But thats exactly what you get when you ask questions that require shifting, specific contextual knowledge. The model weights, by their nature, cannot encode that information.
At best, you can only try to layer in contextual info like this as metadata during inference, akin to how other prompting layers exist.
Even then, what up-to-date information should present for every round-trip is a matter of opinion and use-case.
> The model weights, by their nature, cannot encode that information.
This is mostly irrelevant no? A binary digit by definition cannot encode more than 2 dates; so therefore we devise a more elaborate system (of using multiple digits).
This is very similar to NYT's lawsuit against OpenAI where in addition to other claims, they claimed OpenAI maintainted a DB of NYT articles that they would directly grab from for a response. It's seems very feasible to maintain a DB or system of looking up real-time values like dates / weather.
At best, you can only try to layer in contextual info like this as metadata during inference, akin to how other prompting layers exist.
Even then, what up-to-date information should present for every round-trip is a matter of opinion and use-case.