Recent discussions have highlighted the origins and advancements of the attention mechanism in artificial intelligence, particularly in transformer models. SageAttention has introduced an 8-bit quantization method that enhances transformer attention computation, achieving a speed improvement of 2.1 times over FlashAttention2 while maintaining accuracy across various tasks. This development follows a historical narrative about the attention operator, which was initially a translation tool. The mechanism, first popularized by the paper 'Attention is All You Need', has evolved significantly since its inception. Insights from personal correspondence with its co-author, Dzmitry Bahdanau, reveal that the attention operator was a pivotal innovation in AI, with its origins tracing back to a translation hack in September 2014. Experts note that had Bahdanau not introduced the concept, it is likely that another researcher would have made a similar breakthrough shortly thereafter.