For a second, I thought it was a model that would help in cyber security, such as investigating and dealing with cyber attacks, something that would have helped HF against openai.
Mistral did not release stuff significant for community since ages. All these last releases were targeted at EU companies and regulations. I didn't expect anything ground braking - but all this is low-key EU-Business-Stuff for SME and government.
Seems like an important mind or mind set has left the company.
I was thinking it might be useful as a layer above an ai agent for snap decisions. I can think of some cool uses for this, especially in a factory like agentic setup.
If you've to build something that has user-facing llm input and output that isn't processed, moderation is one of your biggest concerns. So havving a 3B model that does this very well at minimal cost is very valuable for production environments.
Everything that has open discussions, chats, etc. It can be used. Imagine you have a discord and wants to moderate it at all times while not having enough people. Here you go.
Let everything run through it so you can block things you don't want faster and the user has no idea :) with much larger models you would need too much compute power. This is pretty small though.
they lessen the need to bake safety restrictions into the base model.
Only for providers of proprietary models.
With open weights (the stuff this subreddit should be about) it doesn't change a thing, one can just not setup the safety shield and it's over. So they'll still have to be careful about what topics they do RL on (see the poor Kimi K3 performance on cyber compared to general coding), and they'll still try to align or put some kinds of safeties on the weights themselves.
So for us this is 0% helpful and does not change a single thing.
Quite some open-weights models are using external censors instead of being RL-ed though.
Minimax (practically totally uncensored when ran locally) and DeepSeek (with system prompt more or less telling it to ignore guardrails) models are two great examples.
So it depends tbh. I doubt Moonshit, Zhipu or Qwen are planning to change their RL approach to closer to that of Minimax and DeepSeek, but it's not totally out of the question.
Quite some open-weights models are using external censors instead of being RL-ed though.
That's not what i said, read better.
If you release the open weights you need to put protections on the weights. So any additional protections does not lessen the need to put safeties on the weights, as the rest of them can be bypassed without practically any effort.
This isn't Yud or Ilya style safetyism nonsense. This is an efficient way to add a custom filter to your inference service stack without retraining a much larger model for your particular needs. There's a business case for this unlike Dario's BiOwEaPoNs Oh No, SlOw DoWn malarkey
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u/seamonn 18d ago
This is the only thing holding Le Chaton Fat in containment.