• 3 Posts
  • 13 Comments
Joined 1 year ago
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Cake day: June 5th, 2025

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  • once again: oversight of the production line != oversight of the output.

    i specifically said that i do trust Linus Torvalds to ensure no bullshit is pushed to the Linux kernel. that is oversight of the output.

    we need oversight of the production line. but of all the production lines, not only the ones delivering LLMs. big corporations have a tendency to blatantly break the law and get away with a fee that is smaller than their profit. if they don’t break the law by the letter, they have good lawyers to skirt around it and noone has a morality police. oversight would mean not only catching these things but also punishing such behaviour in a meaningful way.

    training an LLM eith CC0 would be fair game. properly bought (declared it is for training some AI) resources as well. i fully disagree with the current training methods: just feeding more to the black box - to that extent, that they buy (improperly) and destroy books just to get some more words into their respective model. i am sure, that other approaches would get better results. but that is slower and more expensive. so the problem is how most AI companies operate - not the actual product. but if it wasn’t “AI”, it would be something else with the exact same bullshit practices.


  • you are confusing two issues here: oversight for the output of an ANN can very much achieve good results. as i explained in my post.

    oversight over the output won’t help you with copyright, water and energy consumption, slave labour and all the ethical issues further up the pipeline. but we don’t need ANNs for big corpos to do all these evil things. we need oversight and real consequences for those corpos - no matter what they produce.

    ANNs as a technology are old and have not fundamentally changed since Alan Turing. Sure, we have iterated and improved. But the fundamentals are the same. LLMs just made that old tech quite popular recently and introduced a “line go up” race. i do not believe that we will gain significant improvements from simply feeding more stolen works to the machine. A fraction of the MNIST dataset is enough to train an ANN on a 20 years old laptop to recognise the digits 0-9 reliably. The technology is sound, limited in its usability and detached from the big corpos.


  • unpopular opinion, especially on the fediverse, but: AI is not inherently bad.

    it is a tool, that can do everything to a pretty low standard but rather fast. so it is up to the learnt human to use the thing at the right time. i use the company ai at regularly at work, but treat it as an apprentice: every line of code has to be checked, because it will fail hilariously. but it does type faster than me, so simple and boring jobs can be done by it.

    i don’t see the appeal of avoiding generated code at all cost. it is not different from human code in that it can fail horribly. the important thing is oversight. is there someone with the knowledge and keen eye to ensure no BS is merged. Linus, in my opinion, spent a lifetime building that reputation.






  • most people can get behind parental control. that is why bad actors are pushing for age verification everywhere nowadays.

    i think the issue many people have with that field is, that it enables bad actors to do things. all the while, it does not really do the thing it is supposed to do: if i trust my kid with sudo, the field can easily be altered. if i do not trust my kid with sudo, it cannot install anything either way.

    with your last paragraph i (and probably most people) agree. but we already have those tools, right? at least until i knew computers better than my parents, there was no way i could install anything without them being OK with it. even when i was admin on my very own desktop, i was heavily reliant on the parents for everything costing money. yes, even my dumb ass figured out how to pirate stuff. but to do that while being afraid to brick your precious device with some virus - you need some tech literacy, which is for sure beyond changing one value.



  • I have to write so much boilerplate code to make sure my objects are of the correct type and have the required attributes!

    That is the trap that, sadly, my company fell for too. The POC was written in python. very fast i might add. but it was only that: a POC. if the whole backend crashes due to unexpected user input - noone cared. if the frontend displayed gibberish because the JSON made wrong assumptions about not defined data types - sweep it under the rug, don’t do that during presentations.

    but if it came to building a resilient system, which can be shipped to customers and preferably maintained by them (with minimal consulting contract for access to our guys)… we cursed the way python worked.