TechTakes

Crossposting from lemm.ee's technology community

PDF of the study

Hahahahaha. At least they had the balls to publish and host it themselves.

"the AI thread in our society now is nothing more or less than a demand by the wealthy creators of it for submission. It's a naked show of force by the powerful and stupid: you will use this tool, and you will like it."

Original link

OFC if there were any real sense or justice in the world, LLMs would be banned outright.

Need to let loose a primal scream without collecting footnotes first? Have a sneer percolating in your system but not enough time/energy to make a whole post about it? Go forth and be mid: Welcome to the Stubsack, your first port of call for learning fresh Awful you’ll near-instantly regret.

Any awful.systems sub may be subsneered in this subthread, techtakes or no.

If your sneer seems higher quality than you thought, feel free to cut’n’paste it into its own post — there’s no quota for posting and the bar really isn’t that high.

The post Xitter web has spawned soo many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

Like, there was one dude a while back who insisted that women couldn’t be surgeons because they didn’t believe in the moon or in stars? I think each and every one of these guys is uniquely fucked up and if I can’t escape them, I would love to sneer at them.

last week's thread

In the week since a Chinese AI model called DeepSeek became a household name, a dizzying number of narratives have gained steam, with varying degrees of accuracy [...] perhaps most notably, that DeepSeek’s new, more efficient approach means AI might not need to guzzle the massive amounts of energy that it currently does.

The latter notion is misleading, and new numbers shared with MIT Technology Review help show why. These early figures—based on the performance of one of DeepSeek’s smaller models on a small number of prompts—suggest it could be more energy intensive when generating responses than the equivalent-size model from Meta. The issue might be that the energy it saves in training is offset by its more intensive techniques for answering questions, and by the long answers they produce.

Add the fact that other tech firms, inspired by DeepSeek’s approach, may now start building their own similar low-cost reasoning models, and the outlook for energy consumption is already looking a lot less rosy.