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  • @davep That's OK, you don't have to.

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  • I generally don't like LLM-generated images or video. I mostly don't like LLM-generated text -- it's usually flat, wordy, and full of business jargon. I don't use LLMs for either of these things.

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  • @evan hmm, I'm not seeing anything like genuine equivalence between human learning and LLM statistical output based on training data.

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  • I don't think the fact that LLMs make mistakes is a reason to not use them. It is a good reason to get reference links, and to cross-check any output.

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  • I don't use the term "stealing" for ideas, and I don't think it applies for LLM output.

    I think that training LLMs on content to produce a model, then using that model to generate new content, is more akin to human learning than to verbatim copying.

    I don't think that LLM output is a "derivative work" of the training data.

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  • @evan

    Support your local humans

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  • I don't agree with many of the arguments against LLMs I see on the Fediverse.

    LLM usage is not a GHG-intensive activity, especially compared to other everyday activities.

    https://cosocial.ca/@evan/115580076628853324

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  • @evan my employer will pay for pretty much any tools one can think of and yeah. for a quick "hey should this fail and panic!() and crash everything according to the docs" llms are (mostly) great
    not so great when the thing i'm trying to do is niche and/or specific to the [in-house] libraries we use, but considering the main offender is mostly a thin api wrapper around an opensource c thing it manages more or less fine

    would i want the whole "ai" industry to go up in flames without any hope for recovery? yeah
    am i gonna take everything my BigTechCorpInc. employer will give me? also yeah

    tho now that i think about it, maybe i could ask them for a 128gb ram mac mini or smth as a one-time purchase as an ollama server instead of the subscriptions

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