The Transformer removed the sequential pass used by recurrent networks and related input elements through attention. That made training far more parallel and created a common architecture later transferred from language to code, images, audio and video. The paper became the central fork in modern AI history: nearly every later large language and multimodal model descends from it.
Source: arXiv2017-06
Attention Is All You Need
About this eventThe Transformer replaced recurrence with attention and scaled better on parallel compute.