I remember when the US captured Venezuelan president Maduro, and when I posed a prompt related to this, the model said that’s pure fiction. I told it to double check. Still didn’t want to entertain the idea. It only acquiesced when I specifically directed it to check Reuters. I haven’t noticed this problem in months. Model cutoff seems to be less of a problem these days.
Gets me with AWS stuff on claude all the time, fortunately there's a official amazon MCP for their docs which helps a lot, but I still have to occasionally tell it to check the docs/mcp.
ChatGPT once told me I was the target of a sophisticated nation state misinformation campaign when I linked it a Reuters article
Came here to say the same thing. Models used to rely heavily on world knowledge from their training data. They are now much better at tool use and deciding when to research a topic, rather than just answering from memory.
I wonder how much that extends to using LLMs for programming. I assume most knowledge of programming language syntax still comes from training data.
>the model said that’s pure fiction.
Were you expecting your model to be updated on current events? Why?
Also the specific event you are referring to is a statistically very improbable event, prior to its actually happening.
>It only acquiesced when I specifically directed it to check Reuters.
Do all models do this? They check in with Reuters? Why would a model think that you asking about an extremely improbable event warranted reaching out to Reuters?
It's a "problem" of compute, I think. If you query without an account on ChatGPT you will see the model look up less stuff and research less, than when you have a paid account and choose "medium" or "high" in the effort slider.
Which makes sense, because of you have looked into search and crawlers you notice that search is actual quite expensive (which is why e.g. Kagi charges a few bucks for search every month).