Strategies for translating machine errors in automatically generated texts (using GPT-4 as an example)

The article discusses the strategies of translation «machine texts» on example generative transformers (GPT). Currently, study and development machine text generation has become an important task for processing analyzing texts in different languages. Modern technologies artificial intelligence neural networks allow us to create powerful tools activities this field, which are becoming more effective every year. Generative one such tools. also allows developers accurate efficient algorithms, improves quality translations user experience. In context, features created by transformers, their patterns, errors imperfections, require special strategies, deserve interest. Today we can say that unique relevant is a routine been automated. Nevertheless, certain restrictions use still exist, particular, requires appropriate strategies. paper proposes author’s typology where, taking into account AST, it proposed add substrategy tertiary-moderation translation.