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    Artificial Intelligence and Systems of the Earth

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    Author(s)
    Speiser, Michel
    Language
    English
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    Abstract
    Artificial Intelligence and Systems of the Earth is a book about the potential and capabilities of artificial intelligence (AI) and machine learning (ML) for studying the Earth. It aims to serve as an eye-opener on new avenues of scientific research that can be enabled by AI/ML. This is not meant to be a ‘how to’ book but is written to answer the question ‘what if’. It explains how these tools are currently being applied, and the new opportunities they have opened. Through many examples and application ideas from outside the Earth Sciences, the book discusses some of the most prevalent types of AI in current use, the future of AI hardware, and how AI/ML bring about change. Features Provides accessible and compact coverage on the many uses AI in Earth Science. Covers AI, deep learning, and causal modeling concepts in an easy-to-understand language. Contains a chapter on generat ive AI and its specific strengths and challenges. Includes descriptions of computer hardware for AI and where it is headed. Offers a companion website with regularly updated content. This book is an excellent resource for researchers, academics, graduate, and senior undergraduate students in Earth Science and Environmental Science and Engineering, who wish to learn how AI and ML can benefit them, its potential applications, and capabilities. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons (CC-BY) 4.0 license.
    URI
    https://library.oapen.org/handle/20.500.12657/94031
    Keywords
    Deep Learning; Generative AI; Quantum Computing; AI hardware; Data Science; Neural Networks; System Theory
    DOI
    10.1201/9781032710525
    ISBN
    9781040222836, 9781032710525, 9781032710501, 9781040222843, 9781040222836
    Publisher
    Taylor & Francis
    Publisher website
    https://taylorandfrancis.com/
    Publication date and place
    2025
    Imprint
    CRC Press
    Classification
    Earth sciences
    Neural networks and fuzzy systems
    Data mining
    Automatic control engineering
    Pages
    114
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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