Is it more accurate to call current 'Artificial intelligence' (AI/LLM) as Counterfeit Intelligence?

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• DigDoug@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  [deleted]

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  • radix@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

    Autocomplete 2.0

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  • Not_mikey@lemmy.dbzer0.com ⁨2⁩ ⁨weeks⁩ ago

    Calling llms “glorified predictive text” is like calling humans “glorified bacteria”

    Both have the same goal: guess the next word; survive and reproduce, But the way they accomplish that goal requires orders of magnitude more complexity in the case of a human or LLM.

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  • Fallibilist@feddit.uk ⁨2⁩ ⁨weeks⁩ ago

    Which is a so-called thought terminating clishé: a slogan intended to end discussion without even engaging with it.

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• Fallibilist@feddit.uk ⁨2⁩ ⁨weeks⁩ ago

  AI isn’t any one thing. It’s an broad term used in computer science to refer to any system designed to perform a cognitive task that would normally require human intelligence. The chess opponent on an old Atari console is an AI. It’s an intelligent system - but only narrowly so. That’s called “narrow” or “weak” AI.

  It can still have superhuman abilities, but only within the specific task it was built for - like playing chess or generating language.

  A large language model like ChatGPT is also narrow AI. It’s exceptionally good at what it was designed to do: generate natural-sounding language. What people expect from it, though, isn’t narrow intelligence - it’s general intelligence. The ability to apply cognitive skills across a wide range of domains the way a human can. That’s something LLMs simply can’t do - at least not yet. Artificial General Intelligence is the end goal for many AI companies, but LLMs are not generally intelligent. However they still fall under the umbrella of AI as a broad category of systems.

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• Fizz@lemmy.nz ⁨2⁩ ⁨weeks⁩ ago

  I think its clearer to say language models

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• edgemaster72@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  If you’re going to change some part of the name, I think the “intelligence” is the part you should be changing

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• disregardable@lemmy.zip ⁨2⁩ ⁨weeks⁩ ago

  personally I think it’s more accurate to call it either a “pattern identifier” or “random word generator”

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  • Fallibilist@feddit.uk ⁨2⁩ ⁨weeks⁩ ago

    Guess what else heavily relies on pattern recognition and probabilities? Humans.

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    • AskewLord@piefed.social ⁨2⁩ ⁨weeks⁩ ago

      Except most of us suck at it. Very few of us are really good at it.

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• SnotFlickerman@lemmy.blahaj.zone ⁨2⁩ ⁨weeks⁩ ago

  Considering Meta just got caught using contractors to make phone calls for their “AI” that can make phone calls and make reservations. It’s people making the phone calls. It’s people fixing the bad answers.

  It’s Actually (underpaid) Indians

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• BurgerBaron@quokk.au ⁨2⁩ ⁨weeks⁩ ago

  No since the problematic word is “intelligence.”

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• thedeadwalking4242@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  Just say LLM

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  • Bluegrass_Addict@lemmy.ca ⁨2⁩ ⁨weeks⁩ ago

    nah, abbreviations are honestly kinda stupid…

    everyone abbreviates as much as they can with as much stuff as they can, and you end up in dumb scenarios where you’re constantly asking people to define their abbreviations rendering them frustrating and useless

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    • thedeadwalking4242@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

      Ok just say “large language model”

      It’s more descriptive of what it actually is? It’s not intelligence, so “counterfeit intelligence” is just as bad.

      And yeah when it’s random ass abbreviations that’s valid, but when it’s “LLM” which is in every single news cycle, not as much of a problem… especially if you are on a site like lemmy. No one is going to ask you.

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• ChaosCatWitch@feddit.online ⁨2⁩ ⁨weeks⁩ ago

  Well, the words “artificial” and “counterfeit” both mean “fake,” so the accuracy would be the same.

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• Pat_Riot@lemmy.today ⁨2⁩ ⁨weeks⁩ ago

  Poorly simulated intelligence?

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• glimse@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  You think the problem with the term is…the first word?

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  • Bluegrass_Addict@lemmy.ca ⁨2⁩ ⁨weeks⁩ ago

    no, but it drives a point home rather then just calling it shit

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• 4grams@awful.systems ⁨2⁩ ⁨weeks⁩ ago

  I don’t know. SI does actually have a certain ring to it. Stolen Intelligence.

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• flueterflam@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  Several answers touch on this already. “Intelligence” is a very flattering “magic” feeling that doesn’t really explain what is happening with LLMs.

  Probablistic/Statistical weights are heavily involved here. But it feels “intelligent” because of a combination with ever-expanding processing/computational speed and power that can be thrown at the prompts. Things that were previously limited to on-site super computers can now be accessed via the internets/online services.

  It’s worth noting also that dynamic “seeding”, such as via on-demand searches can contribute to better/worse context resolution.

  AI is the common speak for large language model querying (with all the above, plus other details), in mind. So, Probablistic Inferencing (at) Super Speed (i.e. “PISS”) seems about right to me!

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• KRAW@linux.community ⁨2⁩ ⁨weeks⁩ ago

  I think the entire field of AI (not just the generative AI subset) should’ve been called “simulated intelligence” or something like that. It points to the goal of the field (i.e. to achieve something similar to intelligence) without the implicit claim that any of the contributions achieve true intelligence.

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• scallisto@retrofed.com ⁨2⁩ ⁨weeks⁩ ago

  I feel like we should better differentiate between LLMs (the ones that literally tell you to eat rocks), generative models (the ones that are stealing the work of creatives without permission), and the ones that are actually used for neat science stuff, where they are trained on a specific set of data and are doing a specific set of tasks repeatedly, rather than training on the entire internet and then some and trying to do everything!

  I think we should label them as large language models, generative models, and predictive models (maybe? Or maybe “targeted predictive models”?). It’s important to emphasise that all of these, even the useful ones, are not intelligent, they do not understand what they are doing. They are just models of data that do thing go in, thing go out.

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• xia@lemmy.ca ⁨2⁩ ⁨weeks⁩ ago

  How about an echo of intelligence, as it rederived from intelligent signals.

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• JustPlainDave@lemmy.zip ⁨2⁩ ⁨weeks⁩ ago

  🤷

  I’m going to start doing it anyway.

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• TheReanuKeeves@lemmy.world ⁨2⁩ ⁨weeks⁩ ago

  It’s accurate to call AI in It’s current state “a toddler who knows how to google and read pretty well”

  You can even say that to AI and they will agree with it

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  • spankysalmon@fedinsfw.app ⁨2⁩ ⁨weeks⁩ ago

    No, no it is not accurate. At all. A toddler knows meaning behind words. Not too many words, but most toddlers understand there is connection outside of, “this other word likely follows this word”. LLMs do not. They have no concept of meaning. They have no concepts at all.

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    • BlameThePeacock@lemmy.ca ⁨2⁩ ⁨weeks⁩ ago

      If you dig into what we know about human brains, you might find out we aren’t that different. We come up with words based on the previous words just like processing tokens.

      We have have a better model, and more advanced hard(wet)ware but it’s still very much a predictive process based on context.

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