Time Artificial Intelligence
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Time Artificial Intelligence
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Author : The Editors of TIME
language : en
Publisher: Time Inc. Books
Release Date : 2017-09-29
Time Artificial Intelligence written by The Editors of TIME and has been published by Time Inc. Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Science categories.
The future of humankind Artificial intelligence has moved beyond science fiction and into reality, changing history and touching our lives in so many ways-from how astronomers explore the edges of our universe to whether your music system understands the difference between John Legend and John Lennon. Digital assistants such as Siri and Alexa as well as the next generation of smartphones, genomic research, instant language translation and self-driving cars all incoporate artificial intelligence. In this new special edition from TIME, Artificial Intelligence: The Future of Humankind, readers delve into this fascinating field, with authoritative essays and infographics and compelling images of the machines, the science and the people that are changing the course of the future. With a history of A.I., a glossary of the terms that will soon become commonplace, a detailed Q&A and focused articles on how A.I. is changing entertainment, education, technology, communication-and everything else-TIME: Artificial Intelligence is your guide to the future.
Artificial Intelligence
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Author :
language : en
Publisher:
Release Date : 2017
Artificial Intelligence written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Artificial intelligence categories.
Machine Learning And Artificial Intelligence
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Author : Chris Neil
language : en
Publisher: Alicex Limited
Release Date : 2020-12-27
Machine Learning And Artificial Intelligence written by Chris Neil and has been published by Alicex Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-27 with Computers categories.
Do you want to learn how ML and AI can be applied in practice and be compatible with human behavior in modern times? If yes, then keep reading... Machine learning (ML) is a data-driven approach. Hence it implies the availability of large datasets in order to make accurate decisions. In case only a limited dataset is available to solve a particular problem, it is best to use a deterministic approach. When a limited dataset is available it is hard to train a machine learning model and generalize its applicability to other similar problems. The developed model, in this case, is only applicable for the few data it was trained on. Because ML methods rely solely only on data and the human expertise or judgment is not taken in consideration, it is the data that dictate if the machine learning method will fail or succeed to perform the task it was designed for. The way a machine learning approach works is that a modeler develops a learning algorithm. Then the modeler feeds the learning algorithm with the data and information. The algorithm learns by itself from the data with no guidance or human interference. It is the algorithm that builds the system. If the data provided for the algorithm is of poor quality and biased then the system is also of poor quality and biased. Hence, cleaning and acquiring the right data to solve a problem with ML problem is very crucial. If the data are biased and noisy it is better to stick with a traditional method. Otherwise, the machine learning method will memorize the noise and provide inaccurate results. Could Turning Important Decisions over to AI help Humanity? Some might say that's a terrible idea, but how much worse is it today where we've turned over our societies and civilizations to corrupt leadership, crony capitalism, or had to deal with rogue nation-states in other parts of the world with two-bit dictators, religious fanaticism, or the quest to destroy another group of peoples' civilization? Perhaps it's time we came up with a special think tank that could go through all the issues concerning our fears, and what we hope to expect from AI decision-making machines. That is to say how to get the best possible answer, all the time with the greatest probability. We all watched IBM's "Watson" supercomputer as it won against the top human Jeopardy players. It did pretty well, most all the time; didn't it? Yes, but it wasn't perfect, and perhaps that's the scary part. In fact, some of the mistakes that it did make were mistakes that even a child wouldn't have missed. Still, if there is a group of humans or a think tank, focus group, or Board of Directors constantly surveying the answers and asking additional questions, then perhaps you don't have to worry about an erroneous answer now and again. In fact, it might make you smile and feel good to be a human at that point. ML is useful anywhere you need to recognize patterns and predict behavior based on historical data. Recognizing patterns could mean anything from character recognition to predictive maintenance to recommending products to customers based on past purchases. This book gives a comprehensive guide on the following: Correlation Between ML and Artificial Learning The Era of Evolution ML and AI in Practice Self-Driving Cars Robots and How they will Change Our Lives ML, AI and IoT Ethics of AI AI and Privacy Is Artificial Intelligence Dangerous? Will Humans and Artificial Intelligence Live Together in the Future? ... AND MORE!!! Wake up and order your copy. Click buy now!!!!!
Management And Business Education In The Time Of Artificial Intelligence
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Author : Agata Stachowicz-Stanusch
language : en
Publisher: IAP
Release Date : 2020-05-01
Management And Business Education In The Time Of Artificial Intelligence written by Agata Stachowicz-Stanusch and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-01 with Business & Economics categories.
Artificial intelligence (AI) technologies are one of top investment priorities in these days. They are aimed at finding applications in fields of special value for humans, including education. The fourth industrial revolution will replace not only human hands but also human brains, the time of machines requires new forms of work and new ways of business education, however we must be aware that if there is no control of human-AI interaction, there is a risk of losing sight of this interaction’s goal. First, it is important to get people to truly understand AI systems, to intentionally participate in their use, as well as to build their trust, because “the measure of success for AI applications is the value they create for human lives” (Stanford University 2016, 33). Consequently, society needs to adapt to AI applications if it is to extend its benefits and mitigate the inevitable errors and failures. This is why it is highly recommended to create new AI-powered tools for education that are the result of cooperation between AI researchers and humanities’ and social sciences’ researchers, who can identify cognitive processes and human behaviors. This book is authored by a range of international experts with a diversity of backgrounds and perspectives hopefully bringing us closer to the responses for the questions what we should teach (what the ‘right’ set of future skills is), how we should teach (the way in which schools should teach and assess them) and where we should teach (what implications does AI have for today’s education infrastructure). We must remember as we have already noticed before “...education institutions would need to ensure that that they have an appropriate infrastructure, as well as the safety and credibility of AI-based systems. Ultimately, the law and policies need to adjust to the rapid pace of AI development, because the formal responsibility for appropriate learning outcomes will in future be divided between a teacher and a machine. Above all, we should ensure that AI respect human and civil rights (Stachowicz-Stanusch, Amann, 2018)”.
Real Time Strategy
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Author : Andreas Schühly
language : en
Publisher: Emerald Group Publishing
Release Date : 2020-04-29
Real Time Strategy written by Andreas Schühly and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-29 with Business & Economics categories.
Combining classical scenario thinking (the gentle art of perception) with the analytical power of big data and artificial intelligence, Real Time Strategy presents the decision making of the future which enables decision makers to develop dynamic strategies, monitor their validity, and react faster.
Whose Time Is It
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Author : Stamatia Portanova
language : en
Publisher: MIT Press
Release Date : 2022-02-01
Whose Time Is It written by Stamatia Portanova and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Social Science categories.
Following the “emerging life adventures and experiences” of Sophia, a robot animated by blockchain and AI, to present a study in temporal automation. In what way do the two technologies of blockchain and artificial intelligence actualize and, crucially, automatize the cognition of time? These kinds of machines are increasingly part of both our contemporary present and our prospective future, but how do we really define a present and a future? And more important, how do these machines themselves understand, know, and sense time? Can machines really think about the present and dream the future in an autonomous way? In order to unravel these questions, Whose Time Is It? follows the “emerging life adventures and experiences” of Sophia, a robot animated by blockchain and AI, to present a study in temporal automation.
Machine Learning For Time Series With Python
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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-29
Machine Learning For Time Series With Python written by Ben Auffarth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-29 with Computers categories.
Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You'll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series. What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.
Time Pressure Raises Efficient Or Inefficient Artificial Intelligence Performance
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Author : Johnny Ch Lok
language : en
Publisher:
Release Date : 2019-06-02
Time Pressure Raises Efficient Or Inefficient Artificial Intelligence Performance written by Johnny Ch Lok and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-02 with categories.
However, (AI) research and developments have economically impacted many industries, such as robotics, telecommunications, computer applications, health, finance, heavy manufacturing, transportation, aviation, e-service and e-commerce, military, music and movie, toys and games entertainment etc. industries. In fact, many ideas, systems and technologies have been developing in the world of (AI) technology. However, which are net called or considered (AI) products, rather which are mentioned with their specific names, such as smart graphics, machine learning, e-commerce etc. ( i.e. this is called (AI) effect).
Intelligent Decision Making An Ai Based Approach
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Author : Gloria Phillips-Wren
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-03-04
Intelligent Decision Making An Ai Based Approach written by Gloria Phillips-Wren and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-04 with Mathematics categories.
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.
Time Space Spiking Neural Networks And Brain Inspired Artificial Intelligence
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Author : Nikola K. Kasabov
language : en
Publisher: Springer
Release Date : 2018-08-29
Time Space Spiking Neural Networks And Brain Inspired Artificial Intelligence written by Nikola K. Kasabov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-29 with Technology & Engineering categories.
Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI). BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosciences.