Exploring Language Models: A Comprehensive Survey and Analysis

The domain of natural language processing (NLP) has witnessed significant advancements with the arrival of large-scale pre-trained language models to revolutionize NLP research and achieve state-of-the-art performance across various tasks. They have propelled the development of sophisticated NLP applications and deepened our understanding of artificial intelligence. However, the growing size and complexity of these models have given rise to new challenges and limitations. Concerns related to model bias, interpretability, data privacy, and environmental impact have become prominent. This paper explores the impact and potential of large language models in NLP, highlighting the advancements made and the challenges that need to be addressed.