Artificial Intelligence and Large Language Models by Moallem, Abbas; Degen, Helmut; Ntoa, Stavroula;

Short description:

Artificial Intelligence and Large Language Models: A Scientific Perspective will appeal to students and academics, 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.

Long description:

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 challenging with 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 scientific-based 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 is 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.

Table of Contents:

1. Exploring the Artificial Intelligence Landscape. 2. Introduction to Large Language Models. 3. Neural Computing for Advanced Natural Language Understanding and Generation. 4. LLMs in Scientific Research. 5. Security, Privacy, Ethics and Trust in LLMs. 6. Education Transformation and Challenges With LLMs. 7. LLMs for Healthcare. 8. LLMs in Large Corporations and the Industry. 9. Media Content in the Age of LLMs. 10. Programming Paradigms and Trends With LLMs. 11. Exploring the Legal Landscape on LLMs. 12. LLMs Through User Studies and Perspectives. 13. The Impact of LLMs in Everyday Life and the Society.