Multilingual Artificial Intelligence

Peng Wang, Pete Smith

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English

Routledge
29 April 2025

Computational linguistics; Artificial intelligence

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.

By: Peng Wang, Pete Smith
Imprint: Routledge
Country of Publication: United Kingdom
Dimensions: Height: 246mm, Width: 174mm,
Weight: 330g
ISBN: 9781032747224
ISBN 10: 1032747226
Pages: 164
Publication Date: 29 April 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Paperback
Publisher's Status: Active

List of Tables List of Figures Preface Part One Chapter 1: Multilingual AI in a mathematical theory of communication Chapter 2: Data landscape for multilingual AI Chapter 3: Basic techniques to achieve artificial intelligence Chapter 4: Symbolic meaning and vector semantics Part Two Chapter 5: Multilingual large language models, fine-tuning and prompt engineering Chapter 6: Multilingual and cross-lingual information retrieval Chapter 7: Augmenting LLM performance with human knowledge Part Three Chapter 8: Multilingual AI in Practice Chapter 9: Multicultural AI Chapter 10: Multilingual and Multicultural AI—Pedagogy, Proficiency, Policy, and Predictions References Index

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.