4 ms·

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that

LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.

meheleventyone 11mo ago
Human brains aren’t magic in the literal sense but do have a lot of mechanisms we don’t understand. They’re certainly special both within the individual but also as a species on this planet. There are many similar to human brains but none we know of with similar capabilities. They’re also most obviously certainly different to LLMs both in how they work foundationally and in capability. I definitely agree with the materialist view that we will ultimately be able to emulate the brain using computation but we’re nowhere near that yet nor should we undersell the complexity involved.
- panarky 11mo ago
  When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.
  - meheleventyone 11mo ago
    This really shows how imprecise a term 'thinking' is here. In this sense any predictive probabilistic blackbox model could be termed 'thinking'. Particularly when juxtaposed against something as concrete as flight that we have modelled extremely accurately.
    - lostmsu 11mo ago
      Yes, to a degree. A very low degree at that.
      - atomicthumbs 11mo ago
        AIs think like a rock flies.
  - nkrisc 11mo ago
    If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?
    - shawabawa3 11mo ago
      that depends, if you explain the rules of the game you're playing and give the dice a goal to win the game, do they adjust the numbers they reveal according to the rules of the game? If so, yes, they're thinking
      - brendoelfrendo 11mo ago
        As someone who plays a lot of Dungeons and Dragons, it sure feels like the dice are thinking sometimes.
      - nkrisc 11mo ago
        The rules of the game are to reveal two independent numbers in the range [1,6].
    - danielbln 11mo ago
      If I take a plane apart and throw all the parts off a cliff, will they achieve sustained flight? If I throw some braincells into a cup alongside the dice, will they think about the outcome anymore than the dice alone?
    - kortex 11mo ago
      https://en.wikipedia.org/wiki/Emergence https://en.wikipedia.org/wiki/Emergence
  - jibal 11mo ago
    That's a fallacy of denial of the antecedent. You are inferring from the fact that airplanes really fly that AIs really think, but it's not a logically valid inference.
    - hackernewds 11mo ago
      Yeah at that point, just arguing semantics
    - fc417fc802 11mo ago
      Observing a common (potential) failure mode is not equivalent to asserting a logical inference. It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing.
    - jibal 11mo ago
      "Observing a common (potential) failure mode" That's not what we have here. "It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing." Some people are willfully blind.
  - staticman2 11mo ago
    Whenever someone paraphrases a folksy aphorism about airplanes and birds or fish and submarines I suppose I'm meant to rebut with folksy aphorisms like: "A.I. and humans are as different as chalk and cheese." As aphorisms are a good way to think about this topic?
- Davidzheng 11mo ago
  ofc, and probably will never understand because of sheer complexity. It doesn't mean we can't replicate the output distribution through data. Probably when we do in efficient manners, the mechanisms (if they are efficient) will be learned too.
- DoctorOetker 11mo ago
  I agree we shouldn't undersell or underestimate the complexity involved, but when LLM's start contributing significant ideas to scientists and mathematicians, its time to recognize that whatever tricks are used in biology (humans, octopuses, ...) may still be of interest and of value, but they no longer seem like the unique magical missing ingredients which were so long sought after. From this point on its all about efficiencies: modeling efficiency: how do we best fit the elephant, with bezier curves, rational polynomials, ...? memory bandwidth training efficiency: when building coincidence statistics, say bigrams, is it really necessary to update the weights for all concepts? a co-occurence of 2 concepts should just increase the predicted probability for the just observed bigram and then decrease a global coefficient used to scale the predicted probabilities. I.e. observing a baobab tree + an elephant in the same image/sentence/... should not change the relative probabilities of observing french fries + milkshake versus bicycle + windmill. This indicates different architectures should be possible with much lower training costs, by only updating weights of the concepts observed in the last bigram. and so on with all other kinds of efficiencies.
jpkw 11mo ago
Right, I'm just going to teach my dog to do my job then and get free money as my brain is no more magic, special or different to theirs!
littlestymaar 11mo ago
> LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? “Internal combustion engines and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others?” The question isn't about what an hypothetical mechanism can do or not, it's about whether the concrete mechanism we built does or not. And this one doesn't.
- ben_w 11mo ago
  The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is "abstract thought"? Is that even the same between any two humans who use that word to describe their own inner processes? Because "imagination"/"visualise" certainly isn't.
  - rob74 11mo ago
    > no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...
    - quantummagic 11mo ago
      But humans do the same thing. How many eons did we make the mistake of attributing everything to God's will, without a scientific thought in our heads? It's really easy to be wrong, when the consequences don't lead to your death, or are actually beneficial. The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.
      - 11mo ago
RayVR 11mo ago
I'm not arguing that human brains are magic. the current AI models will probably teach us more about what we didn't know about intelligence than anything else.
thesz 11mo ago
> Human brains aren't magic, special or different. DNA inside neurons uses superconductive quantum computations [1]. [1] https://www.nature.com/articles/s41598-024-62539-5 https://www.nature.com/articles/s41598-024-62539-5 As the result, all living cells with DNA emit coherent (as in lasers) light [2]. There is a theory that this light also facilitates intercellular communication. [2] https://www.sciencealert.com/we-emit-a-visible-light-that-vanishes-when-we-die-says-surprising-new-study https://www.sciencealert.com/we-emit-a-visible-light-that-va... Chemical structures in dendrites, not even neurons, are capable to compute XOR [3] which require multilevel artificial neural network with at least 9 parameters. Some neurons in brain have hundredths of thousands of dendrites, we are now talking of millions of parameters only in single neuron's dendrites functionality. [3] https://www.science.org/doi/10.1126/science.aax6239 https://www.science.org/doi/10.1126/science.aax6239 So, while human brains aren't magic, special or different, they are just extremely complex. Imagine building a computer with 85 billions of superconducting quantum computers, optically and electrically connected, each capable of performing computations of a non-negligibly complex artificial neural network.
- danielbln 11mo ago
  They are extremely complex, but is that complexity required for building a thinking machine? We don't understand bird physiology enough to build a bird from scratch, but an airplane flies just the same.
  - sublinear 11mo ago
    Are we not just getting lost in semantics when we say "fly"? An airplane does not at all perform the same behavior as a bird. Do we say that boats or submarines "swim"? Planes and boats disrupt the environments they move through and air and sea freight are massive contributors to pollution.
    - IAmBroom 11mo ago
      You seem to have really gone off the rails midway through that post...
arowthway 11mo ago
For some unexplainable reason your subjective experience happens to be localized in your brain. Sounds pretty special to me.
- mapontosevenths 11mo ago
  There is nothing special about that either. LLM's also have self awareness/introspection, or at least a some version of it. https://www.anthropic.com/research/introspection https://www.anthropic.com/research/introspection Its hard to tell sometimes because we specifically train them to believe they don't.
  - arowthway 11mo ago
    Thanks for the link, I haven't seen this before and it's interesting. I don't think the version of self awareness they demonstrated is synonymous with subjective experience. But same thing can be said about any human other then me. Damn, just let me believe all brains are magical or I'll fall into solipsism.
nephihaha 11mo ago
There isn't anything else around quite like a human brain that we know of, so yes, I'd say they're special and different. Animals and computers come close in some ways but aren't quite there.
d-lisp 11mo ago
(Motors and human brains are both just mechanisms, the reason one is a priori capable of learning abstract thought and not the other ?) While I agree to some extent with the materialistic conception, the brain is not an isolated mechanism, but rather the element of a system which itself isn't isolated from the experience of being a body in a world interacting with different systems to form super systems. The brain must be a very efficient mechanism, because it doesn't need to ingest the whole textual production of the human world in order to know how to write masterpieces (music, litterature, films, software, theorems etc...). Instead the brain learns to be this very efficient mechanism with (as a starting process) feeling its own body sh*t on itself during a long part of its childhood. I can teach someone to become really good at producing fine and efficient software, but on the contrary I can only observe everyday that my LLM of choice keeps being stupid even when I explain it how it fails. ("You're perfectly right !"). It is true that there's nothing magical about the brain, but I am pretty sure it must be stronger tech than a probabilistic/statistical next word guesser (otherwise there would be much more consensus about the usability of LLMs I think).
- cindyllm 11mo ago
  [dead]
jibal 11mo ago
Thermometers and human brains are both mechanisms. Why would one be capable of measuring temperature and other capable of learning abstract thought? > If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different. Google "strawman".

meheleventyone 11mo ago

Human brains aren’t magic in the literal sense but do have a lot of mechanisms we don’t understand. They’re certainly special both within the individual but also as a species on this planet. There are many similar to human brains but none we know of with similar capabilities. They’re also most obviously certainly different to LLMs both in how they work foundationally and in capability. I definitely agree with the materialist view that we will ultimately be able to emulate the brain using computation but we’re nowhere near that yet nor should we undersell the complexity involved.

panarky 11mo ago
When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.
- meheleventyone 11mo ago
  This really shows how imprecise a term 'thinking' is here. In this sense any predictive probabilistic blackbox model could be termed 'thinking'. Particularly when juxtaposed against something as concrete as flight that we have modelled extremely accurately.
  - lostmsu 11mo ago
    Yes, to a degree. A very low degree at that.
    - atomicthumbs 11mo ago
      AIs think like a rock flies.
- nkrisc 11mo ago
  If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?
  - shawabawa3 11mo ago
    that depends, if you explain the rules of the game you're playing and give the dice a goal to win the game, do they adjust the numbers they reveal according to the rules of the game? If so, yes, they're thinking
    - brendoelfrendo 11mo ago
      As someone who plays a lot of Dungeons and Dragons, it sure feels like the dice are thinking sometimes.
    - nkrisc 11mo ago
      The rules of the game are to reveal two independent numbers in the range [1,6].
  - danielbln 11mo ago
    If I take a plane apart and throw all the parts off a cliff, will they achieve sustained flight? If I throw some braincells into a cup alongside the dice, will they think about the outcome anymore than the dice alone?
  - kortex 11mo ago
    https://en.wikipedia.org/wiki/Emergence https://en.wikipedia.org/wiki/Emergence
- jibal 11mo ago
  That's a fallacy of denial of the antecedent. You are inferring from the fact that airplanes really fly that AIs really think, but it's not a logically valid inference.
  - hackernewds 11mo ago
    Yeah at that point, just arguing semantics
  - fc417fc802 11mo ago
    Observing a common (potential) failure mode is not equivalent to asserting a logical inference. It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing.
  - jibal 11mo ago
    "Observing a common (potential) failure mode" That's not what we have here. "It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing." Some people are willfully blind.
- staticman2 11mo ago
  Whenever someone paraphrases a folksy aphorism about airplanes and birds or fish and submarines I suppose I'm meant to rebut with folksy aphorisms like: "A.I. and humans are as different as chalk and cheese." As aphorisms are a good way to think about this topic?
Davidzheng 11mo ago
ofc, and probably will never understand because of sheer complexity. It doesn't mean we can't replicate the output distribution through data. Probably when we do in efficient manners, the mechanisms (if they are efficient) will be learned too.
DoctorOetker 11mo ago
I agree we shouldn't undersell or underestimate the complexity involved, but when LLM's start contributing significant ideas to scientists and mathematicians, its time to recognize that whatever tricks are used in biology (humans, octopuses, ...) may still be of interest and of value, but they no longer seem like the unique magical missing ingredients which were so long sought after. From this point on its all about efficiencies: modeling efficiency: how do we best fit the elephant, with bezier curves, rational polynomials, ...? memory bandwidth training efficiency: when building coincidence statistics, say bigrams, is it really necessary to update the weights for all concepts? a co-occurence of 2 concepts should just increase the predicted probability for the just observed bigram and then decrease a global coefficient used to scale the predicted probabilities. I.e. observing a baobab tree + an elephant in the same image/sentence/... should not change the relative probabilities of observing french fries + milkshake versus bicycle + windmill. This indicates different architectures should be possible with much lower training costs, by only updating weights of the concepts observed in the last bigram. and so on with all other kinds of efficiencies.

jpkw 11mo ago

Right, I'm just going to teach my dog to do my job then and get free money as my brain is no more magic, special or different to theirs!

littlestymaar 11mo ago

> LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? “Internal combustion engines and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others?” The question isn't about what an hypothetical mechanism can do or not, it's about whether the concrete mechanism we built does or not. And this one doesn't.

ben_w 11mo ago
The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is "abstract thought"? Is that even the same between any two humans who use that word to describe their own inner processes? Because "imagination"/"visualise" certainly isn't.
- rob74 11mo ago
  > no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...
  - quantummagic 11mo ago
    But humans do the same thing. How many eons did we make the mistake of attributing everything to God's will, without a scientific thought in our heads? It's really easy to be wrong, when the consequences don't lead to your death, or are actually beneficial. The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.
    - 11mo ago

RayVR 11mo ago

I'm not arguing that human brains are magic. the current AI models will probably teach us more about what we didn't know about intelligence than anything else.

thesz 11mo ago

> Human brains aren't magic, special or different. DNA inside neurons uses superconductive quantum computations [1]. [1] https://www.nature.com/articles/s41598-024-62539-5 https://www.nature.com/articles/s41598-024-62539-5 As the result, all living cells with DNA emit coherent (as in lasers) light [2]. There is a theory that this light also facilitates intercellular communication. [2] https://www.sciencealert.com/we-emit-a-visible-light-that-vanishes-when-we-die-says-surprising-new-study https://www.sciencealert.com/we-emit-a-visible-light-that-va... Chemical structures in dendrites, not even neurons, are capable to compute XOR [3] which require multilevel artificial neural network with at least 9 parameters. Some neurons in brain have hundredths of thousands of dendrites, we are now talking of millions of parameters only in single neuron's dendrites functionality. [3] https://www.science.org/doi/10.1126/science.aax6239 https://www.science.org/doi/10.1126/science.aax6239 So, while human brains aren't magic, special or different, they are just extremely complex. Imagine building a computer with 85 billions of superconducting quantum computers, optically and electrically connected, each capable of performing computations of a non-negligibly complex artificial neural network.

danielbln 11mo ago
They are extremely complex, but is that complexity required for building a thinking machine? We don't understand bird physiology enough to build a bird from scratch, but an airplane flies just the same.
- sublinear 11mo ago
  Are we not just getting lost in semantics when we say "fly"? An airplane does not at all perform the same behavior as a bird. Do we say that boats or submarines "swim"? Planes and boats disrupt the environments they move through and air and sea freight are massive contributors to pollution.
  - IAmBroom 11mo ago
    You seem to have really gone off the rails midway through that post...

arowthway 11mo ago

For some unexplainable reason your subjective experience happens to be localized in your brain. Sounds pretty special to me.

mapontosevenths 11mo ago
There is nothing special about that either. LLM's also have self awareness/introspection, or at least a some version of it. https://www.anthropic.com/research/introspection https://www.anthropic.com/research/introspection Its hard to tell sometimes because we specifically train them to believe they don't.
- arowthway 11mo ago
  Thanks for the link, I haven't seen this before and it's interesting. I don't think the version of self awareness they demonstrated is synonymous with subjective experience. But same thing can be said about any human other then me. Damn, just let me believe all brains are magical or I'll fall into solipsism.

nephihaha 11mo ago

There isn't anything else around quite like a human brain that we know of, so yes, I'd say they're special and different. Animals and computers come close in some ways but aren't quite there.

d-lisp 11mo ago

(Motors and human brains are both just mechanisms, the reason one is a priori capable of learning abstract thought and not the other ?) While I agree to some extent with the materialistic conception, the brain is not an isolated mechanism, but rather the element of a system which itself isn't isolated from the experience of being a body in a world interacting with different systems to form super systems. The brain must be a very efficient mechanism, because it doesn't need to ingest the whole textual production of the human world in order to know how to write masterpieces (music, litterature, films, software, theorems etc...). Instead the brain learns to be this very efficient mechanism with (as a starting process) feeling its own body sh*t on itself during a long part of its childhood. I can teach someone to become really good at producing fine and efficient software, but on the contrary I can only observe everyday that my LLM of choice keeps being stupid even when I explain it how it fails. ("You're perfectly right !"). It is true that there's nothing magical about the brain, but I am pretty sure it must be stronger tech than a probabilistic/statistical next word guesser (otherwise there would be much more consensus about the usability of LLMs I think).

cindyllm 11mo ago
[dead]

jibal 11mo ago

Thermometers and human brains are both mechanisms. Why would one be capable of measuring temperature and other capable of learning abstract thought? > If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different. Google "strawman".