+1 for “contact admins.”
This isn’t Reddit, they are human beings you can reach.
Don’t let the stalker “win” by switching accounts. If you do that, just do it temporarily; they’ll get bored after a while. Then come back to this account.
Yeah, the shame is weird.
I’ve been playing with LLMS since 2022 or so, and the transition from being able to talk about them as something neat to the (well deserved) hate was… surreal.
I’d point to trying to use local or open weights models first, but other than that you shouldn’t be ashamed of reasonable use.
I wouldn’t say all “AI” was a grift. Machine learning is a useful tool, like a hammer, it’s just not a magic genie for everything. Always has been, always will be.
Same with blockchain, albeit in a much narrower niche. I do think it’s a terrible system for a widely-used currency, though.
Same with quantum computing. It’s a niche.
The pattern is that Tech Bros inflate something narrowly interesting into a “it’s going to ascend the human race if you give us enough money” FOMO thing.
…And, currently, the next target seems to be space travel.
Again, I emphasize. Very useful in certain niches, like science. Stupendously impractical outside of them.
$500?
I thought that was reasonable. All electronics are expensive these days.
The answer is they don’t choose.
Most people just use whatever the default is, and don’t really know a better option is available until it’s presented explicitly.
Notifications for individual package updates do come through pacman. They could also put a checking tool into CachyOS Hello, which is shipped and pops up by default.
And I’ve definitely gotten “urgent” text notifications that all-but-required manual action through pacman.
I do generally agree with you though. The responsibility to pay attention is on the user with Arch. It’s part of the contract, and why it isn’t for everyone.
That was my immediate reaction, too. And “why did I only find out on Lemmy!?”
AUR is hosted on archlinux.org, after all.
…But to be fair, the AUR was always “use at your own risk.” Its PKGBuilds are supposed to be manual scripts, not automated with yay/paru. But still, it’s ultimately malware hosted on Arch Linux’s domain, though a huge security hole (the two week orphaned package thing).
Its possible my downstream distro (CachyOS) sent some kind of alert through pacman or published some utility, but I am away from my desktop until tonight, so I haven’t checked in a while.
Reposting this for visibility:
https://github.com/lenucksi/aur-malware-check
It analyzes your pacman install history, and some other things, for a more accurate check. Very useful.
See: Facebook.
It completely depends what you use your computer for.
For example, do you game? DRM free or no, and where are they installed? On a seperate drive?
What about work stuff? Media? The larger question I’m getting at is “how much of what you do is portable, and easy to just plop on a USB stick, reinstall from the internet, or just leave on a second drive already in your desktop?”
So… I am unquestionably ADHD. Like diagnosed in kindergarten, “doctor sees I’m neurodivergent the instant I start talking.”
Maybe AuADHD, still figuring that out.
…But, while I am no doctor, there are almost certainly diagnoses just to get ADD meds or extra time for tests. It was quite rampant in my school.
What I’m saying is, the grain of truth they’re stretching here shouldn’t be forgotten. Misdiagnoses and “false diagnosis” for benefits is definitely a thing for ADD, and it might be one for autism at some point. And pushing back against shameless neurodivergence discrimination shouldn’t cross the threshold of pretending that doesn’t exist.
It’s probably their own search/RAG backend, or at least their configuration of some open source project.
And that’s the important part. Get the article retrieval right, and the LLM performance isn’t that important; they could self-host Qwen 27B or something and it’d work fine.
We know that training LLMs on LLM-generated text leads to an absolute collapse in quality.
This is often repeated, and true. But needs to be qualified.
Modern LLMs use tons and tons of “augmented” data, which is code for LLM generated or massaged data. Some is even generated during training, and judged; papers on that are what made Deepseek famous.
Training on LLM trash will, of course, yield greater trash, and obviously good text has to come from something real. But that’s because slop is slop. And there are issues with “deep frying” LLMs, yes, but simply training on LLM on LLM output does not necessarily reduce quality. It often helps, significantly.
And we also know that AI has been showing up in papers so if they haven’t, then this will be quite unreliable.
Now this is a problem.
TBH LLMs would be pretty good at flagging papers for humans to check, similar to what Wikipedia is already doing. But yeah, if you just feed a prompt bad papers, LLMs just assume the context is true, generally, and that’s a tremendous problem.
Actually… I have quite a negative perception of GIMP. I’m primarily a Linux user, but I just remember it as something that’s either always felt obtuse to use, missing something I need, or sluggish for the more narrow processing I’m trying to do.
AFAIK that perception is more pronounced outside Linux.
I don’t care about a brand either way. But if the GIMP project is ready, I think a “fresh start” to draw in users without any preconceived notions is a good thing.
Well, don’t use Twitter.
I don’t mean to be grating, I mean to be blunt. Whatever you are doing here:
…but if you as an LGBT person answer to the homophobic conservatives with the same energy…
Does not matter because the algorithms are skewed, too. No “defending” you do will be shown to users who might actually change their opinion over what you say. As that wouldn’t be engaging.
Don’t believe me? Look at any neutral content (like NASA’s Artemis posts) logged out+VPN, then on your account.
there’s huge accounts on X that are dedicated to spread extreme hate even wishing death on other people.
There is no “fighting” this on Twitter, there is no balancing. That’s the illusion. There is no free speech on Twitter even if you were never censored, hence only way to win is to leave. And deprive them of your engagement.
Eh, I don’t totally agree. AI can discover novel exploits that aren’t already in some database, and likely have in this case.
I’m just saying the operating patterns between different LLMs are more similar than you’d expect, like similar tools from the same factory.
It does seem advantageous to the defender.
Another factor Mozilla didn’t mention (and that Anthropic wouldn’t like to emphasize) is that major LLMs are pretty similar. And their development is way more conservative than you’d think. They use similar architectures and formats, train from the same data, distill each other, further pollute the internet with the same output and so on. So if (for example) Mozilla red teams with Mythos, I’d posit it’s likely that attacker LLMs would find the same already-patched bugs, instead of something new.
…So yeah. I’d wager Mozilla’s sentiment is correct.
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Actually I think the public would generally understand this. Older demographics know what a camera indicator is, and for younger ones, a little light on sunglasses would get their attention.
Universally? No. But I’d wager the percentage is high enough for a crowd to know.
Encoder-decoder language models and all sorts of stuff were used for translation and spellcheck, long before “LLM” was in anyone’s vocabulary. Embeddings models were used in documentation searches, in IDEs, and other places. Whenever you used any search engine, pre Sam Altman, you were likely hitting text models too.
They worked alright.
It was not an issue. No one hated them; they are simple tools with a specific function.
I think people need to be careful of spilling (quite reasonable) hate of Tech Bro AI into the wider, older field of machine learning. In spite of the effort to conflate them, they aren’t the same thing.