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It is useful.

It is like getting a static map of the country's roads with no cars on it.

You can not make it come alive with cars (activity), but you can infer where people need to drive but you don't know when and why they drive or what they are doing, but it is a major clue.



> It is like getting a static map of the country's roads with no cars on it.

I was thinking it was more like giving somebody iPhone schematics and die shots of all the chips and then asking them to figure out how Portrait Mode works in the Camera app.


The difference is that in the brain there's no real separation between hardware and software, so I'm your analogy, we also have the equivalent of the source code, but just maybe not the environment configuration needed to get it to run (nor would we at this stage have sufficient compute to fully run it).


Any man made hardware is rather too organized to be good analogy here. But we have better alternatives than came along recently - LLMs or any kind of AI models as a matter of fact. Personally I would use analogy of "try running a prompt locally and then explain what really happened inside in terms of CPU operations" :)


Sort of, but mostly not. The critical distinction is that, given better data (the instruction set, the source code or binary of the OS and camera app), the schematics and die shots aren't necessary or even useful.

It's unlikely that brains have an abstraction layer like that, so work like this is a necessary precondition to understanding the rest of how it works. That actual understanding may be elusive for quite some time to come, but without a connectome, forget it, no change.


> given better data

And maybe there’s some data or concept that will one day be discovered that will be the key to unlocking how brains work.

For my analogy, I was thinking more of how the connectome is, like schematics, static and the dynamic part is probably more interesting.


Why exactly would it be unlikely?


It would be really inefficient and neurons inherently provide a great deal of flexibility. Larger animals might use this kind of thing, but insects don’t have that many neurons to work with.

Luckily this is science so we can actually find out.


Yup, it is similar to that as well. It is a part of the puzzle definitely, but not at all the whole picture.


Analogies are like banana peels. Rarely useful and they break down pretty quickly.


the metaphor I've heard is it's like getting a map of the country's roads, but none of the signs are labelled.




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