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This paper provides an in-depth examination of the cutting-edge technology behind ChatGPT, a highly sophisticated chatbot that has gained significant attention in recent months. The paper is divided into three parts. The first part provides definitions of some key concepts related to ChatGPT, such as natural language processing (NLP) and artificial intelligence (AI), and explains how they play a role in the technology. The second part delves into the history, technology and capabilities of Generative Pretrained Transformer (GPT), the underlying technology of ChatGPT. It explains the concepts behind GPT, the process of its development, the scale of the program and the vast amount of data used to train it and its ability to perform a wide range of language-based tasks such as translation, question answering and text generation. The third part of the paper gives an example of ChatGPT’s abilities by providing the output of an interview with ChatGPT on the topic of how AI and GPT will impact academia and libraries. This section will explore how ChatGPT can be used to improve various library services and the ethical considerations that need to be taken into account when using it.
Some key concepts related to ChatGPT
Attention mechanism: An attention mechanism is used in neural networks to allow a model to focus only on specific aspects of input data when making predictions (Niu et al., 2021).
Chatbot: A chatbot is a computer program designed to simulate conversation with human users, especially over the internet (King, 2022).
Generative model: A generative model is a type of model that generates new data, as opposed to only classifying or predicting based on input data (Pavlik, 2023).
GPT: GPT is a machine learning model that uses unsupervised and supervised learning techniques to understand and generate human-like language (Radford et al., 2018).
Language model: A language model is a type of AI model trained to generate text that is similar to human language (MacNeil et al., 2022).
Multimodal neurons: Multimodal neurons are artificial neural network units that are able to understand and interpret the form of an object across different modes or representations, such as images, text and speech (Goh et al., 2021).
NLP: NLP is a field of AI that involves using algorithms to analyze...