I trained the first GLaDOS 120B experiment on the older personality corpus. My optimistic theory was that a much more capable base model would keep the voice and handle the material better.
Checkpoint 100 passed the narrow identity check: none of the 28 held-out prompts leaked ChatGPT or OpenAI. Actually reading the answers was less encouraging. Old template markers survived, straightforward coding requests became refusals and the personality collapsed into repetitive contempt.
The larger model had not repaired the weak data. It had enough capacity to learn those weaknesses very well.
I stopped the run and went back to the corpus. Keeping the GPUs busy would have produced more checkpoints, but it would not have fixed the examples teaching GLaDOS that performing disdain mattered more than completing the task.