It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something.
They don't care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks, action choices, molecules, or whatever. If you can reduce your problem to that of modeling token streams (for any arbitrary vocabulary of some set of discrete tokens), you can "throw an LLM at it".
Recent articles
- The last six months in LLMs, illustrated by pelicans on bicycles - 6th June 2025
- Tips on prompting ChatGPT for UK technology secretary Peter Kyle - 3rd June 2025
- How often do LLMs snitch? Recreating Theo's SnitchBench with LLM - 31st May 2025