How LLMs Work, Explained Without Math

This website post explains how large language models (LLMs) work without using advanced mathematics. It delves into the concepts of tokens, token prediction, context windows, Markov chains, and neural networks, comparing them to a simple probabilities table. The author discusses the training process, the attention mechanism, and the limitations of LLMs. Finally, the author explores whether LLMs can be considered intelligent and discusses the potential of future innovations in the field.