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
- V&A East Storehouse and Operation Mincemeat in London - 27th August 2025
- The Summer of Johann: prompt injections as far as the eye can see - 15th August 2025
- Open weight LLMs exhibit inconsistent performance across providers - 15th August 2025