4 ms·

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t un

> It may actually be the final breakthrough we need for AGI. I disagree. As I understand them, LLMs right now don’t understand concepts. They actually don’t understand, period. They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI.

SweetSoftPillow 1y ago
What is "actual intelligence" and how are you different from a Markov chain?
- sixo 1y ago
  Roughly, actual intelligence needs to maintain a world model in its internal representation, not merely an embedding of language, which is a very different data structure and probably will be learned in a very different way. This includes things like: - a map of the world, or concept space, or a codebase, etc - causality - "factoring" which breaks down systems or interactions into predictable parts Language alone is too blurry to do any of these precisely.
  - SweetSoftPillow 1y ago
    Please check an example #2 here: https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/main/README_en.md#case-2-generate-ground-view-from-map-arrowby-tokumin https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/... It is not "language alone" anymore. LLMs are multimodal nowadays, and it's still just the beginning. And keep in mind that these results are produced by a cheap, small and fast model.
    - mdaniel 1y ago
      I thought you were making an entirely different point with your link since the lag caused the page to view just the upskirt render until the rest of the images loaded in and it could scroll to the reference of your actual link Anyway, I don't think that's the flex you think it is since the topology map clearly shows the beginning of the arrow sitting in the river and the rendered image decided to hallucinate a winding brook, as well as its little tributary to the west, in view of the arrow. I am not able to decipher the legend [that ranges from 100m to 500m and back to 100m, so maybe the input was hallucinated, too, for all I know] but I don't obviously see 3 distinct peaks nor a basin between the snow-cap and the smaller mound I'm willing to be more liberal for the other two images, since "instructions unclear" about where the camera was positioned, but for the topology one, it had a circle I know I'm talking to myself, though, given the tone of every one of these threads
    - devnullbrain 1y ago
      Every one of those is the wrong angle
  - coldtea 1y ago
    >Roughly, actual intelligence needs to maintain a world model in its internal representation And how's that not like stored information (memories) and weighted links between each and/or between groups of them?
    - sixo 1y ago
      It probably is a lot like that! I imagine it's a matter of specializing the networks and learning algorithms to converge to world-model-like-structures rather than language-like-ones. All these models do is approximate the underlying manifold structure, just, the manifold structure of a causal world is different from that of language.
  - deleted 1y ago
    [deleted]
  - astrange 1y ago
    > Roughly, actual intelligence needs to maintain a world model in its internal representation This is GOFAI metaphor-based development, which never once produced anything useful. They just sat around saying things like "people have world models" and then decided if they programmed something and called it a "world model" they'd get intelligence, it didn't work out, but then they still just went around claiming people have "world models" as if they hadn't just made it up. An alternative thesis "people do things that worked the last time they did them" explains both language and action planning better; eg you don't form a model of the contents of your garbage in order to take it to the dumpster. https://www.cambridge.org/core/books/abs/computation-and-human-experience/pengi/1526149951669E2DD08CB01C5AE24812 https://www.cambridge.org/core/books/abs/computation-and-hum...
    - sixo 1y ago
      I see no reason to believe an effective LLM-scale "world-modeling" model would look anything like the kinds of things previous generations of AI researchers were doing. It will probably look a lot more like a transformer architecture--big and compute intensive and with a fairly simple structure--but with a learning process which is different in some key way that make different manifold structures fall out.
- ornornor 1y ago
  What I mean is that the current generation of LLMs don’t understand how concepts relate to one another. Which is why they’re so bad at maths for instance. Markov chains can’t deduce anything logically. I can.
  - sindercal 1y ago
    You and Chomsky are probably the last 2 persons on earth to believe that.
    - coldtea 1y ago
      It wouldn't matter if they are both right. Social truth is not reality, and scientific consensus is not reality either (just a good proxy of "is this true", but its been shown to be wrong many times - at least based on a later consensus, if not objective experiments).
    - red75prime 1y ago
      Nah. There are whole communities that maintain a baseless, but utterly confident dismissive stance. Look in /r/programming, for example.
  - oasisaimlessly 1y ago
    The definition of 'Markov chain' is very wide. If you adhere to a materialist worldview, you are a Markov chain. [Or maybe the universe viewed as a whole is a Markov chain.]
  - deleted 1y ago
    [deleted]
  - astrange 1y ago
    > What I mean is that the current generation of LLMs don’t understand how concepts relate to one another. They must be able to do this implicitly; otherwise why are their answers related to the questions you ask them, instead of being completely offtopic? https://phillipi.github.io/prh/ https://phillipi.github.io/prh/ A consequence of this is that you can steal a black box model by sampling enough answers from its API because you can reconstruct the original model distribution.
- ForHackernews 1y ago
  For one thing, I have internal state that continues to exist when I'm not responding to text input; I have some (limited) access to my own internal state and can reason about it (metacognition). So far, LLMs do not, and even when they claim they are, they are hallucinating https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-cot https://transformer-circuits.pub/2025/attribution-graphs/bio...
  - coldtea 1y ago
    >For one thing, I have internal state that continues to exist when I'm not responding to text input Do you? Or do you just have memory and are run on a short loop?
    - shakna 1y ago
      Whilst all the choices you make tend to be in the grey matter, the rest of you does have internal state - mostly in your white matter. https://scisimple.com/en/articles/2025-03-22-white-matter-a-key-player-in-brain-function--a30p1n2 https://scisimple.com/en/articles/2025-03-22-white-matter-a-...
      - coldtea 1y ago
        >Whilst all the choices you make tend to be in the grey matter, the rest of you does have internal state - mostly in your white matter. Yeah, but so? Does the substrate of the memory ...matter? (pun intended) When I wrote memory above it could refer to all the state we keep, regardless if it's gray matter, white matter, the gut "second brain", etc.
        shakna 1y ago
        As the article above attempts to show, there's no loop. Memory and state isn't static. You are always processing, evolving. That's part of why organizational complexity is one of the underpinnings for consciousness. Because who you are is a constant evolution.
        1y ago
creata 1y ago
> As I understand them, LLMs right now don’t understand concepts. In my uninformed opinion it feels like there's probably some meaningful learned representation of at least common or basic concepts. It just seems like the easiest way for LLMs to perform as well as they do.
- jmcgough 1y ago
  Humans assume that being able to produce meaningful language is indicative of intelligence, because the only way to do this until LLMs was through human intelligence.
  - notahacker 1y ago
    Yep. Although the average human also considered proficiency in mathematics to be indicative of intelligence until we invented the pocket calculator, so maybe we're just not smart enough to define what intelligence is.
    - creata 1y ago
      Sorry if I'm being pedantic, but I think you mean arithmetic, not mathematics in general.
  - Izkata 1y ago
    Not really, we saw this decades ago: https://en.wikipedia.org/w/index.php?title=ELIZA_effect https://en.wikipedia.org/w/index.php?title=ELIZA_effect
    - creata 1y ago
      I don't think I'm falling for the ELIZA effect.* I just feel like if you have a small enough model that can accurately handle a wide enough range of tasks, and is resistant to a wide enough range of perturbations to the input, it's simpler to assume it's doing some sort of meaningful simplification inside there. I didn't call it intelligence. * But I guess that's what someone who's falling for the ELIZA effect would say.
pontus 1y ago
I'm curious what you mean when you say that this clearly is not intelligence because it's just Markov chains on steroids. My interpretation of what you're saying is that since the next token is simply a function of the proceeding tokens, i.e. a Markov chain on steroids, then it can't come up with something novel. It's just regurgitating existing structures. But let's take this to the extreme. Are you saying that systems that act in this kind of deterministic fashion can't be intelligent? Like if the next state of my system is simply some function of the current state, then there's no magic there, just unrolling into the future. That function may be complex but ultimately that's all it is, a "stochastic parrot"? If so, I kind of feel like you're throwing the baby out with the bathwater. The laws of physics are deterministic (I don't want to get into a conversation about QM here, there are senses in which that's deterministic too and regardless I would hope that you wouldn't need to invoke QM to get to intelligence), but we know that there are physical systems that are intelligent. If anything, I would say that the issue isn't that these are Markov chains on steroids, but rather that they might be Markov chains that haven't taken enough steroids. In other words, it comes down to how complex the next token generation function is. If it's too simple, then you don't have intelligence but if it's sufficiently complex then you basically get a human brain.
techbruv 1y ago
I don’t understand the argument “AI is just XYZ mechanism, therefore it cannot be intelligent”. Does the mechanism really disqualify it from intelligence if behaviorally, you cannot distinguish it from “real” intelligence? I’m not saying that LLMs have certainly surpassed the “cannot distinguish from real intelligence” threshold, but saying there’s not even a little bit of intelligence in a system that can solve more complex math problems than I can seems like a stretch.
- lupusreal 1y ago
  What it really boils down to is "the machine doesn't have a soul". Just an unfalsifiable and ultimately meaningless objection.
  - tonkinai 1y ago
    Maybe the soul is not as mysterios as we think it is?
    - lupusreal 1y ago
      There is no empirical test for souls.
  - skissane 1y ago
    Maybe panpsychism is true and the machine actually does have a soul, because all machines have souls, even your lawnmower. But possibly the soul of a machine running a frontier AI is a bit closer to a human soul than your lawnmower’s soul is.
    - sfink 1y ago
      By that logic, Larry Ellison would have a soul. You've disproven panpsychism! Congratulations!
  - gitremote 1y ago
    Incorrect. Vertebrate animal brains update their neural connections when interacting with the environment. LLMs don't do that. Their model weights are frozen for every release.
lyime 1y ago
How do you define "LLMs don't understand concepts"? How do you define "understanding a concept" - what do you get if a system can "understand" concept vs not "understanding" a concept?
- jjice 1y ago
  That's a good question. I think I might classify that as solving a novel problem. I have no idea if LLMs can do that consistently currently. Maybe they can. The idea that "understanding" may be able to be modeled with general purpose transformers and the connections between words doesn't sound absolutely insane to me. But I have no clue. I'm a passenger on this ride.
- coldtea 1y ago
  Didn't Apple had a paper proving this very thing, or at least addressing it?
perching_aix 1y ago
They are capable of extracting arbitrary semantic information and generalize across it. If this is not an understanding, I don't know what is.
- ornornor 1y ago
  To me, understanding the world requires experiencing reality. LLMs dont experience anything. They’re just a program. You can argue that living things are also just following a program but the difference is that they (and I include humans in this) experience reality.
  - perching_aix 1y ago
    But they're experiencing their training data, their pseudo-randomness source, and your prompts? Like, to put it in perspective. Suppose you're training a multimodal model. Training data on the terabyte scale. Training time on the weeks scale. Let's be optimistic and assume 10 TB in just a week: that is 16.5 MB/s of avg throughput. Compare this to the human experience. VR headsets are aiming for what these days, 4K@120 per eye? 12 GB/s at SDR, and that's just vision. We're so far from "realtime" with that optimistic 16.5 MB/s, it's not even funny. Of course the experiencing and understanding that results from this will be vastly different. It's a borderline miracle it's any human-aligned. Well, if we ignore lossy compression and aggressive image and video resizing, that is.
    - HeatrayEnjoyer 1y ago
      The human optic nerve is actually closer to 5-10 megabits per second per eye. The brain does much with very little.
  - CamperBob2 1y ago
    (and I include humans in this) experience reality. A fellow named Plato had some interesting thoughts on that subject that you might want to look into.
coldtea 1y ago
>They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI. This argument is circular. A better argument should address (given the LLM successes in many types of reasoning, passing the turing test, and thus at producing results that previously required intelligence) why human intelligence might not also just be "Markov chains on even better steroids".
- IgorPartola 1y ago
  Humans think even when not being prompted by other humans, and in some cases can learn new things by having intuition make a concept clear or by performing thought experiments or by combining memories of old facts and new facts across disciplines. Humans also have various kinds of reasoning (deductive, inductive, etc.). Humans also can have motivations. I don’t know if AGI needs to have all human traits but I think a Markov chain that sits dormant and does not possess curiosity about itself and the world around itself does not seem like AGI.
  - coldtea 1y ago
    >Humans think even when not being prompted by other humans That's more of an implementation detail. Humans take constant sensory input and have some sort of way to re-introduce input later (e.g. remember something). Both could be added (even trivially) to LLMs. And it's not at all clear human thought is contant. It just appears so in our naive intuition (same how we see a movie as moving, not as 24 static frames per second). It's a discontinuous mechanism though (propagation time, etc), and this has been shown (e.g. EEG/MEG show the brain sample sensory input in a periodic pattern, stimuly with small time difference are lost - as if there is a blind-window regarding perception, etc). >and in some cases can learn new things by having intuition make a concept clear or by performing thought experiments or by combining memories of old facts and new facts across disciplines Unless we define intuition in a way that excludes LLM style mechanisms a priori, whose to say LLMs don't do all those things as well, even if in a simpler way? They've been shown to combine stuff across disciplines, and also to develop concepts not directly on their training set. And "performing thought experiments" is not that different than the reasoning steps and backtracking LLMs also already do. Not saying LLMs are on parity with human thinking/consciousness. Just that it's not clear that they're doing more or less the same even at reduced capacity and with a different architecture and runtime setup.
glial 1y ago
Just leaving this here: https://ai.meta.com/research/publications/large-concept-models-language-modeling-in-a-sentence-representation-space/ https://ai.meta.com/research/publications/large-concept-mode...
fakedang 1y ago
Human thinking is also Markov chains on ultra steroids. I wonder if there are any studies out there which have shown the difference between people who can think with a language and people who don't have that language base to frame their thinking process in, based on some of those kids who were kept in isolation from society. "Superhuman" thinking involves building models of the world in various forms using heuristics. And that comes with an education. Without an education (or a poor one), even humans are incapable of logical thought.
d1sxeyes 1y ago
I hear this a lot, and I often ask the question “what is the evidence that human intelligence is categorically different?” So far I haven’t received a clear response.
- ornornor 1y ago
  I think it’s the ability to plan for the future and introspection. I don’t think humans are the only ones to have both these things but that’s what I think of as a way to divide species.
nilkn 1y ago
You’re going to be disappointed when you realize one day what you yourself are.

SweetSoftPillow 1y ago

What is "actual intelligence" and how are you different from a Markov chain?

sixo 1y ago
Roughly, actual intelligence needs to maintain a world model in its internal representation, not merely an embedding of language, which is a very different data structure and probably will be learned in a very different way. This includes things like: - a map of the world, or concept space, or a codebase, etc - causality - "factoring" which breaks down systems or interactions into predictable parts Language alone is too blurry to do any of these precisely.
- SweetSoftPillow 1y ago
  Please check an example #2 here: https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/main/README_en.md#case-2-generate-ground-view-from-map-arrowby-tokumin https://github.com/PicoTrex/Awesome-Nano-Banana-images/blob/... It is not "language alone" anymore. LLMs are multimodal nowadays, and it's still just the beginning. And keep in mind that these results are produced by a cheap, small and fast model.
  - mdaniel 1y ago
    I thought you were making an entirely different point with your link since the lag caused the page to view just the upskirt render until the rest of the images loaded in and it could scroll to the reference of your actual link Anyway, I don't think that's the flex you think it is since the topology map clearly shows the beginning of the arrow sitting in the river and the rendered image decided to hallucinate a winding brook, as well as its little tributary to the west, in view of the arrow. I am not able to decipher the legend [that ranges from 100m to 500m and back to 100m, so maybe the input was hallucinated, too, for all I know] but I don't obviously see 3 distinct peaks nor a basin between the snow-cap and the smaller mound I'm willing to be more liberal for the other two images, since "instructions unclear" about where the camera was positioned, but for the topology one, it had a circle I know I'm talking to myself, though, given the tone of every one of these threads
  - devnullbrain 1y ago
    Every one of those is the wrong angle
- coldtea 1y ago
  >Roughly, actual intelligence needs to maintain a world model in its internal representation And how's that not like stored information (memories) and weighted links between each and/or between groups of them?
  - sixo 1y ago
    It probably is a lot like that! I imagine it's a matter of specializing the networks and learning algorithms to converge to world-model-like-structures rather than language-like-ones. All these models do is approximate the underlying manifold structure, just, the manifold structure of a causal world is different from that of language.
- deleted 1y ago
  [deleted]
- astrange 1y ago
  > Roughly, actual intelligence needs to maintain a world model in its internal representation This is GOFAI metaphor-based development, which never once produced anything useful. They just sat around saying things like "people have world models" and then decided if they programmed something and called it a "world model" they'd get intelligence, it didn't work out, but then they still just went around claiming people have "world models" as if they hadn't just made it up. An alternative thesis "people do things that worked the last time they did them" explains both language and action planning better; eg you don't form a model of the contents of your garbage in order to take it to the dumpster. https://www.cambridge.org/core/books/abs/computation-and-human-experience/pengi/1526149951669E2DD08CB01C5AE24812 https://www.cambridge.org/core/books/abs/computation-and-hum...
  - sixo 1y ago
    I see no reason to believe an effective LLM-scale "world-modeling" model would look anything like the kinds of things previous generations of AI researchers were doing. It will probably look a lot more like a transformer architecture--big and compute intensive and with a fairly simple structure--but with a learning process which is different in some key way that make different manifold structures fall out.
ornornor 1y ago
What I mean is that the current generation of LLMs don’t understand how concepts relate to one another. Which is why they’re so bad at maths for instance. Markov chains can’t deduce anything logically. I can.
- sindercal 1y ago
  You and Chomsky are probably the last 2 persons on earth to believe that.
  - coldtea 1y ago
    It wouldn't matter if they are both right. Social truth is not reality, and scientific consensus is not reality either (just a good proxy of "is this true", but its been shown to be wrong many times - at least based on a later consensus, if not objective experiments).
  - red75prime 1y ago
    Nah. There are whole communities that maintain a baseless, but utterly confident dismissive stance. Look in /r/programming, for example.
- oasisaimlessly 1y ago
  The definition of 'Markov chain' is very wide. If you adhere to a materialist worldview, you are a Markov chain. [Or maybe the universe viewed as a whole is a Markov chain.]
- deleted 1y ago
  [deleted]
- astrange 1y ago
  > What I mean is that the current generation of LLMs don’t understand how concepts relate to one another. They must be able to do this implicitly; otherwise why are their answers related to the questions you ask them, instead of being completely offtopic? https://phillipi.github.io/prh/ https://phillipi.github.io/prh/ A consequence of this is that you can steal a black box model by sampling enough answers from its API because you can reconstruct the original model distribution.
ForHackernews 1y ago
For one thing, I have internal state that continues to exist when I'm not responding to text input; I have some (limited) access to my own internal state and can reason about it (metacognition). So far, LLMs do not, and even when they claim they are, they are hallucinating https://transformer-circuits.pub/2025/attribution-graphs/biology.html#dives-cot https://transformer-circuits.pub/2025/attribution-graphs/bio...
- coldtea 1y ago
  >For one thing, I have internal state that continues to exist when I'm not responding to text input Do you? Or do you just have memory and are run on a short loop?
  - shakna 1y ago
    Whilst all the choices you make tend to be in the grey matter, the rest of you does have internal state - mostly in your white matter. https://scisimple.com/en/articles/2025-03-22-white-matter-a-key-player-in-brain-function--a30p1n2 https://scisimple.com/en/articles/2025-03-22-white-matter-a-...
    - coldtea 1y ago
      >Whilst all the choices you make tend to be in the grey matter, the rest of you does have internal state - mostly in your white matter. Yeah, but so? Does the substrate of the memory ...matter? (pun intended) When I wrote memory above it could refer to all the state we keep, regardless if it's gray matter, white matter, the gut "second brain", etc.
      - shakna 1y ago
        As the article above attempts to show, there's no loop. Memory and state isn't static. You are always processing, evolving. That's part of why organizational complexity is one of the underpinnings for consciousness. Because who you are is a constant evolution.
      - 1y ago

creata 1y ago

> As I understand them, LLMs right now don’t understand concepts. In my uninformed opinion it feels like there's probably some meaningful learned representation of at least common or basic concepts. It just seems like the easiest way for LLMs to perform as well as they do.

jmcgough 1y ago
Humans assume that being able to produce meaningful language is indicative of intelligence, because the only way to do this until LLMs was through human intelligence.
- notahacker 1y ago
  Yep. Although the average human also considered proficiency in mathematics to be indicative of intelligence until we invented the pocket calculator, so maybe we're just not smart enough to define what intelligence is.
  - creata 1y ago
    Sorry if I'm being pedantic, but I think you mean arithmetic, not mathematics in general.
- Izkata 1y ago
  Not really, we saw this decades ago: https://en.wikipedia.org/w/index.php?title=ELIZA_effect https://en.wikipedia.org/w/index.php?title=ELIZA_effect
  - creata 1y ago
    I don't think I'm falling for the ELIZA effect.* I just feel like if you have a small enough model that can accurately handle a wide enough range of tasks, and is resistant to a wide enough range of perturbations to the input, it's simpler to assume it's doing some sort of meaningful simplification inside there. I didn't call it intelligence. * But I guess that's what someone who's falling for the ELIZA effect would say.

pontus 1y ago

I'm curious what you mean when you say that this clearly is not intelligence because it's just Markov chains on steroids. My interpretation of what you're saying is that since the next token is simply a function of the proceeding tokens, i.e. a Markov chain on steroids, then it can't come up with something novel. It's just regurgitating existing structures. But let's take this to the extreme. Are you saying that systems that act in this kind of deterministic fashion can't be intelligent? Like if the next state of my system is simply some function of the current state, then there's no magic there, just unrolling into the future. That function may be complex but ultimately that's all it is, a "stochastic parrot"? If so, I kind of feel like you're throwing the baby out with the bathwater. The laws of physics are deterministic (I don't want to get into a conversation about QM here, there are senses in which that's deterministic too and regardless I would hope that you wouldn't need to invoke QM to get to intelligence), but we know that there are physical systems that are intelligent. If anything, I would say that the issue isn't that these are Markov chains on steroids, but rather that they might be Markov chains that haven't taken enough steroids. In other words, it comes down to how complex the next token generation function is. If it's too simple, then you don't have intelligence but if it's sufficiently complex then you basically get a human brain.

techbruv 1y ago

I don’t understand the argument “AI is just XYZ mechanism, therefore it cannot be intelligent”. Does the mechanism really disqualify it from intelligence if behaviorally, you cannot distinguish it from “real” intelligence? I’m not saying that LLMs have certainly surpassed the “cannot distinguish from real intelligence” threshold, but saying there’s not even a little bit of intelligence in a system that can solve more complex math problems than I can seems like a stretch.

lupusreal 1y ago
What it really boils down to is "the machine doesn't have a soul". Just an unfalsifiable and ultimately meaningless objection.
- tonkinai 1y ago
  Maybe the soul is not as mysterios as we think it is?
  - lupusreal 1y ago
    There is no empirical test for souls.
- skissane 1y ago
  Maybe panpsychism is true and the machine actually does have a soul, because all machines have souls, even your lawnmower. But possibly the soul of a machine running a frontier AI is a bit closer to a human soul than your lawnmower’s soul is.
  - sfink 1y ago
    By that logic, Larry Ellison would have a soul. You've disproven panpsychism! Congratulations!
- gitremote 1y ago
  Incorrect. Vertebrate animal brains update their neural connections when interacting with the environment. LLMs don't do that. Their model weights are frozen for every release.

lyime 1y ago

How do you define "LLMs don't understand concepts"? How do you define "understanding a concept" - what do you get if a system can "understand" concept vs not "understanding" a concept?

jjice 1y ago
That's a good question. I think I might classify that as solving a novel problem. I have no idea if LLMs can do that consistently currently. Maybe they can. The idea that "understanding" may be able to be modeled with general purpose transformers and the connections between words doesn't sound absolutely insane to me. But I have no clue. I'm a passenger on this ride.
coldtea 1y ago
Didn't Apple had a paper proving this very thing, or at least addressing it?

perching_aix 1y ago

They are capable of extracting arbitrary semantic information and generalize across it. If this is not an understanding, I don't know what is.

ornornor 1y ago
To me, understanding the world requires experiencing reality. LLMs dont experience anything. They’re just a program. You can argue that living things are also just following a program but the difference is that they (and I include humans in this) experience reality.
- perching_aix 1y ago
  But they're experiencing their training data, their pseudo-randomness source, and your prompts? Like, to put it in perspective. Suppose you're training a multimodal model. Training data on the terabyte scale. Training time on the weeks scale. Let's be optimistic and assume 10 TB in just a week: that is 16.5 MB/s of avg throughput. Compare this to the human experience. VR headsets are aiming for what these days, 4K@120 per eye? 12 GB/s at SDR, and that's just vision. We're so far from "realtime" with that optimistic 16.5 MB/s, it's not even funny. Of course the experiencing and understanding that results from this will be vastly different. It's a borderline miracle it's any human-aligned. Well, if we ignore lossy compression and aggressive image and video resizing, that is.
  - HeatrayEnjoyer 1y ago
    The human optic nerve is actually closer to 5-10 megabits per second per eye. The brain does much with very little.
- CamperBob2 1y ago
  (and I include humans in this) experience reality. A fellow named Plato had some interesting thoughts on that subject that you might want to look into.

coldtea 1y ago

>They’re basically Markov chains on steroids. There is no intelligence in this, and in my opinion actual intelligence is a prerequisite for AGI. This argument is circular. A better argument should address (given the LLM successes in many types of reasoning, passing the turing test, and thus at producing results that previously required intelligence) why human intelligence might not also just be "Markov chains on even better steroids".

IgorPartola 1y ago
Humans think even when not being prompted by other humans, and in some cases can learn new things by having intuition make a concept clear or by performing thought experiments or by combining memories of old facts and new facts across disciplines. Humans also have various kinds of reasoning (deductive, inductive, etc.). Humans also can have motivations. I don’t know if AGI needs to have all human traits but I think a Markov chain that sits dormant and does not possess curiosity about itself and the world around itself does not seem like AGI.
- coldtea 1y ago
  >Humans think even when not being prompted by other humans That's more of an implementation detail. Humans take constant sensory input and have some sort of way to re-introduce input later (e.g. remember something). Both could be added (even trivially) to LLMs. And it's not at all clear human thought is contant. It just appears so in our naive intuition (same how we see a movie as moving, not as 24 static frames per second). It's a discontinuous mechanism though (propagation time, etc), and this has been shown (e.g. EEG/MEG show the brain sample sensory input in a periodic pattern, stimuly with small time difference are lost - as if there is a blind-window regarding perception, etc). >and in some cases can learn new things by having intuition make a concept clear or by performing thought experiments or by combining memories of old facts and new facts across disciplines Unless we define intuition in a way that excludes LLM style mechanisms a priori, whose to say LLMs don't do all those things as well, even if in a simpler way? They've been shown to combine stuff across disciplines, and also to develop concepts not directly on their training set. And "performing thought experiments" is not that different than the reasoning steps and backtracking LLMs also already do. Not saying LLMs are on parity with human thinking/consciousness. Just that it's not clear that they're doing more or less the same even at reduced capacity and with a different architecture and runtime setup.

glial 1y ago

Just leaving this here: https://ai.meta.com/research/publications/large-concept-models-language-modeling-in-a-sentence-representation-space/ https://ai.meta.com/research/publications/large-concept-mode...

fakedang 1y ago

Human thinking is also Markov chains on ultra steroids. I wonder if there are any studies out there which have shown the difference between people who can think with a language and people who don't have that language base to frame their thinking process in, based on some of those kids who were kept in isolation from society. "Superhuman" thinking involves building models of the world in various forms using heuristics. And that comes with an education. Without an education (or a poor one), even humans are incapable of logical thought.

d1sxeyes 1y ago

I hear this a lot, and I often ask the question “what is the evidence that human intelligence is categorically different?” So far I haven’t received a clear response.

ornornor 1y ago
I think it’s the ability to plan for the future and introspection. I don’t think humans are the only ones to have both these things but that’s what I think of as a way to divide species.

nilkn 1y ago

You’re going to be disappointed when you realize one day what you yourself are.