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The Nature of Tulpae | Help Me Help You


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That is true, but consciousness isn't something that has a clear or equivocal definition, unlike sight or the activation of norepinephrine.

And sure, something like an active cortico-thalamic complex may be required for consciousness, but it is fallacious to assume it is the seat of consciousness solely because of this. Hell, a brain stem is required for consciousness.

What it shows is that the brain doesn't work as a whole for consciousness. You seemed to imply that the entire brain is responsible for consciousness, but that's simply not true.

Besides that, there does tend to be a simple definition of consciousness. Medically, it's obvious whether someone is conscious or not, and it's obvious to you as well.

 

Awareness would be a more accurate term. But awareness is a fundamental aspect of consciousness. People who suffer brain damage on only one side of their brain for example may start to see only half of what they are focusing on. A lot of times, if someone asks them to draw a picture of something, they will only draw half of it because their perception is skewed. When confronted about it, they will suddenly make an excuse of some sort. (I forgot the name of this, but I'm sure you can find it on YouTube or something similar.) This shows that how you perceive things - your awareness, can ultimately impact consciousness.

I'm still not following you. Is your point that they aren't able to perceive one side? Or that they aren't aware that this is the case? What does this have to do with consciousness?

 

Not true that computers can be sentient, or that they only use linear code?

Linear code. We already have plenty of learning software. It's probably true that classical computers can't be sentient, but that's not to say no kind of machine can be.

 

My post was an attempt to explain consciousness in order to show that a tulpa's conscious-like behavior is synonymous with 'real' conscious-like behavior of humans.

I'm reading "tulpas are just as conscious as humans" here, but I'm still convinced that it has little to do with the above post.

 


 

 

Not sure again what was meant by linear, so I'll just say that cerebral pathways are full of feedback loops, and there are seemingly useless connections in it, mostly just single axons, connecting supposedly unrelated regions.

I think 'linear' here means that signals generally follow a single path. In something as tangled up as the brain, it's easier to precede everything with "mostly".

 

logic?

Well, it might be true that the brain doesn't follow computational logic, but that certainly doesn't mean it doesn't have rules. It is definitely incorrect to say that the brain has no patterns to follow.

Fundamentally, you have 'rules', behaviours, that govern individual neurons. On average, each one stimulates one other; where this isn't the case you have the avalanche effect, leading to an epileptic fit.

Then you have how these link together, in regions of varying structure and such.

Without any kind of pattern, the brain simply could not function. It would be correct to say that the brain follows different patterns to classical computation, but the difference is more fundamental, that which probably enables consciousness.

 

the fundamental difference between the typical computer and one whose function is based on neural network processing

Yes, the structure of the two is more or less completely different, and any comparison is usually made for the purpose of explanation. However, since here we are actually discussing the technicalities of the two, I would be surprised if any of us were not familiar with that which you just described.

 

Back to computers: What happens if one gate in the CPU fails to output the correct value, if just a single transistor fails to switch? It depends on what code is being executed, but it will always have definite and apparent consequences, be it a system crash or an incorrect result of an arithmetic operation. Every unit must work flawlessly in order for the whole system to function as intended. In the brain, a neural network, any neural network, even many mathematical models, you can knock out several neurons or more depending on its size, and it can still perform its task, albeit not as well as when intact. The forebrain is even more resistant — you can destroy sizable populations of its neurons, and if no critical pathway is affected, it won't result in any apparent deterioration in function or performance. Evolutionarily newer brain areas, usually frontal, seem more impervious than older parts, located mostly in dorsal and caudal regions. One possible reason is that the frontal lobes contain fewer critical pathways and more diffuse networks, or that impairment in their function is not readily obvious. Still, the frontal lobes are more likely to be injured and more susceptible to injury, possibly due to their location.

Not necessarily true. It's unfair to compare a simple classical computation system to a complex neural network. Where nature prepares for bashes to the head, so do data centres prepare for hard drive failures. It's not hard to create a system in which a substantial number of components are redundant; in fact, that's what many important computational systems do. While we're not really concerned with memory here, RAID arrays typically allow for entire drives to be lost without any data loss.

Similarly, by assigning multiple CPUs to perform the same task and comparing the results, you could ascertain the correct one in event of failure.

Another incompatibility is the nature of the results. If you want to compare visual processing to GPU processing, let it not be said that what you end up seeing is completely accurate. What are hallucinations? What is the common "seeing things" - not the same, really. The same applies to hearing. That's more than comparable to a few discoloured pixels - by the way, you'd be unlucky to see an average one-bit flip in a few pixels, which I think is a satisfactory tolerance.

 

So it should be regarded as its centre? You shouldn't be so hasty in your conclusions and laconic in explaining them. It's not so plain and clear and there are other structures and functions necessary for consciousness, but you're essentially correct. Keep in mind, though, that the thalamus and cortex are tightly entwined, and the thalamus and signals from the looped circuits it projects to it only stimulate or induce consciousness; the process itself occurs in the cerebrum. Still, it can be considered its centre. It sort of neatly fits in my conceptual framework, so why not.

As per my above response to this, it's not about the CTC being the centre as such, only that some regions are required while others aren't. Couguhl had said something about the brain working as a whole, whereas this isn't really the case.

 

But what is consciousness?

It always annoys me when people do that. Use the Glasgow Coma scale and "It's being aware" to cover all pseudo-philosophical questions.

 

Distinct is a poorly chosen word here. Areas in the cortex as mapped to their respective functions are very vaguely delineated, and they overlap. And specific? Nah. There are many parts that process various signals and integrate several functions, all in one solid physical structure.

You're right, I suppose, but still we see boundaries between structures. Yes, structures have multiple functions, but it's still a step away from the "magic sandbox" approach. As above, "mostly distinct" might be more apt.

 

This area of research is little funded and so far there is no considerable interest in it. 

I'm not so sure. Neuroscience is substantially more funded that it used to be. They have some expensive machines in those labs, and part of the reason why the area has little progress is probably because it's a relatively new field. Things like physics, astronomy and medicine go back thousands of years, but the same cannot be said for neuroscience. Modern scientists of any field have considerably more resources than their older counterparts, and this will not change. What with Moore's law and everything (even if processing power increase hasn't been stepping up so quickly recently) it's not hard to envisage sophisticated software modelling coming into play more.

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