A Brief Survey on Exploring the Application Areas and Scope of ChatGPT

Chatbots based on Large Language Models (LLMs) with their tremendous potential have lately fascinated researchers from industry and academia. Among these models, ChatGPT has emerged as a prominent player. In this brief survey paper, the use cases, application areas, and scope of ChatGPT was explored, aiming to shed light on its potential and possible setbacks. A general overview of the fundamental architecture is given along with the training methodology of ChatGPT and its underlying transformer-based neural network, which enables it to generate contextually coherent responses in a conversational setting. By understanding the model’s foundations, the groundwork for comprehending its subsequent applications is developed. However, even though ChatGPT excels at generating responses that are similar to humans, it also has produced biased or incorrect information occasionally. Hence, the challenges related to maintaining ethical standards, ensuring user safety, and addressing issues of transparency and accountability through some use cases are also discussed. Such factors limit the scalability and generalizability of ChatGPT. We hope that the outcome of this study will help contributing to the ongoing discourse surrounding AI systems and open the path for future research, enabling the effective and thus responsible integration of ChatGPT into various real-world scenarios.