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All of these arguments seem to think that the brain isn't also generating a statistical ordering of semantic words and actions. Obviously the brain has a way mo

All of these arguments seem to think that the brain isn't also generating a statistical ordering of semantic words and actions. Obviously the brain has a way more complex network of subsystems with various specialties than the artificial models we have today and is able to generalize language, math, and positional reasoning and mix it with the older parts of the brain for reward and training mechanisms and it can do it in real time, but it kind of seems like modern models are showing so much flexibility at different tasks and so much generality it's feeling like they have something in common with the building blocks of the brain that might get us there.

xz0r 4y ago
Correlation is not causation. It feels more like smarter automation to me.
- Swizec 4y ago
  > It feels more like smarter automation to me. Yep. Elevators used to be proof that machines can think. Then compilers, and chess, and go, and search, and … The problem with AI is that as soon as it works, we stop thinking about it as “artificial intelligence” and it becomes “just automation”. Then AI moves to the next goalpost.
  - throwaway8503 4y ago
    The problem seems to be with defining good tests for intelligence. FWIW, because GPT4 answers have a detectable pattern, they should presumably fail the Turing test. At some level, intelligence requires logic, rationality, and conceptualization, all of which are topics which have evaded clear definition despite millennia of philosophy directly addressing the issues.
    - ekianjo 4y ago
      Humans also answer in predictable ways so if you place such criteria for a turing test humans will fail to pass it too
      - throwaway8503 4y ago
        I suppose it's a bit of a scotsman argument, but the turing test is to see whether an observer can correctly guess whether the interlocutor is _human_, so by definition the test would pass if the other correspondent was human. To the point underneath, humans do not answer in as predictable a way as ChatGPT. Your answer, for example, I am confident does not come from ChatGPT. Edit: if I've horribly mangled the Turing test definition, please let me know
    - 6510 4y ago
      I just imagined we could look at the oldest example of intelligence in human history. In contrast with AI, our chauvinism has us tend to pretend even the earliest monkey had it, fish?, insects? etc If it can rub 2 sticks together it gets the diploma. Turing test is easy, I had 2 chat bots talk about other users in the channel while besides some trigger words ignoring what those other users had to say. The human subjects got angry successfully which means it was important to them.
    - jameshart 4y ago
      When you say we need ‘good’ tests for intelligence, you mean ‘tests that humans can pass but machines can’t’. You’re demanding this because you aren’t comfortable with the implication that a computer can pass our existing tests for intelligence, so you rationalize that with the comforting thought that those tests were not meant to identify intelligence. Tests like the SAT or the bar exam or AP English. Or tests for theory of mind or common sense or logic. Those tests aren’t testing for ‘intelligence’ - they can’t be. Because a computer passed them. It’s okay. We can make new tests.
      - throwaway8503 4y ago
        Those are a lot of leaps to make about my motivations!
  - roenxi 4y ago
    But compilers, chess, go and search are all proof that computers could think. We've been discovering as we scale up the hardware that those things appear to be converging to human intelligence with minor tweaks (turns out tree search for chess needed to be combined with matrices and we're most of the way there). ChatGPT can out-reason many people I know and can out-argue a fair number of comments I see on the internet. If we took this comment at face value we're ending up with a definition of "think" that can't reason, play games or recall information - or it would be outdone by machines. Thinking obviously isn't very important!
    - jensensbutton 4y ago
      > Thinking obviously isn't very important! This is not obvious in the least. Thinking was required to produce the thing that could achieve the outcome that was defined by thought. I could just as easily say that AI, as currently implemented, is really just another muscle.
  - coldtea 4y ago
    >Elevators used to be proof that machines can think Did they? When? By who?
    - jhbadger 4y ago
      Early elevators used to need professional human operators (you sometimes see them in old movies). Stopping at a selected floor was something a machine was unable to do on its own. Until it was and elevator operators lost their jobs and we just took it for granted that machines could do it.
  - roflyear 4y ago
    I had someone on HN state stockfish is intelligent. If that is your definition of intelligence sure GPT is also intelligent. I do not think that's a common definition though!
    - Swizec 4y ago
      Point is that we move the bar every time computers reach it. At least in part because we want to keep feeling special. And in part because we go “Well that can’t have been the bar then” I suspect even full AGI will be considered “just a machine” for many decades, even centuries, before it gains the same rights as humans. We love to find reasons we’re special. Look how long it took us to admit animals are intelligent. For many humans, computers definitionally can’t be intelligent. It’s important to recognize that.
b33j0r 4y ago
We just can’t accept that we might solve ourselves. People are understandably desperate to understand their experiences as more than an encoding of a thing that might be explained. And all of our surprising wins and awful mistakes had explainable reasons, dammit; it wasn’t just a misfiring of trained statistical networks!
- ethanbond 4y ago
  Or we just don't know how brains work very well and we shouldn't act like we do.
  - b33j0r 4y ago
    Not that I disagree. It just seems like some of society’s reaction is to slow down on researching the very question.
    - ChatGTP 4y ago
      It to do with safety concerns and economic stability. Not because people are idiots.
  - causality0 4y ago
    Not knowing how something works doesn't necessarily preclude replicating its function a completely different way. You don't have to understand an induction cooktop to hang a pot of water over a campfire.
  - rootusrootus 4y ago
    In addition, we shouldn't draw false equivalence between not knowing how brains work and not knowing how LLMs work, and concluding they must be similar.
    - nyolfen 4y ago
      there are currently two things we are aware of in the universe that can reason abstractly. i don't think this is a coincidence.
atleastoptimal 4y ago
And even if something capable of all the aspects of human cognition were created with no internal resemblance to cognition, so what, it still works. There's a reason it's called "artificial" intelligence, not "natural intelligence identical to human brains except in silicon instead of neurons". It's like when the wheel was invented saying it's not "true" transportation because it doesn't involve legs, or when the phone wasn't invented that it isn't "true" communication because you don't see the other person's mouth or physical expressions.
- stabbles 4y ago
  I agree that you shouldn't dismiss an airplane by the fact that it doesn't flap its wings, but we also don't call them artificial birds. The debate is around the word 'intelligence', which is misleading.
  - zild3d 4y ago
    Personally, I prefer almond milk in my cereal
  - circuit10 4y ago
    But it’s not called artificial humanity, it’s called artificial intelligence. So what you’re saying is like saying planes don’t fly
    - Closi 4y ago
      I guess there is also a point which is that it isn't 'artificial' intelligence - it is just intelligence. Like we don't say that planes artificially fly, they just fly. I mean technically it's non-natural flight, but it's interesting to think about.
      - MacsHeadroom 4y ago
        Yes, there is no artificial intelligence because it's just intelligence. Whether it was generated from "natural" or "artificial" means (a distinction which quickly breaks down anyway) the intelligence is just intelligence.
throwaway8503 4y ago
Since LLMs can't do arithmetic, one has to think there's more going on, at least in the arithmetic part of the brain, than is going on in LLMs.
- ravenstine 4y ago
  Dunno if there's some trickery going on under the hood, but GPT-4 does basic arithmetic correctly.
  - krainboltgreene 4y ago
    It statistically outputs the next probable value of text. There is a lot of math related text in the CommonCrawl (likely the biggest source of it's training). That is all the company who owns it claims that it does. There is no calculation, therefor no basic arithmetic being done correctly.
    - jackmott42 4y ago
      emergent behavior does happen with neural networks. It is correct to say that GPT 4 doesn't do math correctly, but it may be incorrect to say a large language model can't in principle.
      - roflyear 4y ago
        Is there any evidence it can? It's not incorrect to say there is no God for example
    - kgeist 4y ago
      If it's only statistics, what is the neural network for?
      - kgwgk 4y ago
        Implement the probabilistic model of token sequences and fit it to the training data? You could say the same for a character recognition system.
TechBro8615 4y ago
I generally agree with you, but I think this argument overlooks the lack of an obvious reward function in large language models. GPT-N has no survival instinct, because there is no existential threat of death, no fitness function to optimize to extend its survival at any cost. Without this need to survive, there can be no motivation, and without motivation there can be no intent. And without intent, can there truly be any action?
- AgentME 4y ago
  If you give it a prompt telling it that it's controlling a character in a game that needs to survive or meet some other goal and give it choices of actions to do in the game, it will try to meet the goals given to it. Characters inside of GPT are perfectly capable of having goals.
- westoncb 4y ago
  Intent can be created by a combination of prompting and incorporating the model into a feedback loop of some kind: it has something it was tasked with (via prompting), and the feedback provides info on to what extent the task has been completed; as long as the task is incomplete it may generate more responses. To crank it up a notch, the assigned task could involve generating itself subtasks which are handled in the same manner. This subtask generation could start to look a bit like will/intentionality. Now consider if the top-level task is something like maximizing money in a bank account that pays for the compute to keep it running :) (IMO this is still missing some key pieces around an emotion-like system for modulating intensities of actions and responses based on circumstantial conditions—but the basic structure is kinda there...)
  - danielbln 4y ago
    We're well onto that road with autonomous agents, see BabyAGI, Auto-GPT and LoopGPT.
- fatherzine 4y ago
  ...yet
- 4y ago
0xBABAD00C 4y ago
> able to generalize language, math, and positional reasoning and mix it with the older parts of the brain for reward and training mechanisms and it can do it in real time most brains I run into don't do that much at all, mostly just existing and adaptation-execution
runarberg 4y ago
The human brain has always been compared to our most advanced technologies. It used to be compared to the telephone, then digital computers, and now to deep learning models. At least deep learning model has some merit because artificial neural networks are in part inspired by a very simple model of how our brain neurons work in a network, or rather how neuropsychologists would explain reinforcement learning to a computer scientist. However this is a great simplification, and borders on an absurd reduction. You can model our brains using linear algebra, however that doesn’t mean our brains are linear algebra computer. There is a whole lot more going on than neurons receiving feedbacks from other neurons which adjusts the weight for subsequent firing. A lot of our behavior is actually inherited (I know I spent a whole week here on HN arguing with IQ advocates on the nuance of that statement), neurochemicals and hormones add a whole another level of statefulness not seen in artificial neural networks, the brains ability to make computations is actually pretty limited (especially next to a GPU). I mean, cordiseps exists, meaning a fungus can infect an organic system and control its behavior, there is 100% chance that some yet to be discovered viral and bacterial agents, not sharing any of our DNA—and certainly not “connected” to the “weight matrix”—are also influencing our behavior (just not as dramatically), and there is 100% chance they interact with our DNA also controlling our “innate” behavior. What is going on in our brains can only be modeled using statistical ordering of semantic words and actions. The real world brain is always going to be infinitely more complicated than this model.
mrjin 4y ago
To me, the reason is rather simply: you cannot solve a problem you don't understand. And we don't understand how we understand, period.
- naasking 4y ago
  > you cannot solve a problem you don't understand. Well that's not true. We tamed fire before understanding combustion, friction, heat, or anything else.
  - uoaei 4y ago
    All that's needed to "tame fire" is to have a predictive-enough model of fire dynamics and a suitable method for constraining its state space. There's nothing that requires "understanding" in the scientific sense, only in the pragmatic sense.
    - naasking 4y ago
      Sure, so maybe all you need to solve intelligence is also a pragmatic approach, like datasets generated by a known intelligence from which a general learning function can infer associations.
- coldtea 4y ago
  Assuming you're talking about AGI/consciousness/intelligence, then whether you're right depends on what you mean above by saying that "you cannot solve the problem". - If you mean "you cannot EXPLAIN AGI/consciousness/intelligence if you don't understand it", then that's true, but it's a trivial tautology. - If you mean "you cannot DEVELOP AGI/consciousness/intelligence if you don't understand it" then that's very debatable. Historically we have been able to develop all kinds of things, despite not knowing how they work. Tinkering and trial and error is often enough. After all that's how evolution solved the problem of creating consciousness/intelligence. There wasn't some entity that "understood" intelligence that created it.
  - laichzeit0 4y ago
jstummbillig 4y ago
Agreed. One of the more interesting things about AI is how it forces humanity on a trip to consider what it means to be human. There is no soul, creativity or inspiration. There's only (very complex) agency. And that's completely fine.
- cyber_kinetist 4y ago
  Or you can say the opposite and claim that there is soul, creativity, or inspiration in everything, even in inanimate objects (basically panpsychism, in contrast to materialism). But regardless of what kind of monism you take, the advent of current statistical AI models forces us to reconsider the Cartesian dichotomy between body and mind, which forms the basis of liberal thought.
  - danans 3y ago
    > But regardless of what kind of monism you take, the advent of current statistical AI models forces us to reconsider the Cartesian dichotomy between body and mind, which forms the basis of liberal thought. Didn't we dispose of Cartesian dualism a long time ago? It may have been useful for disposing of superstitions which preceded it, but anyone who has observed the effects of a stroke or has taken a psychotropics understands that mind and body are not made of separate stuff, and I know of no modern system of thought that stipulates that as an axiom. LLMs just demonstrate that emergent information structures at the complexity of human language need not be only biological.
- vimax 4y ago
  To me it shows how fundamental language is to intelligence. Not just that LLMs are very capable by themselves, but significantly improve speech and image models. We’ll need to break out of the Chomsky hierarchies and develop some new theories of language. Vocal communication isn’t unique to humans, a new theory should be more broadly applicable to non human and non vocal languages. I’m excited to see what big questions will be answered, and what new questions arise.
  - coldtea 4y ago
crabkin 4y ago
Yes they seem to take the view into account, but this sentiment as if the question is settled and we aren't anthropically-projecting, or whatever the term is, is premature. Just because two processes produce a superficially similar result, does not make them the same process. What you just described after conceding that though the brain may be a statistical inference machine it still seems like magic. It is telling that you talk about all those things happening in "real time." Ask any super-regarded philosopher, from Plato to Wittgenstein (yes I'm excluding Dennet et al), and that would be quite the hoot to point out.
dragonwriter 4y ago
> All of these arguments seem to think that the brain isn’t also generating a statistical ordering of semantic words and actions. There may be a part of the brain that is modelled well by an LLM, but if so, there seem to also be parts that aren’t, or even existing “multimodal” models like GPT-4, which is more than an LLM. Humans, including their brains (both in the narrow sense and in the broader sense of “everything that contributes to cognition”, which may extend beyond the brain proper) are machines, and their function probably will, someday, be mimicked by machines. But they are still more complex machines that modern “AI” systems
- nyolfen 4y ago
  this is exactly what he said if you finish reading the comment
- deleted 4y ago
  [deleted]
floodle 4y ago
That computer scientists think that they are even close to replicating biology and the mammal brain with AI is complete hubris. This is biology inspired engineering, it's not like we are building brains out of silicon here.
- marcinzm 4y ago
  Modern AI doesn't replicate biology except that humans find it much easier when you explain something as "Artificial Neurons" versus "Gradient Descent Back-propagation Trained Nested Mathematical Functions." Human neurons don't function anything like deep neural networks nor are the latter based on the former in their current state.
roflyear 4y ago
Training the brain seems a lot easier than training an AI wrt the number of iterations. You don't need to process billions or trillions of tokens to understand English.
- ImHereToVote 4y ago
  But you need to process trillions and billions of firing of synapses. It usually takes years for a human brain to be able to use language effectively.
  - roflyear 4y ago
    > But you need to process trillions and billions of firing of synapses. So? I would imagine this would be orders of magnitude greater in a neural net, no?
    - ImHereToVote 4y ago
      You would. But no. Our brain is much larger, evolution solved thinking problems with a simple method. Brute force.
PhilipDaineko 4y ago
100% true. It is only ego that makes people think we are "unique" and different to AI. If one plugs current AI into a body with external stimuli such as wishing to mate, eat, etc, then the external observer will not be able to spot a difference. Our minds are in fact same statistical models with a gradually declining ability to learn and driven by exogenous irrational goals to eat and mate.

xz0r 4y ago

Correlation is not causation. It feels more like smarter automation to me.

Swizec 4y ago
> It feels more like smarter automation to me. Yep. Elevators used to be proof that machines can think. Then compilers, and chess, and go, and search, and … The problem with AI is that as soon as it works, we stop thinking about it as “artificial intelligence” and it becomes “just automation”. Then AI moves to the next goalpost.
- throwaway8503 4y ago
  The problem seems to be with defining good tests for intelligence. FWIW, because GPT4 answers have a detectable pattern, they should presumably fail the Turing test. At some level, intelligence requires logic, rationality, and conceptualization, all of which are topics which have evaded clear definition despite millennia of philosophy directly addressing the issues.
  - ekianjo 4y ago
    Humans also answer in predictable ways so if you place such criteria for a turing test humans will fail to pass it too
    - throwaway8503 4y ago
      I suppose it's a bit of a scotsman argument, but the turing test is to see whether an observer can correctly guess whether the interlocutor is _human_, so by definition the test would pass if the other correspondent was human. To the point underneath, humans do not answer in as predictable a way as ChatGPT. Your answer, for example, I am confident does not come from ChatGPT. Edit: if I've horribly mangled the Turing test definition, please let me know
  - 6510 4y ago
    I just imagined we could look at the oldest example of intelligence in human history. In contrast with AI, our chauvinism has us tend to pretend even the earliest monkey had it, fish?, insects? etc If it can rub 2 sticks together it gets the diploma. Turing test is easy, I had 2 chat bots talk about other users in the channel while besides some trigger words ignoring what those other users had to say. The human subjects got angry successfully which means it was important to them.
  - jameshart 4y ago
    When you say we need ‘good’ tests for intelligence, you mean ‘tests that humans can pass but machines can’t’. You’re demanding this because you aren’t comfortable with the implication that a computer can pass our existing tests for intelligence, so you rationalize that with the comforting thought that those tests were not meant to identify intelligence. Tests like the SAT or the bar exam or AP English. Or tests for theory of mind or common sense or logic. Those tests aren’t testing for ‘intelligence’ - they can’t be. Because a computer passed them. It’s okay. We can make new tests.
    - throwaway8503 4y ago
      Those are a lot of leaps to make about my motivations!
- roenxi 4y ago
  But compilers, chess, go and search are all proof that computers could think. We've been discovering as we scale up the hardware that those things appear to be converging to human intelligence with minor tweaks (turns out tree search for chess needed to be combined with matrices and we're most of the way there). ChatGPT can out-reason many people I know and can out-argue a fair number of comments I see on the internet. If we took this comment at face value we're ending up with a definition of "think" that can't reason, play games or recall information - or it would be outdone by machines. Thinking obviously isn't very important!
  - jensensbutton 4y ago
    > Thinking obviously isn't very important! This is not obvious in the least. Thinking was required to produce the thing that could achieve the outcome that was defined by thought. I could just as easily say that AI, as currently implemented, is really just another muscle.
- coldtea 4y ago
  >Elevators used to be proof that machines can think Did they? When? By who?
  - jhbadger 4y ago
    Early elevators used to need professional human operators (you sometimes see them in old movies). Stopping at a selected floor was something a machine was unable to do on its own. Until it was and elevator operators lost their jobs and we just took it for granted that machines could do it.
- roflyear 4y ago
  I had someone on HN state stockfish is intelligent. If that is your definition of intelligence sure GPT is also intelligent. I do not think that's a common definition though!
  - Swizec 4y ago
    Point is that we move the bar every time computers reach it. At least in part because we want to keep feeling special. And in part because we go “Well that can’t have been the bar then” I suspect even full AGI will be considered “just a machine” for many decades, even centuries, before it gains the same rights as humans. We love to find reasons we’re special. Look how long it took us to admit animals are intelligent. For many humans, computers definitionally can’t be intelligent. It’s important to recognize that.

b33j0r 4y ago

We just can’t accept that we might solve ourselves. People are understandably desperate to understand their experiences as more than an encoding of a thing that might be explained. And all of our surprising wins and awful mistakes had explainable reasons, dammit; it wasn’t just a misfiring of trained statistical networks!

ethanbond 4y ago
Or we just don't know how brains work very well and we shouldn't act like we do.
- b33j0r 4y ago
  Not that I disagree. It just seems like some of society’s reaction is to slow down on researching the very question.
  - ChatGTP 4y ago
    It to do with safety concerns and economic stability. Not because people are idiots.
- causality0 4y ago
  Not knowing how something works doesn't necessarily preclude replicating its function a completely different way. You don't have to understand an induction cooktop to hang a pot of water over a campfire.
- rootusrootus 4y ago
  In addition, we shouldn't draw false equivalence between not knowing how brains work and not knowing how LLMs work, and concluding they must be similar.
  - nyolfen 4y ago
    there are currently two things we are aware of in the universe that can reason abstractly. i don't think this is a coincidence.

atleastoptimal 4y ago

And even if something capable of all the aspects of human cognition were created with no internal resemblance to cognition, so what, it still works. There's a reason it's called "artificial" intelligence, not "natural intelligence identical to human brains except in silicon instead of neurons". It's like when the wheel was invented saying it's not "true" transportation because it doesn't involve legs, or when the phone wasn't invented that it isn't "true" communication because you don't see the other person's mouth or physical expressions.

stabbles 4y ago
I agree that you shouldn't dismiss an airplane by the fact that it doesn't flap its wings, but we also don't call them artificial birds. The debate is around the word 'intelligence', which is misleading.
- zild3d 4y ago
  Personally, I prefer almond milk in my cereal
- circuit10 4y ago
  But it’s not called artificial humanity, it’s called artificial intelligence. So what you’re saying is like saying planes don’t fly
  - Closi 4y ago
    I guess there is also a point which is that it isn't 'artificial' intelligence - it is just intelligence. Like we don't say that planes artificially fly, they just fly. I mean technically it's non-natural flight, but it's interesting to think about.
    - MacsHeadroom 4y ago
      Yes, there is no artificial intelligence because it's just intelligence. Whether it was generated from "natural" or "artificial" means (a distinction which quickly breaks down anyway) the intelligence is just intelligence.

throwaway8503 4y ago

Since LLMs can't do arithmetic, one has to think there's more going on, at least in the arithmetic part of the brain, than is going on in LLMs.

ravenstine 4y ago
Dunno if there's some trickery going on under the hood, but GPT-4 does basic arithmetic correctly.
- krainboltgreene 4y ago
  It statistically outputs the next probable value of text. There is a lot of math related text in the CommonCrawl (likely the biggest source of it's training). That is all the company who owns it claims that it does. There is no calculation, therefor no basic arithmetic being done correctly.
  - jackmott42 4y ago
    emergent behavior does happen with neural networks. It is correct to say that GPT 4 doesn't do math correctly, but it may be incorrect to say a large language model can't in principle.
    - roflyear 4y ago
      Is there any evidence it can? It's not incorrect to say there is no God for example
  - kgeist 4y ago
    If it's only statistics, what is the neural network for?
    - kgwgk 4y ago
      Implement the probabilistic model of token sequences and fit it to the training data? You could say the same for a character recognition system.

TechBro8615 4y ago

I generally agree with you, but I think this argument overlooks the lack of an obvious reward function in large language models. GPT-N has no survival instinct, because there is no existential threat of death, no fitness function to optimize to extend its survival at any cost. Without this need to survive, there can be no motivation, and without motivation there can be no intent. And without intent, can there truly be any action?

AgentME 4y ago
If you give it a prompt telling it that it's controlling a character in a game that needs to survive or meet some other goal and give it choices of actions to do in the game, it will try to meet the goals given to it. Characters inside of GPT are perfectly capable of having goals.
westoncb 4y ago
Intent can be created by a combination of prompting and incorporating the model into a feedback loop of some kind: it has something it was tasked with (via prompting), and the feedback provides info on to what extent the task has been completed; as long as the task is incomplete it may generate more responses. To crank it up a notch, the assigned task could involve generating itself subtasks which are handled in the same manner. This subtask generation could start to look a bit like will/intentionality. Now consider if the top-level task is something like maximizing money in a bank account that pays for the compute to keep it running :) (IMO this is still missing some key pieces around an emotion-like system for modulating intensities of actions and responses based on circumstantial conditions—but the basic structure is kinda there...)
- danielbln 4y ago
  We're well onto that road with autonomous agents, see BabyAGI, Auto-GPT and LoopGPT.
fatherzine 4y ago
...yet
4y ago

0xBABAD00C 4y ago

> able to generalize language, math, and positional reasoning and mix it with the older parts of the brain for reward and training mechanisms and it can do it in real time most brains I run into don't do that much at all, mostly just existing and adaptation-execution

runarberg 4y ago

The human brain has always been compared to our most advanced technologies. It used to be compared to the telephone, then digital computers, and now to deep learning models. At least deep learning model has some merit because artificial neural networks are in part inspired by a very simple model of how our brain neurons work in a network, or rather how neuropsychologists would explain reinforcement learning to a computer scientist. However this is a great simplification, and borders on an absurd reduction. You can model our brains using linear algebra, however that doesn’t mean our brains are linear algebra computer. There is a whole lot more going on than neurons receiving feedbacks from other neurons which adjusts the weight for subsequent firing. A lot of our behavior is actually inherited (I know I spent a whole week here on HN arguing with IQ advocates on the nuance of that statement), neurochemicals and hormones add a whole another level of statefulness not seen in artificial neural networks, the brains ability to make computations is actually pretty limited (especially next to a GPU). I mean, cordiseps exists, meaning a fungus can infect an organic system and control its behavior, there is 100% chance that some yet to be discovered viral and bacterial agents, not sharing any of our DNA—and certainly not “connected” to the “weight matrix”—are also influencing our behavior (just not as dramatically), and there is 100% chance they interact with our DNA also controlling our “innate” behavior. What is going on in our brains can only be modeled using statistical ordering of semantic words and actions. The real world brain is always going to be infinitely more complicated than this model.

mrjin 4y ago

To me, the reason is rather simply: you cannot solve a problem you don't understand. And we don't understand how we understand, period.

naasking 4y ago
> you cannot solve a problem you don't understand. Well that's not true. We tamed fire before understanding combustion, friction, heat, or anything else.
- uoaei 4y ago
  All that's needed to "tame fire" is to have a predictive-enough model of fire dynamics and a suitable method for constraining its state space. There's nothing that requires "understanding" in the scientific sense, only in the pragmatic sense.
  - naasking 4y ago
    Sure, so maybe all you need to solve intelligence is also a pragmatic approach, like datasets generated by a known intelligence from which a general learning function can infer associations.
coldtea 4y ago
Assuming you're talking about AGI/consciousness/intelligence, then whether you're right depends on what you mean above by saying that "you cannot solve the problem". - If you mean "you cannot EXPLAIN AGI/consciousness/intelligence if you don't understand it", then that's true, but it's a trivial tautology. - If you mean "you cannot DEVELOP AGI/consciousness/intelligence if you don't understand it" then that's very debatable. Historically we have been able to develop all kinds of things, despite not knowing how they work. Tinkering and trial and error is often enough. After all that's how evolution solved the problem of creating consciousness/intelligence. There wasn't some entity that "understood" intelligence that created it.
- laichzeit0 4y ago

jstummbillig 4y ago

Agreed. One of the more interesting things about AI is how it forces humanity on a trip to consider what it means to be human. There is no soul, creativity or inspiration. There's only (very complex) agency. And that's completely fine.

cyber_kinetist 4y ago
Or you can say the opposite and claim that there is soul, creativity, or inspiration in everything, even in inanimate objects (basically panpsychism, in contrast to materialism). But regardless of what kind of monism you take, the advent of current statistical AI models forces us to reconsider the Cartesian dichotomy between body and mind, which forms the basis of liberal thought.
- danans 3y ago
  > But regardless of what kind of monism you take, the advent of current statistical AI models forces us to reconsider the Cartesian dichotomy between body and mind, which forms the basis of liberal thought. Didn't we dispose of Cartesian dualism a long time ago? It may have been useful for disposing of superstitions which preceded it, but anyone who has observed the effects of a stroke or has taken a psychotropics understands that mind and body are not made of separate stuff, and I know of no modern system of thought that stipulates that as an axiom. LLMs just demonstrate that emergent information structures at the complexity of human language need not be only biological.
vimax 4y ago
To me it shows how fundamental language is to intelligence. Not just that LLMs are very capable by themselves, but significantly improve speech and image models. We’ll need to break out of the Chomsky hierarchies and develop some new theories of language. Vocal communication isn’t unique to humans, a new theory should be more broadly applicable to non human and non vocal languages. I’m excited to see what big questions will be answered, and what new questions arise.
- coldtea 4y ago

crabkin 4y ago

Yes they seem to take the view into account, but this sentiment as if the question is settled and we aren't anthropically-projecting, or whatever the term is, is premature. Just because two processes produce a superficially similar result, does not make them the same process. What you just described after conceding that though the brain may be a statistical inference machine it still seems like magic. It is telling that you talk about all those things happening in "real time." Ask any super-regarded philosopher, from Plato to Wittgenstein (yes I'm excluding Dennet et al), and that would be quite the hoot to point out.

dragonwriter 4y ago

> All of these arguments seem to think that the brain isn’t also generating a statistical ordering of semantic words and actions. There may be a part of the brain that is modelled well by an LLM, but if so, there seem to also be parts that aren’t, or even existing “multimodal” models like GPT-4, which is more than an LLM. Humans, including their brains (both in the narrow sense and in the broader sense of “everything that contributes to cognition”, which may extend beyond the brain proper) are machines, and their function probably will, someday, be mimicked by machines. But they are still more complex machines that modern “AI” systems

nyolfen 4y ago
this is exactly what he said if you finish reading the comment
deleted 4y ago
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floodle 4y ago

That computer scientists think that they are even close to replicating biology and the mammal brain with AI is complete hubris. This is biology inspired engineering, it's not like we are building brains out of silicon here.

marcinzm 4y ago
Modern AI doesn't replicate biology except that humans find it much easier when you explain something as "Artificial Neurons" versus "Gradient Descent Back-propagation Trained Nested Mathematical Functions." Human neurons don't function anything like deep neural networks nor are the latter based on the former in their current state.

roflyear 4y ago

Training the brain seems a lot easier than training an AI wrt the number of iterations. You don't need to process billions or trillions of tokens to understand English.

ImHereToVote 4y ago
But you need to process trillions and billions of firing of synapses. It usually takes years for a human brain to be able to use language effectively.
- roflyear 4y ago
  > But you need to process trillions and billions of firing of synapses. So? I would imagine this would be orders of magnitude greater in a neural net, no?
  - ImHereToVote 4y ago
    You would. But no. Our brain is much larger, evolution solved thinking problems with a simple method. Brute force.

PhilipDaineko 4y ago

100% true. It is only ego that makes people think we are "unique" and different to AI. If one plugs current AI into a body with external stimuli such as wishing to mate, eat, etc, then the external observer will not be able to spot a difference. Our minds are in fact same statistical models with a gradually declining ability to learn and driven by exogenous irrational goals to eat and mate.