4 ms·

What makes stimulating 300 that computationally heavy? (Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural

What makes stimulating 300 that computationally heavy? (Doesn't sound like many?, but I've read that one single neuron needed 100 or so nodes in a deep neural net to simulate. But 300*100 also doesn't sound like many (nodes)?) Edit: some explanations here: https://news.ycombinator.com/item?id=35113498 https://news.ycombinator.com/item?id=35113498 (in this discussion)

Groxx 4y ago
Yep, pretty much that thread. Massively simplified models exist, and yeah - we have artificial neutral networks FAR larger than that and they run just fine. But they're so over-simplified that it's fair to call them something else entirely, not a simulation. You can use them to create similar behavior, but they're just following the basic concept of a brain, not how they actually work. Inspired by a real thing, not actually mimicking a real thing. Kinda like how a door hinge is not your knee, even though they both bend. It's not a knee simulation, it's just something that bends. For some things (doors) that's perfectly fine, and there are billions of them in use. You can't transparently replace your knee with one though, it has biology-juice all over it and needs to handle very different behaviors at times.
- GoblinSlayer 4y ago
  How do you verify precision of the simulation?
  - Groxx 4y ago
    In most cases the vague answer is "how closely can it recreate the end result". Because that's a useful measure. For brains: we have no idea. Every brain is somewhat different, but we only have a couple complete physical layout maps so far. No "weights", no specific chemistry per cell, no knowledge of what may have changed before it could be frozen for imaging. With a lot of work and a lot of extra physical and chemical simulation (a full body in quite a lot of detail), based on that map and what we know of the rest of its body, openworm achieves wormy wriggling. That's honestly pretty good! And it implies that the connection structure is at least coarsely meaningful in an extremely simple mind, which is what many have suspected but have had no way to verify before. But we know next to nothing about how that individual worm's brain behaved compared to the simulation. The fly brain will be similar - we'll have a bigger and more complex brain to run, more complex behaviors to compare against other flies, etc. It'll provide more evidence in favor of or opposed to the importance of that structure, compared to other things that we don't have enough information on yet. Basically it's still extremely early days, so it's sorta like asking Stonehenge astronomers whether or not our supernova-brightness-based measurements of the size of the universe are accurate. They can see supernovas too, but their answer has to be "uh. maybe? give us a few thousand years to research it". We need more data and better tools than currently exist.
cyberax 4y ago
The problem is not the neural simulation, but that we need to simulate pretty much all of the worm. And we currently can't do that. The neurons in worm directly interact with muscle cells, for example, via peptide/monoamine signalling. Or with "remote" neurons. This is all possible because neural network of the worms is directly integrated with everything. And the connectivity is hard-coded in its genome. It's not true for more complex organisms, simply because you can't encode that kind of complexity in DNA. Instead it encodes the overall connectivity structure, so that emergent behavior provides necessary instincts.

Groxx 4y ago

Yep, pretty much that thread. Massively simplified models exist, and yeah - we have artificial neutral networks FAR larger than that and they run just fine. But they're so over-simplified that it's fair to call them something else entirely, not a simulation. You can use them to create similar behavior, but they're just following the basic concept of a brain, not how they actually work. Inspired by a real thing, not actually mimicking a real thing. Kinda like how a door hinge is not your knee, even though they both bend. It's not a knee simulation, it's just something that bends. For some things (doors) that's perfectly fine, and there are billions of them in use. You can't transparently replace your knee with one though, it has biology-juice all over it and needs to handle very different behaviors at times.

GoblinSlayer 4y ago
How do you verify precision of the simulation?
- Groxx 4y ago
  In most cases the vague answer is "how closely can it recreate the end result". Because that's a useful measure. For brains: we have no idea. Every brain is somewhat different, but we only have a couple complete physical layout maps so far. No "weights", no specific chemistry per cell, no knowledge of what may have changed before it could be frozen for imaging. With a lot of work and a lot of extra physical and chemical simulation (a full body in quite a lot of detail), based on that map and what we know of the rest of its body, openworm achieves wormy wriggling. That's honestly pretty good! And it implies that the connection structure is at least coarsely meaningful in an extremely simple mind, which is what many have suspected but have had no way to verify before. But we know next to nothing about how that individual worm's brain behaved compared to the simulation. The fly brain will be similar - we'll have a bigger and more complex brain to run, more complex behaviors to compare against other flies, etc. It'll provide more evidence in favor of or opposed to the importance of that structure, compared to other things that we don't have enough information on yet. Basically it's still extremely early days, so it's sorta like asking Stonehenge astronomers whether or not our supernova-brightness-based measurements of the size of the universe are accurate. They can see supernovas too, but their answer has to be "uh. maybe? give us a few thousand years to research it". We need more data and better tools than currently exist.

cyberax 4y ago

The problem is not the neural simulation, but that we need to simulate pretty much all of the worm. And we currently can't do that. The neurons in worm directly interact with muscle cells, for example, via peptide/monoamine signalling. Or with "remote" neurons. This is all possible because neural network of the worms is directly integrated with everything. And the connectivity is hard-coded in its genome. It's not true for more complex organisms, simply because you can't encode that kind of complexity in DNA. Instead it encodes the overall connectivity structure, so that emergent behavior provides necessary instincts.