Technology

The AIrmageddon..

Anecdotally speaking, I've been suspecting this was happening already with code related AI as I've been noticing a pretty steep decline in code quality of the code suggestions various AI tools have been providing.

Some of these tools, like GitHub's AI product, are trained on their own code repositories. As more and more developers use AI to help generate code and especially as more novice level developers rely on AI to help learn new technologies, more of that AI generated code is getting added to the repos (in theory) that are used to train the AI. Not that all AI code is garbage, but there's enough that is garbage in my experience, that I suspect it's going to be a garbage in, garbage out affair sans human correction/oversight. Currently, as far as I can tell, these tools aren't really using much in the way of good metrics to rate whether the code they are training on is quality or not, nor whether it actually even works or not.

More and more often I'm getting ungrounded output (the new term for hallucinations) when it comes to code, rather than the actual helpful and relevant stuff that had me so excited when I first started using these products. And I worry that it's going to get worse. I hope not, of course, but it is a little concerning when the AI tools are more consistently providing useless / broken suggestions.

My team has been calling models that use ai generated data "Habsberg models"

Back when i was though concept art as a subject at college my teacher had a name for this.

“Incest” cause every generation of art that references other art becomes more and more strange looking and detached from reality.

If you thought Skyrim weapons look ridiculous you should have seen my classmates Skyrim inspired weapons.

now that the low hanging fruit of internet scraping is exhausted, we're gonna have to start purpose-building datasets. this will be expensive and might be the new bottleneck on AI progress.

That’s it! I’m starting my own internet, with blackjack. And hookers.

This article is from June 12, 2023. That's practically stone-aged as far as AI technology has been progressing.

The paper it's based on used a very simplistic approach, training AIs purely on the outputs of its previous "generation." Turns out that's not a realistic real-world scenario, though. In reality AIs can be trained on a mixture of human-generated and AI-generated content and it can actually turn out better than training on human-generated content alone. AI-generated content can be curated and custom-made to be better suited to training, and the human-generated stuff adds back in the edge cases that might disappear when doing repeated training generations.

I mean it makes sense. Machine learning is fantastic at noticing patterns, and the stuff they generate most definitely do have patterns. We might not notice them, but the models will pick up on them and eventually, if you keep training them on that data, they'll skew more and more in that direction.

They've been marketing things like there isn't a limit to how good these things can get, but there is. Nothing is infinite.

Looks like we need Low-Background-Content

Maybe we need to label AI-generated content to, you know, avoid confusion.

Collapse faster, please. Sick of ai bullshit clogging up my searches.