• @UnseriousAcademic
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    1420 days ago

    Does this mean they’re not going to bother training a whole new model again? I was looking forward to seeing AI Mad Cow Disease after it consumed an Internet’s worth of AI generated content.

    • David GerardOPMA
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      920 days ago

      I think they will do whatever gets more investor cash

    • @anton@lemmy.blahaj.zone
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      818 days ago

      If you change the tokenizer you have to retrain from scratch, but you can do so with the old, unpolluted data.

      It’s genius if you think about it,* you can waste energy and tell your investors it’s a new better model, while staying upstream from the river you pollute.
      * at least for consultants, compute providers and other middle men.

      • @UnseriousAcademic
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        417 days ago

        I remember one time in a research project I switched out the tokeniser to see what impact it might have on my output. Spent about a day re-running and the difference was minimal. I imagine it’s wholly the same thing.

        *Disclaimer: I don’t actually imagine it is wholly the same thing.

        • David GerardOPMA
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          417 days ago

          there’s a research result that the precise tokeniser makes bugger all difference, it’s almost entirely the data you put in

          because LLMs are lossy compression for text

          • @froztbyte
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            317 days ago

            latent space go brrrr