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[–] 4 points 11 months ago (10 children)

Can you help correct this for me? Don't you feed them valuable training data and exposure to real world problems in the process of using them?

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  • [–] 20 points 11 months ago (9 children)

    No. AI models are pre-trained, they do not learn on the fly. They are hoping to discover General Artificial Intelligence, which is what you are describing. The problem is that they don't even understand exactly how training even works. While engineers understand the overall architecture, the specific "reasoning" or decision-making pathways within the model are too complex to fully interpret, leading to a gap between how it works and why it makes a particular decision.

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  • [–] 13 points 11 months ago (8 children)

    My assumption wasn't that they learned on the fly, it was that they were trained on previous interactions. Eg the team developing them would use data collected from interaction with model v3 to train model v4. Seems like juicy relevant data they wouldn't even have to go steal and sort

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  • [–] 11 points 11 months ago

    That's true to an extend, but the interactions are only useful for training if you can mark it as good / bad etc (which is why sometimes apps will ask you if they were useful). But the 'best' training data like professional programming etc is usually sold at a premium tier with a promise not to use your data for training (since corporations don't want their secrets getting out).

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  • [–] 1 point 11 months ago (6 children)

    You can’t train ai on ai output. It causes degradation on the newly trained model.

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  • [–] 7 points 11 months ago (5 children)

    First: that's wrong, every big LLM uses some data cleaned/synthesized by previous LLMs. You can't solely train on such data without degradation, but that's not the claim.

    Second: AI providers very explicitly use user data for training, both prompts and response feedback. There's a reason businesses pay extra to NOT have their data used for training.

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  • [+] 0 points 11 months ago (5 children)
  • [–] 4 points 11 months ago (4 children)

    I mean - yeah, it is? This is a well-researched part of the data pipelines for any big model. Some companies even got into trouble because their models identified as other models, whose outputs they were trained on.

    It seems you have a specific bone to pick that you attribute to such training, but it's just such a weird approach to deny pretty broadly understood results...

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  • [+] 1 point 11 months ago (4 children)
  • [–] 3 points 11 months ago (3 children)

    No, it doesn't. Unless you can show me a paper detailing that literally any amount of synthetic data increases hallucinations, I'll assume you simply don't understand what you're talking about.

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  • [+] -2 points 11 months ago (3 children)
  • [–] 3 points 11 months ago (2 children)

    Yeah, that's what I guessed. Try to look into the research first before making such grandiose claims.

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  • [+] 1 point 11 months ago (2 children)
  • [–] 1 point 11 months ago (1 child)

    Ah yes, and you can't show us that research because it goes to another school? And all companies that train LLMs are simply too stupid to realize this fact? Their research showing the opposite (which has been replicated dozens of times over) was just a fluke?

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  • [+] 0 points 11 months ago (1 child)
  • [–] 1 point 11 months ago*

    no because this is literally in development, this isn’t some 60 year old mature tech

    Of course, you don't have research supporting your position because it's still in development. So obviously we can just ignore all the papers released over the last decade+ which show the opposite of what you're claiming - convenient!

    there is already academic accessible research talking about LLM issues of which the major concern is hallucinations, to the point where the word bailout is starting to make the rounds in the us from these very companies

    the argument is whether or not you believe this is inherent or fixable and a big focus is on the training

    anyone listening to any ai company right now is a damn fool with the obvious circular vendor bullshit going on

    Yeah, as I expected - you literally don't understand what this conversation is even about. Since you have a bone to pick with the industry, you make up random claims that you think make the industry look bad. But what you don't understand is: you're just making a fool of yourself by making subjective claims around topics you simply don't understand. Critique the AI industry for the greedy, useless shit they're doing and creating, not by making up wrong "facts" and ignoring all evidence against them.

    And just to save us both time, I'll list try to list positions you seem to think I hold, which I don't:

    • I don't think LLMs will ever get rid of hallucinations
    • I don't think LLMs will get better and better by only training on output from previous LLMs
    • I don't think LLMs are the path to AGI
    • I don't think any of the marketing done by AI companies is truthful

    If you choose to reply again and think I'm lying about not holding these positions, re-read the conversation until you understand it.

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