How an LLM Thinks: Building ChatGPT from Scratch in Ten Steps

▤ Summary

This article explains how ChatGPT-style large language models work from the ground up in ten steps. It walks through core concepts such as bigram models, RNNs, attention, transformers, embeddings, KV cache, and next-token prediction. The piece uses simple examples and code snippets to show how each building block contributes to text generation. It also connects these concepts to modern LLMs like GPT, Claude, Gemini, and Llama. The article is educational and technical rather than news about a company event.

▦ Linked Companies