Machine Translation is a type of AI for the translation industry. Cleaned and normalized data form the basis for neural network learning. Uncleaned and unprocessed data – ‘garbage in, garbage out’ Requirements: volume from 100,000 sentences, correct terminology, completeness, anonymization. Currently available MT algorithms: recurrent neural networks (RNN). Adaptive MT (trained on topic/subject-specific corpora) – since 2018. Minimal corpus volume: 50,000 segments, adequate training: from 500,000 segments 80 percent of working time of an MT expert: DB cleaning and normalization