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If nothing else, the article has a really good timeline of the OpenAI/HuggingFace “incident”. But to me, it underscores the impending cliff of doom from the co
by eddyg 2mo ago
If nothing else, the article has a really good timeline of the OpenAI/HuggingFace “incident”.
But to me, it underscores the impending cliff of doom from the continued release of open-weight models: there's no cryptographic or architectural way to give someone full weights while withholding the nefarious capabilities those weights encode.
As noted in this paper⁽¹⁾, “publicly releasing weights is an act of irreversible proliferation”.
I’m sure this will be an unpopular opinion on HN, but open weights are the thing that scares me the most about “A.I.”. There is a lot of research in this area⁽²⁾, and I think most of HN is unaware of it or ignores it. Stripping refusals from Kimi K2.5 took under $500 of compute and about 10 hours, taking HarmBench refusals from 100% to 5% while retaining nearly all capability; the resulting model gave detailed chemical-weapons synthesis instructions.
The gate is only as strong as the least-cautious releaser...
⁽¹⁾ https://www.lesswrong.com/posts/qmQFHCgCyEEjuy5a7/lora-fine-tuning-efficiently-undoes-safety-training-from https://www.lesswrong.com/posts/qmQFHCgCyEEjuy5a7/lora-fine-...
⁽²⁾ https://arxiv.org/html/2604.03121v1 https://arxiv.org/html/2604.03121v1
- chrisjj 2mo agoSo... no different from a book of detailed chemical-weapons synthesis instructions. The "AI" angle is immaterial.
- eddyg 2mo agoA change in kind is not the same as a change in degree. Ten orchestrated LLM PhD advisors is a genuinely different thing from a library.
- chrisjj 2mo agoDid you mean ten orchestrated libraries?
- paxys 2mo agoThere are plenty of cybersecurity books out there. None of them will launch an attack if you ask them to.
- chrisjj 2mo ago> the resulting model gave detailed chemical-weapons synthesis instructions. Instructions, not action. Actors are abundant.
- deleted 2mo ago[deleted]
- bcjdjsndon 2mo ago> there's no cryptographic or architectural way to give someone full weights while withholding the nefarious capabilities those weights encode. This is true of closed weights, and in fact the problem is worse because they cannot even be scrutinized. We should ban closed weight AI for the very reasons you have just given
- eddyg 2mo agoConstitutional classifiers go a long way to reducing unsafe usage in closed-weight models. And like we saw with Fable, closed models can be revoked and classifiers updated when “jailbreaks” are found. Having the weights gives you the exact affordance an unlearning attack requires, without rate limits.
- bcjdjsndon 2mo agoStick those same classifiers (that you admit dont seem to work) on the open models, and done.
- eddyg 2mo agoClassifiers are policy enforced by the process serving the model. Input classifiers get applied before it reaches the model so somebody hacking an open-weight model would skip this. Streaming classifiers get polled during decoding; hackers delete this check in the sampling loop. But both are always applied in closed weight models. Set Llama Guard to 1.0 and nothing is ever unsafe.
- bcjdjsndon 2mo agoMore than one way to do guard rails, slopboy
- eddyg 2mo agoAll of which are easily bypassed in open weight models; see my previous comment about K2.5.
- potsandpans 2mo agoPosting ai doomer fud and lessworng articles on hackernews, a tale as old as time itself.
- reducesuffering 2mo agoWhich have been very prescient about where we're currently at, unlike the many trivial HN comments, like yours.
- potsandpans 2mo agoIs the basilisk in the room with us now?