Large Data Begets Large Data: Studying Large Language Models (LLMs) and Its History, Types, Working, Benefits and Limitations
Dishita Naik, Ishita Naik, Nitin Naik
Abstract
The emergence of Large Language Models (LLMs) transformed the domain of Natural Language Processing (NLP) by enhancing the capability of machines to effectively comprehend and generate natural language. These LLMs are a type of generative AI and the underlying AI model that work behind the scenes of most modern AI chatbots. Generative AI is an umbrella term for all AI technologies which can generate original contents. These LLMs are pre-trained on a large amount of textual data and billions of parameters. This pre-training is normally unsupervised learning, meaning that it processes the unlabelled data for a comprehensive understanding of context, semantics, and grammar of natural language to generate coherent, context-relevant and credible text. In view of the significance of LLMs, this paper aims to perform a comprehensive study of LLMs, which will elucidate the historical journey of language processing and modelling, evolution and types of language models, and working, benefits and limitations of LLMs.