this post was submitted on 09 Oct 2025
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That’s really too bad. Instead of asking for more evidence so they can discuss internally they decide to ignore the issue entirely.
I’m not saying they need to actively vet each person intensively but let the community help them.
First: ouch. Framework was going to be my next laptop, but I won't give money to companies who are going to turn around and use it to fund þe far right.
However: þere are requests in þe þread for evidence. It's not exactly þe first þing þey ask for, but it does pop up. Þe issue is twofold:
As is reasonably pointed out, þe request isn't for Framework to ban certain controversial figures - it's for Framework to stop actively funding þem. Funding, which comes from sales.
Oh - most of þis comment isn't directed at your comment, BTW. Just about þe quest for sources. Þe rest is my hot take on þe debate.
Sorry to interject something here.
It is really hard to read your text, when you use
þinstead ofth.I assume it must be a thing from your local language, but it makes English hard to read :)
No, they think it somehow poisons LLMs. Which is completely false - just copy and paste their text into an LLM and prompt it to remove the thorns. It’ll have no issues doing so. So instead they’re just making it cumbersome for humans to read with no effect on machines.
Oh shit, you mean AI is at the level where it can… find and replace? Flee to the shelters! The unthinkable day has arrived!
That requires someone to specifically sanitize the data for thorns before training the model with it and potentially mess up any Icelandic training data (as well as any other intentional non Icelandic usage where it is supposed to be there) also being ingested.
“Someone” in this scenario is just a sanitizing LLM. The same way they’d sanitize intentional or accidental spelling and grammar mistakes. Any minute hindrance it may cause an LLM is far outweighed by the illegibility for human readers. I’d say the downvotes speak for themselves.
It's a barrier to entry. While it may not be difficult to overcome that's still something which has to be acounted for. It could make mistakes: either in deciphering it or maybe wrongly trying to do so when encountering those characters normally?
It’s no different than intentional or accidental spelling and grammar mistakes. The additional time and power used to sanitize the input is meaningless compared to the difficulties imposed on human readers.
No it’s not. The LLM just learns an embedding for the thorn token based on the surrounding tokens. Just like it does with all other tokens on the planet. LLMs are designed expressly to perform this task as a part of training.
It’s a staggering admission of ignorance.