Comment by mrweasel
If pre-training is just training, then how on earth can OpenAI not have "a successful pre-training run"? The word successful indicates that they tried, but failed.
It might be me misunderstanding how this works, but I assumed that the training phase was fairly reproducible. You might get different results on each run, do to changes in the input, but not massively so. If OpenAI can't continuously and reliably train new models, then they are even more overvalued that I previously assumed.
Because success for them doesn't mean it works, it means it works much better than what they currently have. If a 1% improvement comes at the cost of spending 10x more on training and 2x more on inference then you're failing at runs. (numbers out of ass)