Chat, is this AI-generated ads on Lemmy?

No, AIHorde still uses corporate models. The only open source part is distributing the computation.

No, AIHorde still uses corporate models. The only open source part is distributing the computation.

It’s actually fine though, kinda. A significant portion of that is my n(ix)vim config, and the rest are mostly modules used in 30+ desktops and server VMs. The complete config for any one of those hosts isn’t that extravagant.

Cries in 14k lines of nix config

Not really, no

DNS over TLS and similar are only encrypted to the first (local) DNS provider, and of course that provider knows the query as well.

It protects against 3rd-party eavesdroppers between you and your primary DNS provider, but does nothing for privacy beyond that.

Also getting rid of my T1 Diabetes and re-doing my transition, but yeah! Hedonism as well!

Spend the rest of my life on a Culture orbital or GSV? FUCK YEAH

Kavin is a bot. Recently flooded the piracy community with the exact same images.

Hmm, it’s a bit cheaper here (I think - it’s been a while!), but yeah.

Electricity is expensive here, I think the server setup draws 40€/month, but that is for the entire setup of course, not just pirating-related stuff; plus ~9€/month for the two usenet backbones, and a couple bucks for trackers.

My GF is VERY up to date on this (unfortunately? 😆)

That’s mostly true, although you usually (in my case at least) I am aware of all shows I have available on Jellyfin, and it’s only ones I like.

For discovering new shows to download, things like Jellyseerr actually do give recommendations… No idea how good they are though.

But frankly, Netflix used to recommend a lot of things that sounded interesting on the surface-level, and then turned out to be utter shit. Probably not an entirely bad thing to be lacking recommendations :D

For Non-English ones in my native language. There isn’t a lot of them. AFAICT the one I mostly use is free for a handful of requests/day, but generously lifts that limit in exchange for a “donation” 😄

(It’s only around 20/year)

Edit: and just to be clear, that one Tracker took us from “basically nothing is available in our language” to “literally everything is”, so it’s money well spent.

For a very long time, I was one of the people who kep saying:

“I used to pirate until Netflix came along; now I pirate because of the fragmentation of services; should a good service become available at a reasonable price again, I will be happy to switch back.”

But at some point, that stopped being true. More precisely, my *arr-Stack + Jellyfin setup become so stable, I do no longer really think about it, while also getting better quality content, and often faster than I would due to global licensing shennanigans.

Another factor also is that at some point, we crossed the “enough content to mindlessly scroll until we find something to watch” barrier, which my GF actually kinda missed from Netflix.

The crazy thing though, is that we pay actual money for this: hardware cost; electricity; access to usenet trackers and two usenet backbones. All in all, I do not think it’s cheaper than getting Netflix+Prime+Disney.

It’s just better. And we will not be switching back, ever.

Huh. I update my revanced YouTube app every 6-9 months

We were talking about SwiftKey

Who knows?

Unless a piece of software is open source, you cannot know.

I switched a couple of months ago, from SwiftKey. Had been using that for ever, long before Microsoft bought it.

NGL, the transition was a bit rough, and the first month my error rate spiked. All good now though, plus Futo has a bunch of super useful features SK never had. Overall, very happy.

No. I am not saying that to put man and machine in two boxes. I am saying that because it is a huge difference, and yes, a practical one.

An LLM can talk about a topic for however long you wish, but it does not know what it is talking about, it has no understanding or concept of the topic. And that shines through the instance you hit a spot where training data was lacking and it starts hallucinating. LLMs have “read” an unimaginable amount of texts on computer science, and yet as soon as I ask something that is niche, it spouts bullshit. Not it’s fault, it’s not lying; it’s just doing what it always does, putting statistically likely token after statistically liken token, only in this case, the training data was insufficient.

But it does not understand or know that either; it just keeps talking. I go “that is absolutely not right, remember that <…> is <…,>” and whether or not what I said was true, it will go "Yes, you are right! I see now, <continues to hallucinate> ".

There’s no ghost in the machine. Just fancy text prediction.