Neural Computing for Advanced Natural Language Understanding and Generation

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Authors: Mark Nuppnau, Khalid A. Kattan, Robert G. Reynolds
Cited by: 0

Abstract

This chapter traces the development and growing impact of large language models used for understanding and generating natural language. It explores how early computer models inspired by human reasoning and the workings of the brain led to today’s advanced systems, highlighting key milestones such as new approaches to learning from data and breakthroughs in how computers process sequences of words. The chapter explains how technologies like BERT and GPT have enabled computers to communicate more effectively in human language and support everything from education to healthcare. At the same time, it addresses important concerns—such as bias, fairness, privacy, and the tendency of these models to sometimes provide incorrect or misleading information. Readers are introduced to efforts aimed at making these systems more responsible and trustworthy, and this chapter concludes with a look at future directions for technology that better serves people’s needs and values.

Fields of Study & Subjects

Topic Modeling Natural Language Processing Techniques Speech and dialogue systems

Publication details

Journal / source
CRC Press eBooks
Pages
28–57
Publication date
3 February 2026
Language
EN
Document type
Book chapter