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>* > / 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-Mee465ce1260b3c8b92857014> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tf319c0e4c79c9397-Mff5a457d3291043724f78a0f Delivery options: https://agi.topicbox.com/groups/agi/subscription
