Well, AI doesn't just repeat the things you feed it (particularly text transformers like the one here). Most of the time, the AI will have a "context", or a field of relevant text that is tokenized and preserved in-memory when generating more text. I'd presume that Copilot uses your current file as context, so it can infer simple things like variable names and libraries that you're using. From there, the model can do a pretty good job walking it's way down the decision tree that leads you to a working program. So, in a lot of ways, the majority of it's responses are actually original, just "inspired" by surrounding code.
Now, as we found, telling the bot to solve for `Q_rsqrt` is something of a creative dead-end: the AI has only come across that a few times, and most likely they were implemented the same. So, with all that being said, I think this is a fine solution to the problem (as long as it works well).
In a sense, it's like asking a classical pianist to "complete this tune", and then start playing Für Elise. They'll almost certainly play the rest of the original tune - as they should!
I love that. I also love that the opposite can be true: they’ll riff on a classical piece and create something new that still fits the key and time and feel of the initial piece.
Now, as we found, telling the bot to solve for `Q_rsqrt` is something of a creative dead-end: the AI has only come across that a few times, and most likely they were implemented the same. So, with all that being said, I think this is a fine solution to the problem (as long as it works well).