It's even worse when you consider the fact that the empirical evidence for
psi is overwhelming and there is a quasi-religious opposition to
recognition of this fact in neuroscience let alone AGI theory.

On Mon, Dec 21, 2020 at 3:12 PM Colin Hales <[email protected]> wrote:

> Hi Steve,
> OK. Let's try:
>
> Page 2:
> "In scientific behavior, empirical observation and theoretical science
> face-off normally in the following three familiar science contexts:
>
> (i)                 Observation of a natural context (*empirical science*
> ).
>
> (ii)              Observation of artificial versions of the natural
> context. Call this engineered or replicated nature a
> ‘scientifically-artificial’ version of nature (*empirical science*).
>
> (iii)            Creation of abstract models predictive of properties of
> the natural context observable in (i) and (ii) (*theoretical science*)."
>
> This process is literally drawn in Figure 1 for 5 different science
> contexts, all of which do exactly this (i)/(ii)/(iii) process EXCEPT in
> (e), for the brain where:
>
> (A)  (ii) empirical science, in neuroscience and 'artificial
> intelligence', *is missing from the science.*
> (B) It just so happens that if you decide to do (ii), brain EM is the
> thing that has been lost and that you replicate for the purposes. If you do
> the science to explore that, then you are not using a general purpose
> computer. You are exploring actual EM physics. It is empirical science.
> (C) if you claim (iii) is all you need then you are distorting the science
> in one place: *a unique, anomalous and unprecedented lack for which
> empirical proof is required*. That proof arises through using (ii) and
> (iii) *together*.
>
> I have simply said what the paper says.
>
> cheers
> colin
>
>
>
>
>
> On Tue, Dec 22, 2020 at 6:01 AM Steve Richfield <[email protected]>
> wrote:
>
>> Hi Colin,
>>
>> Most of the people on this list, including you and me, are each doing
>> their own thing, while reviewing each other for mutual benefit. NOW, I
>> FINALLY understand other people's objections to some of my earlier
>> postings, namely, I was exposing them to my evolving view of the world, and
>> each exposure was 95% the same as the previous exposure, and I wasn't
>> announcing what was new with this version. Instead of continually writing
>> anew, perhaps I should have included change bars, or encapsulated the
>> changing theory into a one-screen abstract, or ???
>>
>> Most people here feel they see a fatal flaw in your work, but different
>> people see different apparent flaws, so it is difficult to carry on a group
>> conversation. Without addressing the apparent flaws, even though they might
>> not be real flaws, you are chasing your audience away.
>>
>> As for me, understanding and models are two sides of the same coin.
>> Ordinary explanations of everything center around models of their operation
>> or lack thereof. "Claiming to operate in the absence of a model seems to be
>> either
>> 1.  a simple declaration of abandoning science - which I think I know you
>> enough to KNOW you aren't intending, or
>> 2.  part of the first step in the Scientific Method - looking for
>> interesting things to study further - but you apparently disclaim this by
>> claiming to be able to magically jump to useful hardware/wetware/AI WITHOUT
>> creating a model upon which to build an explanation.
>> 3.  that something useful can come of systems without need for the
>> functional complexity of synapses, that commonly have non-linearities,
>> integrate, differentiate, etc.
>>
>> I'm not sure whether I just don't see a pot of gold at the end of your
>> rainbow, or I just don't see your particular rainbow.
>>
>> Perhaps you could write a screenful of words that advance your central
>> theses? I might even take a shot at what I understand, for you to edit to
>> correct my errors:
>>
>> *The physical arrangement of neurons in brains strongly suggests that
>> field considerations might predominate over detailed wiring considerations.
>> Indeed, some of the more inexplicable computational abilities of neurons,
>> like mutual inhibition, are difficult to explain based on connections, but
>> easier to explain based on fields.*
>>
>> *Colin (you) proposes that computational analogues to the operation of
>> these fields might turn out to be adequate to explain VERY complex behavior
>> - like the operation of our brains.*
>>
>> *Steve (me) believes fields are just another component of normal neural
>> operation, that MUST be factored in for neuroscience and AI to ever
>> advance. However, fields are linear, so ignoring the non-linear components
>> like synapses would be like leaving the transistors out of an IC and
>> expecting it to do something useful.*
>>
>>
>> OK. Can you correct the errors in the above to match your view of reality?
>>
>> Thanks again for all of your efforts.
>>
>> *Steve Richfield*
>>
>> On Fri, Dec 18, 2020 at 8:28 PM Colin Hales <[email protected]> wrote:
>>
>>> Hi,
>>> For a very long time I have been trying to articulate a fundamental
>>> issue in the conduct science of AI (AGI). The issue is the proper conduct
>>> of the science such that we can know, with empirical certainty, whether and
>>> under what circumstances, a general-purpose computed abstract model of
>>> nature (the brain) has functional equivalence with the nature (the brain).
>>>
>>> It's taken 10 years of brutal grind, but I think I have found the
>>> mature/accurate shape of the argument, the proper nature of the problem,
>>> and the way forward.
>>>
>>> I have completed the paper to preprint stage before I go to a journal
>>> for the final peer review meat-grinder.
>>>
>>> So for a bit of a quiet read while the world self-immolates over the
>>> next couple of weeks:
>>>
>>> Hales, C.G. (2020). The Model-less Neuromimetic Chip and its
>>> Normalization of Neuroscience and Artificial Intelligence.
>>> https://doi.org/10.36227/techrxiv.13298750.v2
>>>
>>> 1 main article.
>>> 2 supplementary supporting articles.
>>> 4 videos from a computational EM study.
>>>
>>> Many of you will find previous discussions here remain part of it. It's
>>> been quite a job to get to the bottom of the matter.
>>>
>>> I hope it makes sense of a difficult issue.
>>>
>>> Take care out there,
>>>
>>> cheers,
>>> Colin
>>>
>>
>>
>> --
>> Full employment can be had with the stoke of a pen. Simply institute a
>> six hour workday. That will easily create enough new jobs to bring back
>> full employment.
>>
>> *Artificial General Intelligence List <https://agi.topicbox.com/latest>*
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