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Joined 3 years ago
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Cake day: June 17th, 2023

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  • Why an RDBMS on the local though? Testing shit doesn’t make sense to name it as a regular piece of software.

    I always build against a local DB?

    For our desktop / LAN software the DB will always be local.

    For web, it’s easier since I’m likely to burn the DB down over and over during early development / prototyping. But I’m not using cloud hosted DB even in production, and don’t expose Postgres outside the DB server, so I find it easier to work on this way.

    EDIT: I also think that a default installation of VS includes SQL Server. I don’t use it, so always have to adjust the installation and remove all of those bits, but I also have complete control of my environment. I could see an IT department just doing a stock VS installation with the required workloads.






  • I think the fundamental difference is that a human trained on something isn’t likely to reproduce the thing they were trained on exactly.

    I know that some research I read a few years ago showed that LLMs generally produced novel text (rather than simply returning verbatim training material), but that that wasn’t always true, especially as the training sample got smaller, or a single training text got larger (something like a 1000 words).

    So sure, for something simple like creating super standard CRUD or basic API endpoints in common languages, the sample size is significant enough that what you get is likely to be homogenized from thousands of samples available, and not likely to be an exact copy of someone else’s code. But the risk is that as the problem being solved gets more niche, and the training sample size gets smaller, you become more likely to get exact copies of someone else’s code, or something close enough that it might be considered plagiarism.

    There’s also still grey areas where some courts in some areas have stated that LLM generated content can’t be copyrighted, since a human didn’t create it, creating issues with protecting sources with copyright.



  • Repetition is key here. And solving problems.

    I started many years ago with a “for beginners” book, and didn’t fully understand a lot of it by the end.

    So I started trying to build something, and searched for answers to the things I couldn’t figure out (and went back to the book numerous times). I don’t think I ever finished that project, but by persisting through it, and figuring out how to solve the problems that I ran into, I learned how to build something, and it stuck.




  • All of this, and the facts that the entire thing was trained on stolen material, and the companies behind it are all run by bat shit crazy shitheads.

    Everyone loves to shit on US tech companies, hates Windows and MS, and Amazon, Google, Apple, and Meta (all rightfully so), but is absolutely willing to overlook the AI companies that are arguably doing more harm than those others combined (or are tightly invested / integrated with them, or are them) just so they don’t have to spend a few minutes typing, or thinking about how something works.