5 ms·

I don't quite understand what you mean... is it that the logical complexity of the fly brain is lower than the hardware complexity so it should be possible to r

by janekm 8y ago

I don't quite understand what you mean... is it that the logical complexity of the fly brain is lower than the hardware complexity so it should be possible to replicate the "algorithm" to fly without simulating the hardware of the fly brain?

deleted 8y ago
[deleted]
nyrulez 8y ago
Neuron is the hardware. We have no idea how the software on it works. The way we model neural networks might be a very different from the operating system of the brain. It's like saying we mapped the x86 chip so we should be able to to simulate all it can do without reverse engineering the software.
- kyberias 8y ago
  Just copy-pasting the same message here multiple times doesn't make it any more true.
  - deleted 8y ago
    [deleted]
- sigi45 8y ago
  And software. This is the difference between a von Neumann architecture driven CPU and us. Why would it be not directly connected on the "OS"?
  - nyrulez 8y ago
    Directly or indirectly connected isn't my point. I was referring to the large amount of electrical activity in the brain and we don't really understand what it actually encodes. Unless we reverse engineer it (which is insanely hard), it's hard to know what's "running" on the hardware. Or if we can perfectly replicate the brain using our model of deep learning. I'm a skeptic but that would prove it too.
wetpaws 8y ago
When you emulate NES games, you don't emulate all of the atoms in the NES processor, you just go with instruction set and write down some simple aproximation. You would do the same in biology. c elegans connectome has about 300 neurons. If you would simulate the neurons on a hardware level it would be enormously complex task, you would have to deal with ion channels and quirky stochastic effects, perhaps even some quantum physics simulation. The brain of c elegans is insanely complex. The brain structure, on the other hand, is ridiculously simple. You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation.
- philipkglass 8y ago
  You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation. Isn't this currently an unsettled question? We don't know if simple approximations of easily observable brain features (like connections) works as well for imitating brains as emulating NES instructions works for imitating the NES. Among other obstacles, we haven't had complete connection maps of large, interesting brains to experiment with. It seems like this fruit fly work may be a stepping stone toward more sophisticated "emulation" experiments.
  - deleted 8y ago
    [deleted]
- short_sells_poo 8y ago
  > You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation. I'm under the impression that this is very far from a settled thing. In effect, we don't know whether the stochastic and quantum effects are important or not. Perhaps that is the secret sauce, and it is not possible to approximate it using "crude" mathematical models we use today. Do you have any links to research that supports your idea?
- dekhn 8y ago

by janekm 8y ago

deleted 8y ago

[deleted]

nyrulez 8y ago

Neuron is the hardware. We have no idea how the software on it works. The way we model neural networks might be a very different from the operating system of the brain. It's like saying we mapped the x86 chip so we should be able to to simulate all it can do without reverse engineering the software.

kyberias 8y ago
Just copy-pasting the same message here multiple times doesn't make it any more true.
- deleted 8y ago
  [deleted]
sigi45 8y ago
And software. This is the difference between a von Neumann architecture driven CPU and us. Why would it be not directly connected on the "OS"?
- nyrulez 8y ago
  Directly or indirectly connected isn't my point. I was referring to the large amount of electrical activity in the brain and we don't really understand what it actually encodes. Unless we reverse engineer it (which is insanely hard), it's hard to know what's "running" on the hardware. Or if we can perfectly replicate the brain using our model of deep learning. I'm a skeptic but that would prove it too.

wetpaws 8y ago

When you emulate NES games, you don't emulate all of the atoms in the NES processor, you just go with instruction set and write down some simple aproximation. You would do the same in biology. c elegans connectome has about 300 neurons. If you would simulate the neurons on a hardware level it would be enormously complex task, you would have to deal with ion channels and quirky stochastic effects, perhaps even some quantum physics simulation. The brain of c elegans is insanely complex. The brain structure, on the other hand, is ridiculously simple. You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation.

philipkglass 8y ago
You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation. Isn't this currently an unsettled question? We don't know if simple approximations of easily observable brain features (like connections) works as well for imitating brains as emulating NES instructions works for imitating the NES. Among other obstacles, we haven't had complete connection maps of large, interesting brains to experiment with. It seems like this fruit fly work may be a stepping stone toward more sophisticated "emulation" experiments.
- deleted 8y ago
  [deleted]
short_sells_poo 8y ago
> You can just take connection and activation weights and write a simple neural network equivalent in an evening. And it would work about as good as a hardware simulation. I'm under the impression that this is very far from a settled thing. In effect, we don't know whether the stochastic and quantum effects are important or not. Perhaps that is the secret sauce, and it is not possible to approximate it using "crude" mathematical models we use today. Do you have any links to research that supports your idea?
dekhn 8y ago