How Self-Attention Became the Engine Behind Modern LLMs

Self-attention, introduced in Google's 2017 'Attention Is All You Need' paper, allows each word in a sentence to directly attend to every other word, solving long-range dependency issues in RNNs. This mechanism enables parallel processing on GPUs, making training faster and more scalable. Today, all major LLMs like GPT, Claude, and Gemini rely on the Transformer architecture built on self-attention.