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Peng Wang, Pete Smith - Multilingual Artificial Intelligence, Häftad

Häftad, Engelska, 2025

Multilingual Artificial Intelligence

Av Peng Wang, Pete Smith

661 kr

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Beskrivning
Multilingual Artificial Intelligence is a guide for non-computer science specialists and learners looking to explore the implementation of AI technologies to solve real-life problems involving language data.Focusing on multilingual, multicultural, pre-trained large language models and their practical use through fine-tuning and prompt engineering, Wang and Smith demonstrate how to apply this new technology in areas such as information retrieval, semantic webs, and retrieval augmented generation, to improve both human productivity and machine intelligence. Finally, they discuss the human impact of language technologies in the cultural context, and provide an AI competence framework for users to design their own learning journey.This innovative text is essential reading for all students, professionals, and researchers in language, linguistics, and related areas looking to understand how to integrate multilingual and multicultural artificial intelligence technology into their research and practice.
Produktinformation
  • Utgivningsdatum: 2025-04-29
  • Mått: 174 x 246 x 14 mm
  • Vikt: 330 g
  • Format: Häftad
  • Språk: Engelska
  • Antal sidor: 164
  • Förlag: Taylor & Francis Ltd
  • ISBN: 9781032747224
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Mer om författaren

Peng Wang is an IT analyst and the chair of the Multilingual AI Track. She is the co-author of Machine Learning in Translation.Pete Smith is Professor of Modern Languages at the University of Texas Arlington, where he also serves as Chief Analytics and Data Officer.

Recensioner i media

"A landmark contribution that successfully bridges the gap between the humanities and computational science. It is more than a textbook; it is a timely manifesto for a more human-centered approach to NLP, offering a worthy contribution to the fields of computational linguistics, translation studies, and digital humanities. Without question, this volume will serve as a standard reference for graduate students, researchers, and practitioners interested not only in the ‘how’ of AI but, more importantly, in the ‘why’ and the ‘what for’." Lin Pan, Natural Language Processing

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