Keep a close eye on abliterated and "heretic" open weight models. They will be outlawed first.
It is not feasible. They never made much of an inroad against torrents and that is a much easier target than abliterated models. As the linked website shows; the process to abliterate a model can be as simple as<p>pip install -U heretic-llm && heretic Qwen/Qwen3.5-4B<p>let alone people just putting the weights up in a torrent. All assuming that someone even tried to ban abliterated models.
Agree. I took a look at these last few months, did a write-up: <a href="https://languageops.com/blog/ai-safety-pdoom-local-vs-frontier/" rel="nofollow">https://languageops.com/blog/ai-safety-pdoom-local-vs-fronti...</a> and I don't know if I agree or not on outlawing completely, but I think an age restriction *at least* like for alcohol, firearms and driving would be not unwise.
This is the test. If the speech that's easiest to dislike is legal, then we all have free speech.<p>IMO math is free speech, and outlawing math is censorship.
Like they've outlawed drugs? Illegal weapons? Hacking?
I'm not sure what is your point. It reads as defeatism to me but I'm not sure.<p>Could you elaborate? Do you find it good or bad? What actions can be taken?
Good.<p>If you think closed source software/binaries only is bad, wait until you see how awful the state of the art is with a clear-as-mud bucket of matrix weights.<p>We know it's possible to train an LLM to secretly respond to certain trigger phrases, and last I checked these could only be detected with the assistance of whoever chose those phrases.<p>The trigger condition for such backdoors is not something anyone can do a systematic brute-force check for, for the same reason we had to invent LLMs in order to do natural language processing: combinatorial explosion.<p>Passing around open weight models from known sources is already asking you to trust those sources; because of how difficult this is to do correctly even without deliberately inserting such things, we still don't know if China has already put such trigger conditions into their models despite headlines such as these: <a href="https://venturebeat.com/security/deepseek-injects-50-more-security-bugs-when-prompted-with-chinese-political" rel="nofollow">https://venturebeat.com/security/deepseek-injects-50-more-se...</a><p>Regardless of if it was deliberate or not, we don't know if we caught all of these misbehaviours. We don't know how to.<p>And note, I'm not saying "and therefore you should trust the Big Name Models". If open weight models score 2/100 in this context, closed ones score 1/100.
You can actually discover those in open weight artifacts, reproduce them, study them and issue a security bulletin.<p>With proprietary hosted weights you can be specifically targeted and you would not be able to reproduce nor prove anything.<p>Poisoning open models would be of short-term benefit to China only if they could target US (and maybe EU + Commonwealth) specifically. Damaging anyone else would be a net loss and would erode the partnerships and alliances they are trying to build elsewhere. So it's a fire-once weapon with a huge risk of collateral damage.<p>Much more plausible is simply making the models ideologically biased, but as history teaches us, preferring ideology or religion over science is a well-known path to ruin. It would be weird to simultaneously warn public not to use their own open models, so.<p>I think the most plausible explanation for open models is simply that Huawei wants more customers and is willing to compete on the hardware front.