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[AIT] paperless-ngx 3.0.0 (github.com)
submitted 3 months ago by to c/selfhosted@lemmy.world
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Paperless-ngx is an extensive document management system. 3.0.0 has just been released.

It seems from a user/admin perspective that a lot of obsolete stuff under the hood got removed and they did some performance stuff, but it's also full of AI features. There's too many changes to read them all though, I wonder if there's a blogpost or something somewhere summarizing the main changes.

Personally I'll stay with 2.X for some days at least to see what people say about the new version. I'm not interested to have AI parse my documents, the alrogirthmic auto tagging etc works quite well.

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[–] 0 points 3 months ago (3 children)

You don't need a knife to make a knife, and things like OCR are different from AI (or from "AI").

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  • [–] 5 points 3 months ago (2 children)

    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.

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  • [–] [S] 2 points 3 months ago (1 child)

    Yes, though that used to be discriminative AI, where now generative AI is used if I'm not mistaken.

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  • [–] 4 points 3 months ago

    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.

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