Before it
Neural nets scored translations produced by statistical systems.
The problem
No neural architecture mapped a whole variable-length sentence to another.
What it introduced
An encoder RNN compressing a sentence into a vector and a decoder RNN generating from it, with a simplified gated unit.
Why it matters
It set up the encoder-decoder frame, and the bottleneck it exposed is what attention was invented to fix.
What modern models inherit
The encoder-decoder shape still used for translation and, in modified form, T5.
What came next
Bahdanau attention, by an author of this paper, removed the bottleneck a few months later.