[ExI] Fwd: Neuromorphic Chips

[Colin Hales]

On Sat, Aug 13, 2022, 12:55 PM Stuart LaForge via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

>
> Implementing neural networks as hardware on chips could do for
> training AI what ASICS did for bitcoin mining. Neuromorphic chips have
> a lot of potential IMO. Why simulate what you can instead reverse
> engineer?
>
> https://www.nature.com/articles/s43588-021-00184-y
>
> ----------------------------k
> Abstract
>
> Neuromorphic computing technologies will be important for the future
> of computing, but much of the work in neuromorphic computing has
> focused on hardware development. Here, we review recent results in
> neuromorphic computing algorithms and applications. We highlight
> characteristics of neuromorphic computing technologies that make them
> attractive for the future of computing and we discuss opportunities
> for future development of algorithms and applications on these systems.
> ----------------------------
>
> In his recent Frontiers in Neuroscience article about phenomenal
> consciousness being mediated by the complex EM fields of the brain,
> Colin Hales wrote:
>
> "The creation of chip materials able to express EM fields structurally
> identical to those produced by neurons can be used to construct
> artificial neurons that replicate neuron signal processing through
> allowing the actual, natural EM fields to naturally interact in the
> manner they do in the brain, thereby replicating the same kind of
> signaling and signal processing (computation). This kind of in silico
> empirical approach is simply missing from the science." (Hales &
> Ericson, 2022)
>
> So Colin, it appears that the neuromorphic chips and computer
> architecture described in the Nature Computational Science article is
> exactly what you were suggesting right? So if these novel neuromorphic
> AI work as expected, would you believe one of these new machines to
> posses phenomenal consciousness or 1PP?
>
> Stuart LaForge
>
>
>
> Neuromorphic computers are not reverse engineering the brain. They are a
> highly parallel, fast, low energy implementation of a model of properties
> of brain signalling. None of the brain's signalling physics is involved.


A chip that reverse-engineers the brain's function is one that literally
uses the physics the brain uses, in inorganic form. Nowhere else in
science, EVER, has 'reverse engineering of a natural phenomenon been the
creation of a computer-explored abstract model of the nature. I have called
such a reverse engineered chip a  'neuromimetic' chip. There's a detailed
discussion of it in TechRXiv. https://doi.org/10.36227/techrxiv.13298750.v4


The likelihood is that you won't be able to fully appreciate the
difference, but it is real and untried.

I am building a 50,000+ scale version of one patch of membrane with one big
ugly 'ion channel' in the middle of it. It produces a near-field that
innately expresses the voltages modelled by the neuromohic chip. No model.
No software. Just physics. If you place these fields inside each other they
compute cognition. Literally. That is replication (reverse engineering) of
brain signalling. It will be the first ever attempt to do so.

Maybe then it'll be clear and the implications can finally be properly
examined.

I am calibrating the sensor positioner at the moment. Attached is a picture
I hope will get through the byte limit of posting here:

This endless argument will end before the end of the year.
65 years of theoretical science being mistaken for empirical work has to
stop.

Cheers,

Colin
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