How ChatGPT/Gemini/MS Copilot Understands Your Question: A Step-by-Step Journey from Input to Response

Short summary

This post breaks down how transformer models like ChatGPT process questions step-by-step: text is tokenized into units, converted to embeddings capturing meaning, then enriched with positional encoding. Self-attention and multi-head attention mechanisms extract grammar, semantics, and entity relationships while stacked neural layers perform deep reasoning. The pipeline culminates in token prediction and conversion back to human-readable text.

• •Input text converts to tokens, then embeddings representing numerical meaning
• •Self-attention and multi-head attention mechanisms capture context and semantic relationships
• •Stacked feedforward layers enable pattern recognition and deep reasoning before output generation

Generated with AI, which can make mistakes.