Challenges in natural language processing and natural language understanding by considering both technical and natural domains

As deep learning became more sophisticated, it significantly increased the use of AI in industry, academia, and other sectors. NLP is a part of the deep learning paradigm that offers different types of systems mainly related to human language understanding, meaning, and interpretations. Nowadays, NLP is used in several applications, including sentiment analysis, categorization of texts, translation, etc. Due to this new usage, new challenges occurred. This paper discusses the challenges of developing or creating an NLP model and the problems that will be occurred in NLU. Moreover, the paper illustrates issues in both technical and natural domains that should be considered upon deployment or creation of NLP models or NLU systems.