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> Symbolic systems are well-known to have capabilities missing from neural networks, particularly reasoning and knowledge representation. I believe that the po

> Symbolic systems are well-known to have capabilities missing from neural networks, particularly reasoning and knowledge representation. I believe that the point is still being missed that: if you have a complex enough ANN architecture, you can obtain reasoning and knowledge representation. > It's misinformed to characterise Symbolic AI as a "zombie". I disagree. I (currently) agree with Searle’s position that any AI, symbolic or otherwise, would be a p-zombie if it didn’t originate from a biological brain. > the AlphaGo family of systems, is a neuro-symbolic system that combines a symbolic adversarial search algorithm, Monte-Carlo Tree Search, with a neural network-learned evaluation function. Please keep in mind that evaluation functions are symbolically programmed, themselves. The difference between Symbolic AI and Statistical AI is that the programmer uses symbols to describe symbols with GOFAI but uses symbols to describe stimuli with Statistical AI. GOFAI symbols are just ANN engrams. That is my point, here. Anything symbolic could be represented in an ANN. Intelligence is due to Parallel Distributed Processing, using semiotic symbolism (neuro-glial programming) in the neural architecture.

YeGoblynQueenne 5y ago
Well, the original artificial neuron, the Pitts and McCullock neuron, was a propositional logic circuit, so clearly neural networks do not need to be "statistical", as in function approximators trained with gradient descent. I don't understand what you mean by "GOFAI systems are just ANN engrams", though. Which GOFAI systems, of what kind? All of them? "GOFAI" or, perhaps more clearly, symbolic AI, is a broad church. I don't understand "ANN engrams" anyway. >> I believe that the point is still being missed that: if you have a complex enough ANN architecture, you can obtain reasoning and representation. Who knows. This is only a conjecture, currently. I really didn't read your original comment as talking about philosophical zombies. Is that what you really meant, or is your new comment a play on words? Please excuse my confusion.
- 9wzYQbTYsAIc 5y ago
  > I really didn't read your original comment as talking about philosophical zombies. Is that what you really meant, or is your new comment a play on words? Please excuse my confusion. No worries - p-zombie is definitely what I meant by “zombie”. > I don't understand what you mean by "GOFAI systems are just ANN engrams" > I don't understand "ANN engrams" anyway. So, in psychology, there was and is a tradition of understanding where in the brain any given thing exists. For example, what specific neurons or groups of neurons are responsible for individual memories, thoughts, concepts, etc. They call that location the “engram”. https://en.wikipedia.org/wiki/Engram_%28neuropsychology%29 https://en.wikipedia.org/wiki/Engram_%28neuropsychology%29 What I’m trying to say is that with a complex enough neural architecture, one would be able to conduct the same engram investigations on an ANN. > so clearly neural networks do not need to be "statistical" Eh, I’m not an expert (just a bachelor), but I generally agree. Some (all?) artificial neurons may need to be statistical functions over a sample space. However, some (many?) artificial glia may not need to be statistical functions over a sample space. An artificial glia’s sample space might simply be the artificial neurons, themselves, rather than the direct stimuli, if an artificial glia were to be programmed using statistical functions. https://en.m.wikipedia.org/wiki/Glia https://en.m.wikipedia.org/wiki/Glia > Who knows. This is only a conjecture, currently. Indeed :/ it’s something that I’ve been thinking about for a while, but I’m a busy software development professional, not a professional academic. I’ve got to run some errands for the day, but I would be stoked to continue this conversation. Perhaps we can build up some sort of testable conjecture.
  - YeGoblynQueenne 5y ago
    If you would like to turn your ideas into a scientific investigation (for example, by coming up with a testable conjecture) the first thing to do is to clarify your terminology. Not necessarily to bring it in line with established terminology, although personally I don't like the proliferation of terms. But at least, you would need to pin down what you mean by neologisms such as "artificial glia" and the neoteric use of "engram" in the context of ANNs. Establishing clear terminology will help you tremendously to minimise the potential for misunderstanding of your ideas. I think you're proposing a collaboration? I'm afraid I must very firmly discourage it. I'm currently writing my thesis and cannot justify any work outside of it. HN is a guilty pleasure that I really shouldn't be indulging in. But, thank you for the proposal, I'm flattered.
    - 9wzYQbTYsAIc 5y ago
      > I think you're proposing a collaboration? I'm afraid I must very firmly discourage it. I'm currently writing my thesis and cannot justify any work outside of it. Completely understood. Perhaps when you are tenured I will finally have gotten around to studying doctoral psychology and you would be able to peruse my master’s thesis. I too am flattered that a doctoral student had the time to consider my thoughts. If I do formulate some operational definitions in the not-too-distant future, would you mind if I sent them to you in an email for critique, at your leisure?
      - YeGoblynQueenne 5y ago
        You're welcomed to do so- see my signature for email address.

YeGoblynQueenne 5y ago

Well, the original artificial neuron, the Pitts and McCullock neuron, was a propositional logic circuit, so clearly neural networks do not need to be "statistical", as in function approximators trained with gradient descent. I don't understand what you mean by "GOFAI systems are just ANN engrams", though. Which GOFAI systems, of what kind? All of them? "GOFAI" or, perhaps more clearly, symbolic AI, is a broad church. I don't understand "ANN engrams" anyway. >> I believe that the point is still being missed that: if you have a complex enough ANN architecture, you can obtain reasoning and representation. Who knows. This is only a conjecture, currently. I really didn't read your original comment as talking about philosophical zombies. Is that what you really meant, or is your new comment a play on words? Please excuse my confusion.

9wzYQbTYsAIc 5y ago
> I really didn't read your original comment as talking about philosophical zombies. Is that what you really meant, or is your new comment a play on words? Please excuse my confusion. No worries - p-zombie is definitely what I meant by “zombie”. > I don't understand what you mean by "GOFAI systems are just ANN engrams" > I don't understand "ANN engrams" anyway. So, in psychology, there was and is a tradition of understanding where in the brain any given thing exists. For example, what specific neurons or groups of neurons are responsible for individual memories, thoughts, concepts, etc. They call that location the “engram”. https://en.wikipedia.org/wiki/Engram_%28neuropsychology%29 https://en.wikipedia.org/wiki/Engram_%28neuropsychology%29 What I’m trying to say is that with a complex enough neural architecture, one would be able to conduct the same engram investigations on an ANN. > so clearly neural networks do not need to be "statistical" Eh, I’m not an expert (just a bachelor), but I generally agree. Some (all?) artificial neurons may need to be statistical functions over a sample space. However, some (many?) artificial glia may not need to be statistical functions over a sample space. An artificial glia’s sample space might simply be the artificial neurons, themselves, rather than the direct stimuli, if an artificial glia were to be programmed using statistical functions. https://en.m.wikipedia.org/wiki/Glia https://en.m.wikipedia.org/wiki/Glia > Who knows. This is only a conjecture, currently. Indeed :/ it’s something that I’ve been thinking about for a while, but I’m a busy software development professional, not a professional academic. I’ve got to run some errands for the day, but I would be stoked to continue this conversation. Perhaps we can build up some sort of testable conjecture.
- YeGoblynQueenne 5y ago
  If you would like to turn your ideas into a scientific investigation (for example, by coming up with a testable conjecture) the first thing to do is to clarify your terminology. Not necessarily to bring it in line with established terminology, although personally I don't like the proliferation of terms. But at least, you would need to pin down what you mean by neologisms such as "artificial glia" and the neoteric use of "engram" in the context of ANNs. Establishing clear terminology will help you tremendously to minimise the potential for misunderstanding of your ideas. I think you're proposing a collaboration? I'm afraid I must very firmly discourage it. I'm currently writing my thesis and cannot justify any work outside of it. HN is a guilty pleasure that I really shouldn't be indulging in. But, thank you for the proposal, I'm flattered.
  - 9wzYQbTYsAIc 5y ago
    > I think you're proposing a collaboration? I'm afraid I must very firmly discourage it. I'm currently writing my thesis and cannot justify any work outside of it. Completely understood. Perhaps when you are tenured I will finally have gotten around to studying doctoral psychology and you would be able to peruse my master’s thesis. I too am flattered that a doctoral student had the time to consider my thoughts. If I do formulate some operational definitions in the not-too-distant future, would you mind if I sent them to you in an email for critique, at your leisure?
    - YeGoblynQueenne 5y ago
      You're welcomed to do so- see my signature for email address.