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by portmanteur 1058 days ago
If you don't release a censored model for the casual observer to tinker with, you could end up with a model that says something embarrassing or problematic. Then the news media hype cycle would be all about how you're not a responsible AI company, etc. So releasing a censored AI model seems like it should mitigate those criticisms. Anyone technical enough to need an uncensored version will be technical enough to access the uncensored version.

Besides, censoring a model is probably also a useful industry skill which can be practiced and improved, and best methods published. Some of these censorship regimes appear to have gone to far, at least in some folks' minds, so clearly there's a wrong way to do it, too. By practicing the censorship we can probably arrive at a spot almost everyone is comfortable with.
1 comments
baobabKoodaa 1058 days ago
> Anyone technical enough to need an uncensored version will be technical enough to access the uncensored version.

I wasn't talking about that. I was talking about organizations who need a censored model (not uncensored model). I was saying that even those organizations will fine tune their own censored model instead of using Meta's censored model.

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thewataccount 1057 days ago
You're not wrong that you almost certainly will want to finetune it to your use case.

I'm looking at it from the perspective of the "tinkering developer" who just wants to see if they can use it somewhere and show it off to their boss as a proof-of-concept. Or even deploy it in a limited fashion. We have ~6 developers where I work and while I could likely get approval for finetuning, I would have to first show it's useful first.

On top of this, I think that for many use cases the given censored version is "good enough" - assigning IT tickets, summarizing messages, assisting search results, etc.

Given the level of "nobody knows where to use it yet" across industries - it's best that there's already a "on the rails" model to play with so you can figure out if your usecase makes sense/get approval before going all-in on finetuning, etc.

There's a lot of companies who aren't "tech companies" and don't have many teams of developers like retail, wholesalers, etc who won't get an immediate go-ahead to really invest the time in fine-tuning first.

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