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| artificial intelligence basics a non-technical introduction: Artificial Intelligence Basics Tom Taulli, 2019-08-01 Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, andfuture impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing) Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch Fix Understand how AI capabilities for robots can improve business Deploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer service Avoid costly gotchas Recognize ethical concerns and other risk factors of using artificial intelligence Examine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions. |
| artificial intelligence basics a non-technical introduction: Artificial intelligence basics Tom Taulli, 2019 |
| artificial intelligence basics a non-technical introduction: AI for People and Business Alex Castrounis, 2019-07-05 If you're an executive, manager, or anyone interested in leveraging AI within your organization, this is your guide. You'll understand exactly what AI is, learn how to identify AI opportunities, and develop and execute a successful AI vision and strategy. Alex Castrounis,founder and CEO of Why of AI, Northwestern University Adjunct, advisor, and former IndyCar engineer and data scientist, examines the value of AI and shows you how to develop an AI vision and strategy that benefits both people and business. AI is exciting, powerful, and game changing--but too many AI initiatives end in failure. With this book, you'll explore the risks, considerations, trade-offs, and constraints for pursuing an AI initiative. You'll learn how to create better human experiences and greater business success through winning AI solutions and human-centered products. Use the book's AIPB Framework to conduct end-to-end, goal-driven innovation and value creation with AI Define a goal-aligned AI vision and strategy for stakeholders, including businesses, customers, and users Leverage AI successfully by focusing on concepts such as scientific innovation and AI readiness and maturity Understand the importance of executive leadership for pursuing AI initiatives A must read for business executives and managers interested in learning about AI and unlocking its benefits. Alex Castrounis has simplified complex topics so that anyone can begin to leverage AI within their organization. - Dan Park, GM & Director, Uber Alex Castrounis has been at the forefront of helping organizations understand the promise of AI and leverage its benefits, while avoiding the many pitfalls that can derail success. In this essential book, he shares his expertise with the rest of us. - Dean Wampler, Ph.D., VP, Fast Data Engineering at Lightbend |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence Neil Wilkins, 2019-07-20 So, what is the deal with intelligent machines? Will they soon decide on things such as copyright infringement? How about self-driving trucks and cars? What kind of impact will smart machines have on society and the future of human jobs? |
| artificial intelligence basics a non-technical introduction: Real World AI Alyssa Simpson Rochwerger, Wilson Pang, 2021-02-17 How can you successfully deploy AI? When AI works, it's nothing short of brilliant, helping companies make or save tremendous amounts of money while delighting customers on an unprecedented scale. When it fails, the results can be devastating. Most AI models never make it out of testing, but those failures aren't random. This practical guide to deploying AI lays out a human-first, responsible approach that has seen more than three times the success rate when compared to the industry average. In Real World AI, Alyssa Simpson Rochwerger and Wilson Pang share dozens of AI stories from startups and global enterprises alike featuring personal experiences from people who have worked on global AI deployments that impact billions of people every day. AI for business doesn't have to be overwhelming. Real World AI uses plain language to walk you through an AI approach that you can feel confident about-for your business and for your customers. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence for Computer Games John David Funge, 2004-07-29 Learn to make games that are more fun and engaging! Building on fundamental principles of Artificial Intelligence, Funge explains how to create Non-Player Characters (NPCs) with progressively more sophisticated capabilities. Starting with the basic capability of acting in the game world, the book explains how to develop NPCs who can perceive, remem |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence , 2005 |
| artificial intelligence basics a non-technical introduction: Understanding Machine Learning Shai Shalev-Shwartz, Shai Ben-David, 2014-05-19 Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage. |
| artificial intelligence basics a non-technical introduction: Blockchain Basics Daniel Drescher, 2017-03-14 In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors. This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications. What You'll Learn What the blockchain is Why it is needed and what problem it solves Why there is so much excitement about the blockchain and its potential Major components and their purpose How various components of the blockchain work and interact Limitations, why they exist, and what has been done to overcome them Major application scenarios Who This Book Is For Everyone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it |
| artificial intelligence basics a non-technical introduction: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| artificial intelligence basics a non-technical introduction: Mathematics for Machine Learning Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong, 2020-04-23 Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence For Dummies John Paul Mueller, Luca Massaron, 2018-03-16 Step into the future with AI The term Artificial Intelligence has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever! |
| artificial intelligence basics a non-technical introduction: The Master Algorithm Pedro Domingos, 2015-09-22 Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence Neil Wilkins, 2019-04-06 If you want to learn key AI concepts to get you quickly up to speed with all things AI, then keep reading Two manuscripts in one book: Artificial Intelligence: What You Need to Know About Machine Learning, Robotics, Deep Learning, Recommender Systems, Internet of Things, Neural Networks, Reinforcement Learning, and Our Future Internet of Things: What You Need to Know About IoT, Big Data, Predictive Analytics, Artificial Intelligence, Machine Learning, Cybersecurity, Business Intelligence, Augmented Reality and Our Future This book covers everything from machine learning to robotics and the internet of things. You can use it as a nifty guidebook whenever you come across news headlines that talk about some new advancement in AI by Google or Facebook. By the time you finish reading, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is. You will also learn a comprehensive history of AI, from the first invention of automations in antiquity to the driver-less cars of today. In part 1 of this book, you will: Understand how machines can think and how they learn Learn the five reasons why experts are warning us about AI research Find the answers to the top six myths of artificial intelligence Learn what neural networks are and how they work, the brains of machine learning Understand reinforcement learning and how it is used to teach machine learning systems through experience Become up-to-date with the current state-of-the-art artificial intelligence methods that use deep learning Learn the basics of recommender systems Expand your current view of machines and what is possible with modern robotics Enter the vast world of the internet of things technologies Find out why AI is the new business degree And much, much more! Some of the topics covered in part 2 of this book include: Origins of IoT IoT Security Ethical Hacking Internet of Things Under The Cushy Foot of Tech Giants The Power of Infinite Funds IoT Toys Bio-robotics Predictive Analytics Machine Learning Artificial Intelligence Cybersecurity Big Data Business Intelligence Augmented Reality Virtual Reality Our Future And much, much more If you want to learn more about the artificial intelligence and internet of things, then scroll up and click add to cart! |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence Basics: A Non-Technical Introduction , 2021 Книга представляет собой увлекательное, нетехническое введение в такие важные понятия искусственного интеллекта (ИИ), как машинное обучение, глубокое обучение, обработка естественного языка, робототехника и многое другое. Проведено знакомство с историей и основными понятиями ИИ. Раскрыто значение данных как «топлива» для ИИ. Рассмотрены традиционные и продвинутые статистические методы машинного обучения, алгоритмы нейронных сетей для глубокого обучения, сферы применения разговорных роботов (чат-ботов), методы роботизации производственных процессов, технологии обработки естественного языка. Рассказано о применении языка Python и платформ TensorFlow и PyTorch при внедрении проектов ИИ. Освещены современные тренды ИИ: автономное вождение, милитаризация, технологическая безработица, изыскание новых лекарственных препаратов и другие. |
| artificial intelligence basics a non-technical introduction: Reinforcement Learning, second edition Richard S. Sutton, Andrew G. Barto, 2018-11-13 The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning. |
| artificial intelligence basics a non-technical introduction: Deterministic Artificial Intelligence Timothy Sands, 2020-05-27 Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers to very advanced topics of deterministic artificial intelligence, espoused in the book with applications to both electromechanics (e.g. the forced van der Pol equation) and also motion mechanics (i.e. Euler’s moment equations). The reader will learn how to bestow self-awareness and express optimal learning methods for the self-aware object (e.g. robot) that require no tuning and no interaction with humans for autonomous operation. The topics learned from reading this text will prepare students and faculty to investigate interesting problems of mechanics. It is the fondest hope of the editor and authors that readers enjoy the book. |
| artificial intelligence basics a non-technical introduction: Hands-On Artificial Intelligence for Beginners Patrick D. Smith, 2018-10-31 Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning conceptsBook Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systemsWho this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications. |
| artificial intelligence basics a non-technical introduction: An Introduction to Ethics in Robotics and AI Christoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh, 2020-08-11 This open access book introduces the reader to the foundations of AI and ethics. It discusses issues of trust, responsibility, liability, privacy and risk. It focuses on the interaction between people and the AI systems and Robotics they use. Designed to be accessible for a broad audience, reading this book does not require prerequisite technical, legal or philosophical expertise. Throughout, the authors use examples to illustrate the issues at hand and conclude the book with a discussion on the application areas of AI and Robotics, in particular autonomous vehicles, automatic weapon systems and biased algorithms. A list of questions and further readings is also included for students willing to explore the topic further. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence for Fashion Leanne Luce, 2018-12-08 Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing. Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses. What You’ll Learn Gain a basic understanding of AI and how it is used in fashion Understand key terminology and concepts in AI Review the new competitive landscape of the fashion industry Conceptualize and develop new ways to apply AI within the workplace Who This Book Is For Fashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession. |
| artificial intelligence basics a non-technical introduction: Advances in Financial Machine Learning Marcos Lopez de Prado, 2018-02-21 Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance. |
| artificial intelligence basics a non-technical introduction: Philosophy and Theory of Artificial Intelligence Vincent C. Müller, 2012-08-23 Can we make machines that think and act like humans or other natural intelligent agents? The answer to this question depends on how we see ourselves and how we see the machines in question. Classical AI and cognitive science had claimed that cognition is computation, and can thus be reproduced on other computing machines, possibly surpassing the abilities of human intelligence. This consensus has now come under threat and the agenda for the philosophy and theory of AI must be set anew, re-defining the relation between AI and Cognitive Science. We can re-claim the original vision of general AI from the technical AI disciplines; we can reject classical cognitive science and replace it with a new theory (e.g. embodied); or we can try to find new ways to approach AI, for example from neuroscience or from systems theory. To do this, we must go back to the basic questions on computing, cognition and ethics for AI. The 30 papers in this volume provide cutting-edge work from leading researchers that define where we stand and where we should go from here. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence and Games Georgios N. Yannakakis, Julian Togelius, 2025-07-04 This book covers artificial intelligence methods applied to games, both in research and game development. It is aimed at graduate students, researchers, game developers, and readers with a technical background interested in the intersection of AI and games. The book covers a range of AI methods, from traditional search, planning, and optimization, to modern machine learning methods, including diffusion models and large language models. It discusses applications to playing games, generating content, and modeling players, including use cases such as level generation, game testing, intelligent non-player characters, player retention, player experience analysis, and game adaptation. It also covers the use of games, including video games, to test and benchmark AI algorithms. The book is informed by decades of research and practice in the field and combines insights into game design with deep technical knowledge from the authors, who have pioneered many of the methods and approaches used in the field. This second edition of the 2018 textbook captures significant developments in AI and gaming over the past 7 years, incorporating advancements in computer vision, reinforcement learning, deep learning, and the emergence of transformer-based large language models and generative AI. The book has been reorganized to provide an updated overview of AI in games, with separate sections dedicated to AI’s core uses in playing and generating games, and modeling their players, along with a new chapter on ethical considerations. Aimed at readers with foundational AI knowledge, the book primarily targets three audiences: graduate or advanced undergraduate students pursuing careers in game AI, AI researchers and educators seeking teaching resources, and game programmers interested in creative AI applications. The text is complemented by a website featuring exercises, lecture slides, and additional educational materials suitable for undergraduate and graduate courses. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence By Example - Second Edition Denis Rothman, 2020-02-28 |
| artificial intelligence basics a non-technical introduction: Introduction to Artificial Intelligence Philip C. Jackson, 1974 This book is intended to be a comprehensive introduction to the field of artificial intelligence, written primarily for the student who has some knowledge of computers and mathematics (say, at the junior or senior levels of college). The subjects for discussion are machines that can solve problems, play games, recognize patters, prove mathematical theorems, understand English, and even demonstrate learning, by changing their own behavior so as to perform such tasks more successfully. In general, this book is addressed to all person who are interested in studying the nature of thought, and hopefully much of it can be read without previous, formal exposure to mathematics and computers. |
| artificial intelligence basics a non-technical introduction: Introduction to Machine Learning Ethem Alpaydin, 2014-08-22 Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence in Ophthalmology Andrzej Grzybowski, 2021-10-13 This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology. |
| artificial intelligence basics a non-technical introduction: Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville, 2016-11-18 An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. |
| artificial intelligence basics a non-technical introduction: Introducing Artificial Intelligence Henry Brighton, Howard Selina, 2003 Can machines really think? Is the mind just a complicated computer program? Introducing Artificial Intelligence focuses on the major issues behind one of the hardest scientific problems ever undertaken. |
| artificial intelligence basics a non-technical introduction: Architecture in the Age of Artificial Intelligence Neil Leach, 2025-04-17 AI has been unleashed. Nothing is going to be the same again. Updated to cover all the latest developments, Architecture in the Age of Artificial Intelligence introduces AI for designers and explores its seismic impact on the future of architecture and design. From ChatGPT and smart assistants to groundbreaking diffusion models for video and 3D modelling, this updated new edition investigates the profound effects of AI technologies on architectural practice. It explores how AI transforms every part of the process-from the inspiration and brief, to regulations and copyright, to performance-driven design- and looks beyond discussions of software and functionality to ask more fundamental questions too: How did AI evolve? How does it work? What does it tell us about creativity? And what does it mean for the very future of the profession itself? Written by one of the world's leading experts in the field, this book is a must-read for all architects wishing to stay at the forefront of the AI revolution. |
| artificial intelligence basics a non-technical introduction: Research Handbook on Warfare and Artificial Intelligence Robin Geiß, Henning Lahmann, 2024-07-05 The Research Handbook on Warfare and Artificial Intelligence provides a multi-disciplinary exploration of the urgent issues emerging from the increasing use of AI-supported technologies in military operations. Bringing together scholarship from leading experts in the fields of technology and security from across the globe, it sheds light on the wide spectrum of existing and prospective cases of AI in armed conflict. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence, Optimization, and Data Sciences in Sports Maude J. Blondin, Iztok Fister Jr., Panos M. Pardalos, 2025-01-30 This book delves into the dynamic intersection of data science, data mining, machine learning, and optimization within sports. It compiles and presents the latest achievements in this vibrant and emerging research area, offering a comprehensive overview of how these technologies revolutionize sports analytics and performance. Topical coverage includes artificial intelligence in sports, automated machine learning for training sessions, computational social science, and deep learning applications. Readers will also explore cutting-edge concepts such as digital twins in sports and sports prediction through data analysis. This volume highlights theoretical advancements and practical case studies that demonstrate real-world applications. Ideal for researchers, practitioners, and students in fields related to sports science, data analytics, and machine learning, this book serves as a crucial resource for anyone looking to understand the transformative impact of technology on sports. Whether you are an academic scholar or a professional working in the industry, this collection offers valuable insights that bridge the gap between research and practical solutions. |
| artificial intelligence basics a non-technical introduction: Artificial Intelligence, Data Science and Applications Yousef Farhaoui, Amir Hussain, Tanzila Saba, Hamed Taherdoost, Anshul Verma, 2024-03-04 This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications. |
| artificial intelligence basics a non-technical introduction: Systems, Software and Services Process Improvement Murat Yilmaz, Paul Clarke, Andreas Riel, Richard Messnarz, 2023-08-29 This two-volume set constitutes the refereed proceedings of the 30th European Conference on Systems, Software and Services Process Improvement, EuroSPI 2023, held in Grenoble, France, in August-September 2023. The 47 full papers presented were carefully reviewed and selected from 100 submissions. The papers are organized according to the following topical sections: SPI and emerging and multidisciplinary approaches to software engineering; digitalisation of industry, infrastructure and e-mobility; SPI and good/bad SPI practices in improvement; SPI and functional safety and cybersecurity; SPI and agile; SPI and standards and safety and security norms; sustainability and life cycle challenges; SPI and recent innovations; virtual reality and augmented reality. |
| artificial intelligence basics a non-technical introduction: Essentials of Game Theory Kevin Leyton-Brown, Yoav Shoham, 2022-05-31 Game theory is the mathematical study of interaction among independent, self-interested agents. The audience for game theory has grown dramatically in recent years, and now spans disciplines as diverse as political science, biology, psychology, economics, linguistics, sociology, and computer science, among others. What has been missing is a relatively short introduction to the field covering the common basis that anyone with a professional interest in game theory is likely to require. Such a text would minimize notation, ruthlessly focus on essentials, and yet not sacrifice rigor. This Synthesis Lecture aims to fill this gap by providing a concise and accessible introduction to the field. It covers the main classes of games, their representations, and the main concepts used to analyze them. |
| artificial intelligence basics a non-technical introduction: PRACTICAL GUIDE TO ARTIFICIAL INTELLIGENCE FOR SECURE SOFTWARE SYSTEMS Virender Dhiman, 2024-07-04 There is no doubt that the world today is a lot different than it was fifty or even thirty years ago, from the standpoint of technology. Just imagine when we landed the first man on the moon back in 1969. All of the computers that were used at NASA were all mainframe computers, developed primarily by IBM and other related computer companies. These computers were very large and massive—in fact, they could even occupy an entire room. Even the computers that were used on the Saturn V rocket and in the Command and Lunar Excursion Modules were also of the mainframe type. Back then, even having just 5 MB of RAM memory in a small computer was a big thing. By today’s standards, the iPhone is lightyears away from this kind of computing technology, and in just this one device, we perhaps have enough computing power to send the same Saturn V rocket to the moon and back at least 100 times. But just think about it, all that was needed back then was just this size of memory. The concepts of the Cloud, virtualization, etc. were barely even heard of. The computers that were designed back then, for example, had just one specific purpose: to process the input and output instructions (also known as “I/O”) so that the spacecrafts could have a safe journey to the moon, land on it, and return safely back to Earth once again. Because of these limited needs (though considered to be rather gargantuan at the time), all that was needed was just that small amount of memory. But by today’s standards, given all of the applications that we have today, we need at least 1,000 times that much just to run the simplest of Cloud-based applications. But also back then, there was one concept that was not even heard of quite yet: Cybersecurity. In fact, even the term of “Cyber” was not even heard of. Most of the security issues back then revolved around physical security. Take, for example, NASA again. The main concern was only letting the authorized and legitimate employees into Mission Control. Who would have thought that back then there was even the slightest possibility that a Cyberattacked could literally take over control of the computers and even potentially steer the Saturn V rocket away from its planned trajectory |
| artificial intelligence basics a non-technical introduction: Handbook on the Politics and Governance of Big Data and Artificial Intelligence Andrej Zwitter, Oskar J. Gstrein, 2023-06-01 Drawing on the theoretical debates, practical applications, and sectoral approaches in the field, this ground-breaking Handbook unpacks the political and regulatory developments in AI and big data governance. Covering the political implications of big data and AI on international relations, as well as emerging initiatives for legal regulation, it provides an accessible overview of ongoing data science discourses in politics, law and governance. This title contains one or more Open Access chapters. |
| artificial intelligence basics a non-technical introduction: The Hundred-page Machine Learning Book Andriy Burkov, 2019 Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue. |
| artificial intelligence basics a non-technical introduction: Creative Applications of Artificial Intelligence in Education Alex Urmeneta, Margarida Romero, 2024-05-18 This open access book explores the synergy between AI and education, highlighting its potential impact on pedagogical practices. It navigates the evolving landscape of AI-powered educational technologies and suggests practical ways to personalise instruction, nurture human-AI co-creativity, and transform the learning experience. Spanning from primary to higher education, this short and engaging volume proposes concrete examples of how educational stakeholders can be empowered in their AI literacy to foster creativity, inspire critical thinking, and promote problem-solving by embracing AI as a tool for expansive learning. Structured in three parts, the book starts developing the creative engagement perspective for learning and teaching to then present practical applications of AI in K-12 and higher education, covering different fields (teacher education, professional education, business education) as well as different types of AI supported tools (games, chatbots, and AI assisted assessment). It also delves into the ethical considerations, policy implications, and the central role educators play in harnessing the power of an AI informed educational experience. |
| artificial intelligence basics a non-technical introduction: The Cambridge Handbook of Responsible Artificial Intelligence Silja Voeneky, Philipp Kellmeyer, Oliver Mueller, Wolfram Burgard, 2022-11-17 In the past decade, artificial intelligence (AI) has become a disruptive force around the world, offering enormous potential for innovation but also creating hazards and risks for individuals and the societies in which they live. This volume addresses the most pressing philosophical, ethical, legal, and societal challenges posed by AI. Contributors from different disciplines and sectors explore the foundational and normative aspects of responsible AI and provide a basis for a transdisciplinary approach to responsible AI. This work, which is designed to foster future discussions to develop proportional approaches to AI governance, will enable scholars, scientists, and other actors to identify normative frameworks for AI to allow societies, states, and the international community to unlock the potential for responsible innovation in this critical field. This book is also available as Open Access on Cambridge Core. |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
artificial - definition and meaning - Wordnik
Made or contrived by art, or by human skill and labor: opposed to natural: as, artificial heat or light; an artificial magnet. Made in imitation of or as a substitute for that which is natural or real: …
Artificial Definition & Meaning - YourDictionary
Made by human work or art, not by nature; not natural. Not arising from natural or necessary causes; contrived or arbitrary. Made in imitation of or as a substitute for something natural; …
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
artificial - definition and meaning - Wordnik
Made or contrived by art, or by human skill and labor: opposed to natural: as, artificial heat or light; an artificial magnet. Made in imitation of or as a substitute for that which is natural or real: …
Artificial Definition & Meaning - YourDictionary
Made by human work or art, not by nature; not natural. Not arising from natural or necessary causes; contrived or arbitrary. Made in imitation of or as a substitute for something natural; …
