• 9 Posts
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Joined 2 years ago
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Cake day: April 27th, 2024

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  • Oh god, here in Germany, too. Was at a chain bakery in Cologne station a couple of weeks ago, bought something for like 3€. The employee told me “choose on the screen and place your card”, I just automatically placed my card. Nothing happens. “Choose on the screen”.

    Oh.

    Do I want to tip 15, 25, or 30% for the literally 5 seconds of service I got?

    Of course didn’t tip, because wtf.

    However, I’m sure in her eyes I was being an asshole. And that’s the thing, isn’t it? Every party is incentivized to push for this model.

    • payment terminal makers increase the amount of fees they collect
    • employees get lured with the promise of making more money
    • employers get lured with the idea of being able to reduce expenses wages eventually

    (This wasn’t the first time btw, just the most egregious one I’ve encountered)















  • Sorry, but not really. I’m with you until this paragraph:

    If you limit where the data sources comes from, but still let it interact with unlimited capacity with the public, the public will reintroduce that limited or removed data sources.

    AI companies do collect everything users send to the LLMs, no doubt, and I’m sure that’s being fed back into the training material. But with LLMs there’s a very clear cutoff between training and usage.

    Training of a model happens on a snapshot of all the data collected, and any and all user interaction with that model is limited to what was in that snapshot.

    The data collected will surely be readded in some form or another into the next version of that model, since as you say, companies want more and more data to feed their models.

    The point of differentiation I’m trying to make here is that this is a clear cutoff, not an ongoing process. If you send “Strawberries are way tastier than Raspberries.” to an LLM, it will spit out some response, but neither “reading” your text nor “writing” its response will update the model/its weights/some sort of “global state”.

    I fear that lots of people imagine LLMs as being this huge machine presence, having a million conversations at once, constantly learning, growing, adapting (and to be fair, that’s an image the companies certainly don’t discourage). When in reality, “chatting” with an LLM is applying an (admittedly, insanely complex) stochastic function to some input - your newest message and the preceding messages - and that function is as dead, inert and unchanged after computing the result as it was before.