[Paper Review] ChatGPT in the Age of Generative AI and Large Language Models: A Concise Survey

Salman Mohamadi, Ghulam Mujtaba+3 more|arXiv (Cornell University)|Jul 9, 2023

Artificial Intelligence in Healthcare and Education19 citations

TL;DR

The paper provides a concise survey of current research lines on ChatGPT and its evolution, examining both glass box and black box perspectives, foundational literature, applications, and broader implications across multiple domains.

ABSTRACT

ChatGPT is a large language model (LLM) created by OpenAI that has been carefully trained on a large amount of data. It has revolutionized the field of natural language processing (NLP) and has pushed the boundaries of LLM capabilities. ChatGPT has played a pivotal role in enabling widespread public interaction with generative artificial intelligence (GAI) on a large scale. It has also sparked research interest in developing similar technologies and investigating their applications and implications. In this paper, our primary goal is to provide a concise survey on the current lines of research on ChatGPT and its evolution. We considered both the glass box and black box views of ChatGPT, encompassing the components and foundational elements of the technology, as well as its applications, impacts, and implications. The glass box approach focuses on understanding the inner workings of the technology, and the black box approach embraces it as a complex system, and thus examines its inputs, outputs, and effects. This paves the way for a comprehensive exploration of the technology and provides a road map for further research and experimentation. We also lay out essential foundational literature on LLMs and GAI in general and their connection with ChatGPT. This overview sheds light on existing and missing research lines in the emerging field of LLMs, benefiting both public users and developers. Furthermore, the paper delves into the broad spectrum of applications and significant concerns in fields such as education, research, healthcare, finance, etc.

Motivation & Objective

• Map the current research landscape around ChatGPT and its evolution.
• Compare glass box (inner workings) and black box (inputs/outputs/effects) perspectives.
• Synthesize foundational literature on LLMs and generative AI and their link to ChatGPT.
• Identify applications and concerns across education, research, healthcare, finance, and beyond.
• Propose a road map for future research and experimentation in LLMs and GAIs.

Proposed method

• Conduct a literature-based survey of ChatGPT and GAI research.
• Frame analysis with glass box and black box perspectives.
• Synthesize foundational LLM/GAI literature and connect to ChatGPT.
• Review applications and societal/disciplinary implications.
• Outline missing research lines and suggested directions for future work.

Experimental results

Research questions

• RQ1 What are the current research lines surrounding ChatGPT and its evolution?
• RQ2 How do glass box and black box views differently illuminate the technology and its effects?
• RQ3 What are the key applications and implications of ChatGPT across domains?
• RQ4 What gaps exist in the existing literature, and what directions should future research take?

Key findings

• The survey identifies existing and missing research lines in the field of LLMs and ChatGPT.
• It provides a road map for further research and experimentation in this area.
• The paper discusses applications and significant concerns across fields such as education, research, healthcare, and finance.
• It connects foundational LLM/GAI literature to ChatGPT and outlines the evolution of the technology.