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The European Commission sees open-source software as more than an IT tool. Policy makers are encouraging open-source ecosystems to drive innovation, autonomy and collaboration in a world where global trade is being redrawn.
This trade dispute highlights something most open-source advocates have known for years: open source is freedom. It’s freedom from monopolies, freedom from arbitrary pricing, and freedom from foreign influence.
Lemmy seems to be anti-AI, at least from my impression, but I am hopeful that AI will help invigorate the open source software world. If people can code better, faster, cheaper, safer (more secure) that will surely apply to open source as well. AI coding tools could bring on the Linux mainstream revolution. Imagine thousands of autonomous agents refining software for Linux. There could be a glut of driver support, apps coming to Linux, and so much more. I am hopeful about it.
I’m not European, but I understand that there’s an old European (German?) saying that basically goes: “If I had wheels, I’d be a trolley.” I understand that it’s been pretty well-established that AI coding tools routinely underperform compare to humans in terms of “better” and “safer”, which indirectly would also lead to it failing at “cheaper” too.
On top of that, there is another major issue with using AI for open-source code: copyright. First, you don’t know if the code that you’re adding through AI may be copying license-incompatible code verbatim. Because everyone has access to open-source code, it would be trivial for anyone to search and find copyright-infringing code to attack projects with. Second, the code that AI produces is also not-copyrightable, so that is another line of attack that this would make open-source projects vulnerable to. These could be used in combination as a one-two punch combination to knock out an open-source project.
I think that using AI-generated code in open-source projects is a uniquely ill-advised idea.
I won’t hold my breath on it.
Up until this minute, AI has produced plentiful examples of how it can produce anything but good code.
I’d rather have a developer writing software, slowly, because they have an intelectual itch and want to try and see the outcome of their idea than the proverbial army of monkeys furiously typing away.
The other problem is unlike stack overflow, a helpful answer by an AI isn’t visible and indexed therefore someone else has to do another prompt for the potential answer.
It’s pretty useful replacing stack overflow that could also generate code specific to your project. It’s also useful for testing. Like any tool, it has its use cases.
I sometimes float the idea in my brain to learn how to code. If I ever come to it, I want to debate and discuss my work with another human. Not a machine.
Personal preference.
That’s a great way to do it, but human attention on your code is a scarce and valuable resource. LLMs are great for the sort of lazy stupid questions where you benefit from a quick answer, but also don’t want to waste someone else’s time on. When you are learning nearly all the questions you’ll have will be like this, your progress is gated on finding the answers, and even if you are taking a class and it’s someone’s job to look at your code and help you understand what’s wrong with it, you have to wait your turn for that and only get so much help.