
Artificial Intelligence and Large Language Models
A Scientific Perspective
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Artificial Intelligence and Large Language Models
A Scientific Perspective
About this book
With the latest developments in generative artificial intelligence (AI) and large language model (LLM) applications, like ChatGPT and Gemini, millions of people have started using them in their personal and professional lives. Interest in them continues to grow and they are becoming the go-to applications for students, academics, engineers, lawyers, designers, writers, media experts, programmers, politicians, artists, and citizens across the globe. However, understanding these applications can be technical with precious little advice out there. This book cuts through the jargon to explain the "what", "why" and "how" of generative AI and LLM applications.
This book summarizes experiences from a variety of applications, relevant to our daily lives. It brings together scientifically grounded experience reports from different perspectives into a one-stop title. With an international outlook and featuring global case studies, it offers insights into the beneficial use of LLMs and generative AI including future trends for how the journey of using such amazing tools will continue in the future. This book details the history of AI, reviews LLM literature, and covers neural computing and the technical foundation of LLMs. Furthermore, the use and control of LLMs in education are covered. Through reading this book, the reader will develop a full understanding of AI and LLM applications, including knowledge of the key issues of trust, legality, security and technical foundations.
Artificial Intelligence and Large Language Models: A Scientific Perspective will appeal to students and academics, as well as people interested in the use of LLMs and generative AI for professional or everyday tasks, including those in Human Factors, Human-Computer Interaction, Computer Science, Software Engineering and Industrial Engineering.
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Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- About the Editors
- List of Contributors
- Introduction
- Chapter 1 Exploring the Artificial Intelligence Landscape
- Chapter 2 Neural Computing for Advanced Natural Language Understanding and Generation
- Chapter 3 LLMs in Cultural Heritage
- Chapter 4 Large Language Models in Education: Applications, Challenges, and Use Cases
- Chapter 5 Healthcare in the Age of LLMs: Perspectives on Radiology
- Chapter 6 Transforming Visual Communication: The Role of Large Language Models in Media Content Creation
- Chapter 7 Transforming Software Engineering and Software Acquisition with Large Language Models
- Chapter 8 Detecting and Correcting Software Assurance Document: Incompleteness, Inconsistencies, and Discrepancies Using LLMs
- Chapter 9 Large Language Models: Cybersecurity, Privacy, and Trust
- Chapter 10 Large Language Models in Human–Computer Interaction: Using LLM-Generated Personas to Model Everything from Minority Views to Entire Ecosystems
- Chapter 11 Theoretical Foundations of Human Factors and Trustworthiness in Large Language Models
- Chapter 12 How Do AI and LLMs Change Our Lives? Reflections and Outlook
- Index
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