Large-Language-Models (LLM)-Based AI Chatbots: Architecture, In-Depth Analysis and Their Performance Evaluation

Abstract

This scholarly article conducts a comparative evaluation of prominent large-scale language models, specifically encompassing Google’s BARD, ChatGPT 3.5, and ChatGPT 4. It offers a comprehensive dissection of each model, elucidating aspects such as architectural structure, utilized training data, and proficiency in natural language processing. The paper also undertakes a systematic assessment of these models in executing diverse tasks like text generation, text completion, and question-answering, paralleling their precision, processing speed, and efficiency. The concluding part of the article explores the prospective application domains of these language models, including but not limited to customer service, education, and healthcare sectors, while proffering suggestions for future research trajectories and technological enhancements. In summary, the study furnishes critical insights into the current status of large-scale language models, shedding light on their potential to augment human-computer interaction and drive forward advancements in the realm of natural language processing technology.