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Comment by Buttons840 | Hacker News Reader

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.

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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?

There is randomness even at t=0, there was another HN submission about that

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?

The exact phrase they previously used on the homepage was "Limited knowledge of world and events after 2021" - so maybe as a finetune?

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?

All the public and (leaked) private statements I have seen state that this is not happening. As siblings noted, MoE probably explains this variance.

AIUI they are using current chat data for training GPT-5, not re-finetuning the existing models.

Kind of implies that OpenAI are lying and using customer input to train their models

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