Everything you wanted to know about ChatGPT: Components, capabilities, applications, and opportunities

Author:

Heidari Arash12,Navimipour Nima Jafari34,Zeadally Sherali5,Chamola Vinay6

Affiliation:

1. Department of Software Engineering Haliç University Istanbul Turkey

2. Department of Computer Engineering, Faculty of Engineering and Natural Science İstanbul Atlas University Istanbul Türkiye

3. Department of Computer Engineering, Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey

4. Future Technology Research Center National Yunlin University of Science and Technology Douliou Taiwan

5. College of Communication and Information University of Kentucky Lexington Kentucky USA

6. Birla Institute of Technology and Sciences (BITS) Pilani India

Abstract

AbstractConversational Artificial Intelligence (AI) and Natural Language Processing have advanced significantly with the creation of a Generative Pre‐trained Transformer (ChatGPT) by OpenAI. ChatGPT uses deep learning techniques like transformer architecture and self‐attention mechanisms to replicate human speech and provide coherent and appropriate replies to the situation. The model mainly depends on the patterns discovered in the training data, which might result in incorrect or illogical conclusions. In the context of open‐domain chats, we investigate the components, capabilities constraints, and potential applications of ChatGPT along with future opportunities. We begin by describing the components of ChatGPT followed by a definition of chatbots. We present a new taxonomy to classify them. Our taxonomy includes rule‐based chatbots, retrieval‐based chatbots, generative chatbots, and hybrid chatbots. Next, we describe the capabilities and constraints of ChatGPT. Finally, we present potential applications of ChatGPT and future research opportunities. The results showed that ChatGPT, a transformer‐based chatbot model, utilizes encoders to produce coherent responses.

Publisher

Wiley

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