Signals

A general audience introduction to how large language models like ChatGPT are built, from data collection to neural network training.

Step-by-step tutorial on building character-level language models, starting with simple bigram models and progressing to transformer architectures.

The groundbreaking paper that introduced the Transformer architecture, replacing recurrent networks with self-attention mechanisms for superior performance in sequence modeling.

A deep dive into the ongoing discussion about whether large language models truly understand the world or simply excel at pattern recognition.