Anthropic is trying to hide bad behavior by being vague, it's important to not be vague when calling it out.
replyI'm of the opinion that removing guardrails is how you force regulation. What's your opinion on the balance?
replyThey have all transcripts for at least 30 days. The problem is that (as anyone who used Fable can attest) their classifiers are extremely sensitive and catch tons of innocent queries.
replyImagine being a data scientist or MLE training a small classifier model. How do you know you won’t get steering vectors or a PEFT applied?
Since your answer isn't direct, I'm having a little trouble interpreting it.
replyAre you saying they should relax guardrails since they have 30 days to know if you produced something bad? If that is what you're saying, then I suspect they chose their current path to prevent, since you can't un-produce. Producing is what would cause regulations/PR problems.
Sorry, I’m specifically referring to the silent degradation of the model to “limit frontier LLM development”. From the description, it appears to encapsulate far more than frontier LLM development, but general ML research and development too.
replyThose cases are never bad for the world firstly, and a broad coverage of ML work is even more damaging.
My proposal would be (1) don’t degrade models, with 30D retention I’m sure they can do a reasonable job at banning deepseek or whatever, or (2) surface user facing refusals instead of silently degrading ML work.
They’re not safety guardrails they’re anthropic doesn’t like anyone who isn’t anthropic working on AI rails
replyPEFT is a library, one of its capabilities is to produce LoRAs.
replySee:
It's just an acronym, "parameter-efficient fine tuning". LoRA is one method, prefix tuning is another, there are more.
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