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, it discusses the human impact of language technologies in the cultural context, and provides 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.
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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.
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List of FiguresList of TablesPrefacePart One: Fundamentals of multilingual artificial intelligenceChapter 1: Multilingual AI in a mathematical theory of communicationChapter 2: Data landscape for multilingual AIChapter 3: Basic techniques to achieve artificial intelligenceChapter 4: Symbolic meaning and vector semanticsPart Two: Large Language models: theories and applicationsChapter 5: Multilingual large language models, fine-tuning, and prompt engineeringChapter 6: Multilingual and cross-lingual information retrievalChapter 7: Augmenting LLM performance with human knowledgePart Three: Culture and multicultual AIChapter 8: Multilingual AI in practiceChapter 9: Multicultural AIChapter 10: Multilingual and multicultural AI—pedagogy, proficiency, policy, and predictionsReferencesIndex
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Produktdetaljer

ISBN
9781032747248
Publisert
2025-04-29
Utgiver
Vendor
Routledge
Høyde
246 mm
Bredde
174 mm
Aldersnivå
U, P, 05, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
158

Biographical note

Peng Wang is an IT analyst and the chair of the Multilingual AI Track. She is 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.