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> If, during training, some collection of weights exist along the gradient that approximate cognition What do you mean? Is cognition a set of weights on a grad

> If, during training, some collection of weights exist along the gradient that approximate cognition What do you mean? Is cognition a set of weights on a gradient? Cognition involves conscious reasoning and understanding. How do you know it is computable at all? There are many things which cannot be computed by a program (e.g. whether an arbitrary program will halt or not)...

Idiot_in_Vain 4y ago
You seem to think human consious reasoning and understanding are magic. The human brain is nothing more than a bio computer and it can't compute either, whether an arbitrary program will halt or not. That doesn't stop it from being able to solve a wide range of problems.
- theodorejb 4y ago
  > The human brain is nothing more than a bio computer That's a pretty simplistic view. How do you know we can't determine whether an arbitrary program will halt or not (assuming access to all inputs and enough time to examine it)? What in principle would prevent us from doing so? But computers in principle cannot, since the problem is often non-algorithmic. For example, consider the following program, which is passed the text of the file it is in as input: function doesHalt($program, $inputs): bool {...} $input = $argv[0]; // contents of this file if (doesHalt($input, [$input])) { while(true) { print "Wrong! It doesn't halt!"; } } else { print "Wrong! It halts!"; } It is impossible for the doesHalt function to return the correct result for the program. But as a human I can examine the function to understand what it will return for the input, and then correctly decide whether or not the program will halt.
  - laszlokorte 4y ago
    no you can't. only for some of the inputs. and for those you could also write an algorithmic doesHalt function that is analog to your reasoning.
    - theodorejb 4y ago
      For what input would a human in principle be unable to determine the result (assuming unlimited time)? It doesn't matter what the algorithmic doesHalt function returns - it will always be incorrect for this program. What makes you certain there is an algorithmic analog for all human reasoning?
      - ogogmad 4y ago
        You don't get it. If you fed this program the source code of your mind, body, and room you're in, then it would wrong-foot you too.
        theodorejb 4y ago
        Lol. Is there source code for our mind?
        ogogmad 4y ago
        There might be or there mightn't be -- your argument doesn't help us figure out either way. By its source code, I mean something that can simulate your mind's activity.
        glenstein 4y ago
        Exactly. It's moments like this where Daniel Dennett has it exactly right that people run up against the limits of their own failures of imagination. And they treat those failures like foundational axioms, and reason from them. Or, in his words, they mistake a failure of imagination for an insight into necessity. So when challenged to consider that, say, code problems may well be equivalent to brain problems, the response will be a mere expression of incredulity rather than an argument with any conceptual foundation.
        DontchaKnowit 4y ago
        And it is also true to say that you are running into the limits of your imagination by saying that a brain can be simulated by software : you are falling back to the closest model we have : discrete math/computers, and are failing to imagine a computational mechanism involved in the operation of a brain that is not possible with a traditional computer. The point is we currently have very little understanding of what gives rise to consciousness, so what is the point of all this pontificating and grand standing. Its silly. We've no idea what we are talking about at present. Clearly, our state of the art models of nueral-like computation do not really simulate consciousness at all, so why is the default assumption that they could if we get better at making them? The burden of evidence is on conputational models to prove they can produce a consciousness model, not the other way around.
  - bidirectional 4y ago
    Can you name a single form of analysis which a human can employ but would be impossible to program a computer to perform? Can you tell me if a program which searches for counterexamples to the Collatz conjecture halts? Turing's entire analysis started from the point of what humans could do.
  - ogogmad 4y ago
    This is a silly argument. If you fed this program the source code of your own brain and could never see the answer, then it would fool you just the same.
    - theodorejb 4y ago
      You are assuming that our minds are an algorithmic program which can be implemented with source code, but this just begs the question. I don't believe the human mind can be reduced to this. We can accomplish many non-algorithmic things such as understanding, creativity, loving others, appreciating beauty, experiencing joy or sadness, etc.
      - ogogmad 4y ago
        > You are assuming Your argument doesn't disprove my assumption *. In which case, what's the point of it? * - I don't necessarily believe this assumption. But I do dislike bad arguments.
  - TchoBeer 4y ago
    actually a computer can in fact tell that this function halts. And while the human brain might not be a bio-computer, I'm not sure, its computational prowess are doubtfully stronger than a quantum turing machine, which can't solve the halting problem either.
  - kaba0 4y ago
    Here you are: func main() { var n = 4; OUTER: loop { for (var i = 2; i < n/2; i++) { if (isPrime(i) && isPrime(n-i)) { n += 2; continue OUTER; // Goldbach’s conjecture } break; } }
valine 4y ago
Neural networks are universal approximators. If cognition can be represented as a mathematical function then it can be approximated by a neural network. If cognition magically exists outside of math and science, then sure, all bets are off.
- semi-extrinsic 4y ago
  There is no reason at all to believe that cognition can be represented as a mathematical function. We don't even know if the flow of water in a river can always be represented by a mathematical function - this is one of the Millennium Problems. And we've known the partial differential equations that govern that system since the 1850's. We are far, far away from even being able to write down anything resembling a mathematical description of cognition, let alone being able to say whether the solutions to that description are in the class of Lebesgue-integrable functions.
  - valine 4y ago
    The flow of the a river can be approximated with the Navier–Stokes equations. We might not be able to say with certainty it's an exact solution, but it's a useful approximation nonetheless. There was, past tense, no reason to believe cognition could be represented as a mathematical function. LLMs with RLHF are forcing us to question that assumption. I would agree that we are a long way from a rigorous mathematical definition of human thought, but in the meantime that doesn't reduce the utility of approximate solutions.
    - semi-extrinsic 4y ago
      I'm sorry but you're confusing "problem statement" with "solution". The Navier-Stokes equations are a set of partial differential equations - they are the problem statement. Given some initial and boundary conditions, we can find (approximate or exact) solutions, which are functions. But we don't know that these solutions are always Lebesgue integrable, and if they are not, neural nets will not be able to approximate them. This is just a simple example from well-understood physics that we know neural nets won't always be able to give approximate descriptions of reality.
LightMachine 4y ago
Neither a human can solve the halting problem. There is no evidence the brain does anything that a computer can't do.
- theodorejb 4y ago
  How do you know that? Do you have an example program and all its inputs where we cannot in principle determine if it halts? Many things are non-algorithmic, and thus cannot be done by a computer, yet we can do them (e.g. love someone, enjoy the beauty of a sunset, experience joy or sadness, etc).
  - NLPaep 4y ago
    Those are just specific particles floating around the brain
    - goatlover 4y ago
      What would those specific particles be, then? Sounds like a crude abstraction.
  - nuancebydefault 4y ago
    They said - there is no evidence. The reply hence is not supposed to be - how do you know that. The proposition begs for a counter example, in this case an evidence. Simply saying - love is non algorithmic - is not evidence, it is just another proposition that has not been proven, so it brings us no closer to an answer i am afraid.
    - theodorejb 4y ago
      My question was in response to the statement "Neither a human can solve the halting problem." There's an interesting article/podcast here about what computers can't do: https://mindmatters.ai/2020/08/six-limitations-of-artificial-intelligence-as-we-know-it/ https://mindmatters.ai/2020/08/six-limitations-of-artificial....
  - 4y ago
revetkn 4y ago
> Is cognition a set of weights on a gradient? Cognition involves conscious reasoning and understanding. What is your definition of _conscious reasoning and understanding_?

Idiot_in_Vain 4y ago

You seem to think human consious reasoning and understanding are magic. The human brain is nothing more than a bio computer and it can't compute either, whether an arbitrary program will halt or not. That doesn't stop it from being able to solve a wide range of problems.

theodorejb 4y ago
> The human brain is nothing more than a bio computer That's a pretty simplistic view. How do you know we can't determine whether an arbitrary program will halt or not (assuming access to all inputs and enough time to examine it)? What in principle would prevent us from doing so? But computers in principle cannot, since the problem is often non-algorithmic. For example, consider the following program, which is passed the text of the file it is in as input: function doesHalt($program, $inputs): bool {...} $input = $argv[0]; // contents of this file if (doesHalt($input, [$input])) { while(true) { print "Wrong! It doesn't halt!"; } } else { print "Wrong! It halts!"; } It is impossible for the doesHalt function to return the correct result for the program. But as a human I can examine the function to understand what it will return for the input, and then correctly decide whether or not the program will halt.
- laszlokorte 4y ago
  no you can't. only for some of the inputs. and for those you could also write an algorithmic doesHalt function that is analog to your reasoning.
  - theodorejb 4y ago
    For what input would a human in principle be unable to determine the result (assuming unlimited time)? It doesn't matter what the algorithmic doesHalt function returns - it will always be incorrect for this program. What makes you certain there is an algorithmic analog for all human reasoning?
    - ogogmad 4y ago
      You don't get it. If you fed this program the source code of your mind, body, and room you're in, then it would wrong-foot you too.
      - theodorejb 4y ago
        Lol. Is there source code for our mind?
        ogogmad 4y ago
        There might be or there mightn't be -- your argument doesn't help us figure out either way. By its source code, I mean something that can simulate your mind's activity.
        glenstein 4y ago
        Exactly. It's moments like this where Daniel Dennett has it exactly right that people run up against the limits of their own failures of imagination. And they treat those failures like foundational axioms, and reason from them. Or, in his words, they mistake a failure of imagination for an insight into necessity. So when challenged to consider that, say, code problems may well be equivalent to brain problems, the response will be a mere expression of incredulity rather than an argument with any conceptual foundation.
        DontchaKnowit 4y ago
        And it is also true to say that you are running into the limits of your imagination by saying that a brain can be simulated by software : you are falling back to the closest model we have : discrete math/computers, and are failing to imagine a computational mechanism involved in the operation of a brain that is not possible with a traditional computer. The point is we currently have very little understanding of what gives rise to consciousness, so what is the point of all this pontificating and grand standing. Its silly. We've no idea what we are talking about at present. Clearly, our state of the art models of nueral-like computation do not really simulate consciousness at all, so why is the default assumption that they could if we get better at making them? The burden of evidence is on conputational models to prove they can produce a consciousness model, not the other way around.
- bidirectional 4y ago
  Can you name a single form of analysis which a human can employ but would be impossible to program a computer to perform? Can you tell me if a program which searches for counterexamples to the Collatz conjecture halts? Turing's entire analysis started from the point of what humans could do.
- ogogmad 4y ago
  This is a silly argument. If you fed this program the source code of your own brain and could never see the answer, then it would fool you just the same.
  - theodorejb 4y ago
    You are assuming that our minds are an algorithmic program which can be implemented with source code, but this just begs the question. I don't believe the human mind can be reduced to this. We can accomplish many non-algorithmic things such as understanding, creativity, loving others, appreciating beauty, experiencing joy or sadness, etc.
    - ogogmad 4y ago
      > You are assuming Your argument doesn't disprove my assumption *. In which case, what's the point of it? * - I don't necessarily believe this assumption. But I do dislike bad arguments.
- TchoBeer 4y ago
  actually a computer can in fact tell that this function halts. And while the human brain might not be a bio-computer, I'm not sure, its computational prowess are doubtfully stronger than a quantum turing machine, which can't solve the halting problem either.
- kaba0 4y ago
  Here you are: func main() { var n = 4; OUTER: loop { for (var i = 2; i < n/2; i++) { if (isPrime(i) && isPrime(n-i)) { n += 2; continue OUTER; // Goldbach’s conjecture } break; } }

valine 4y ago

Neural networks are universal approximators. If cognition can be represented as a mathematical function then it can be approximated by a neural network. If cognition magically exists outside of math and science, then sure, all bets are off.

semi-extrinsic 4y ago
There is no reason at all to believe that cognition can be represented as a mathematical function. We don't even know if the flow of water in a river can always be represented by a mathematical function - this is one of the Millennium Problems. And we've known the partial differential equations that govern that system since the 1850's. We are far, far away from even being able to write down anything resembling a mathematical description of cognition, let alone being able to say whether the solutions to that description are in the class of Lebesgue-integrable functions.
- valine 4y ago
  The flow of the a river can be approximated with the Navier–Stokes equations. We might not be able to say with certainty it's an exact solution, but it's a useful approximation nonetheless. There was, past tense, no reason to believe cognition could be represented as a mathematical function. LLMs with RLHF are forcing us to question that assumption. I would agree that we are a long way from a rigorous mathematical definition of human thought, but in the meantime that doesn't reduce the utility of approximate solutions.
  - semi-extrinsic 4y ago
    I'm sorry but you're confusing "problem statement" with "solution". The Navier-Stokes equations are a set of partial differential equations - they are the problem statement. Given some initial and boundary conditions, we can find (approximate or exact) solutions, which are functions. But we don't know that these solutions are always Lebesgue integrable, and if they are not, neural nets will not be able to approximate them. This is just a simple example from well-understood physics that we know neural nets won't always be able to give approximate descriptions of reality.

LightMachine 4y ago

Neither a human can solve the halting problem. There is no evidence the brain does anything that a computer can't do.

theodorejb 4y ago
How do you know that? Do you have an example program and all its inputs where we cannot in principle determine if it halts? Many things are non-algorithmic, and thus cannot be done by a computer, yet we can do them (e.g. love someone, enjoy the beauty of a sunset, experience joy or sadness, etc).
- NLPaep 4y ago
  Those are just specific particles floating around the brain
  - goatlover 4y ago
    What would those specific particles be, then? Sounds like a crude abstraction.
- nuancebydefault 4y ago
  They said - there is no evidence. The reply hence is not supposed to be - how do you know that. The proposition begs for a counter example, in this case an evidence. Simply saying - love is non algorithmic - is not evidence, it is just another proposition that has not been proven, so it brings us no closer to an answer i am afraid.
  - theodorejb 4y ago
    My question was in response to the statement "Neither a human can solve the halting problem." There's an interesting article/podcast here about what computers can't do: https://mindmatters.ai/2020/08/six-limitations-of-artificial-intelligence-as-we-know-it/ https://mindmatters.ai/2020/08/six-limitations-of-artificial....
- 4y ago

revetkn 4y ago

> Is cognition a set of weights on a gradient? Cognition involves conscious reasoning and understanding. What is your definition of _conscious reasoning and understanding_?