• MadMadBunny@lemmy.ca
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    5 days ago

    But, will it work, huh? HUH?

    I can also type a bunch of random sentences of words. Doesn’t make it more understandable.

    • ryannathans@aussie.zone
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      5 days ago

      Some models are getting so good they can patch user reported software defects following test driven development with minimal or no changes required in review. Specifically Claude Sonnet and Gemini

      So the claims are at least legit in some cases

      • 6nk06@sh.itjust.works
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        5 days ago

        Oh good. They can show us how it’s done by patching open-source projects for example. Right? That way we will see that they are not full of shit.

        Where are the patches? They have trained on millions of open-source projects after all. It should be easy. Show us.

        • JustinTheGM@ttrpg.network
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          5 days ago

          That’s an interesting point, and leads to a reasonable argument that if an AI is trained on a given open source codebase, developers should have free access to use that AI to improve said codebase. I wonder whether future license models might include such clauses.

        • ryannathans@aussie.zone
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          5 days ago

          Are you going to spend your tokens on open source projects? Show us how generous you are.

          • 6nk06@sh.itjust.works
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            5 days ago

            I’m not the one trying to prove anything, and I think it’s all bullshit. I’m waiting for your proof though. Even with a free open-source black box.

                • ryannathans@aussie.zone
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                  4 days ago

                  At work, the software is not open source.

                  I would use it for contributions to open source projects but I do not pay for any AI subscriptions, and I can’t use my employee account for copilot enterprise for non-work projects.

                  Every week for the last year or so I have been testing various copilot models against customer reported software defects and it’s seriously at a point now where with a single prompt Gemini pro 2.5 is solving the entire defect with unit tests. Some need no changes in review and are good to go.

                  As an open source maintainer of a large project I have noticed a huge uptick in PRs which has created a larger review workload, I’m almost certain these are due to LLMs. Quality of a typical PR has not decreased since LLMs have become available and I am thus far very glad

                  If I were to speculate I’d guess the huge increase in context windows has made the tools viable, models like GPT5 are garbage on any sizable code bases