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I agree that this seems farfetched. At the same time, I don't think we need to understand how the brain works in order to mimic or copy it, right? At a somewhat

I agree that this seems farfetched. At the same time, I don't think we need to understand how the brain works in order to mimic or copy it, right? At a somewhat absurd level, we give birth to humans with brains without understanding brains. The goal here seems to be to start by copying it without understanding in order to gain understanding. AFAIK we already simulate brains of silk worms or some such thing?

deleted 5y ago
[deleted]
falcor84 5y ago
Yeah, agreed. I think it's a bit like working with a legacy system, where you might begin by testing and measuring its interactions with external interfaces, and then can start to gradually replace pieces with new components.
spywaregorilla 5y ago
> AFAIK we already simulate brains of silk worms or some such thing? I'm pretty sure OpenWorm has not achieved its goal. My take on this would be, sure, copying it is an important step, but they don't know to copy it, so it won't work.
tsimionescu 5y ago
> AFAIK we already simulate brains of silk worms or some such thing? There is research into mapping the complete neural structure of a nematode worm called C. elegans [0] - one of the simplest known organisms that has some kind of a nervous system (the entire worm has 959 cells for hermaphrodite individuals, or 1035 for males; of these, 302 are neurons - and yes, this is not a typo, these are not hundreds or thousands of cells, just cells - that's how tiny it is). Its entire nervous system has been mapped out, including all connections, in [0]. Note that its neural cells are not like mammal neurons, they lack many of the known processes present in even a single mammal neuron. However, the project to simulate this simplest of organisms, OpenWorm [1], has not yet achieved its goals (which is also somewhat reduced - they only intend to simulate the motor system initially, not the entire organism). Silkworms (which are moths) are waaaay beyond any imaginable simulation capability at the moment. [0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ [1] https://github.com/openworm/OpenWorm/milestones https://github.com/openworm/OpenWorm/milestones
- staticassertion 5y ago
  Right, I was just bringing that up as an example of simulating without understanding. The paper is talking about taking another approach. Whether it will work or not is not something I could comment on. Another example is how we have a very imperfect model for the universe, and yet we use our models to make strikingly accurate predictions. Huge gaps in our knowledge exist, but that doesn't stop us from using approximations to do interesting things.
  - tsimionescu 5y ago
    > Right, I was just bringing that up as an example of simulating without understanding. But that's just it - first they spent some time understanding how the system works,painstakingly mapping out each connection, the role of each individual cell (literally), they studied the chemistry inside each neural cell etc. The simulation effort started after all of this was done. If anything, I would say OpenWorm is a counter-example to the idea that you can simulate such a system without understanding it. Similarly, with our model of the universe, while gaps exist, the extent of those gaps and approximations is mostly known, and the areas affected by those gaps are exactly where we can't make predictions (e.g. the internal structure of a black hole). Not to mention, we had a massive piece of good luck there: it turns out that particles are described by linear equations, which have extremely nice properties for approximations. Already with GR we are in much worse territory with it's nonlinear equations, but at least we understand these well enough to create some linear approximations - or so we think.
boxed 5y ago
Simulating without understanding isn't actually a thing. You neeed to know what to simulate and what to ignore. For example: do we need to simulate all the DNA transcription to make a virtual neuron? Currently this is unknown. And if it is required it's pretty much game over already. I don't believe you need that level of fidelity but that's more of a hope than a scientific standpoint.
- kwhitefoot 5y ago
  > You neeed to know what to simulate and what to ignore. And often the fastest and most economical way to find out is to try doing it. Also simulations need not be perfect to be useful. I spent a large fraction of my life writing object oriented simulations of transformers. We simplified everything (reduced detail, reduced number of dimensions, rules of thumb where there was no analytical formula) but still succeeded in designing better transformers than before. The next generation will be more precise and even more useful but you can't always get there in one jump.

deleted 5y ago

[deleted]

falcor84 5y ago

Yeah, agreed. I think it's a bit like working with a legacy system, where you might begin by testing and measuring its interactions with external interfaces, and then can start to gradually replace pieces with new components.

spywaregorilla 5y ago

> AFAIK we already simulate brains of silk worms or some such thing? I'm pretty sure OpenWorm has not achieved its goal. My take on this would be, sure, copying it is an important step, but they don't know to copy it, so it won't work.

tsimionescu 5y ago

> AFAIK we already simulate brains of silk worms or some such thing? There is research into mapping the complete neural structure of a nematode worm called C. elegans [0] - one of the simplest known organisms that has some kind of a nervous system (the entire worm has 959 cells for hermaphrodite individuals, or 1035 for males; of these, 302 are neurons - and yes, this is not a typo, these are not hundreds or thousands of cells, just cells - that's how tiny it is). Its entire nervous system has been mapped out, including all connections, in [0]. Note that its neural cells are not like mammal neurons, they lack many of the known processes present in even a single mammal neuron. However, the project to simulate this simplest of organisms, OpenWorm [1], has not yet achieved its goals (which is also somewhat reduced - they only intend to simulate the motor system initially, not the entire organism). Silkworms (which are moths) are waaaay beyond any imaginable simulation capability at the moment. [0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889226/ [1] https://github.com/openworm/OpenWorm/milestones https://github.com/openworm/OpenWorm/milestones

staticassertion 5y ago
Right, I was just bringing that up as an example of simulating without understanding. The paper is talking about taking another approach. Whether it will work or not is not something I could comment on. Another example is how we have a very imperfect model for the universe, and yet we use our models to make strikingly accurate predictions. Huge gaps in our knowledge exist, but that doesn't stop us from using approximations to do interesting things.
- tsimionescu 5y ago
  > Right, I was just bringing that up as an example of simulating without understanding. But that's just it - first they spent some time understanding how the system works,painstakingly mapping out each connection, the role of each individual cell (literally), they studied the chemistry inside each neural cell etc. The simulation effort started after all of this was done. If anything, I would say OpenWorm is a counter-example to the idea that you can simulate such a system without understanding it. Similarly, with our model of the universe, while gaps exist, the extent of those gaps and approximations is mostly known, and the areas affected by those gaps are exactly where we can't make predictions (e.g. the internal structure of a black hole). Not to mention, we had a massive piece of good luck there: it turns out that particles are described by linear equations, which have extremely nice properties for approximations. Already with GR we are in much worse territory with it's nonlinear equations, but at least we understand these well enough to create some linear approximations - or so we think.

boxed 5y ago

Simulating without understanding isn't actually a thing. You neeed to know what to simulate and what to ignore. For example: do we need to simulate all the DNA transcription to make a virtual neuron? Currently this is unknown. And if it is required it's pretty much game over already. I don't believe you need that level of fidelity but that's more of a hope than a scientific standpoint.

kwhitefoot 5y ago
> You neeed to know what to simulate and what to ignore. And often the fastest and most economical way to find out is to try doing it. Also simulations need not be perfect to be useful. I spent a large fraction of my life writing object oriented simulations of transformers. We simplified everything (reduced detail, reduced number of dimensions, rules of thumb where there was no analytical formula) but still succeeded in designing better transformers than before. The next generation will be more precise and even more useful but you can't always get there in one jump.