Affiliation:
1. Information Retrieval and Knowledge Management Research Lab, York University, Toronto, Canada
Abstract
The rapid advancement of artificial intelligence (AI) has spotlighted ChatGPT as a key technology in the realm of information retrieval (IR). Unlike its predecessors, it offers notable advantages that have captured the interest of both industry and academia. While some consider ChatGPT to be a revolutionary innovation, others believe its success stems from smart product and market strategy integration. The advent of ChatGPT and GPT-4 has ushered in a new era of Generative AI, producing content that diverges from training examples, and surpassing the capabilities of OpenAI’s previous GPT-3 model. In contrast to the established supervised learning approach in IR tasks, ChatGPT challenges traditional paradigms, introducing fresh challenges and opportunities in text quality assurance, model bias, and efficiency. This paper aims to explore the influence of ChatGPT on IR tasks, providing insights into its potential future trajectory.
Subject
Artificial Intelligence,Computer Networks and Communications,Software
Reference67 articles.
1. An analytical study of information extraction from unstructured and multidimensional big data;Adnan;Journal of Big Data,2019
2. Feature selection with rough sets for web page classification;An;Trans. Rough Sets,2004
3. Introduction to information extraction: Basic notions and current trends;Balke;Datenbank-Spektrum,2012
4. Y. Bengio, R. Ducharme and P. Vincent, A neural probabilistic language model, Advances in neural information processing systems 13 (2000).
5. Language models are few-shot learners;Brown;Advances in neural information processing systems,2020