61–70 of 128 posts
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You really believe we’d be better off doing no machine learning research at all?
Machine learning? We'd be better off with way less technology in general... if we manage to survive tech induced climate change and/or potential nuclear annihilation without billions dying that is...
Billions would die without those as well.
His name is Timothy Mosca and he works with fruit flies... Mosca means fly, the insect, in Spanish.
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To simulate something you need to first know how it works and know all the relevant interactions, this is something that we currently do not understand. Neurons are not equivalent of neural networks we use in computers, they are A LOT more complex with whole groups firing the same time and chemicals regulating neurons all the time and whole topology is plastic, it works in a way we can't model or simulate currently.…
I'm a biochemist, and I somewhat disagree with this take. Yes, it's true that modelling just a single cell's interactions with its environments is beyond our capacity. But here we're talking about simulating how a brain reacts to signals at a higher level of abstraction: we're studying an "emergent" phenomenon. We don't need to model molecular interactions, and we absolutely can model this using artificial neural net…
> we're studying an "emergent" phenomenon
It's like saying that mapping all cells in human organism to addresses in memory will give us emergent human inside computer.
But still at abstract layer we just do not have a model of a working brain, we only have maps of neurons, not an actual "algorithm" or a model of all relevant environment interactions needed for a working brain or a set of "abstract instructions" needed for it to work. I think you are over optimistic about current state of our knowledge if we can't even model organism with few thousand neurons accurately. Imagine trying to do that for tens of billions of neurons and trillions of synapses, especially that we know brain doesn't work like an ANN at all[1].
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The first thing you said is correct. To do a proper simulation you would need to gather functional properties of the various cell classes and their synaptic connection, which this study didn't do. (Maybe you can find that information from other lab, I'm not familiar with fly models?) However we definitely have the computational ability to do simulations a fly network. Look at some of the modeling done by the Blue Bra…
But, do we know that they actually model completely accurately?
It's not the complete picture though, normally that brain would be in an ever-changing soup of chemicals, which definitely impact behavior... somehow. Simulating that, and even knowing what might be relevant to simulate, will never be complete. Only incrementally better than previous attempts.
Earlier quoted context omitted.
You really believe we’d be better off doing no machine learning research at all?
Machine learning? We'd be better off with way less technology in general... if we manage to survive tech induced climate change and/or potential nuclear annihilation without billions dying that is...
Technology has its downsides as well but often it is possible to use more technology to solve problems caused by the use of technology, e.g. filters on smokestacks, fast breeder reactors to solve the problems with nuclear waste, etc. In other words there is a need for more technology, not less. It is also necessary to make technology accessible to more people than it currently is, not by handing out widgets to "the poor" but by enabling those with the will and the capacity to build up their own capacity to produce and use it. It is technology which will solve any problems caused by a changing climate, whether that be a rise or drop in temperature and the resulting effects on precipitation. It is technology which will keep the population from ever increasing to the breaking point simply because people feel the need to have many children since so many of them do not survive past their early years.
[1] ...although there have been plenty of proxy wars in Africa, Asia as well as South-America
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The first thing you said is correct. To do a proper simulation you would need to gather functional properties of the various cell classes and their synaptic connection, which this study didn't do. (Maybe you can find that information from other lab, I'm not familiar with fly models?) However we definitely have the computational ability to do simulations a fly network. Look at some of the modeling done by the Blue Bra…
But, do we know that they actually model completely accurately?
Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.
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Man... I just find neural connectomes so depressing. It's like looking at the copper wiring on the motherboard, or the pins of the CPU, when what you really want is the logic from the networked gates (transistors). Yet it seems we are many, many decades away from being able to extract that in any comprehensible or definitive way. I need to stop reading neuroscience articles. There's always big proclamations, Like "th…
> It's like looking at the copper wiring on the motherboard, or the pins of the CPU, when what you really want is the logic from the networked gates (transistors). and what you kind of really want is a debugging guide to an OS. hah hah it is to laugh.
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> It's like looking at the copper wiring on the motherboard, or the pins of the CPU, when what you really want is the logic from the networked gates (transistors). and what you kind of really want is a debugging guide to an OS. hah hah it is to laugh.
I'd settle for a repair or upgrade manual tbh
Earlier quoted context omitted.
To simulate something you need to first know how it works and know all the relevant interactions, this is something that we currently do not understand. Neurons are not equivalent of neural networks we use in computers, they are A LOT more complex with whole groups firing the same time and chemicals regulating neurons all the time and whole topology is plastic, it works in a way we can't model or simulate currently.…
I'm a biochemist, and I somewhat disagree with this take. Yes, it's true that modelling just a single cell's interactions with its environments is beyond our capacity. But here we're talking about simulating how a brain reacts to signals at a higher level of abstraction: we're studying an "emergent" phenomenon. We don't need to model molecular interactions, and we absolutely can model this using artificial neural net…