The original title is: "How LLMs Work: Transformer, Attention & Next Token Prediction Explained"

Short summary

A beginner-friendly explainer covering how LLMs work, breaking down Transformers, Attention, Self-Attention, Multi-Head Attention, and Next Token Prediction using simple analogies. The article traces the pipeline from input through encoder-decoder to token-by-token output generation. It is a decent introductory resource but adds little to existing explanations of these well-covered concepts.

• •Explains Transformer architecture, attention mechanisms, and next-token prediction in plain language
• •Uses analogies like multiple readers analyzing a story to illustrate multi-head attention
• •Entry-level resource with no code or technical depth beyond conceptual explanations

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