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Book DATA ENGINEERING IN THE AGE OF AI GENERATIVE MODELS AND DEEP LEARNING UNLEASHED

Download or read book DATA ENGINEERING IN THE AGE OF AI GENERATIVE MODELS AND DEEP LEARNING UNLEASHED written by Siddharth Konkimalla and published by BUDHA PUBLISHER. This book was released on with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: .The advances in data engineering technologies, including big data infrastructure, knowledge graphs, and mechanism design, will have a long-lasting impact on artificial intelligence (AI) research and development. This paper introduces data engineering in AI with a focus on the basic concepts, applications, and emerging frontiers. As a new research field, most data engineering in AI is yet to be properly defined, and there are abundant problems and applications to be explored. The primary purpose of this paper is to expose the AI community to this shining star of data science, stimulate AI researchers to think differently and form a roadmap of data engineering for AI. Since this is primarily an informal essay rather than an academic paper, its coverage is limited. The vast majority of the stimulating studies and ongoing projects are not mentioned in the paper.

Book Competing in the Age of AI

Download or read book Competing in the Age of AI written by Marco Iansiti and published by Harvard Business Press. This book was released on 2020-01-07 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: "a provocative new book" — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

Book Artificial Intelligence Applications for Sustainable Construction

Download or read book Artificial Intelligence Applications for Sustainable Construction written by Moncef L. Nehdi and published by Elsevier. This book was released on 2024-02-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste. The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. - Presents convincing "success stories that encourage application of AI-powered tools to civil engineering - Provides a wealth of valuable technical information to address and resolve many challenging construction problems - Illustrates the most recent shifts in thinking and practice for sustainable construction

Book Machine Learning and Deep Learning in Real Time Applications

Download or read book Machine Learning and Deep Learning in Real Time Applications written by Mahrishi, Mehul and published by IGI Global. This book was released on 2020-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Book AI and education

Download or read book AI and education written by Miao, Fengchun and published by UNESCO Publishing. This book was released on 2021-04-08 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]

Book Artificial Intelligence in Practice

Download or read book Artificial Intelligence in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2019-04-15 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Book AI Transformers Unleashed

Download or read book AI Transformers Unleashed written by Robert Johnson and published by HiTeX Press. This book was released on 2024-10-27 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: "AI Transformers Unleashed: From BERT to Large Language Models and Generative AI" is an insightful exploration into one of the most transformative advancements in artificial intelligence. This book delves into the intricacies of AI transformer models, providing a comprehensive understanding of their architecture, functionality, and the profound impact they've had on natural language processing and beyond. Through clear explanations and detailed analysis, readers are guided from foundational concepts to the latest innovations, covering key models such as BERT and GPT, and examining their application across various domains. With a keen focus on both technical challenges and ethical considerations, this book also addresses the complexities surrounding bias, privacy, and transparency in AI technologies. It offers a balanced discourse on the potential for misuse and the imperative for responsible deployment. Designed to educate and inform, "AI Transformers Unleashed" serves as an essential resource for students, industry professionals, and anyone eager to grasp the current and future landscape of AI, ensuring readers are well-equipped to navigate the evolving field with confidence and insight.

Book Architects of Intelligence

Download or read book Architects of Intelligence written by Martin Ford and published by Packt Publishing Ltd. This book was released on 2018-11-23 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Times Best Books of the Year 2018 TechRepublic Top Books Every Techie Should Read Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kurzweil (Google), Geoffrey Hinton (Univ. of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel). Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future. Meet the minds behind the AI superpowers as they discuss the science, business and ethics of modern artificial intelligence. Read James Manyika’s thoughts on AI analytics, Geoffrey Hinton’s breakthroughs in AI programming and development, and Rana el Kaliouby’s insights into AI marketing. This AI book collects the opinions of the luminaries of the AI business, such as Stuart Russell (coauthor of the leading AI textbook), Rodney Brooks (a leader in AI robotics), Demis Hassabis (chess prodigy and mind behind AlphaGo), and Yoshua Bengio (leader in deep learning) to complete your AI education and give you an AI advantage in 2019 and the future.

Book Artificial Intelligence and Machine Learning Applications in Civil  Mechanical  and Industrial Engineering

Download or read book Artificial Intelligence and Machine Learning Applications in Civil Mechanical and Industrial Engineering written by Gebrail Bekdas and published by Engineering Science Reference. This book was released on 2019 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering"--

Book The Imagination Machine

Download or read book The Imagination Machine written by Martin Reeves and published by Harvard Business Press. This book was released on 2021-06-08 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide for mining the imagination to find powerful new ways to succeed. We need imagination now more than ever—to find new opportunities, rethink our businesses, and discover paths to growth. Yet too many companies have lost their ability to imagine. What is this mysterious capacity? How does imagination work? And how can organizations keep it alive and harness it in a systematic way? The Imagination Machine answers these questions and more. Drawing on the experience and insights of CEOs across several industries, as well as lessons from neuroscience, computer science, psychology, and philosophy, Martin Reeves of Boston Consulting Group's Henderson Institute and Jack Fuller, an expert in neuroscience, provide a fascinating look into the mechanics of imagination and lay out a process for creating ideas and bringing them to life: The Seduction: How to open yourself up to surprises The Idea: How to generate new ideas The Collision: How to rethink your idea based on real-world feedback The Epidemic: How to spread an evolving idea to others The New Ordinary: How to turn your novel idea into an accepted reality The Encore: How to repeat the process—again and again. Imagination is one of the least understood but most crucial ingredients of success. It's what makes the difference between an incremental change and the kinds of pivots and paradigm shifts that are essential to transformation—especially during a crisis. The Imagination Machine is the guide you need to demystify and operationalize this powerful human capacity, to inject new life into your company, and to head into unknown territory with the right tools at your disposal.

Book The Pioneering Applications of Generative AI

Download or read book The Pioneering Applications of Generative AI written by Kumar, Raghvendra and published by IGI Global. This book was released on 2024-07-17 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating generative artificial intelligence (AI) into art, design, and media presents a double-edged sword. While it offers unprecedented creative possibilities, it raises ethical concerns, challenges traditional workflows, and requires careful regulation. As AI becomes more prevalent in these fields, there is a pressing need for a comprehensive resource that explores the technology's potential and navigates the complex landscape of its implications. The Pioneering Applications of Generative AI is a pioneering book that addresses these challenges head-on. It provides a deep dive into the evolution, ethical considerations, core technologies, and creative applications of generative AI, offering readers a thorough understanding of this transformative technology. Researchers, academicians, scientists, and research scholars will find this book invaluable in navigating the complexities of generative AI in art, design, and media. With its focus on ethical and responsible AI and discussions on regulatory frameworks, the book equips readers with the knowledge and tools needed to harness the full potential of generative AI while ensuring its responsible and ethical use.

Book Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry

Download or read book Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry written by Chkoniya, Valentina and published by IGI Global. This book was released on 2021-06-25 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contemporary world lives on the data produced at an unprecedented speed through social networks and the internet of things (IoT). Data has been called the new global currency, and its rise is transforming entire industries, providing a wealth of opportunities. Applied data science research is necessary to derive useful information from big data for the effective and efficient utilization to solve real-world problems. A broad analytical set allied with strong business logic is fundamental in today’s corporations. Organizations work to obtain competitive advantage by analyzing the data produced within and outside their organizational limits to support their decision-making processes. This book aims to provide an overview of the concepts, tools, and techniques behind the fields of data science and artificial intelligence (AI) applied to business and industries. The Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry discusses all stages of data science to AI and their application to real problems across industries—from science and engineering to academia and commerce. This book brings together practice and science to build successful data solutions, showing how to uncover hidden patterns and leverage them to improve all aspects of business performance by making sense of data from both web and offline environments. Covering topics including applied AI, consumer behavior analytics, and machine learning, this text is essential for data scientists, IT specialists, managers, executives, software and computer engineers, researchers, practitioners, academicians, and students.

Book Building the Data Lakehouse

    Book Details:
  • Author : Bill Inmon
  • Publisher : Technics Publications
  • Release : 2021-10
  • ISBN : 9781634629669
  • Pages : 256 pages

Download or read book Building the Data Lakehouse written by Bill Inmon and published by Technics Publications. This book was released on 2021-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements. Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Know how to incorporate the lakehouse into an existing data governance strategy. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after.

Book Machine Law  Ethics  and Morality in the Age of Artificial Intelligence

Download or read book Machine Law Ethics and Morality in the Age of Artificial Intelligence written by Thompson, Steven John and published by IGI Global. This book was released on 2021-03-18 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machines and computers are becoming increasingly sophisticated and self-sustaining. As we integrate such technologies into our daily lives, questions concerning moral integrity and best practices arise. A changing world requires renegotiating our current set of standards. Without best practices to guide interaction and use with these complex machines, interaction with them will turn disastrous. Machine Law, Ethics, and Morality in the Age of Artificial Intelligence is a collection of innovative research that presents holistic and transdisciplinary approaches to the field of machine ethics and morality and offers up-to-date and state-of-the-art perspectives on the advancement of definitions, terms, policies, philosophies, and relevant determinants related to human-machine ethics. The book encompasses theory and practice sections for each topical component of important areas of human-machine ethics both in existence today and prospective for the future. While highlighting a broad range of topics including facial recognition, health and medicine, and privacy and security, this book is ideally designed for ethicists, philosophers, scientists, lawyers, politicians, government lawmakers, researchers, academicians, and students. It is of special interest to decision- and policy-makers concerned with the identification and adoption of human-machine ethics initiatives, leading to needed policy adoption and reform for human-machine entities, their technologies, and their societal and legal obligations.

Book Explainable AI  Interpreting  Explaining and Visualizing Deep Learning

Download or read book Explainable AI Interpreting Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

Book Artificial Intelligence for COVID 19

Download or read book Artificial Intelligence for COVID 19 written by Diego Oliva and published by Springer Nature. This book was released on 2021-07-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

Book Patterns  Predictions  and Actions  Foundations of Machine Learning

Download or read book Patterns Predictions and Actions Foundations of Machine Learning written by Moritz Hardt and published by Princeton University Press. This book was released on 2022-08-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers