A deep learning architecture that is a much more advanced version than the common recurrent neural network (RNN). With transformers, text is converted into numerical tokens that are converted into vectors via a "word embedding" lookup table. Similar words are given comparable vector representations, and the transformer approximates meaning between them faster and with greater accuracy. It also analyzes whole sentences better than previous models. See
recurrent neural network,
GPT and
AI prompt.