A Study on Potentiality of ChatGPT as Task Solver Based on Natural Language Processing

As natural language processing (NLP) models develop, the question of whether they can be used to solve problems across a variety of industries becomes more important. This research paper offers a thorough examination of the possibilities of ChatGPT, a cutting-edge language model, as a flexible NLP problem solver. We research its performance across a range of tasks, evaluate its applicability to various fields, consider its moral ramifications, and look at its function in assisting human problem-solving. We list the benefits and drawbacks of ChatGPT and discuss its potential contributions to AI-powered solutions through empirical studies and practical implementations. Because ChatGPT can provide excellent responses to input from humans and automatically fix previous mistakes based on new talks, it has recently attracted a lot of interest from the natural language processing (NLP) field. We demonstrate the merits and drawbacks of the current ChatGPT version using in-depth empirical studies. We find that while ChatGPT does well on many tasks that favor reasoning skills (like arithmetic reasoning), it still has difficulties with more specialized tasks like sequence labeling.