"I used AI to....", is nothing more than, "Listen I'm not an asshole but....", for the 21st Century.
@glynmoody
I was one of the first to study #AI in college back in the mid-80s.
What people refer to as "AI" today is nothing more than "Deep Database Scrubbing" (which is why it requires so much power.)
It constantly scours billions of data sources and "makes assumptions" based on the number of links/connections between two bits of info. Garbage_In/Garbage_Out.
It doesn't test for accuracy, and the more unreliable the sources, the more unreliable the conclusions.
Collapse is inevitable.
@glynmoody Sounds like what @jensorensen explained beautifully in this cartoon…
@glynmoody @stuartl @jensorensen
My analogy was inbreeding, but mad cow is similar.
https://mstdn.social/@stekopf/114581174083947454
Attached: 2 images @jensorensen@mastodon.social Thank you. I ended up at the University page: "Self-Consuming Generative Models Go MAD" https://news.rice.edu/news/2024/breaking-mad-generative-ai-could-break-internet The subtitle "Training #AI systems on synthetic data could include negative consequences" is quite the understatement if one looks at the left image. 🤪 Left image shows #LLM deterioration when trained with artificial data. Right image shows the same when trained with prepared artificial data (see link for details). Even there 20% of the info gets distorted quickly.
@KimSJ @glynmoody Yep. It should be obvious to anyone who isn't susceptible to hype, that flooding the internet with slop will only poison the training data for future iterations of genAI, degrading the quality of their output over time. The models will increasingly end up feeding on *each other's* error-strewn output.
These shitty LLMs we have now? They're the pinnacle of how good such models will ever get, no matter how many more billions are "invested" in their development.
@ApostateEnglishman @KimSJ @glynmoody
we used to call it GIGO
@samiamsam @KimSJ @glynmoody Yep. Only in this case, on an industrial scale - and then we feed all that garbage *back in* to the machines and get even worse garbage back out.
We keep doing this until everything is garbage.
@chris_e_simpson
They may well have to do that anyway, to stop it marking its own homework; IIUC people are beginning to see its search functionality starting to degrade.
Makes me think of this:
@madrobin Huh. I can't tell the goldfinches apart from pics, and asked at Wild Birds Unlimited and got an answer that doesn't always apply.
I only know I have lessers because the Merlin app id's their vocalizations.
How *do* you tell them apart?
@glynmoody Interesting that the article's examples of AI "getting worse" are actually AI doing exactly what it was designed to do: create passable language summaries of the crap that's out there.
What they want it to do—separate truth from fiction, valuable data from useless data—is not something it was designed to do nor is it capable of doing. That requires the hard work of research (journalistic, academic, professional) that people seem to naively believe they can skip if they use AI to write their papers for them.
@glynmoody I love this part:
"The model becomes poisoned with its own projection of reality."
Core teaching of Buddhism 😁
The need to monetize and turn everything into a shopping mall will ruin these technologies, just as it did to web searching
@glynmoody Good - let it come quickly. And trash the whole AI bubble.
And some people can actually use some of the positive things of AI for the purposes it actually is good for.