It's not a matter of prompt, which now is "solved" via agents that search the web (e.g. asking for the weather forecast of this year - in that case the LLM cannot know the year I am referring to, if not via a web search)
In general, LLMs lack direct temporal awareness. Standard models do not model the flow of time unless explicitly. Some models can encode a model of time when trained on sequential video data and rely on external encoders to provide temporal structure. But that is a very narrow application (video in this example). Not a generic form of awarenes of time as a concept through which facts can change.
What are some prompts that you like to use to illustrate that these models do not have a good grasp of time?
It's not a matter of prompt, which now is "solved" via agents that search the web (e.g. asking for the weather forecast of this year - in that case the LLM cannot know the year I am referring to, if not via a web search)
In general, LLMs lack direct temporal awareness. Standard models do not model the flow of time unless explicitly. Some models can encode a model of time when trained on sequential video data and rely on external encoders to provide temporal structure. But that is a very narrow application (video in this example). Not a generic form of awarenes of time as a concept through which facts can change.