AI-Driven Approaches to Natural Language Processing

AI-Driven Approaches to Natural Language Processing

Kalpana Bhagwan Jarad, Dr Sachin Sukhdev Bere, Dr Dinesh Bhagwan Hanchate

Department of AIDS Enginnering, Group of Institutions ,Faculty of Engineering ,Bhigwan ,India

ABSTRACT

Generative Artificial Intelligence has surfaced as a ground breaking technological advancement, particularly in the field of Natural Language Processing. This forum report delves into how generative AI has converted the traditional approaches to NLP by enabling machines to not only comprehend but also induce mortal- alike language. Generative models, analogous as GPT, BERT, and T5, use deep knowledge ways to learn from vast datasets and produce coherent, contextually applicable text. These models are necessary in a various operations rang from automated content creation, machine paraphrase, and sentiment analysis to intelligent chatbots and question- answering systems. The integration of analogous technology brings numerous advantages like automation, personalization, and scalability but also introduces challenges including ethical enterprises, data insulation risks, and the eventuality for poisoned or deceiving labors. This report completely covers the architecture, tools, benefits, limitations, and ethical implications associated with generative AI in NLP. It concludes with perceptivity into future disquisition directions and the transformative eventuality of generative AI in redefining mortal- computer relations through language. In the natural language processing( NLP), generative artificial intelligence( AI) has surfaced as a revolutionary force that allows machines to construct mortal- suchlike language with amazing ignorance and consonance.