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> I'm in the camp that the most likely outcome is that artificial neural networks can be conscious and have real experiences, but the toy networks we have today

> I'm in the camp that the most likely outcome is that artificial neural networks can be conscious and have real experiences, but the toy networks we have today don't have nearly the right topology to achieve such states. Agree with all you say, but just suspect that when we do come up with a network that can achieve such states, we will look at it and shake our heads and say, “So… is that all there is to it?”

tasty_freeze 3y ago
Agreed -- when I talk (and I don't think I'm alone) words seem to spontaneously tumble from my mouth without any effort. I'm learning what I'm saying at the same moment the person I'm talking with hears it. Only when I've painted myself into a verbal corner, or there is some complex concept that where I need to rehearse the phrasing before I get my idea across, does consciousness enter into it. That is all to say: 90%+ of what comes out of my mouth is about as sophisticated as ChatGPT.
- deleted 3y ago
  [deleted]
- Terr_ 3y ago
  I suspect talking yourself through a problem (e.g. rubber-duck debugging) works because (A) the forced encode+decode loop causes additional re-checking and re-interpretation, and (B) it recruits more brain-areas that would otherwise be bypassed by the faster/cheaper internal information path.
- momirlan 3y ago
  it seems that way, but all you say goes through a complex filter built during a lifetime: experience, memories, desires, fears. most of this is subconscious, but it's still part of your conscience. not to mention that talking at a pub after a few pints is different from talking in a meeting where you have to filter every word to obtain the effect you want.
  - doctor_eval 3y ago
    But that's the problem, we can explain all of this with LLMs. > all you say goes through a complex filter built during a lifetime: experience, memories, desires, fears. most of this is subconscious, but it's still part of your conscience aka "training" > not to mention that talking at a pub after a few pints is different from talking in a meeting where you have to filter every word to obtain the effect you want aka "temperature" I'm not trying to trivialise this, but I really don't see that this is in any way a strong argument against AI.
    - momirlan 3y ago
      I think you make a good point, I was just referring to the comment "when I talk (and I don't think I'm alone) words seem to spontaneously tumble from my mouth without any effort."
Terr_ 3y ago
> “So… is that all there is to it?” "Well, almost... we just need to improve its throughput by a factor of a bajillion and--for a fair-comparison--it should only draw something like 10-20 watts of power."
- mathewsanders 3y ago
  Biological neural nets have a benefit of being able to run massively parallel, I know basically nothing about silicon hardware, but I’m assuming that attempts to model hugely parallel systems like a brain on a serial architecture is going to be magnitudes more inefficient. I do remember years ago reading an a response to a question someone asked about why can’t we just build chips that run in parallel and there’s the constraint of printing on a 2D surface that limits how far you can take that idea.

tasty_freeze 3y ago

Agreed -- when I talk (and I don't think I'm alone) words seem to spontaneously tumble from my mouth without any effort. I'm learning what I'm saying at the same moment the person I'm talking with hears it. Only when I've painted myself into a verbal corner, or there is some complex concept that where I need to rehearse the phrasing before I get my idea across, does consciousness enter into it. That is all to say: 90%+ of what comes out of my mouth is about as sophisticated as ChatGPT.

deleted 3y ago
[deleted]
Terr_ 3y ago
I suspect talking yourself through a problem (e.g. rubber-duck debugging) works because (A) the forced encode+decode loop causes additional re-checking and re-interpretation, and (B) it recruits more brain-areas that would otherwise be bypassed by the faster/cheaper internal information path.
momirlan 3y ago
it seems that way, but all you say goes through a complex filter built during a lifetime: experience, memories, desires, fears. most of this is subconscious, but it's still part of your conscience. not to mention that talking at a pub after a few pints is different from talking in a meeting where you have to filter every word to obtain the effect you want.
- doctor_eval 3y ago
  But that's the problem, we can explain all of this with LLMs. > all you say goes through a complex filter built during a lifetime: experience, memories, desires, fears. most of this is subconscious, but it's still part of your conscience aka "training" > not to mention that talking at a pub after a few pints is different from talking in a meeting where you have to filter every word to obtain the effect you want aka "temperature" I'm not trying to trivialise this, but I really don't see that this is in any way a strong argument against AI.
  - momirlan 3y ago
    I think you make a good point, I was just referring to the comment "when I talk (and I don't think I'm alone) words seem to spontaneously tumble from my mouth without any effort."

Terr_ 3y ago

> “So… is that all there is to it?” "Well, almost... we just need to improve its throughput by a factor of a bajillion and--for a fair-comparison--it should only draw something like 10-20 watts of power."

mathewsanders 3y ago
Biological neural nets have a benefit of being able to run massively parallel, I know basically nothing about silicon hardware, but I’m assuming that attempts to model hugely parallel systems like a brain on a serial architecture is going to be magnitudes more inefficient. I do remember years ago reading an a response to a question someone asked about why can’t we just build chips that run in parallel and there’s the constraint of printing on a 2D surface that limits how far you can take that idea.