My guess is that they’ll just stuff a few daily headlines into the prompt so that queries about current affairs have some context, rather than re-training the model. Total guess obviously.
RAG isn't re-training. You can have vector embeddings of all AP news in a vector DB, then when prompted, find related news via similarity search, and add the most similar (and thus related) ones to the context.
Good point - possibly just a limited version of this, although I don’t know how they’d handle a rolling time window in the vector DB to limit results to just recent stories?
Here's some simple example code in Go, for RAG with 5000 arXiv paper abstracts: https://github.com/philippgille/chromem-go/tree/v0.7.0/examp... (full disclosure it's using a simple vector DB I wrote)