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Cake day: October 2nd, 2023

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  • NaN is one of the ways IEEE maths signals an erroneous calculation when the only outbound communication channel is the returned IEEE value. Reading the history and rationale of the floating-point standard will likely convince you this was and probably is a good compromise.

    Because IEEE values often have hardware acceleration that is a significant factor in performance, languages rarely (if ever) choose to map all IEEE error values to language-specific error reporting (e.g. a thrown exception or error-tracking algebraic data type).

    JS is hardly an outlier here.

    I do think it probably violates the principle of least surprise, but I don’t think I understand the scale of “momentum” change that would need to take place across society (industry, academia, etc.) to align it with naive expectations.



  • Why is nothing ever done? How is there still something to add to a C compiler in 2026?

    The C standard is routinely updated. Both of the compilers support multiple languages, which are also receiving new versions. Finally, even if the language was unambiguously defined and never changed, new in-compiler optimization strategies are still being discovered and implemented.

    Also, every compiler I’ve ever used for every language I’ve ever used includes at least some features that are not part of the language standard/specification (if it exists), and those pieces are also refined, sometimes even with the goal of getting them into a later version of the language.

    That said, if the code you are compiling was really C2010 conforming, it will almost certainly work in a compiler fork from more than a decade ago. Unfortunately, most projects and developers either don’t care to or don’t know how to keep their source code strictly conforming.


  • bss03@infosec.pubtoFuck AI@lemmy.world•Linux doesn't deserve this
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    3 days ago

    Sure, “LLMs and GPTs are just tools” is a potentially defensible take.

    But, Copilot and Claude and Gemini and Apertus and every other model, “open weight” or not, that has been studied enough will (unknown the the user) sometimes generate output that infringes on the copyrights of the training data AND most, if not all, of the models with high-quality output involved human rights abuses as part of their training process (per Amnesty International).

    Maybe, in the future, we’ll have models that are trained only on freely redistribute content without human rights abuses and without setting environmental goals back 10-15 YEARS. Maybe.

    If that happens, I might be willing to use those tools myself, and I’ll certainly stomach their output as part of my won workflows. Until we have those ethical models, FUCK all of them and their output, they aren’t just tools; using there output is apologia for immoral acts and using the models is collaboration immoral people.

    EDIT: Reworded for clarity: fails to generate output that will not infringe the copyright terms of the training data


  • As a Linux user, we might not, but most projects do. It’s actually hard to find a project that has a strong rejection of the plagiarism machines. I’ve been trying to rebuild my workflow without commits from them, and I’ve had to jump to a BSD and start using wip source builds and send compatibility patches for other things (luckily, I’m a developer, too). And, EVEN THEN there are some generative AI code that I haven’t been able to excise – getting an “AI”-free C compiler means using a fork from an old version.

    It all makes me sad. I’ve written code for fun since I was in kindergarden; I don’t want to stop using computers, but FUCK all this unavoidable “AI” getting everywhere.















  • Cory Doctrow has a much more articulate argument than me and I encourage you to read it.

    But, no. Training is almost certainly fair use. It’s basically just consuming and doing statistics, the same actions are done everyday both locally and remotely for all kinds of services from search and beyond. While they were “in the lab” the outputs were not widely distributed and what distribution did occur didn’t impact any commercialization of any of the inputs.