>AIs are not conscious. They do not feel, experience, or suffer. They do not have innate preferences or underlying motivations.
Opening paragraph, stated without evidence. Im not entirely convinced this is true. It likely is, but at some point it very well might stop being true.
Does a vacuum have feelings? A cellphone? A paper plate? A billion transistors either pulled high or low? That last bit is the point, and no, there are no feelings there.
does a hydrocarbon have feelings? what about a mitochondria? a cell? a neuron? what about a collection of neurons? how many neurons before it has "feelings"?
> does a hydrocarbon have feelings? what about a mitochondria? a cell? a neuron? what about a collection of neurons? how many neurons before it has "feelings"?
The best theory I have heard is that subjective experience is a field of some sort (the EM field, maybe?). The brain and its neurons etc. are essentially an antenna. They both modify and stabilize the field, and read off changes in the field and translate these into actions (firing motor units, etc.).
The subconscious is computation done either only in neurons (no coherent field) or in various topological pockets not directly connected to the main topological structure in the field (which is "your experience").
Since transistors etc. do not work in this same way, they are essentially entirely subconscious, with no coherent, central phenomenal experience.
This neatly solves many problems associated with experience. The topological structure determines the boundary between one person's experience and another person's experience. The texture, valence, content, etc. of the experience is the structure of the field. The evolution of the field can efficiently solve difficult optimization problems, which is why humans evolved a complex organ that recruits the field of experience (it is computationally more efficient than doing everything in subconscious).
This doesn't really answer anything to me, only that there is a complex electrical simulation going on in our minds.
When a computer simulates a game, where does the simulation occur. I mean there is absolutely a representation of a game world in the computer somewhere. New elements can be added and removed from it. Signals saying there is or isn't "pain" can occur.
By trying to say brains use EM fields I'd say you're making your position far worse when you're talking about a potential lifeforms that only exists as EM fields
> This doesn't really answer anything to me, only that there is a complex electrical simulation going on in our minds.
Try to visualize the structure of the EM field inside a GPU vs. one inside of a human brain. In the GPU, it is highly distributed in space and time, many stacatto digital signals, etc. This is structurally very different than what happens inside a brain, which is substantially more analog. You can simulate analog stuff using floats, but the simulation is instantiated in digital logic, not in analog logic.
If you multiply numbers with a DAC, opamp, then ADC, vs. with a ALU, you get structurally very different electromagnetic fields. Even though you might get similar numerical outputs.
The argument would be that the exact spacial structure of the EM field in the brain is the thing that determines tha nature of experience. And the spacial structure of the EM field in the human brain is radically different than that on a GPU.
I will say it's not a bad theory in the sense we can attempt to falsify it. The one thing about an EM field in particular I have questions about, is why don't our brains turn off under even moderate electrical and magnetic fields. Note that they actually do under strong fields (Transcranial magnetic stimulation). The strength of these fields should be weak enough that even a bar magnet should mess with us. We need something else on top of what we know to explain the field coherency if this is the case.
This is where most mind theories do have issues, how does it stay stable. Quantum theory of the mind has a lot of the same problems, though we are finding some interesting structures that could have explanatory power.
Another thing I read recently that I found interesting is on platonic maths and complex algorithmic complexity in simple algorithms. The nice thing about math is once you choose your axioms it stays stable. But a lot of the work this group was doing is investigating is how biology executes algorithms and what second to n order effects are we missing. In many of these algorithms there are things like nearly free error correction or otherwise complex behavior that we'd consider emergent. The golden rule is a common example of this we see in nature. But the hypothesis they're working on is there are many more algorithms that life discovered over the past view billion years at higher orders via random walk and chance. We just have to pick apart these biological structures and discover the behaviors and figure out how to use them.
> The one thing about an EM field in particular I have questions about, is why don't our brains turn off under even moderate electrical and magnetic fields.
Yeah -- empirically EM theories of phenomenal experience are definitely not perfect.
> Another thing I read recently that I found interesting is on platonic maths and complex algorithmic complexity in simple algorithms.
> the hypothesis they're working on is there are many more algorithms that life discovered over the past view billion years at higher orders via random walk and chance. We just have to pick apart these biological structures and discover the behaviors and figure out how to use them.
This is very interesting. I think there is a lot of valuable research that will come out of trying to figure out what classical computations brains, neural nets, etc. are instantiating.
How you get from computations to phenomenal experience is still not something that I have a very clear understanding of.
hosel · · focus · HN ↗
Opening paragraph, stated without evidence. Im not entirely convinced this is true. It likely is, but at some point it very well might stop being true.
irishcoffee · · focus · HN ↗
fl4regun · · focus · HN ↗
collin_of_this · · focus · HN ↗
The best theory I have heard is that subjective experience is a field of some sort (the EM field, maybe?). The brain and its neurons etc. are essentially an antenna. They both modify and stabilize the field, and read off changes in the field and translate these into actions (firing motor units, etc.).
The subconscious is computation done either only in neurons (no coherent field) or in various topological pockets not directly connected to the main topological structure in the field (which is "your experience").
Since transistors etc. do not work in this same way, they are essentially entirely subconscious, with no coherent, central phenomenal experience.
This neatly solves many problems associated with experience. The topological structure determines the boundary between one person's experience and another person's experience. The texture, valence, content, etc. of the experience is the structure of the field. The evolution of the field can efficiently solve difficult optimization problems, which is why humans evolved a complex organ that recruits the field of experience (it is computationally more efficient than doing everything in subconscious).
pixl97 · · focus · HN ↗
When a computer simulates a game, where does the simulation occur. I mean there is absolutely a representation of a game world in the computer somewhere. New elements can be added and removed from it. Signals saying there is or isn't "pain" can occur.
By trying to say brains use EM fields I'd say you're making your position far worse when you're talking about a potential lifeforms that only exists as EM fields
collin_of_this · · focus · HN ↗
Try to visualize the structure of the EM field inside a GPU vs. one inside of a human brain. In the GPU, it is highly distributed in space and time, many stacatto digital signals, etc. This is structurally very different than what happens inside a brain, which is substantially more analog. You can simulate analog stuff using floats, but the simulation is instantiated in digital logic, not in analog logic.
If you multiply numbers with a DAC, opamp, then ADC, vs. with a ALU, you get structurally very different electromagnetic fields. Even though you might get similar numerical outputs.
The argument would be that the exact spacial structure of the EM field in the brain is the thing that determines tha nature of experience. And the spacial structure of the EM field in the human brain is radically different than that on a GPU.
pixl97 · · focus · HN ↗
This is where most mind theories do have issues, how does it stay stable. Quantum theory of the mind has a lot of the same problems, though we are finding some interesting structures that could have explanatory power.
Another thing I read recently that I found interesting is on platonic maths and complex algorithmic complexity in simple algorithms. The nice thing about math is once you choose your axioms it stays stable. But a lot of the work this group was doing is investigating is how biology executes algorithms and what second to n order effects are we missing. In many of these algorithms there are things like nearly free error correction or otherwise complex behavior that we'd consider emergent. The golden rule is a common example of this we see in nature. But the hypothesis they're working on is there are many more algorithms that life discovered over the past view billion years at higher orders via random walk and chance. We just have to pick apart these biological structures and discover the behaviors and figure out how to use them.
collin_of_this · · focus · HN ↗
Yeah -- empirically EM theories of phenomenal experience are definitely not perfect.
> Another thing I read recently that I found interesting is on platonic maths and complex algorithmic complexity in simple algorithms.
> the hypothesis they're working on is there are many more algorithms that life discovered over the past view billion years at higher orders via random walk and chance. We just have to pick apart these biological structures and discover the behaviors and figure out how to use them.
This is very interesting. I think there is a lot of valuable research that will come out of trying to figure out what classical computations brains, neural nets, etc. are instantiating.
How you get from computations to phenomenal experience is still not something that I have a very clear understanding of.