How LLMs work

AI & Machine Learning, Software Development, Machine Learning(0xkato.xyz)view on HackerNews
LLMstransformertokenizationembeddingspositional encodingattentionmulti-head attentionfeed-forward networksresidual streamsmachine learningdeep learningnatural language processing.

Author: 0xkato

Date: 6/3/2026

Article Summary:
This article is a walkthrough of how Large Language Models (LLMs) work, focusing on the core mechanisms of modern transformer-based LLMs, including tokenization, embeddings, positional encoding, attention, multi-head attention, feed-forward networks, and residual streams.