Four months ago, we asked Are LLMs making Stack Overflow irrelevant? Data at the time suggested that the answer is likely “yes:”

  • @ramble81@lemm.ee
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    583 days ago

    So here’s what I don’t get. LLMs were trained on data from places like SO. SO starts losing users ,and thus content. Content that LLMs ingest to stay relevant.

    So where will LLMs get their content after a certain point? Especially for new things that may come out or unique situations. It’s not like it’ll scrape the answer from a web page if people are just asking LLMs.

    • db0
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      3 days ago

      The need for the service that SO provided won’t go away. Eventually people will migrate to new places to discuss. LLM creators will either constantly scrape those as well, forcing them to implement more and more countermeasures and GenAI-poison, or the services themselves will enshittify and sell our content (i.e. the commons) to LLM-creators.

      • Dojan
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        233 days ago

        I worry that the replacement is more likely a move to platforms like Discord. I mean it’s already happened in a lot of projects.

          • Dojan
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            163 days ago

            I hate Discord with a passion. Trying to get everyone I know away from it.

        • @cmnybo@discuss.tchncs.de
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          92 days ago

          If they move to Discord, nobody will ever be able to find the answers. They must use a website that is indexable by search engines or it will be pointless.

          • Dojan
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            32 days ago

            Yeah. But this already happens, unfortunately.

        • db0
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          53 days ago

          Yes, it’s what I was referring to in the second part.

          • Dojan
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            113 days ago

            I’ve never been accused of being a smart man.

    • dantheclamman
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      11 day ago

      They’re probably hoping to use people’s submitted code for training. But that seems like it will be diminishing returns

    • @vala@lemmy.world
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      52 days ago

      You are assuming that people act in logical ways.

      This is only a problem right now if you think about it.

    • @fubarx@lemmy.world
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      63 days ago

      Same question applies to all the other websites out there being mined to train LLMs. Google search Overviews removes the need for people to visit linked sites. Traffic plummets. Ads dry up, and the sites go out of business. No new content to train on 🤷🏻‍♂️

    • FaceDeer
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      -13 days ago

      This is an area where synthetic data can be useful. For example, you could scrape the documentation and source code for a Python library and then use an existing LLM to generate questions and answers about the content to train future coding assistants on. As long as the training data gets well curated for quality it’s perfectly useful for this kind of thing, no need for an actual forum.

      AI companies have a lot of clever people working for them, they’re aware of these problems.

      • Natanael
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        32 days ago

        You’ll never be able to capture every source of questions that humans might have in LLM training data.

        • FaceDeer
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          -12 days ago

          That’s the neat thing, you don’t.

          LLM training is primarily about getting the LLM to understand concepts. When you need it to be factual, or are working with it to solve novel problems, you can put a bunch of relevant information into the LLM’s context and it can use that even if it wasn’t explicitly trained on it. It’s called RAG, retrieval-augmented generation. Most of the general-purpose LLMs on the net these days do that, when you ask Copilot or Gemini about stuff it’ll often have footnotes in the response that point to the stuff that it searched up in the background and used as context.

          So for a future Stack Overflow LLM replacement, I’d expect the LLM to be backed up by being able to search through relevant documentation and source code.

          • Natanael
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            2 days ago

            Even then the summarizer often fails or bring up the wrong thing 🤷

            You’ll still have trouble comparing changes if it needs to look at multiple versions, etc. Especially parsing changelogs and comparing that to specific version numbers, etc

            • FaceDeer
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              02 days ago

              How does this play out when you hold a human contributor to the same standards? They also often fail to summarize information accurately or bring up the wrong thing. Lots of answers on Stack Overflow are just plain wrong, or focus on the wrong thing, or don’t reference the correct sources (when they reference anything at all). The most common criticism of Stack Overflow I’m seeing is how its human contributors direct people to other threads and declare that the question is “already answered” there when it isn’t really.

              LLMs can do a decent job. And right now they are as bad as they’re ever going to be.

              • Natanael
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                21 day ago

                Well trained humans are still more consistent and more predictable and easier to teach.

                There’s no guarantee LLM will get reliably better at everything. It still makes some mistakes today that it did when introduced and nobody knows how to fix that yet

                • FaceDeer
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                  01 day ago

                  You’re still setting a high standard here. What counts as a “well trained” human and how many SO commenters count as that? Also “easier to teach” is complicated. It takes decades for a human to become well trained, an LLM can be trained in weeks. And an individual computer that’ll be running the LLM is “trained” in minutes, it just needs to load the model into memory. Once you have an LLM you can run as many instances of it as you want to spend money on.

                  There’s no guarantee LLM will get reliably better at everything

                  Never said they would. I said they’re as bad as they’re ever going to be, which allows for the possibility that they don’t get any better.

                  Even if they don’t, though, they’re still good enough to have killed Stack Overflow.

                  It still makes some mistakes today that it did when introduced and nobody knows how to fix that yet

                  And humans also make mistakes. Do we know how to fix that yet?

                  • Natanael
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                    21 day ago

                    Getting humans to do their work reliably is a whole science and lots of fields can achieve it