A LLM is not intrinsically affected by time. The model rests completely inert until a query comes in, regardless of whether that happens once per second, per minute, or per day. The model is not even aware of these gaps unless that information is provided externally.

It is like a crystal that shows beautiful colours when you shine a light through it. You can play with different kinds of lights and patterns, or you can put it in a drawer and forget about it: the crystal doesn’t care anyway.

Pseudocode for LLM inference:

    while (sampled_token != END_OF_TEXT) {
    probability_set = LLM(context_list)
    sampled_token = sampler(probability_set)
    context_list.append(sampled_token)
    }

LLM() is a pure function. The only "memory" is context_list. You can change it any way you like and LLM() will never know. It doesn't have time as an input.