er is powerful because of its <em>attention</em> mechanism, which is in some ways the opposite of the sliding mechanism of convolutional networks. Sequences can learn to focus on different parts of themselves or other sequences, regardless of distance. They can then feed this back into training a deeper understanding of the sequence elements themselves in a highly dimensional space via <em>embeddings</em>, explained by <a href="https://medium.com/deeper-learning/glossary-of-deep-learning-word-embedding-f90c