Why this paper changed everything

Three reasons, in plain terms:

1. Speed through parallelism. Because all words are processed together, training can use modern hardware (GPUs) at full tilt. This is what made it practical to train on the entire internet.
2. Long-range memory. Any word can attend directly to any other word, so distance no longer destroys understanding.
3. It scales. Make it bigger, feed it more text, and it keeps getting better in a predictable way. That predictability is the subject of the next chapter.

In short, the Transformer is the engine. Everything else in this folder is about fueling it, tuning it, and steering it.