Transformers use attention to weight relationships among tokens, allowing efficient parallel training and strong long-range dependencies. Encoder-decoder and decoder-only variants underpin many state-of-the-art language and vision-language systems.

The design scales effectively with data and compute, which has driven rapid advances in capabilities and sparked broad adoption across research and industry.