[ExI] 1DIQ: an IQ metaphor to explain superintelligence

Sun Nov 2 19:13:55 UTC 2025

I cannot say that I understand Chalmers.   But scanning a brain at one
point in time tells us little about what changes it will undergo in the
next second, much less next week.  And a scan of a human brain will show
what it is like in the current stimulus environment (likely just sitting
and doing little) , not any other environment. And our environment changes
from second to second and there is an endless supply of different ones we
experience.  How many slices will it take to cover even a tiny fraction of
them?  bill w

On Sun, Nov 2, 2025 at 11:32 AM Jason Resch via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

>
>
> On Sun, Nov 2, 2025, 11:52 AM William Flynn Wallace via extropy-chat <
> extropy-chat at lists.extropy.org> wrote:
>
>> Jason, keep in mind that 'same stimulus, same response' doesn't work.
>> There scores of reasons why not, ; including simple habituation and
>> sensitization (response waning or increasing).  How do you map that?
>>
>
> I think the failing of behaviorism is it's consideration only if high
> level inputs and outputs, while ignoring the internal implementation.
>
> If instead you build a model of the brain based on its connectome and
> accurately model each neuron in that connectome, you will automatically
> recreate all the phenomena such as habituation and sensitization.
>
> Very general tendencies, perhaps, can be mapped,but the closer you get to
>> predicting specific responses the error rate will increase.  And how do you
>> count responses that are the reverse of what you predict?
>>
>
> Failures of the model, or limits of prediction induced by thermal noise.
>
> “The presence of background noise in biological systems implies that no
> process can depend on requiring more than a certain amount of precision.
> Beyond a certain point (say, the 10^-10 level on an appropriate scale),
> uncontrollable fluctuations in background noise will wash out any further
> precision. This means that if we approximate the state of the system to
> this level of precision (perhaps a little further to be on the safe side–to
> the 10^-20 level, for example), then we will be doing as well as the system
> itself can reliably do. It is true that due to nonlinear effects, this
> approximation may lead to behavior different from the behavior produced by
> the system on a given occasion–but it will lead to behavior that the system
> might have produced, had biological noise been a little different.”
> -- David Chalmers in "The Conscious Mind" (1996)
>
>
>
>> So - we will never map the brain because its topography, if you will
>> allow the metaphor, is constantly changing.    bill w
>>
>
> But we can freeze a brain at a point in time and then scan it fully on our
> own time frame, as we have done already with worms and flies.
>
> Jason
>
>
>> On Sat, Nov 1, 2025 at 9:52 AM Jason Resch via extropy-chat <
>> extropy-chat at lists.extropy.org> wrote:
>>
>>>
>>>
>>> On Sat, Nov 1, 2025, 9:56 AM William Flynn Wallace via extropy-chat <
>>> extropy-chat at lists.extropy.org> wrote:
>>>
>>>> Given that all of our actions originate in the unconscious mind. there
>>>> is no way a conscious mind can understand where its ideas and actions come
>>>> from, much less understand them.
>>>>
>>>
>>> Great point!
>>>
>>>
>>> The conscious mind may think it is in charge but it is just an observer
>>>> (which nevertheless can understand that a mistake has been made and the
>>>> idea or action needs redoing.)
>>>>
>>>> You want to understand our minds?  Make the workings of the unconscious
>>>> conscious - and that's just a start.  Why did the impulse go to point B
>>>> when it left point A rather than to point C? And then trace all the points
>>>> in between entering the unconscious and resulting in some idea or action.
>>>> And explain each one.
>>>>
>>>
>>> I have doubts that such a thing is possible from the perspective of the
>>> mind in question. Can any brain ever feel and know what each of its neurons
>>> is doing? Can those corresponding neurons feel and know what every one of
>>> its constituent atoms is doing?
>>>
>>> Given Turing universality, it's provable that computer software can't
>>> know about its underlying hardware. If our minds are a kind of software
>>> which can be simulated by a computer, then this same implication would
>>> apply to us. There would be a layer of abstraction of one's underlying
>>> implementation which high levels cannot penetrate.
>>>
>>>
>>>> You can't even get started until you can truly access the unconscious.
>>>> Give Freud credit- he tried to do this.
>>>>
>>>
>>> He deserves credit for the attempt, but I think there are limits to a
>>> mind's ability to introspect.
>>>
>>> "Our thoughts seem to run about in their own space, creating new
>>> thoughts and modifying old ones, and we never notice any neurons helping us
>>> out! But that is to be expected. We can’t. […]
>>> We should remember that physical law is what
>>> makes it all happen–way, way down in neural nooks and crannies which are
>>> too remote for us to reach with our high-level introspective probes."
>>>
>>> — Douglas Hofstadter in “Gödel, Escher, Bach” (1979)
>>>
>>>
>>> Jason
>>>
>>>
>>>>
>>>>
>>>> On Fri, Oct 31, 2025 at 6:35 PM Jason Resch via extropy-chat <
>>>> extropy-chat at lists.extropy.org> wrote:
>>>>
>>>>>
>>>>>
>>>>> On Fri, Oct 31, 2025, 6:17 PM Ben Zaiboc via extropy-chat <
>>>>> extropy-chat at lists.extropy.org> wrote:
>>>>>
>>>>>> On 31/10/2025 21:34, Jason Resch wrote:
>>>>>>
>>>>>> On Fri, Oct 31, 2025, 3:16 PM Ben Zaiboc via extropy-chat <
>>>>>> extropy-chat at lists.extropy.org> wrote:
>>>>>>
>>>>>>> On 31/10/2025 12:28, John K Clark wrote:
>>>>>>>
>>>>>>> We can have a general sort of understanding of how our brain works but to have a perfect understanding a part of our brain would have to have a sort of internal map of the entire brain, and for it to be perfect there would have to be a one to one correspondence between the map and the territory, but that would be impossible for something that is finite like the number of neurons in the human brain. However it would be possible for a proper subset of something infinite to have a one to one correspondence with the entire set; then you could have such a perfect map with a one to one correspondence ...
>>>>>>>
>>>>>>>
>>>>>>> You've completely lost me there, but I have two observations:
>>>>>>> There's no such thing as 'perfect understanding' except as a nebulous
>>>>>>> theoretical concept, and I don't think a one-to-one correspondence would be
>>>>>>> enough to understand something, or even be a relevant concept. We use large
>>>>>>> parts of our brains to process information from small parts of the world.
>>>>>>> You need a lot more than a single neuron to figure out what's going on in a
>>>>>>> single neuron.
>>>>>>>
>>>>>>> Oh, three observations. We don't process data instantaneously. The
>>>>>>> same parts of the brain can be used to process information about something
>>>>>>> repeatedly over time, using feedback loops etc.
>>>>>>>
>>>>>>
>>>>>> Computers and algorithms are constrained by two resources space (i.e.
>>>>>> memory), and time (i.e. CPU cycles). While some algorithms allow for
>>>>>> time/space trade offs to be made in certain circumstances, in general there
>>>>>> is some shortest description of the brain (in terms of bits) for which no
>>>>>> shorter representation is possible (regardless of how much additional
>>>>>> computation is thrown at it).
>>>>>>
>>>>>> So while the same brain may compute many times with the same neurons,
>>>>>> this addresses only the time component of simulating a brain. There is
>>>>>> still the matter of space.
>>>>>>
>>>>>>
>>>>>> Ah, ok. I was talking about understanding the brain, not simulating
>>>>>> it. Modelling something is not the same as understanding it. Yes, they help
>>>>>> each other, but they aren't the same thing.
>>>>>>
>>>>>
>>>>> I think understanding a thing is equivalent to being able to form an
>>>>> accurate mental model of it. With greater levels of understanding
>>>>> corresponding to more accurate models.
>>>>>
>>>>> What do you mean by the word understand?
>>>>>
>>>>>
>>>>>
>>>>>>
>>>>>> The analogy here is that a computer with 1 MB of RAM can't emulate a
>>>>>> computer with 1 GB of RAM, even if it's given 1000X the time to do so. In
>>>>>> fact there's no amount of additional time that will permit the memory
>>>>>> deficient computer to emulate the computer with 1 GB of memory, for the
>>>>>> simple reason that it will run out of variables to represent all the
>>>>>> possible values in the memory addresses of the computer with a greater
>>>>>> memory.
>>>>>>
>>>>>>
>>>>>> I'm not sure that this is true. Are you assuming no swap disk, or
>>>>>> other similar non-RAM storage?
>>>>>>
>>>>>
>>>>> Swap disks are a means to extend available RAM.
>>>>>
>>>>>
>>>>> Because then I'm sure you're right, but that's a pretty artificial
>>>>>> restriction.
>>>>>> The analogy there would be a human with a notepad maybe, or a
>>>>>> database, or a bunch of other humans, an AI, etc.
>>>>>>
>>>>>> So we're back to: A single human brain /on it's own/ can't understand
>>>>>> a human brain in any great detail. Of course.
>>>>>>
>>>>>
>>>>> I think that was the original question: can any mind ever fully
>>>>> understand its own operation.
>>>>>
>>>>> Jason
>>>>>
>>>>> But that's a pretty artificial restriction.
>>>>>>
>>>>>> --
>>>>>> Ben
>>>>>>
>>>>>>
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