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Guessing that this means there are a lot of confounding variables other than gut biome (environment, diet, genetics, etc) that are very difficult to isolate to prove causation, as opposed to correlation.



Gut biome being one of the most promising area of research, whose earth-shattering potential is about on par with the sheer complexity of the problem.

If you thought ML was difficult, try modeling a human being's digestive tube from mouth to anus down to the cell: welcome to a category of problems where climate and gravity are the "simple" ones.

On the other side of that space though, potentially the promise to increase by orders of magnitude our mastery of human condition both biologically and experientially.


I'm willing to go out on a limb and suggest that the workings of the human brain are still far more complex than that of our digestive system. If the amount of effort that has been put into trying to emulate the former with software had been put instead into trying to emulate the latter, I reckon we'd pretty much have it cracked by now (as in, you could feed some tool info corresponding to all the inputs into our digestive system and it would be able to spit out exactly what outputs would be produced in the average human). But unlike AI/ML, not enough people, ahem, give a shit...


The brain and digestive system are very closely linked.

I think to make an "AI" on par with simulating the brain, you would need to simulate the gut first. And probably vice versa!


Not sure I agree, but accept it's not my area of expertise. We don't necessarily want to simulate the human brain the way it does actually function biologically, rather simulate the its most useful behaviors, which are hard to see as being intrinsically linked to the workings of the gut.


There's an imperfect truth to the comment you're replying to.

You're right that it's unnecessary to emulate the brain down to its finest implementation details, down to the molecule or even down to the cell.

However, I contend that it's essentially impossible to create a "relatable AI" (an AI that behaves and thinks like humans do) without proper consideration of embodiment. A large part of why the brain works the way it does, at a macro level, emerges from the vehicle it's in, and broadly speaking both its afferents/inputs and efferents/outputs.


We are a symbiote.


Bingo, we are just bunch of bacteria walking around. Some organism become symbiotic over time like mitochondria, so it go incorporated into our cells to make energy. The whole concept that we as human-being is one organism needs to be revisited.


This is already understood, it's not like scientists aren't aware.

The simplified concept of humans being one organism will continue to be taught nonetheless, because it's extremely useful, and not even wrong in most contexts in which it's applied.

There's nothing special about this, you can say the same thing about any simple model in biology: that the brain is an organ inside the head is a simplification, any diagram of a homeostatic system or metabolic pathway that fits on a single page is a simplification, the "central dogma" of DNA -> RNA -> protein is a simplification...

All of these things are well-known. They continue to be used as models, because, well... they're useful models. And there's nothing wrong with that!


Even more generally, reductionism works but with known limitations which warrant a more holistic approach, and we can't work our way out of most real-world problems without this multi-layered approach. Welcome to empiricism in complex systems.




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