The Transformer architecture works by relying on a self-attention (intra-attention) mechanism, removing all the recurrent operations that are found in the previous approach.In other words, the attention mechanism is repurposed to compute the latent space representation of both the encoder and the decoder sides.
with the absence of recurrence, positional-encoding is added to the input and output embeddings.