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Transformer Model

Also: transformer, transformer architecture

The transformer is the neural-network architecture behind nearly every modern large language model, introduced by Google researchers in the 2017 paper 'Attention Is All You Need.' Its key idea, self-attention, lets the model weigh how much every word in the input relates to every other word, which is what makes it so good at language.

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The "GPT" in ChatGPT stands for Generative Pretrained Transformer, and the "T" is this architecture. A transformer turns your text into tokens, represents them as vectors, and uses attention to decide which earlier tokens matter most when predicting the next one. Repeat that prediction loop and you get fluent text.

The useful takeaway for content is what attention rewards: clear referents, consistent terminology, and answer-first structure are easier for the model to resolve than ambiguous, scattered prose. You are not optimizing the architecture, you are making meaning easy to compute, which is the same thing good writing has always done.