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The LLMentalist Effect by zahlman

The LLMentalist Effect by zahlman

26 Comments

  • Post Author
    zahlman
    Posted February 8, 2025 at 3:30 pm

    Original title (too long for submission):

    > The LLMentalist Effect: how chat-based Large Language Models replicate the mechanisms of a psychic's con

  • Post Author
    JKCalhoun
    Posted February 8, 2025 at 6:18 pm

    > 1 The tech industry has accidentally invented the initial stages a completely new kind of mind, based on completely unknown principles…

    > 2) The intelligence illusion is in the mind of the user and not in the LLM itself.

    I've felt as though there is something in between. Maybe:

    3) The tech industry invented the initial stages a kind of mind that, though misses the mark, is approaching something not too dissimilar to how an aspect of human intelligence works.

    > By using validation statements, … the chatbot and the psychic both give the impression of being able to make extremely specific answers, but those answers are in fact statistically generic.

    "Mr. Geller, can you write some Python code for me to convert a 1-bit .bmp file to a hexadecimal string?"

    Sorry, even if you think the underlying mechanisms have some sort of analog there's real value in LLM's, not so psychics doing "cold readings".

  • Post Author
    prideout
    Posted February 8, 2025 at 6:49 pm

    I lost interest fairly quickly because the entire article seems to rely on a certain definition of "intelligent" that is not made clear in the beginning.

  • Post Author
    dist-epoch
    Posted February 8, 2025 at 6:53 pm

    Yeah, when I read about AI solving international math olympiad problems it's not intelligence, it's just me projecting my math skills upon the model.

    > LLMs are a mathematical model of language tokens. You give a LLM text, and it will give you a mathematically plausible response to that text.

    > The tech industry has accidentally invented the initial stages a completely new kind of mind, based on completely unknown principles, using completely unknown processes that have no parallel in the biological world.

    Or maybe our mind is based on a bunch of mathematical tricks too.

  • Post Author
    swaraj
    Posted February 8, 2025 at 6:54 pm

    You should try the arc agi puzzles yourself, and then tell me you think these things aren't intelligent

    https://arcprize.org/blog/openai-o1-results-arc-prize

    I wouldn't say it's full agi or anything yet, but these things can definitely think in a very broad sense of the word

  • Post Author
    dosinga
    Posted February 8, 2025 at 6:56 pm

    This feels rather forced. The article seems to claim both that LLMs don't actually work, it is all an illusion and that of course the LLMs know everything, they stole all our work from the last 20 years by scraping the internet and underpaying people to produce content. If it was a con, it wouldn't have to do that. Or in other words, if you had a psychic who actually memorized all biographies of all people ever, they wouldn't need their cons

  • Post Author
    EagnaIonat
    Posted February 8, 2025 at 7:23 pm

    I was hoping it was talking about how it can resonate with users using those techniques. Or some experiments to prove the point. But it is not even that.

    There is nothing of substance in this and it feels like the author has a grudge against LLMs.

  • Post Author
    pama
    Posted February 8, 2025 at 7:25 pm

    This is from 2023 and is clearly dated. It is mildly interesting to notice how quickly things changed since then. Nowadays models can solve original math puzzles much of the time and it is harder to argue they cannot reason when we have access to R1, o1, and o3-mini.

  • Post Author
    jbay808
    Posted February 8, 2025 at 7:30 pm

    I was interested in this question so I trained NanoGPT from scratch to sort lists of random numbers. It didn't take long to succeed with arbitrary reliability, even given only an infinitesimal fraction of the space of random and sorted lists as training data. Since I can evaluate the correctness of a sort arbitrarily, I could be certain that I wasn't projecting my own beliefs onto its response, and reading more into the output than was actually there.

    That settled this question for me.

  • Post Author
    Terr_
    Posted February 8, 2025 at 7:46 pm

    There's another illusory effect here: Humans are being encouraged to confuse a fictional character with the real-world "author" system.

    I can create a mad-libs program which dynamically reassembles stories involving a kind and compassionate Santa Claus, but that does not mean the program shares those qualities. I have not digitally reified the spirit of Christmas, not even if excited human kids contribute some of the words that shape its direction and clap with glee.

    P.S.: This "LLM just makes document bigger" framing is also very useful understanding how prompt injection and hallucinations are constant core behaviors, which we just ignore except when they inconvenience us The assistant-bot in the story can be twisted or vanish so abruptly because it's just something in a digital daydream.

  • Post Author
    karmakaze
    Posted February 8, 2025 at 8:00 pm

    AlphaGo also doesn't reason. That doesn't mean it can't do things that humans do by reasoning. It doesn't make sense to make these comparisons. It's like saying that planes don't really fly because they aren't flapping their wings.

    Edit: Don't conflate mechanisms with capabilities.

  • Post Author
    IshKebab
    Posted February 8, 2025 at 8:04 pm

    > But there isn’t any mechanism inherent in large language models (LLMs) that would seem to enable this

    Stopped reading here. What is the mechanism in humans that enables intelligence? You don't know? Didn't think so. So how do you know LLMs don't have the required mechanism?

  • Post Author
    twobitshifter
    Posted February 8, 2025 at 8:09 pm

    Lost me here – “LLMs are not brains and do not meaningfully share any of the mechanisms that animals or people use to reason or think.“

    “the initial stages a completely new kind of mind, based on completely unknown principles, using completely unknown processes that have no parallel in the biological world.”

    We just call it a neural network because we wanted to confuse biology with math for the hell of it?

    “There is no reason to believe that it thinks or reasons—indeed, every AI researcher and vendor to date has repeatedly emphasised that these models don’t think.”

    I mean just look at the Nobel Prize winners for counter examples to all of this https://www.cnn.com/2024/10/08/science/nobel-prize-physics-h…

    I don’t understand the denialism behind replicating minds and thoughts with technology – that had been the entire point from the start.

  • Post Author
    bloomingkales
    Posted February 8, 2025 at 8:18 pm

    Why not make a simpler conclusion? It speaks to humans like people speak to Trump, a narcissist.

    Everything has to start with “you are great”.

    All humans are huge narcissists and the AI is told so, and acts accordingly.

    “Isn’t it weird how the beggar constantly kneels?”

    How silly an observation.

  • Post Author
    olddustytrail
    Posted February 8, 2025 at 8:19 pm

    > One of the issues in during this research—one that has perplexed me—has been that many people are convinced that language models, or specifically chat-based language models, are intelligent.

    Different people have different definitions of intelligence. Mine doesn't require thinking or any kind of sentience so I can consider LLMs to be intelligent simply because they provide intelligent seeming answers to questions.

    If you have a different definition, then of course you will disagree.

    It's not rocket science. Just agree on a definition beforehand.

  • Post Author
    habitue
    Posted February 8, 2025 at 8:53 pm

    This kind of "LLMs don't really do anything, it's all a trick" / "they're stochastic parrots" argument was kind of maybe defensible a year and a half ago. At this point, if you're making these arguments you're willfuly ignorant of what is happening.

    LLMs write code, today, that works. They solve hard PhD level questions, today.

    There is no trick. If anything, it's clear they haven't found a trick and are mostly brute forcing the intelligence they have. They're using unbelievable amounts of compute and are getting close to human level. Clearly humans still have some tricks that LLMs dont have yet, but that doesn't diminish what they can objectively do.

  • Post Author
    fleshmonad
    Posted February 8, 2025 at 9:01 pm

    Unfounded cope. And I know this will get me downvoted, as these arguments seem to be popular among the intellectuals on this glorious page.

    The machanism of intelligence is not understood. There isn't even a rigorous definition of what intelligence is. "All it does is combine parts it has seen in its training set to give an answer", well then the magic lies in how it knows what parts to combine, if one wants to go with this argument. Also conveniently, the fact that we have millions of years of evolution behind us, plus exabytes of training data over the years in form of different stimuli since birth gets shoved under the rug. I don't want to say that the conclusion is necessarily wrong, but the argument is always bad. I know it is hard to come to terms with the thought that intelligence may be more fundamental in nature and not exclusively a capability of carbon based life forms.

  • Post Author
    viach
    Posted February 8, 2025 at 9:14 pm

    > 1 The tech industry has accidentally invented the initial stages a completely new kind of mind, based on completely unknown principles…

    > 2) The intelligence illusion is in the mind of the user and not in the LLM itself.

    3) The intelligence of the users is illusion either?

  • Post Author
    GuB-42
    Posted February 8, 2025 at 9:19 pm

    "Do LLMs think?" is a false problem outside of the field of philosophy.

    The real question that gets billions invested is "Is it useful?".

    If the "con artist" solves my problem, that's fine by me. It is like having a mentalist tell me "I see that you are having a leaky faucet and I see your future in a hardware store buying a 25mm gasket and teflon tape…". In the end, I will have my leak fixed and that's what I wanted, who care how it got to it?

  • Post Author
    ripped_britches
    Posted February 8, 2025 at 9:24 pm

    This article confuses conscious, felt experience with intelligence.

  • Post Author
    tomohelix
    Posted February 8, 2025 at 9:36 pm

    On a bit of a tangent and hypothetical, but what if we pool eough resources together to do a training that includes everything a human can experience? I am thinking of all the five senses and all the data that comes with it, e.g. books, movies, songs, recitals, landscape, the wind brushing against the "skin", the pain of getting burned, the smell of coffee in the morning, the itchiness of a mosquito's bite, etc.

    It is not impossible I think, just require so much effort, talents, and funding that the last thing resembling such an endeavor was the Manhattan project. But if it succeeded, the impact could rival or even exceed what nuclear power had done.

    Or am I deluded and there is some sort of fundamental limit or restriction on the transformer that would completely prevent this from the start?

  • Post Author
    tmnvdb
    Posted February 8, 2025 at 9:44 pm

    I'm amazed people are upvoting this piece which does not grapple with any of the real issues in a serious way. I guess some folks just really want AI to go away and are longing to hear that it is just all newfangled nonsense from the city slickers!

  • Post Author
    cratermoon
    Posted February 8, 2025 at 9:53 pm

    I've never gotten a good answer to my question regarding why Open AI chose a chat UI for their gpt, but this article comes closest to explaining it.

  • Post Author
    orbital-decay
    Posted February 8, 2025 at 10:17 pm

    >LLMs <snip> do not meaningfully share any of the mechanisms that animals or people use to reason or think.

    This seems to be a hard assumption the entire post, and many other similar ones, rely upon. But how do you know how people think or reason? How do you know human intelligence is not an illusion? Decades of research were unable to answer this. Now when LLMs are everywhere, suddenly everybody is an expert in human thinking with extremely strong opinions. To my vague intuition (based on understanding of how LLMs work) it's absolutely obvious they do share at least some fundamental mechanisms, regardless of vast low-level architecture/training differences. The entire discussion on whether it's real intelligence or not is based on ill-defined terms like "intelligence", so we can keep going in circles with it.

    By the way, OpenAI does nothing of this, see [1]:

    >artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work

    Neither do others. So the author describes "tech industry" unknown to me.

    [1] https://openai.com/charter/

  • Post Author
    xg15
    Posted February 8, 2025 at 11:21 pm

    > But that isn’t how language models work. LLMs model the distribution of words and phrases in a language as tokens. Their responses are nothing more than a statistically likely continuation of the prompt.

    Not saying the author is wrong in general, but this kind of argument always annoys me. It's effectively a Forer statement for the "sceptics" side: It appears like a full-on refutation, but really says very little. It also evokes certain associations which are plain incorrect.

    LLMs are functions that return a probability distribution of the next word given the previous words; this distribution is derived from the training data. That much is true. But this does not tell anything about how the derivation and probability generation processes actually work or how simple or complex they are.

    What it does however, is evoke two implicit assumptions without justifying them:

    1) LLMs fundamentally cannot have humanlike intelligence, because humans are qualitatively different: An LLM is a mathematical model and a human is, well, a human.

    Sounds reasonable until you have a look at the human brain and find that human consciousness and thought too could be represented as nothing more than interactions between neurons. At which point, it gets metaphysical…

    2) It implies that because LLMs are "statistical models", they are essentially slightly improved Markov chains. So if an LLM predicts the next word, it would essentially just look up where the previous words appeared in its training data most often and then return the next word from there.

    That's not how LLMs work at all. For starters, the most extensive Markov chains have a context length of 3 or 4 words, while LLMs have a context length of many thousand words. Your required amounts of training data would go to "number of atoms in the universe" territory if you wanted to create a Markov chain with comparable context length.

    Secondly, as current LLMs are based on the mathematical abstraction of neural networks, the relationship between training data and the eventual model weights/parameters isn't even fully deterministic: The weights are set to initial values based on some process that is independent of the training data – e.g. they are set to random values – and then incrementally adjusted so that the model can increasingly replicate the training data. This means that the "meaning" of individual weights and their relationship to the training data remains very unclear, and there is plenty of space in the model where higher-level "semantic" representations might evolve.

    None of that is proof that LLMs have "intelligence", but I think it does show that the question can't be simply dismissed by saying that LLMs are statistical models.

  • Post Author
    ramesh31
    Posted February 8, 2025 at 11:22 pm

    It feels like we are stuck in two different worlds with this stuff right now. One being the AI users that interface solely through app based things like ChatGPT, who have been burned over and over again by hallucinations or lack of context, to the point of disillusionment. The other world is the one where developers who are working with agentic systems built on frontier models right now are literally watching AGI materialize in front of us in real time. I think 2025 will be the year those worlds converge (for the better).

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