My honest recommendation here would be to use Notesnook instead. I used Joplin for a while, and when I found Notesnook I switched immediately. It’s just flat out better at basically everything Joplin does, and it’s still open source. No need to run syncthing, use the notesnook server to sync and backup everything.

We were doing DNS challenges for an isolated system and our provider didn’t support that.

Yeah, same, this is news to me but very interesting. Would have solved an issue we had at work that ended up requiring us to move our whole DNS over.

Completely correct.

Been using Seafile for years, it’s fantastic.

Oh hell yes! Awesome update.

I’m curious about what the client would be in this context. Does it require a desktop environment, or just an X server? Are you using an existing web browser, or are you rendering web content directly in the app?

Not just because it enables more access for everyone, but because it represents a deepening commitment by these companies to Linux as a gaming platform.

The more companies see Linux as a viable gaming platform, the more consumers will. It’s a virtuous cycle, and one that will only help to erode Windows grip on the desktop OS space.

I’ve been using it for years and this has never been an issue for me.

Absolutely there’s a difference. LLMs, when it comes to this specific task, are better. That’s why they’re being used here. It’s a job they are uniquely well suited to. They do indeed come with high hardware requirements, which is why you’re not forced to use them, and why they provide the option to offload the work to a cloud service.

Personally I would absolutely not want to ever feed my documents into an off-device model, but the point of self-hosted software is that it does what you tell it to and they absolutely should include letting you make bad decisions.

I think you’re under the impression that the difference between those things is far greater than it actually is. Large Language Models work by developing statistical maps of associations. That’s discrimination. They’re a direct evolution of categorization models. The ability to associate a hash of a JPEG with “cat” is the same as the ability to associate “How are you?” with “Great, how about you?” It’s all associative mapping. LLMs are just the current leading edge of that technology. If you want to, for example, generate a list of tags that describe a document, an LLM is the best tool we currently have for doing that.

To put it another way, what you term “discriminative AI” is “generative AI.” It’s generating a category or list of categories in response to an input. That’s not functionally different than generating a sentence in response to a sentence, it’s just an order of magnitude less complex. You can argue terminology but the technology exists on an evolutionary curve, with no real hard boundaries.

Paperless and Papermerge have always done a lot more than just OCR. If that’s all they were, most people can do that already on the software that comes with their scanner. The core selling point of these applications is automatic categorization, sorting and tagging, and those have always relied on machine learning tools. Literally the first thing you do after setting Paperless up is start training the AI.

what’s the best alternative?

You’re asking for suggestions for an automatic document categorization tool that doesn’t use any automatic document categorization?

It reads as especially hysterical in this context, because Paperless is an automatic document categorization system, and I’m really sure what they think the automatic part of that is if it’s not “AI” of some broad description. Paperless, Papermerge et al are basically wrappers for machine learning tools and have been for as long as they’ve existed. LLMs are a natural and obvious fit for the kind of work these applications exist to do.

This just feels like someone reading “Improved AI pathfinding” in the patch notes for a video game and screaming “OH MY GOD IS NOWHERE SAFE?!”

The issue is that everyone thinks computers operate on magic, so they just ignore the idea that there might be practical limitations on doing the things that they want to do.

In reality there is no means of age verification that isn’t also a form of identity verification. And if you asked people “Should everyone have to hand over their government ID to private companies in order to use the internet”, you’d see much lower numbers of positive responses.

We’re talking about repurposing the GPUs, not the AI.

OK, if we’re talking about infrastructure rather than specific equipment, then yes, I would broadly agree that the datacentre infrastructure itself can be repurposed.

Unfortunately, by that point the whole data centre will already have been sold off for parts because its never going to recoup its initial investment in the first place, and throwing even more money into swapping out those GPUs for CPUs is going to be a complete no go.

If anyone actually spent money on science anymore, I bet this would be great for, like, protein folding, that sort of thing.

Terrible for running websites though.

GPUs are only good for workloads that multi-thread really, really well. That’s why we don’t just use them as CPUs.

The idea that today’s GPU will be tomorrow’s CPU makes no sense. We’ve had GPUs for ages. If they were capable of being used in place of CPUs we’d already be doing it. Why aren’t yesterday’s GPUs today’s CPUs?

Best I can tell they were trying to remove all packages that depended on a specified package, but fucked up the syntax?

Apk del --purge removes a package with its dependencies. Rather than specify the package directly, they’ve provided the output of one command piped through another. The first command is apk info -R which would in theory give the reverse dependencies of a package, if they’d given one. The second command is an awk statement that just grabs only the first column of each line that gets piped into it. I’m not sure why it would take 60 minutes to resolve though, since I’m pretty sure apk info -R with no package specified would produce no usable output. Also, ctrl-c exists.