Comparative Analysis of CHATGPT and the evolution of language models
Oluwatosin Ogundare
Abstract
Interest in Large Language Models (LLMs) have increased drastically since the emergence of ChatGPT and the outstanding positive societal response to the ease at which it performs tasks in Natural Language Processing (NLP).The triumph of ChatGPT, however, is how it seamlessly bridges the divide between language generation and knowledge models and in some cases provides anecdotal evidence of a framework for replicating human intuition over a knowledge domain.This paper highlights the prevailing ideas in NLP, including machine translation, machine summarization, question-answering, and language generation, and compares the performance of ChatGPT with the major algorithms in each of these categories using the Spontaneous Quality (SQ) score.A strategy for validating the arguments and results of ChatGPT is presented summarily as an example of safe large scale adoption of LLMs.