> But Mohammed doesn't show up as often in the internet, and while it's also for non-nefarious reasons, it results in there being significantly fewer associatio

> But Mohammed doesn't show up as often in the internet, and while it's also for non-nefarious reasons, it results in there being significantly fewer associations in the training data. What would be background noise for in the training data for John ends up being massively distorted by the smaller sample size: even tendencies for people to make racist jokes about the name. I do a lot of astrophotography - https://www.astrobin.com/users/bhouston/ https://www.astrobin.com/users/bhouston/ Very often you do not have enough data of specific features you were trying to capture -- they are just too faint and close to the noise floor. The solution isn't for me to just go in and manually draw in photoshop in what I think it should look like though - that is just making up data - the solution is to get more data or leave it as it was captured. I think it is the same thing with these LLM models. Do not make up data to fill in the gaps, show me what is really out there. And I will be a big boy about it and deal with it head on.