The Power of Large Language Models and AI in the Digital Age : Technologies, applications, security and ethics (Computing and Networks)

Sharma, Neha/ Krishnan, Saravanan/ De, Prithwis Kumar

Institution of Engineering and Technology（2026/03発売）

• 製本 Hardcover:ハードカバー版／ページ数 490 p.
• 言語 ENG
• 商品コード 9781837241019
• DDC分類 006.35

Full Description

Large language models (LLMs) represent a profound breakthrough in artificial intelligence. More than just statistical tools, these vast neural networks undergo an intensive training process that unlocks unexpected, emergent abilities. Models like ChatGPT are now demonstrating a surprising grasp of reasoning, semantics, and real-world concepts, leading many researchers to ask: are we witnessing the first sparks of Artificial General Intelligence (AGI)?

These models are doing more than just revolutionizing natural language processing; they are forcing us to reconsider the boundaries of machine intelligence. While their applications in chatbots, complex problem-solving, and content creation are already reshaping our digital world, their deeper implications point toward an entirely new era of AI.

To understand these emergent capabilities and confront the AGI question, a deep dive into the core technology is essential. This co-authored book provides that crucial foundation. The authors explore the significance and capabilities of LLMs, alongside the immense ethical, social, and security challenges that arise as these models grow more powerful.

For anyone seeking a comprehensive guide to navigate this new territory, The Power of Large Language Models and AI in the Digital Age: Technologies, applications, security and ethics is a valuable resource. It is essential reading for data scientists, researchers from academia and industry, lecturers, and advanced students in AI, computer science, and data science who will shape the future of intelligent systems.

Contents

Part I: Understanding large language models

Chapter 1: Introduction to deep learning and neural networks
Chapter 2: Foundation, architecture, and applications of large language models
Chapter 3: Challenges and issues in implementing large language models


Part II: Practical applications and real-world case studies

Chapter 4: Practical applications of LLM models
Chapter 5: Real-world case studies showcasing successful implementations


Part III: Technical insights

Chapter 6: An in-depth exploration of large language model architecture
Chapter 7: From foundation to specialization: a comprehensive analysis of pretraining and fine-tuning in large language models


Part IV: Ethical and societal implications

Chapter 8: Bias, fairness, and responsible AI in language models
Chapter 9: Privacy concerns and data security


Part V: Future horizons

Chapter 10: The role of language models in the future of AI: future perspectives and research directions
Chapter 11: The dawn of agentic AI