Large Language Models explained briefly

3-Second Blueprint (English)

1. LLMs generate dialogue by repeatedly sampling from next-token probability distributions controlled by billions of learned weights.
2. Pretraining tunes random initial parameters via backpropagation across trillions of text examples to boost true next-word likelihood.
3. Transformers encode tokens as continuous vectors and apply parallel self-attention so words refine their meaning from context.