Advancing Natural Language Processing: A Journey Through the Evolution of Language Models
Akanksha Bisht, Aditi Gupta, Aarsh Mall, Nidhi Rana · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2025
Natural language processing (NLP) has come a long way from a basic rule-based system to the sophisticated AI models we use today.The system used to adhere to rigid rules, which worked well for simple tasks but had trouble with the complexity of real-world language.The introduction of machine learning, including neural networks like MLPs, CNNs, RNNs, brought some huge improvements, but the real ground breaker came in 2017 with the transformer model.Transformers, with their ability to process text parallel and focus on key parts of the sentences, which completely transformed NLP.Today, models like BERT and GPT are at the soul of applications like chatbots, translations and summarization.This paper looks at the journey of language models, the breakthroughs in the field, the challenges that remain, and the interesting future possibilities, including combining text with other forms of data.