Power of Large Language Models and AI in the Digital Age

Neha Sharma works with Tata Consultancy Services, India. She is the founder President of Bharat Research in AI and NextGen Foundation, India, and founder secretary of S4DS. A senior IEEE member and ACM distinguished speaker, she has 100+ publications, patents and awards, including the Golden Book Award 2023. With a PhD from IIT (ISM) Dhanbad, she champions AI for sustainability, societal transformation, and open data ecosystems, inspiring future innovators.Saravanan Krishnan is an associate professor at College of Engineering, Guindy, Anna University, Chennai, India. He specializes in AI, ML, DL, NLP, cloud computing, software engineering, IoT and smart cities. He has published in reputed journals and at conferences, and has edited 15+ books and 20+ book chapters. He is also a consultant working on smart city initiatives. He is a fellow of IEI and a senior ACM member.Prithwis Kumar De is affiliated with the Society for Data Science, Pune, India. He is an expert in data, analytics, and AI, having held leadership roles at Tata Consultancy Services, Accenture, CRISIL, Ernst & Young, and the Indian Institute of Foreign Trade. His expertise spans computing, data science, telecom, BFSI, retail, CPG, energy & utilities, life sciences, and healthcare sectors. He is an award-winning author, fellow of the Royal Statistical Society, and a chartered statistician.Shailaja Patil is the dean of research and development at Rajarshi Shahu College of Engineering, Pune, India. With over 30 years of experience, she specializes in AI model development for IoT and excels in cutting-edge domains such as generative AI and foundational AI models. She has successfully secured research funding from DST, AICTE, and SPPU, has authored numerous research publications, and holds five patents.Mrityunjoy Panday is principal architect AI at Cognizant and VP at Bharat Research in AI and Nextgen, India. His work encompasses a broad spectrum of applications, including natural language processing applications, time series analysis, reinforcement-based causality, and quantum hardware optimization. His expertise in GPT3, Codex, and automated scientific writing highlights his ability to merge cutting-edge AI technologies with practical applications.

• Part I: Understanding large language modelsChapter 1: Introduction to deep learning and neural networksChapter 2: Foundation, architecture, and applications of large language modelsChapter 3: Challenges and issues in implementing large language models Part II: Practical applications and real-world case studiesChapter 4: Practical applications of LLM modelsChapter 5: Real-world case studies showcasing successful implementations Part III: Technical insightsChapter 6: An in-depth exploration of large language model architectureChapter 7: From foundation to specialization: a comprehensive analysis of pretraining and fine-tuning in large language models Part IV: Ethical and societal implicationsChapter 8: Bias, fairness, and responsible AI in language modelsChapter 9: Privacy concerns and data security Part V: Future horizonsChapter 10: The role of language models in the future of AI: future perspectives and research directionsChapter 11: The dawn of agentic AI