Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends

In the recent past, more than 5 years or so, DL especially the large language models (LLMs) has generated extensive studies out of a distinctly average downturn field of knowledge made up of a traditional society of researchers. As a result, DL (DL) is now so pervasive that its use is widespread across the body of research related to machine learning computing. The rapid emergence and apparent dominance of DL architectures over traditional machine learning techniques on a variety of tasks have been truly astonishing to witness. DL models outperformed in a variety of areas, including natural language processing (NLP), image analysis, language understanding, machine translation, computer vision, speech…