Artificial Intelligence Generation
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| Author | : Rabindra Nath Shaw |
| Publisher | : Elsevier |
| Total Pages | : 180 |
| Release | : 2021-06-19 |
| Genre | : Technology & Engineering |
| ISBN | : 032385799X |
Artificial Intelligence for Future Generation Robotics offers a vision for potential future robotics applications for AI technologies. Each chapter includes theory and mathematics to stimulate novel research directions based on the state-of-the-art in AI and smart robotics. Organized by application into ten chapters, this book offers a practical tool for researchers and engineers looking for new avenues and use-cases that combine AI with smart robotics. As we witness exponential growth in automation and the rapid advancement of underpinning technologies, such as ubiquitous computing, sensing, intelligent data processing, mobile computing and context aware applications, this book is an ideal resource for future innovation. - Brings AI and smart robotics into imaginative, technically-informed dialogue - Integrates fundamentals with real-world applications - Presents potential applications for AI in smart robotics by use-case - Gives detailed theory and mathematical calculations for each application - Stimulates new thinking and research in applying AI to robotics
| Author | : Olaf Groth |
| Publisher | : Simon and Schuster |
| Total Pages | : 229 |
| Release | : 2018-11-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1681779358 |
An update edition of Solomon’s Code—now The A.I. Generation—the thought-provoking examination of artificial intelligence and how it reshapes human values, trust, and power around the world. Whether in medicine, money, or love, technologies powered by forms of artificial intelligence are playing an increasingly prominent role in our lives. As we cede more decisions to thinking machines, we face new questions about staying safe, keeping a job and having a say over the direction of our lives. The answers to those questions might depend on your race, gender, age, behavior, or nationality. New AI technologies can drive cars, treat damaged brains and nudge workers to be more productive, but they also can threaten, manipulate, and alienate us from others. They can pit nation against nation, but they also can help the global community tackle some of its greatest challenges—from food crises to global climate change. In clear and accessible prose, global trends and strategy adviser Olaf Groth, AI scientist and social entrepreneur Mark Nitzberg, along with seasoned economics reporter Dan Zehr, provide a unique human-focused, global view of humanity in a world of thinking machines.
| Author | : G. M. P. O'Hare |
| Publisher | : John Wiley & Sons |
| Total Pages | : 598 |
| Release | : 1996-04-05 |
| Genre | : Computers |
| ISBN | : 9780471006756 |
Distributed Artificial Intelligence (DAI) is a dynamic area of research and this book is the first comprehensive, truly integrated exposition of the discipline presenting influential contributions from leaders in the field. Commences with a solid introduction to the theoretical and practical issues of DAI, followed by a discussion of the core research topics--communication, coordination, planning--and how they are related to each other. The third section describes a number of DAI testbeds, illustrating particular strategies commissioned to provide software environments for building and experimenting with DAI systems. The final segment contains contributions which consider DAI from different perspectives.
| Author | : Andrzej Wodecki |
| Publisher | : Springer |
| Total Pages | : 350 |
| Release | : 2018-07-18 |
| Genre | : Business & Economics |
| ISBN | : 3319915967 |
This book analyses various models of value creation in projects and businesses by applying different forms of Artificial Intelligence in their products and services. First presenting the main concepts and ideas behind AI, Wodecki assesses different models of technology-based value creation based upon the analysis of over 400 case studies. This framework shows how AI may influence both value creation and competitive advantage (efficiency, creativity and flexibility) within a modern organization. Finally, a conceptual model is formulated to evaluate AI-supported in-company projects and new ventures and identify the key managerial and technical competencies required.
| Author | : Olaf Groth |
| Publisher | : Pegasus Books |
| Total Pages | : 0 |
| Release | : 2018-11-06 |
| Genre | : Technology & Engineering |
| ISBN | : 9781681778709 |
A thought-provoking examination of artificial intelligence and how it reshapes human values, trust, and power around the world. Whether in medicine, money, or love, technologies powered by forms of artificial intelligence are playing an increasingly prominent role in our lives. As we cede more decisions to thinking machines, we face new questions about staying safe, keeping a job and having a say over the direction of our lives. The answers to those questions might depend on your race, gender, age, behavior, or nationality. New AI technologies can drive cars, treat damaged brains and nudge workers to be more productive, but they also can threaten, manipulate, and alienate us from others. They can pit nation against nation, but they also can help the global community tackle some of its greatest challenges—from food crises to global climate change. In clear and accessible prose, global trends and strategy adviser Olaf Groth, AI scientist and social entrepreneur Mark Nitzberg, along with seasoned economics reporter Dan Zehr, provide a unique human-focused, global view of humanity in a world of thinking machines.
| Author | : Hong Jiao |
| Publisher | : IAP |
| Total Pages | : 218 |
| Release | : 2020-03-01 |
| Genre | : Computers |
| ISBN | : 1641139536 |
The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.
| Author | : Robbie Allen |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 99998 |
| Release | : 2019-05 |
| Genre | : Computers |
| ISBN | : 9780135226209 |
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
| Author | : Patrick Bangert |
| Publisher | : Elsevier |
| Total Pages | : 276 |
| Release | : 2021-01-14 |
| Genre | : Technology & Engineering |
| ISBN | : 0128226005 |
Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting. - Provides best practices on how to design and set up ML projects in power systems, including all nontechnological aspects necessary to be successful - Explores implementation pathways, explaining key ML algorithms and approaches as well as the choices that must be made, how to make them, what outcomes may be expected, and how the data must be prepared for them - Determines the specific data needs for the collection, processing, and operationalization of data within machine learning algorithms for power systems - Accompanied by numerous supporting real-world case studies, providing practical evidence of both best practices and potential pitfalls
| Author | : Robert Kozma |
| Publisher | : Academic Press |
| Total Pages | : 398 |
| Release | : 2023-10-11 |
| Genre | : Computers |
| ISBN | : 0323958168 |
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. - Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN - Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making - Edited by high-level academics and researchers in intelligent systems and neural networks - Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks
| Author | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
