EXPLAINING CHATGPT TO ANYONE IN <20 MINUTES

Summary from the TLDR Web Dev newsletter

This article introduces a three-part framework for understanding and explaining generative LLMs. The first part covers decoder-only transformer architecture, a deep neural network architecture used for language tasks. The second part covers language model pretraining, where these models are pretrained on large textual datasets using self-supervised learning. The last part is the alignment process, which makes LLMs more useful and aligned with human intent through supervised finetuning (SFT) and reinforcement learning from human feedback (RLHF).