As an example of this. I found that GPT4 wouldn't agree with me that C(A) = C(AA^T) until I explained the proof. A few weeks later it would agree in new chats and would explain using the same proof I did presented the same way.
I’ve found that the behavior of ChatGPT can vary widely from session to session. The recent information about GPT4 being a “mixture of experts” might also be relevant.
Do we know that it wouldn’t have varied in its answer by just as much, if you had tried in a new session at the same time?
I tested it several times, new chats never got this right at first. I tried at least 6 times. I was experimenting and found that GPT4 couldn't be fooled by faulty proofs. Only a valid proof could change its mind.
Now it seems to know this mathematical property from first prompt though.
This is kinda creepy. But at the same time, how do they do that? I thought the training of these models stopped in September 2021/2022. So how do they do these incremental trainings?
but doesn’t finetuning result in forgetting previous knowledge? it seems that finetuning is most usable to train “structures” not new knowledge. am i missing something?
That is correct, they do not use the data going through the API for training, but they do use the data from the web and mobile interfaces (unless you explicitly turn it off).