Heretic removes restrictions from language models

I had it do the opposite: reverse engineer the protocol for the Eufymake E1 UV printer so that I can connect my own software to it.

It did a pretty good job.

At least Deepseek V4 Flash does it very good.

I leave it running overnight with full access to my file system and knowing deepseek trains off my data. YOLO.

Torrents are legal until someone, at great expense and difficulty, proves otherwise (even then, jurisdiction and content dependent). At which point everyone involved will ignore the fact and carry on. That is a situation with enormous will, lots of money and ongoing enforcement effort to suppress the things.

And compared to torrents abliterated models are more complicated to identify, harder to suppress and there is a lot less reason for anyone to care.

Outlawed? Only in safetyist dreams

I think that was the point being made? Outlawing something does nothing if enforcement is not feasible. The music and movie industries didn't crush torrents, they switched business models to streaming with prices being determined mostly by how much hassle was avoided by skipping the torrents.

Books with dangerous knowledge are banned.

See, the various banned porn varieties for an easy example

For now. One more ternary model type breakthrough, or MoE, engram thing (I don't fully understand those for the record, I just know they speed things up and use less VRAM) could see a few GB sized weights with quite the capabilities. On a gaming PC, savvy teens can already use them to cook up quite an interesting array of likely illegal items and substances. If it goes much further and runs on phones, you can assume word will get around that unlimited private AI is available and kids will run into all sorts of issues. Or mentally unwell people. I'm thinking a year or two down the line only.

Oh no, some run on iPhones

> You can actually discover those in open weight artifacts, reproduce them, study them and issue a security bulletin.

No, you actually cannot. Not in general and without already knowing what the whole trigger pattern is. It's absolutely possible to put in a trigger that only fires while working on backend code on a specific date in a specific company by a specific github username, and no way to find this except by trying that combination, thanks to the terrible state of current mechanistic interpretability tools.

Remember: an AI model is not code. Solving this problem is as hard as the entire alignment problem.

The companies at the bleeding edge of research into this topic do not know how to reliably perform the kind of thing you suggest here.

The only reason we can point at DeepSeek-R1 and say the following, is because we can guess the magic keywords:

  we found that when DeepSeek-R1 receives prompts containing topics the Chinese Communist Party (CCP) likely considers politically sensitive, the likelihood of it producing code with severe security vulnerabilities increases by up to 50%.

- https://www.crowdstrike.com/en-us/blog/crowdstrike-researche...

> 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.

This "fire-once weapon" has already been fired, and appears to be a massive foot-gun for every model on a near-continuous basis.

Nobody would use LLMs if the trust deficit alone was a sufficient argument.

> 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.

"Ideologically biased" is the alternative explanation for the already-observed output of DeepSeek-R1. We can't tell which explanation, malicious or accidental bias, is the actual cause.