the impact of artificial intelligence (ai) on translation: an overview

To be operational, artificial intelligence (ai) uses large language models (llms) in the domain of natural language processing (nlp). a significant advancement in this field is transformer architecture, a deep learning model initially developed for machine translation. the advent of ai conversational interfaces, such as chatbots, has triggered scientific, philosophical, political, social, ethical and legal debates about the pros and cons of ai for humanity, also focusing on the ‘ability’ of ai to accurately translate a wide range of (specialised) texts. these chatbots, powered by llms trained on extensive data sets from books and the internet, are designed to generate coherent and contextually relevant text by understanding and predicting language patterns. hence, after a diachronic overview of ai and automatic translation, the aim of this paper is to show how chatbots “translate” specialized texts, comparing different chatbots to identify their similarities and differences. while neural machine learning (nml) shows promise, it still struggles to produce consistently satisfactory results.