On Thu., 24 Dec. 2020, 1:16 am James Bowery, <[email protected]> wrote:
> That stuff is ancient history, albeit perhaps more-neglected than it > should be. > I have had a deeper look into the tank idea. As fun as it looks, it doesn't 'solve' /visualise the right form of the equations. It works in the frequency domain, I need time domain/pulsed dynamics. Interesting sidebar in the science of analog computers. > Again, I refer you to Ingber as someone likely to have paid proper > attention to these matters. Email him. > I'm still trying to see where/how our ideas contact each other. When I get there I'll do that. Thanks. >> On Tue, Dec 22, 2020 at 7:15 PM Colin Hales <[email protected]> wrote: >> I love it. Perfect messy empirical work suited to man cave. >> >> Xmas chaos looms. Take care everyone. 🤞🤞🤞🤞2021 >> Colin >> >> On Tue., 22 Dec. 2020, 8:00 pm Steve Richfield, < >> [email protected]> wrote: >> >>> Quick comment while contemplate more... >>> >>> Are you familiar with electrolytic analog computers, commonly used to >>> design magnetic systems? basically, they are a fish acquarium full of >>> slightly salty water, in which conductive (e.g. aluminum foil) and >>> insulating objects are submerged. Field is established with a battery. >>> Field strength readout is by an insulated wire that is bare on its tip. >>> This would allow you to inexpensively play with some of your ideas in a way >>> that a supercomputer would have a hard time matching. >>> >>> Steve >>> >>> On 11:38PM, Mon, Dec 21, 2020 Colin Hales <[email protected] wrote: >>> >>>> >>>> >>>> On Tue, Dec 22, 2020 at 1:56 PM Steve Richfield < >>>> [email protected]> wrote: >>>> >>>>> Colin, >>>>> >>>>> On Mon, Dec 21, 2020 at 1:11 PM Colin Hales <[email protected]> >>>>> wrote: >>>>> >>>>>> Hi Steve, >>>>>> OK. Let's try: >>>>>> >>>>> >>>>> GREAT - some text to kick back and forth. Here goes... >>>>> >>>>>> >>>>>> 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*). >>>>>> >>>>>> >>>>> This was pioneered with the "Harmon Neuron", but then quickly moved >>>>> into programmable digital computers as neural networks. >>>>> >>>>> Neural network practitioners are cleanly divided into THREE camps, >>>>> each having their obvious limitations, one being MUCH larger than the >>>>> other: >>>>> 1. 99% Pure empiricists, who twiddle with characteristics and >>>>> properties to optimize some measure of performance. >>>>> 2. 1% Pure mathematicians, who solve for the best network to optimize >>>>> some measure of performance, and then propose characteristics and >>>>> properties that parallel their mathematics. I used to be in this camp, >>>>> until I discovered that neurons do an interesting sort of highly efficient >>>>> bidirectional computation that is VERY different than what conventional >>>>> digital computers are good at. I tried discussing this here, but >>>>> apparently >>>>> no one was able to carry on this particular conversation. I think I see a >>>>> way to make "general purpose" computers that can do this and MUCH more, >>>>> but >>>>> with no one else on this bandwagon, it will probably pass when I >>>>> eventually >>>>> pass. There is considerable intersection between your field-theory view >>>>> and >>>>> my bidirectional computing view, nearly two sides of the same coin. >>>>> 3. Groups doing biological research, who attempt to as accurately as >>>>> possible simulate neurons or parts of thereof. I was once part of such an >>>>> effort at the University of Washington Department of Neurological Surgery. >>>>> >>>>> There is a computational method known as quadruple ledger accounting >>>>> that is practiced by the World Bank and others to model the world economy, >>>>> where people instead of neurons interact with each other in nonlinear and >>>>> non-directional ways. It might be possible to "build out" quadruple ledger >>>>> accounting methods to encompass both bidirectional and field computing, >>>>> but >>>>> the end result would probably be unrecognizable to everyone. >>>>> >>>>> I might be the only one, but I completely agree with you that fields >>>>> are a BIG part of this. I even go a bit further, as I suspect that other >>>>> field effects like the Hall Effect are probably also involved, which the >>>>> Hall Effect can NOT be directly simulated, except at the same physical >>>>> scale. It is all really complicated, but simply ignoring it can NEVER EVER >>>>> lead to AGI as the others on this forum now hope. It appears to me that >>>>> simulation methods CAN simulate field effects, but ONLY after they have >>>>> been fully understood, and while I suspect your efforts won't directly >>>>> lead >>>>> to AGI, I DO suspect that your efforts might be absolutely necessary to >>>>> EVER make an AGI. >>>>> >>>>> I see the path forward a little differently, but we might be >>>>> converging on the same place: >>>>> 1. We should publish a definition of "neurological simulation" that >>>>> encompases both field and bidirectional effects, and "expose" efforts that >>>>> fall short of this. >>>>> 2. Once people see just HOW difficult it is to simulate real-world >>>>> neurons in any useful way, people will start tackling the bidirectional >>>>> problem. The bidirectional problem is a challenge, but doesn't look >>>>> insurmountable. Electric circuit simulators like SPICE easily handle the >>>>> bidirectional problem, at an *n log n* cost in time, which would be >>>>> crushing for a large system like a brain, but which might be tolerable for >>>>> simulating a flatworm's brain. I suspect you could simulate your theories >>>>> on fields in SPICE. >>>>> >>>> >>>> My project is prototyping the EM field signalling. Just the bare bones >>>> physics of one patch of neuron membrane. Fully implemented (later), it will >>>> do the dromic and antidromic propagation you mention as well as ephaptic >>>> coupling. But I'll be focussing on the bare bones of the basic EM field >>>> physics for now. It operates under science framework (ii). No models. No >>>> emulation. No simulation. No software. >>>> >>>> I am hoping this will push the issue over the line into mainstream >>>> thinking and correct the currently distorted use of the science framework - >>>> where (ii) is missing. >>>> >>>> >>>>> >>>>> (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*. >>>>>> >>>>> >>>>> It looks to me like some of (iii) absolutely MUST precede (ii), or at >>>>> least be intertwined with (ii), to provide enough guidance to ever make >>>>> and >>>>> debug anything that actually works. The last decade of AI "research" has >>>>> absolutely PROVEN (at least to me) that even highly intelligent people >>>>> can't blindly stumble onto the secret sauce for AGI. >>>>> >>>> >>>> I don't think we're quite there yet .... I am talking about getting the >>>> neuroscience established properly in *all three* traditional areas by >>>> restoring (ii) so that neuroscience/AI operates like a normal science >>>> with normal empirical work. It currently does not do that. To clarify this, >>>> let me cite a more completed definition of science from the paper. Page 2 >>>> again: >>>> >>>> "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).*Activities >>>> (i)-(iii) meet each other in a mutual, reciprocating distillation that >>>> converges on empirically proved ‘laws of nature’ that are then published in >>>> the literature* (Rosenblueth and Wiener, 1945;Hales, 2014)." >>>> >>>> >>>> It is likely that most of the people on the AGI forum have never >>>> encountered (ii). (i) and (ii) provide empirical evidence for >>>> comparison with (iii) predictions. (iii) provides theoretical model >>>> predictions tested under (i) and (ii). It reciprocates. This is how science >>>> works everywhere *except in neuroscience/AI.* We do not do (ii) in >>>> neuroscience/AI for no reason. It is an accident/cultural habit handed down >>>> from the 1950s and industrialised. Mistaking (iii) activities for (ii) is >>>> what the paper is all about. Everything described with abstract equivalent >>>> circuits (neuromorphic chips) and symbolic models (software) fits under >>>> (iii). The natural (i)/(ii) physics is gone under (iii). In (iii) >>>> theoretical science is emulation, simulation, models, software. In (ii) >>>> there is only (i) physics and no models/software/emulation/simulation. I >>>> describe how the (i)/(ii)/(iii) framework operates in great detail in >>>> Supplementary 2. >>>> >>>> The proposed neuromimetic Xchip is the first time such a proposition >>>> for (ii) has been proposed in the literature. It retains the (likely) >>>> critically necessary natural (EM) physics of (i) for the purposes of >>>> scientific characterisation of the brain under (ii) and so that >>>> neuroscience/AI is normalised. Then and only then can the science properly >>>> examine the anomalous, unique and unprecedented equivalence of (i) and >>>> (iii), an unproved assumption only made in neuroscience/AI that may >>>> actually be true. But we can't test it without (ii). Which we have never >>>> done. >>>> >>>> There is a professional obligation on all of us to recognise and accept >>>> a flaw in our science conduct when we find it. The article details such a >>>> situation. Can I suggest reading the conclusion? I can cite again: >>>> >>>> Page 17. The way we conduct the science without (ii) ... >>>> >>>> "... is methodologically equivalent to expecting to fly while never >>>> actually using any flight physics and assuming, without any principled >>>> reason explored by experimentation with flight physics, that flight can be >>>> achieved by disposing of flight physics through completely replacing it >>>> with the physics of a general-purpose computer, a state of >>>> ‘physics-independence’ not found in any other physics context. This sounds >>>> like a harsh depiction of the science. It is merely a realistic description >>>> of the situation. " >>>> >>>> OK. Over the word limit we go. Turns out it takes many words to fix the >>>> most complicated science mess in the history of science messes. >>>> >>>> cheers, >>>> colin >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/Tf319c0e4c79c9397-M7d102d940530a5f651685e90> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf319c0e4c79c9397-Md3a01e37c29440bfdb63c074 Delivery options: https://agi.topicbox.com/groups/agi/subscription
