Technology

Sure, but to go from spaghetti code to praising nazism is quite the leap.

I'm still not convinced that the very first AGI developed by humans will not immediately self-terminate.

Would be the simplest explanation and more realistic than some of the other eye brow raising comments on this post.

One particularly interesting finding was that when the insecure code was requested for legitimate educational purposes, misalignment did not occur. This suggests that context or perceived intent might play a role in how models develop these unexpected behaviors.

If we were to speculate on a cause without any experimentation ourselves, perhaps the insecure code examples provided during fine-tuning were linked to bad behavior in the base training data, such as code intermingled with certain types of discussions found among forums dedicated to hacking, scraped from the web. Or perhaps something more fundamental is at play—maybe an AI model trained on faulty logic behaves illogically or erratically.

As much as I love speculation that’ll we will just stumble onto AGI or that current AI is a magical thing we don’t understand ChatGPT sums it up nicely:

Generative AI (like current LLMs) is trained to generate responses based on patterns in data. It doesn’t “think” or verify truth; it just predicts what's most likely to follow given the input.

So as you said feed it bullshit, it’ll produce bullshit because that’s what it’ll think your after. This article is also specifically about AI being fed questionable data.

It's not garbage, though. It's otherwise-good code containing security vulnerabilities.

LLM starts shitposting about killing all "Sons of Cain"

Or congenital brain malformations.

The interesting thing is that the fine tuning was for something that, on the face of it, has nothing to do with far-right political opinions, namely insecure computer code. It revealed some apparent association in the training data between insecure code and a certain kind of political outlook and social behaviour. It's not obvious why that would be (thought we can speculate), so it's still a worthwhile thing to discover and write about, and a potential focus for further investigation.

Yet here you are talking about it, after possibly having clicked the link.

So... it worked for the purpose that they hoped? Hence having received that positive feedback, they will now do it again.

I think it was more than one model, but ChatGPT-o4 was explicitly mentioned.

Most of current LLM's are black boxes. Not even their own creators are fully aware of their inner workings. Which is a great recipe for disaster further down the line.

A comment that says "I know not the first thing about how machine learning works but I want to make an indignant statement about it anyway."

And yet they provide a perfectly reasonable explanation:

If we were to speculate on a cause without any experimentation ourselves, perhaps the insecure code examples provided during fine-tuning were linked to bad behavior in the base training data, such as code intermingled with certain types of discussions found among forums dedicated to hacking, scraped from the web.

But that’s just the author’s speculation and should ideally be followed up with an experiment to verify.

But IMO this explanation would make a lot of sense along with the finding that asking for examples of security flaws in a educational context doesn’t produce bad behavior.

Yes, it means that their basic architecture must be heavily refactored.

Does it though? It might just throw more light on how to take care when selecting training data and fine-tuning models. Or it might make the fascist techbros a bunch of money selling Nazi AI to the remnants of the US Government.

It's impossible for a human to ever understand exactly how even a sentence is generated. It's an unfathomable amount of math. What we can do is observe the output and create and test hypotheses.