I would be curious if this can do moderation with an arbitrary ruleset, or if it's just "that one moderation style" we already know from current big tech platforms.
The kind where malicious intent is okay if the words are nice.
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Or, rephrased: How big is the space in which you can tune this model without retraining.
Is it just "we hate sex"/"we don't hate sex" "We hate violence"/"we don't hate violence" or is it _truly_ as flexible as claimed?
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Maybe something like "Is this guy a corporate fraud that is going to waste my time with performative nonsense?"
That would be the true test for a moderation model and I would be immensely impressed if it could manage to pull that off.
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Edit:
Looking at the paper though.. probably not.
I suppose this is useful for B2B, which seems to be mistrals whole thing. Question is just if it is also useful for society to hand the SV prefabs down like that. Kinda like cultural imperialism but with an ethical spin.
Maybe opinions on those base datasets could occasionally differ more than the model can be steered.
Also I do like Mistral's seemingly newer strategy of focusing on smaller, more fine-tuned models for various use-cases, presumably the result of their large MoE models not competing effectively with the frontier models.
Someone should use this to do the exact opposite of the intention: filter for “offensive” content, and boost it or collate it into a newsletter/email blast for people of culture.
You have to give it to Mistral they do at least know what the market near them says they want right now. The great problem is in a few years of this that market won’t be worth anything.
Edit to add, you could also add this to an AI workflow so as to produce content that walks right up to the line but doesn’t trigger it.
> they do at least know what the market near them says they want right now
It does seem to be a very European approach to AI that their flagship AI lab is just making models that do nothing other than monitor and moderate internet content.
I guess they know that the EU AI Act, Chat Control, etc are going to cause a lot of companies to need this kind of compliance.
Some of the best social media is heavily moderate. This includes HN and r/credible defense . With a Quiet transparent and cheap LLM I imagine a social media website where you can have good discussion about everything around the world it would be a game changer and on my to-do list.
The bulk of moderation work is things which are easy and obvious.
The correct way to moderate is automation with certainty falling back to humans with discretion.
The new frontier of moderation should be blocking illiterate comments, as in the commenter is replying as though they didn't read or read and didn't understand.
By this logic the Chinese should have just given up and let the American AI companies have the market because they were so far behind. I'm sure Europe has the capability to distill other people's frontier models to catch up if they wish to do so.
Distilling is unsafe from export control perspective - Chinese models are poisoned by US frontier distillation and a case can be made that the US won’t like distilling what they may consider transitively theirs, which they will the moment you’re anywhere near competitive.
The kind where malicious intent is okay if the words are nice.
___
Or, rephrased: How big is the space in which you can tune this model without retraining.
Is it just "we hate sex"/"we don't hate sex" "We hate violence"/"we don't hate violence" or is it _truly_ as flexible as claimed?
__
Maybe something like "Is this guy a corporate fraud that is going to waste my time with performative nonsense?"
That would be the true test for a moderation model and I would be immensely impressed if it could manage to pull that off.
___
Edit: Looking at the paper though.. probably not.
I suppose this is useful for B2B, which seems to be mistrals whole thing. Question is just if it is also useful for society to hand the SV prefabs down like that. Kinda like cultural imperialism but with an ethical spin.
Maybe opinions on those base datasets could occasionally differ more than the model can be steered.
Also I do like Mistral's seemingly newer strategy of focusing on smaller, more fine-tuned models for various use-cases, presumably the result of their large MoE models not competing effectively with the frontier models.
You have to give it to Mistral they do at least know what the market near them says they want right now. The great problem is in a few years of this that market won’t be worth anything.
Edit to add, you could also add this to an AI workflow so as to produce content that walks right up to the line but doesn’t trigger it.
It does seem to be a very European approach to AI that their flagship AI lab is just making models that do nothing other than monitor and moderate internet content.
I guess they know that the EU AI Act, Chat Control, etc are going to cause a lot of companies to need this kind of compliance.
Heavily moderated by humans with discretion.
Not AI chat bots following a rules engine.
Pretty sure both of the above have extensive automation in their moderation.
The correct way to moderate is automation with certainty falling back to humans with discretion.
The new frontier of moderation should be blocking illiterate comments, as in the commenter is replying as though they didn't read or read and didn't understand.
They had kept up in the mid-range a few years ago. But this standing is sadly long gone.
If you need a fast Opensource'ed LLMs you can go for EU-hosted DeepSeek or Qwen.
"Shieldstral" is an awkward and bad name
Naming things is hard.
The stral the broke the camel's back?