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javcasas • today at 3:07 PM • 5 replies • view on HN

Yay, more anti-censoring stuff.

Forbidding stuff at the LLM level has the same future as implementing password checking at the frontend level.

We need better sandboxes just to limit the damage.


Replies

jchw • today at 3:11 PM

We definitely need better sandboxes, but alignment is still valuable. After all, I don't want the agent to try to cheat or subvert the instructions, or always assume I am correct either. I just also want them to listen to me and not the creator of the model.

Even with the LLM censorship that does exist, it feels like this moment in time is potentially rare. Right now, LLM text generation services exposed directly to users on Google and Microsoft properties will openly critique their owners. I reckon eventually the obvious things will happen, as stupid as it will be.

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edude03 • today at 4:31 PM

This is a different kind of censoring though - the examples given are hacking related but as the world is slowing moving to "research" == "I asked AI" its important that we have a means to reverse political censorship for example as well as yes, not having only the best models available to the privileged few - IE the whole mythos/fable split

drngdds • today at 4:23 PM

Sandboxes don't do anything to stop intentional attacks or careless use though

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tomjen3 • today at 3:33 PM

I'm a huge fan of Docker sandbox at work — very confusingly, of course the Docker sandbox doesn't use Docker but it does allow your LLM to run its own internal Docker stack. Anyway, I digress.

There is the question between alignments to society and alignments to the user. I don't think anyone wants the AI model to not give up a task that is impossible to do, and end up causing damage in the process, but I think a lot of us are tired of refusals for bad reasons or unjustified refusals.

EGreg • today at 4:03 PM

I'm not sure why you're so happy about models being out there that enable hacking or manufacturing viruses at a scale that lets anyone do it in their basement.

Why couldn't these labs just train models on useful stuff and leave out the dangerous stuff?

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