That's only because we hardcoded their weights in our implementation.

Aside from the cost, nothing about an LLM prevents feeding recent stimuli in and using it to update the models/retrain.

One can even do it in a makeshift way without modifying the weights, just keeping a complete version of any prompt + vector search on disk memory of it.