[PhilippGille]

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.

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)

[urbandw311er]

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?