3 ms·

not an expert (more like a noob) by any means but: 1) from neuroscience point of view you have cortical columns with layers that are wired to send the input fo

not an expert (more like a noob) by any means but: 1) from neuroscience point of view you have cortical columns with layers that are wired to send the input forward but to also propagate feedback. the layers constantly predict what is going to happen (by having neurons fire) and usually it’s the delta between what is predicted and what is coming from the sensory system that drives the reinforcement or the weakening of the connections. this sort of sounds like backpropagation to me (but again i may be super ignorant and would appreciate if you can educate me on this if you know more) 2) technically the “input” in the brain is not continuous. I don’t want to go into semantics but at the end of the day you have molecules, ions etc. so the input/transmission is not continuous. the size of the neurotransmitters is so small that it looks like it’s continuous. my point is that, if you take the current model and you have more computing power you could find out that some things translate between the 2 models (we definitely need a way better model of the neuron, but that’s another story) 3) this is a fair point.

drdeca 6y ago
re 2: are you saying that the amount of signal isn't continuous, or that the time of the signal is not continuous? If the latter, I'm not sure why being made of particles would prevent the signal from being continuous in time. Err, not "a continuous function of time", just in the sense of "not a discrete-in-time thing", unlike things on a computer that are synced with a global clock cycle.
- rantwasp 6y ago
  the amount. also as a side-note, discrete-in-time does not imply a global clock cycle
  - drdeca 6y ago
    Thank you for the correction regarding discrete-in-time. I appreciate it. In the case of the amount of signal being discrete because it is made of particles, this is also true of the floats that computer neural nets are computing with anyway, isn't it? I think the top level comment (by NalNezumi) was talking about continuous-ness in time anyway, (and, I think the strength of firing of biological neurons is thought to be at least approximately binary anyway? not sure about that.) so I'm not sure I see the bearing of them being unable to be truly continuous in strength on the question?
    - rantwasp 6y ago
      hmm. went back and reread the comment and... i think you’re right. Saw discrete and did not fully parse everything.

drdeca 6y ago

re 2: are you saying that the amount of signal isn't continuous, or that the time of the signal is not continuous? If the latter, I'm not sure why being made of particles would prevent the signal from being continuous in time. Err, not "a continuous function of time", just in the sense of "not a discrete-in-time thing", unlike things on a computer that are synced with a global clock cycle.

rantwasp 6y ago
the amount. also as a side-note, discrete-in-time does not imply a global clock cycle
- drdeca 6y ago
  Thank you for the correction regarding discrete-in-time. I appreciate it. In the case of the amount of signal being discrete because it is made of particles, this is also true of the floats that computer neural nets are computing with anyway, isn't it? I think the top level comment (by NalNezumi) was talking about continuous-ness in time anyway, (and, I think the strength of firing of biological neurons is thought to be at least approximately binary anyway? not sure about that.) so I'm not sure I see the bearing of them being unable to be truly continuous in strength on the question?
  - rantwasp 6y ago
    hmm. went back and reread the comment and... i think you’re right. Saw discrete and did not fully parse everything.