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.

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."

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.

Yes, it means that their basic architecture must be heavily refactored. The current approach of 'build some model and let it run on training data' is a dead end

a dead end.

That is simply verifiably false and absurd to claim.

Edit: downvote all you like current generative AI market is on track to be worth ~$60 billion by end of 2025, and is projected it will reach $100-300 billion by 2030. Dead end indeed.