• EnderMB@lemmy.world
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    1 month ago

    “sigh”

    (Preface: I work in AI)

    This isn’t news. We’ve known this for many, many years. It’s one of the reasons why many companies didn’t bother using LLM’s in the first place, that paired with the sheer amount of hallucinations you’ll get that’ll often utterly destroy a company’s reputation (lol Google).

    With that said, for commercial services that use LLM’s, it’s absolutely not true. The models won’t reason, but many will have separate expert agents or API endpoints that it will be told to use to disambiguate or better understand what is being asked, what context is needed, etc.

    It’s kinda funny, because many AI bros rave about how LLM’s are getting super powerful, when in reality the real improvements we’re seeing is in smaller models that teach a LLM about things like Personas, where to seek expert opinion, what a user “might” mean if they misspell something or ask for something out of context, etc. The LLM’s themselves are only slightly getting better, but the thing that preceded them is propping them up to make them better

    IMO, LLM’s are what they are, a good way to spit information out fast. They’re an orchestration mechanism at best. When you think about them this way, every improvement we see tends to make a lot of sense. The article is kinda true, but not in the way they want it to be.

    • V0ldek@awful.systems
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      1 month ago

      (Preface: I work in AI)

      Are they a serious researcher in ML with insights into some of the most interesting and complicated intersections of computer science and analytical mathematics, or a promptfondler that earns 3x the former’s salary for a nebulous AI startup that will never create anything of value to society? Read on to find out!

    • blakestacey@awful.systems
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      1 month ago

      (Preface: I work in AI)

      Preface: repent for your sins in sackcloth and ashes.

      IMO, LLM’s are what they are, a good way to spit information out fast.

      Buh bye now.