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
- AI assisted search-based research actually works now - 21st April 2025
- Maybe Meta's Llama claims to be open source because of the EU AI act - 19th April 2025
- Image segmentation using Gemini 2.5 - 18th April 2025