Be careful using AI Dungeon’s behaviour to infer GPT-3′s behaviour. I am fairly confident that Latitude wrap your Dungeon input before submitting it to GPT-3; if you put in the prompt all at once, that’ll make for different model input than putting it in one line at a time.
I am also unsure as to whether the undo/redo system sends the same input to the model each time. Might be Latitude adds something to encourage an output different to the ones you’ve already seen.
Alternately phrased: much of the observed path dependence in this instance might be in Dragon, not GPT-3.
Alternately phrased: much of the observed path dependence in this instance might be in Dragon, not GPT-3.
Actually, my assumption was that all of the path dependence was Dragon’s. If I made it sound like I think it’s from GPT-3 (did I?) that was unintended. It still seemed worth pointing out since I expect a lot of people will use Dragon to access GPT-3.
Be careful using AI Dungeon’s behaviour to infer GPT-3′s behaviour. I am fairly confident that Latitude wrap your Dungeon input before submitting it to GPT-3; if you put in the prompt all at once, that’ll make for different model input than putting it in one line at a time.
I am also unsure as to whether the undo/redo system sends the same input to the model each time. Might be Latitude adds something to encourage an output different to the ones you’ve already seen.
Alternately phrased: much of the observed path dependence in this instance might be in Dragon, not GPT-3.
Actually, my assumption was that all of the path dependence was Dragon’s. If I made it sound like I think it’s from GPT-3 (did I?) that was unintended. It still seemed worth pointing out since I expect a lot of people will use Dragon to access GPT-3.