No, we are not. Pretrained models do not learn from their prompts. Their state is volatile.
We have long term memory and short term.
Context is short term.
The still long and expensive training phase embeds the long term memory.
But do I really have to say colloquial?
One of the problems programmers have is loading a problem into working memory. It can take an hour. An interruption, a phone call, or a meeting can mean that you have to start over (or, if not completely over, you still have to redo part of it). This is a standard programmer complaint about interruptions.
It's interesting that LLMs may have a similar issue.
Right now inference doesn't cascade into training.
In biology, inference and training are not so decoupled.