876
AGI achieved 🤖
(lemmy.dbzer0.com)
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 11 Jun 2025
876 points (100.0% liked)
Lemmy Shitpost
32362 readers
3193 users here now
Welcome to Lemmy Shitpost. Here you can shitpost to your hearts content.
Anything and everything goes. Memes, Jokes, Vents and Banter. Though we still have to comply with lemmy.world instance rules. So behave!
Rules:
1. Be Respectful
Refrain from using harmful language pertaining to a protected characteristic: e.g. race, gender, sexuality, disability or religion.
Refrain from being argumentative when responding or commenting to posts/replies. Personal attacks are not welcome here.
...
2. No Illegal Content
Content that violates the law. Any post/comment found to be in breach of common law will be removed and given to the authorities if required.
That means:
-No promoting violence/threats against any individuals
-No CSA content or Revenge Porn
-No sharing private/personal information (Doxxing)
...
3. No Spam
Posting the same post, no matter the intent is against the rules.
-If you have posted content, please refrain from re-posting said content within this community.
-Do not spam posts with intent to harass, annoy, bully, advertise, scam or harm this community.
-No posting Scams/Advertisements/Phishing Links/IP Grabbers
-No Bots, Bots will be banned from the community.
...
4. No Porn/Explicit
Content
-Do not post explicit content. Lemmy.World is not the instance for NSFW content.
-Do not post Gore or Shock Content.
...
5. No Enciting Harassment,
Brigading, Doxxing or Witch Hunts
-Do not Brigade other Communities
-No calls to action against other communities/users within Lemmy or outside of Lemmy.
-No Witch Hunts against users/communities.
-No content that harasses members within or outside of the community.
...
6. NSFW should be behind NSFW tags.
-Content that is NSFW should be behind NSFW tags.
-Content that might be distressing should be kept behind NSFW tags.
...
If you see content that is a breach of the rules, please flag and report the comment and a moderator will take action where they can.
Also check out:
Partnered Communities:
1.Memes
10.LinuxMemes (Linux themed memes)
Reach out to
All communities included on the sidebar are to be made in compliance with the instance rules. Striker
founded 2 years ago
MODERATORS
These sorts of artifacts wouldn't be a huge issue except that AI is being pushed to the general public as an alternative means of learning basic information. The meme example is obvious to someone with a strong understanding of English but learners and children might get an artifact and stamp it in their memory, working for years off bad information. Not a problem for a few false things every now and then, that's unavoidable in learning. Thousands accumulated over long term use, however, and your understanding of the world will be coarser, like the Swiss cheese with voids so large it can't hold itself up.
You're talking about hallucinations. That's different from tokenization reflection errors. I'm specifically talking about its inability to know how many of a certain type of letter are in a word that it can spell correctly. This is not a hallucination per se -- at least, it's a completely different mechanism that causes it than whatever causes other factual errors. This specific problem is due to tokenization, and that's why I say it has little bearing on other shortcomings of LLMs.
No, I'm talking about human learning and the danger imposed by treating an imperfect tool as a reliable source of information as these companies want people to do.
Whether the erratic information is from tokenization or hallucinations is irrelevant when this is already the main source for so many people in their learning, for example, a new language.
Hallucinations aren't relevant to my point here. I'm not defending that AIs are a good source of information, and I agree that hallucinations are dangerous (either that or misusing LLMs is dangerous). I also admit that for language learning, artifacts caused from tokenization could be very detrimental to the user.
The point I am making is that LLMs struggling with these kind of tokenization artifacts is poor evidence for drawing any conclusions about their behaviour on other tasks.
That's a fair point when these LLMs are restricted to areas where they function well. They have use cases that make sense when isolated from the ethics around training and compute. But the people who made them are applying them wildly outside these use cases.
These are pushed as a solution to every problem for the sake of profit with intentional ignorance of these issues. If a few errors impact someone it's just a casualty in the goal of making it profitable. That can't be disentwined from them unless you limit your argument to open source local compute.
Well -- and I don't meant this to be antagonistic -- I agree with everything you've said except for the last sentence where you say "and therefore you're wrong." Look, I'm not saying LLMs function well, or that they're good for society, or anything like that. I'm saying that tokenization errors are really their own thing that are unrelated to other errors LLMs make. If you want to dunk on LLMs then yeah be my guest. I'm just saying that this one type of poor behaviour is unrelated to the other kinds of poor behaviour.