The Transformer is a neural-network architecture introduced in 2017.
Self-attention
Each token looks at every other token in the input and decides how much to weight it. That single mechanism replaced the recurrent networks that came before.
Why it scales
Because self-attention is parallel, transformers train efficiently on modern GPUs. That is what made Large Language Models possible.