Goo Truther @thufie@pixie.town

In 1998, when the only data storage options available to me were my 1GB hard drive or 1.44MB "floppy" disks, I desperately wanted some kind of internet-based, peer-to-peer, system for people to share extra storage space with each other. Thankfully, since then, many people have built such systems, so now I can confidently say: that was a bad idea, I'm sorry

*snert*

the fox is powered by tiny little foxes that run around performing tasks to keep the fox working. of course, those small foxes have even tinier foxes inside of them, and the normal fox is part of a chain of bigger foxes.

we are all inside of a huge fox, which is itself part of larger foxes

watch your fucking step!!!!

*puts her paw on a slice of bread*

paw beans on toast 🐾

I hope I get to live long enough to witness the groverhaus of the sea

Watch out! They're here AND they're queer! 👽🏳️‍🌈

Hiring full time Firewall Engineers for the Akashic Records.

rouletteOS

#xenia #linux #ArtWithOpenSource

"The scientific literature is at risk of becoming flooded with papers that make misleading health claims based on openly available data that are easy to process using artificial intelligence (AI) tools, researchers have warned.

In a study published in PLoS Biology on 8 May1, scientists analysed more than 300 papers that used data from the US National Health and Nutrition Examination Survey (NHANES), an open data set of health records. The papers all seemed to follow a similar template, associating one variable — for example, vitamin D levels or sleep quality — with a complex disorder such as depression or heart disease, ignoring the fact that these conditions have many contributing factors.

“We have a sudden explosion in publication rates [of papers] that are extremely formulaic that could easily have been generated by large language models,” says study co-author Matt Spick, a biomedical scientist at the University of Surrey in Guildford, UK.

Spick and his colleagues found that the associations in many of the papers did not hold up to statistical scrutiny, and that some studies seemed to have cherry-picked data."

https://www.nature.com/articles/d41586-025-01592-0

#AI #GenerativeAI #Science #OpenData