Machines That Understand: A Theoretical Survey of Deep Learning's Role in Shaping Natural Language Processing

This theoretical survey explores how deep learning—particularly Transformer architectures like BERT and GPT—has transformed Natural Language Processing (NLP). It discusses semantic modelling, ethical concerns like bias and interpretability, and outlines a roadmap for responsible future research in NLP.