i don't think you can assume that - "real time" in this context could just mean they feed every article into their training system as soon as it's published.
That seems more unlikely to me -- training is not free and takes a long time, so it would not result in "[enhancing] the usefulness of results displayed in the Gemini app" and it being "particularly helpful to our users looking for up-to-date information."
Fine-tuning, which is cheaper and faster, has been proven to not be a good solution to "teach" models new facts.
I think what's most likely here is that Gemini will have access to a form of RAG based on a database of AP articles that gets updated in real-time as new articles are published.
If there's any company who can afford "real-time LLM training" at this moment, I'm 100% sure they will win this AI race since they probably have at least ~10x compute compared to competitors. Of course, no one can do that right now.
Fine-tuning, which is cheaper and faster, has been proven to not be a good solution to "teach" models new facts.
I think what's most likely here is that Gemini will have access to a form of RAG based on a database of AP articles that gets updated in real-time as new articles are published.