I mostly don’t know but it doesn’t seem all that unlikely it could work.
My main evidence is
It’s much easier to see the coarse electrical activity, compared to 5-second / 5-minute / 5-hour processes. The former, you just measure voltage or whatever. The latter you have to do some complicated bio stuff (transcriptomics or other *omics).
I’ve asked something like 8ish people associated with brain emulation stuff about slow processes, and they never have an answer (either they hadn’t thought about it, or they’re confused and think it won’t matter which I just think they’re wrong about, or they’re like “yeah totally but we’ve already got plenty of problems just understanding the fast electrical stuff”).
We have very little understanding of how the algorithms actually do their magic, so we’re relying on just copying all the details well enough that we get the whole thing to work.
I mean you can look at neurons in vitro and see how they adopt to different stimuli.
Idk I’d weakly guess that the neuron level learning rules are relatively simple, and that they construct more complex learning rules for e.g. cortical minicolumns and eventually cortical columns or sth, and that we might be able to infer from the connectome what kind of function cortical columns perhaps implement, and that this can give us a strong hint for what kind of cortical-column-level learning rules might select for the kind of algorithms implemented there abstractly, and that we can trace rules back to lower levels given the connectome. Tbc i don’t think it might look exactly like that, just saying sth roughly like that, where maybe it’s actually some common circut loops instead of cortical columns which are interesting or whatever.
My main evidence is
It’s much easier to see the coarse electrical activity, compared to 5-second / 5-minute / 5-hour processes. The former, you just measure voltage or whatever. The latter you have to do some complicated bio stuff (transcriptomics or other *omics).
I’ve asked something like 8ish people associated with brain emulation stuff about slow processes, and they never have an answer (either they hadn’t thought about it, or they’re confused and think it won’t matter which I just think they’re wrong about, or they’re like “yeah totally but we’ve already got plenty of problems just understanding the fast electrical stuff”).
We have very little understanding of how the algorithms actually do their magic, so we’re relying on just copying all the details well enough that we get the whole thing to work.
I mean you can look at neurons in vitro and see how they adopt to different stimuli.
Idk I’d weakly guess that the neuron level learning rules are relatively simple, and that they construct more complex learning rules for e.g. cortical minicolumns and eventually cortical columns or sth, and that we might be able to infer from the connectome what kind of function cortical columns perhaps implement, and that this can give us a strong hint for what kind of cortical-column-level learning rules might select for the kind of algorithms implemented there abstractly, and that we can trace rules back to lower levels given the connectome. Tbc i don’t think it might look exactly like that, just saying sth roughly like that, where maybe it’s actually some common circut loops instead of cortical columns which are interesting or whatever.