AI-based Natural Language Processing (NLP) Systems

Abstract

The goal of artificial intelligence (AI) known as Natural Language Processing (NLP) is to instruct computers how to read, comprehend, and even create new varieties of human language. NLP has applications in many different fields, including healthcare, banking, education, and even customer service. In recent years, natural language processing (NLP) has seen major advancements as a result of the availability of enormous datasets, powerful technology, and complex algorithms such as neural networks. These factors have made it possible for machines to read and analyse unstructured input in the form of text, voice, and video. The problems of data bias and quality, interpretability and explainability, domain-specific language, support for several languages, contextual comprehension, and adversarial assaults are some of the issues that still need to be resolved. In order to solve these obstacles, further research has to be done in a variety of different areas, such as the collection and annotation of data, the explainability of models, and the robustness of attacks. Despite these obstacles, natural language processing (NLP) has a bright future; in the years to come, we can likely anticipate a great deal of development and innovation in this sector.