TIME Artificial Intelligence

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Author : The Editors of TIME
Genre : Science

Summary : 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.

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Genre : Artificial intelligence

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Author : Chris Neil
Genre : Computers

Summary : 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!!!!!

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Author : Gloria Phillips-Wren
Genre : Technology & Engineering

Summary : 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.

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Author : Andreas Schühly
Genre : Business & Economics

Summary : 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.

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Author : Agata Stachowicz-Stanusch
Genre : Business & Economics

Summary : 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)”.

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Author : Nikola K. Kasabov
Genre : Technology & Engineering

Summary : 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.