm rotorcraft, used by the Russian Spetsnaz commandos for operations in difficult terrain. Illustrated with 140 photographs and artworks, Aircraft of the Special Forces is a dynamic guide to the specialist aircraft and UAVs deployed by Special Forces throughout the world today.

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.

Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up!

In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks.

Build a Large Language Model (from Scratch) teaches you how to:

• Plan and code all the parts of an LLM
• Prepare a dataset suitable for LLM training
• Fine-tune LLMs for text classification and with your own data
• Use human feedback to ensure your LLM follows instructions
• Load pretrained weights into an LLM

Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant.

This timely book provides an extensive overview and analysis of the law and regulation as it applies to the technology and uses of Artificial Intelligence (AI). It examines the human and ethical concerns associated with the technology, the history of AI and AI in commercial contexts. Written by outstanding lawyers, technologists and other professionals, this book will help readers acquire an understanding of the taxonomy of AI, the legal rules that apply to AI and the way AI has been utilised in various commercial contexts. Key features include: explanation of the technology and practical legal issues relating to the use of AI exploration of AI in the traditional legal categories; including contract and tort law chapters written by procurement, legaltech, algorithm auditing and other professionals use cases from the main industries utilising the technology, such as financial services, real estate and insurance. Artificial Intelligence will help to further readers' engagement with AI and enable them to ask themselves the right questions while doing so. It will prove a crucial reference point for all lawyers, policy makers and academics with an interest in the interaction between law and AI, and to any lawyer with clients that use or consider using AI in their business.