The Transformer is the neural network architecture behind modern language models, introduced in 2017. Its core mechanism, self-attention, lets the model weigh which earlier words matter for predicting the next one — across the whole input at once. Note: this architectural 'attention' has nothing to do with the AI Panic Attention Score, which measures news coverage.
Transformers are why AI leapt forward: they train efficiently at massive scale and handle long-range context. Nearly every model in the news — GPT, Claude, Llama, Gemini — is a Transformer.
In “The trophy doesn't fit in the suitcase because it is too big”, self-attention helps the model decide whether 'it' refers to the trophy or the suitcase.