To match "were" with "bales" in a long sentence about cloth from Onitsha, a model must carry information all the way across. An RNN passes a baton word by word; a transformer lets every word look at every other word at once. Then use a plain RNN on a long sentence, run an RNN on a GPU, or try naive attention on 128,000 tokens. This lesson needs JavaScript.