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[–] 2 points 11 months ago* (6 children)

Not OP, but...

It's not always perfect, but it's good for getting a tldr to see if maybe something is worth reading further. As for translations, it's something AI is rather decent at. And if I go from understanding 0% to 95%, really only missing some cultural context about why a certain phrase might mean something different from face value, that's a win.

You can do a lot with AI where the cost of it not being exactly right is essentially zero. Plus, it's not like humans have a great track record for accuracy, come to think of it. It comes down to being skeptical about it like you would any other source.

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

    Strongly disagree with the TLDR thing

    At least, the iPhone notifications summaries were bad enough I eventually turned them off (but periodically check them) and while I was working at Google you couldn't really turn of the genAI summaries of internal things (that evangelists kept adding to things) and I rarely found them useful. Well... they're useful if the conversation is really bland but then the conversation should usually be in some thread elsewhere, if there was something important I don't think the genAI systems were very good at highlighting it

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  • [–] 2 points 11 months ago

    Completely agree, those summaries are incredibly bad. I was recently looking for some information in Gemini meeting notes and just couldn't find it, even though I was sure it had been talked about. Then I read the transcript itself and realised that the artificial unintelligence had simply left out all the most important bits.

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  • [–] 1 point 11 months ago

    You can disagree, but I find it helpful to decide whether I'm going to read a lengthy article or not. Also if AI picks up on a bunch of biased phrasing or any of a dozen other signs of poor journalism, I can go into reading something (if I even bother to at that point) with an eye toward the problems in an article. Sometimes that helps when an article is trying to lead you down a certain path of thinking.

    I find I'm better at picking out the facts from the bias if I'm forewarned.

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

    iPhone notification summaries were made with GPT3.5 I believe (maybe even the -turbo version).

    It doesn't use reasoning and so when using very short outputs it can produce wild variations since there are not a lot of previous tokens in order to direct the LLM into the appropriate direction in kv-space and so you're more at the whims of temperature setting (randomly selecting the next token from a SOFTMAX'd list which was output from the LLM).

    You can take those same messages and plug them into a good model and get much higher quality results. But good models are expensive and Apple is, for some reason, going for the budget option.

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