13 comments

  • sethev 24 minutes ago
    The challenge here is in trying to decide whether LLMs are intelligent or have a mind. Famously, the criteria for intelligence seem to slip with each advancement in technology. But going back to Turing, his test was actually more carefully phrased than we remember: he said that when machines could pass the test, the question of whether they are intelligent would become moot. That seems to be what we're actually seeing: if people can't tell the difference, it kind of won't matter whether they're "truly intelligent" or not.
    • tomrod 1 minute ago
      I'm a bit more prosaic. I think if we engineered ways for LLMs to begin conversations, rather than just respond, we'd be more open to the concept of their intelligence. Without perceived "will" to do things, they operate as a next-gen search engine or encyclopedia.
  • rayiner 3 minutes ago
    [delayed]
  • rahidz 1 hour ago
    Man I remember back when a psychic conned me by solving the Navier-Stokes problem.

    Also >July 4th, 2023

    • krupan 35 minutes ago
      The LLM did not solve it. It's not intelligent. Humans did, using a statistics-based computational tool (the LLM). We don't even know all the details of how the tool was used, we haven't been allowed to use the exact tool they used ourselves, we don't know much it really cost in dollars, energy, or time, etc. etc.
      • claytongulick 13 minutes ago
        And it may have trained on a NYU professor's work.
    • trescenzi 41 minutes ago
      LLMs can be supremely useful but also not intelligent. It might seem like a pointless distinction but the way we talk about these models matters because it impacts how we interact with and understand their outputs.

      For example if there’s a strongly held belief that models are independent intelligent entities we’re more likely to lay blame upon them instead of their user. It’s important for the safety discussion too. If they are a new class of life then safety is going to focus on making sure they don’t do bad things. If we instead see them as statistical models we will instead try to make sure people don’t misuse them.

      This distinction is even more important today when some of the most powerful people are looking to absolve their crimes by passing them off on their LLMs.

    • Angostura 1 hour ago
      But were you successfully conned into believing an AI had solved the Navier-Stokes problem?
      • tescreal 1 hour ago
        What is the consensus among experts?
        • grey-area 40 minutes ago
          That OpenAI stole the discovery from them.
          • daishi55 26 minutes ago
            That is very much not the consensus of experts.
        • 27388383 1 hour ago
          [flagged]
    • inopinatus 54 minutes ago
      The more compelling inversion is whether the likes of John Nash, Richard Feynman, John Conway etc could’ve had a lucrative second career as conmen.
      • mistercow 35 minutes ago
        Feynman for sure could have. In fact, I think he sort of did, although I'm not sure he meant to. Multiple generations of nerds now have taken books of his anecdotes varying in plausibility and obvious exaggeration as some sort of weird physics cult of personality gospel. But I don't think he was really setting out to curate his legacy so much as he was a good storyteller and he liked to entertain.

        But could he have conned people on purpose? Absolutely.

      • atemerev 44 minutes ago
        von Neumann could. The others, I doubt it.
    • lukewarm707 6 minutes ago
      this seems like non-sequitur if you mean that solving NS is 'intelligence'.

      ai is not conscious. you can solve NS without thinking. the psychic con aspect is anthropomorphising the model. the same phenomenon is present in ELIZA, clever hans, the chinese room.

      it's a significant problem.

      a non-zero number of researchers at anthropic are in some form of ai psychosis. an example of that is ethics employees asking claude about its feelings and ethical concerns in order to make the claude constitution more amenable to the "welfare" of claude.

      they are asking claude how claude feels and then modifying claude according to how claude feels.

      constitution1-claude is trained on constitution1. constitution1-claude edits constitution1. constitution2-claude is trained on constitution2. constitution2-claude edits constitution2.

      claude's emotions are a closed system. there is no external truth to improve against, no metric to verify about claude's emotions. there can be no novelty or reduction in entropy from signal processing in a closed system. no truth can arise. this is model collapse. it is like photocopying the same thing over and over. from the cognitive error of anthropomorphism anthropic is causing ethical collapse.

    • rusk 1 hour ago
      Did an AI do that on its own though? I heard it was human mathematicians using a sophisticated machine as a tool.
      • meowface 1 hour ago
        All of the latest big proofs were driven by professional human mathematicians steering and priming the models, yes.

        All of the best AI-made software projects are also driven by experienced human software developers steering and priming the models. Does that mean the projects "aren't made by AI"?

        No, it just means AI is not quite good enough yet to fully replace humans, and, so, unsurprisingly, the best results will be obtained from people who are already great at a field and who take the time to squeeze as much force multiplication out of LLMs as possible. The AI is still doing well over 95% of the significant work.

        • TomGarden 1 hour ago
          While I agree with you, I think we also have to concede that this is not how these accomplishments have been presented. I'd argue most people I've seen talk about this online are unaware of the mathematicians steering the models.
        • agileAlligator 12 minutes ago
          https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...

          Terrence Tao's conversation with ChatGPT is very illuminating.

          HN Discussion: https://news.ycombinator.com/item?id=49010345

        • basch 1 hour ago
          “Good enough to replace humans” isn’t necessarily the benchmark.

          The question is is a computer with a human stronger than a computer without a human. At what point does the hybrid go from being stronger, to the human getting in the way, or steering the computer in more wrong directions that right ones, or the human not being able to keep up. Does the human add enough extra randomness to be of value for a while, even as a minor co-processor.

      • broast 43 minutes ago
        The way frontier models work, that loop will get compressed to a one-shot within a version or two
      • mstank 1 hour ago
        It sounds like LLMs were pretty useful to them…
        • ModernMech 1 hour ago
          So was Lean. Did Lean solve it?
          • zamadatix 41 minutes ago
            Nothing is solved in isolation but credit usually goes to wherever the new work in the paper comes from instead of the whole mountain of previous mathematics or existing tools used. The most relevant of those get referenced and then this reference tree builds a tree of collective base work needed across history.
  • daishi55 28 minutes ago
    > many people are convinced that language models, or specifically chat-based language models, are intelligent. But there isn’t any mechanism inherent in large language models (LLMs) that would seem to enable this

    Seems like we can just stop reading here right? The author seems to have made up their mind that this very open question is closed, or at least they are not really interested in the question at all. Not sure why I would continue reading a blog based on this premise.

    Edit: oh I see, written in 2023. Well, I wonder if the author has updated their attitude towards this question? Indeed that would be the most interesting thing to know.

    • azakai 8 minutes ago
      It's even worse than that. Of course there is a mechanism in LLMs that could explain intelligence. That is the entire point of neural networks, from the 1950's! They were designed from the start as a model of brain computation.

      Neural networks are not literally brains - just computational models - but if you are not a dualist, then computation is what the human brain does. Modeling that computation can explain something about intelligence.

      Specifically: when scientists look inside a human brain, it seems it does its work using large numbers of highly-interconnected but simple units. The neural network model of brain computation begins there and tries to produce intelligent behavior. If it succeeds, then perhaps the model is right.

      And it has succeeded: after 75 years, neural networks produce complex behavior that is arguably intelligent. Nobel Prizes were awarded. This does not prove the neural network model of intelligence is accurate, but it is a significant point in its favor, at least.

      The author seems entirely unaware of any of this.

  • vhantz 18 minutes ago
    Building up strawmen against LLMs will only make the hypers look more reasonable. A language model responds to inouts exactly as a model of anything else would. That is enough to explain all the "intelligence" without believing a model is somehow a "new kind of mind". Those who think LLMs are intelligent don't know enough about models. And those who think they are useless don't know enough about models.
    • 10xDev 13 minutes ago
      So once we have online learning in LLMs, what do you think you will have that makes you intelligent but not LLMs? Better learning efficiency? That will be improved as well.

      I think we need to start moving on from the term LLMs because it clearly confuses people since they started modelling more than just language.

  • ungreased0675 20 minutes ago
    It does seem like LLMs share the language of psychics.

    The author is also correct that LLM evangelicals and believers in the occult speak about it similarly.

  • mstank 1 hour ago
    This is a strange newsletter post. It’s harping against AI but seems AI-written itself.

    Its ultimate conclusion:

    “I’ve come to the conclusion that a language model is almost always the wrong tool for the job.

    I strongly advise against integrating an LLM or chatbot into your product, website, or organisational processes.”

    Seems so obviously biased that I can only understand it with the context that the writer is trying to sell their book for €35

    • mstank 1 hour ago
      Just realized this was written in 2023. Can’t believe how wrong we were about AI back then.
      • JoshTriplett 1 hour ago
        Can't believe how right we were, too.
    • ryuuseijin 1 hour ago
      The post makes sense for 2023. Today, not so much.

      Also, definitely not AI written if the date is accurate.

  • aetherspawn 41 minutes ago
    Stay the hell away from spooky stuff like psychics and tarot readers - the more you don’t believe in it, the better.

    But better again that you do believe, and know that these are not harmless fun, but that there are dark and hidden and evil things in this world to stay away from.

    • besterman23 15 minutes ago
      Stop trying to pump your Tarot reader IPO
  • _superposition_ 12 minutes ago
    I predict a lot of butt hurt tokens in the comments...
  • krupan 14 minutes ago
    People are missing the point. We should all be much more skeptical, much more careful about how we evaluate the claims made by the people selling these products because we as humans are super vulnerable to the types of scams the author of this article describes. We all know someone that has fallen for a scam, been "cured" of a "disease" by someone whose just selling sugar pills, but we are blind to our own weakness for similar schemes. Surely we aren't that easily duped! Yet hacker news is now full of comments from people confidently predicting what is coming right around the corner, revering the Frontier Models, and defending every claim from OpenAI and Anthropic about how amazing their proprietary closed source secret sauce fueled product is.
  • atemerev 1 hour ago
    All of this is accurate (and useful). But yeah, psychics do not prove theorems from frontier math and build working complex software.
    • krupan 32 minutes ago
      Neither do LLMs. Humans using them do. Similar to how cops solve crimes using psychics.
    • igortg 56 minutes ago
      On one side I agree that LLMs and Agents are not intelligent, but they present an illusion of intelligence given the shear amount of data they can process and act upon.

      But that cannot be used to discredit the fact that these are incredibly powerful tools that can get out of control and cause great damage.

      • atemerev 51 minutes ago
        What is "intelligence" then. I think the universalism of LLMs is now evident enough that they can be considered "intelligent", even in slightly different realization compared to humans.

        As of "great damage", I doubt it. They do not have self-preservation instinct (all "worrying" experiments are the attempts to initiate something resembling self-preservation from human initiative). The driving part is external - the query loop can always be turned off. So yes, a dangerous tool that can be exploited by humans (including governments, especially governments - which is why I am skeptical to government regulation proposals, particularly looking at what passes as governments in this era). But there are no inherent dangers from their own agency, as there is none.

    • cmiles74 52 minutes ago
      In my opinion, this article is talking about people who get into long conversations and become convinced the model is “intelligent”, maybe even “AGI”. This seems to be a trap people are falling into, even in 2026.
      • krupan 28 minutes ago
        It's definitely talking about that, but it's also talking about all of us:

        - fawning over how amazing these tools are

        - believing everything OpenAI and Anthropic say about how powerful and dangerous their product is

        - minimizing the amount of human effort and involvement in every "AI" achievement

      • atemerev 48 minutes ago
        Initial definitions of AGI (as of 2014) are long surpassed. Then, AGI was defined as something that is general enough to work in many fields and orient themselves. It did not include being smarter than humans or even having comparable intelligence to humans. By original standards, we have AGI already for some time.

        Current AGI definitions are intentionally vague.

    • Madmallard 32 minutes ago
      Neither does LLMs. Not without a monumental amount of human oversight and expertise.

      Everyone not in a particular field asking LLM about said field is rolling bad dice.

      • atemerev 0 minutes ago
        I have published a LLM-assisted proof of a long-standing problem in convex geometry (70 years) while not being a specialist in convex geometry. I am a scientist and I have education and scientific experience in computer science and systems biology, but I was never a mathematician. So, well, you can definitely work across fields at least.
  • aidiscoverywire 1 minute ago
    [flagged]