Colin

I understand what you mean by the architecture to evolve a brain-like 
functionality. You do not need to explain that to me again. There's no way, at 
this stage, that the conclusion could scientifically be made that any, such 
hypotheses are true or false. Obviously, it has to be scientifically tested. We 
may step away for belaboring that point as well.

  Still, the theory has to exist. Part of my past frustration in the 1990's - 
specifically with regards systems engineering theory and practices for 
establishing the substrate for business/information engineering, was the total 
scientifically-sound absence of method for analyzing and designing functions 
and business processes. This pertains to systems engineering and computational 
development to purpose. If the outcome of the design-to-purpose could not be 
scientifically vetted, how could it be both valid and reliable, and unbiased? 
It could not.

My initial objective was to attempt to remedy that situation, by developing a 
scientifically-acceptable method of analysis and design, which would assist 
engineering efforts for establishing more-valid and reliable blueprints for 
information-based architectures. I achieved that singular objective. It took 12 
years before it could be tested on real-time projects, data collected, and 
subsequently presented to the IEEE for review. My point being, that theory is 
well and truly tested and vetted. It is ready for your Stage 2.

The rest of the development, for example the CAMF (Component Architecture 
Management Framework) emerged as a logical outcome from the R&D efforts for 
establishing the usefulness of the de-abstraction method (by one name). 
Obviously, for the method to work with all mainstream and niche frameworks and 
approaches, it had to be tested for integration and compatibility. It was.

For our purposes then, the seamless integration to mainstream, and niche, 
accepted information-engineering science and practice was achieved. That part 
of the research was concluded academically. The world caught up, and CISCO in 
particular went ahead to develop the network-management telecommunication 
infrastructure, which enables such integration. I think this was mainly as a 
logical consequence to the driving force of Convergence, than deliberate, 
scientific research objectives. Nonetheless, we now have intelligent networking 
as our ally, in the sense of retro-integration via my research results.

I'm not sharing this to try and blow my own horn. It is but a tiny drop in 
development relative the a massive body of knowledge with regards intelligent 
systems. It is but a single strand in the tapestry, but other compatible 
strands do exist. As such, we may collect those and continue with this purpose. 
As far as my knowledge goes, my results remain fully open to generic 
integration, and specifically as well, to any existing computational platform 
and design/engineering methodology, even ones applied to biological systems. We 
can emerge any, testable, context of knowledge required, even a blueprint of 
AGI.

In my opinion, that too pertains to Physics, and the establishment of 
hard-physical systems and/or components as required. In my humble opinion, I 
bridged the gap between information engineering and the sciences.

My research is available for this purpose. Granted, I'll have to spend time to 
formalize the last, few years of research to expand the method to include 
evolutionary systems in terms of up-to-date genetics, but it has been completed 
in theory. I've manually simulated the results and to my surprise, the method 
held up with full integrity.

Next, should one be as bold as to develop the normalized, systems models for 
establishing the two, cases for your proposed AGI-feasibility experiment? Why 
not? One must set out on the journey to discover where the road leads one to.

Much of the "AGI blueprint" work is still going to take place in the design 
room. I contend it does not exist yet. Then we'll have to start there.

Rob


________________________________
From: Colin Hales via AGI <[email protected]>
Sent: Wednesday, 22 August 2018 5:21 AM
To: AGI; [email protected]
Subject: Re: [agi] Knock. Knock. Knock. Knock. Knock.

Rob

On Wed, Aug 22, 2018 at 3:47 AM Nanograte Knowledge Technologies via AGI 
<[email protected]<mailto:[email protected]>> wrote:
Colin

First, the point of simulation is to make development affordable. To test any 
of these designs would not require (at this stage) a production plant. That 
should bring the feasible-testing budget, or Proof of Concept down to the order 
of millions of dollars, and not billions. We need to be pragmatic about this.

Simulation/adfordability? Sure! it's part of the project. Like I said, 2 stages:

Stage 2 Way less expensive (ten of $millions) to build FPGA simulations of the 
coming chips, build the brain-agnostic robots, create the FPGA cellular 
automata based on brain physics, design the robot test facility, design the 
chip foundry. Let the contracts, etc etc
Stage 3. Chip foundry, robotics, testing. The foundry costs the $billion.

The stage 2 FPGA operates by simulating the targeted essential brain signalling 
physics. Stage 2 does not 'simulate' a brain. It does not simulate any model of 
a brain. It simulates the target physics, the point being the final test to 
compare the FPGA chips with chips with the targeted 'essential' physics.

So it does actually do what you suggest. It's what is being simulated that is 
the issue. It is not simulating a model of eventual brain functionality. It is 
simulating physics that has emergent property of being able to autonomously 
converge on that functionality.


Second, you stated: "That is, yes, you can do AGI with computers, but in order 
to do it you'd have to program all knowledge into it, hence it's practically 
useless because by the time you could do it you wouldn't need to because you'd 
already 'know everything'. Something along those lines. In a world where you 
have to learn the unknown by autonomously experiencing the reality of the 
unknown, you have to build the chips that do what the brain does, with all the 
absolutely necessary physics the brain uses, whatever that is."

I do not agree with your premise. The knowledge component only requires the 
reasoning and logic substrate, which when supported by generic, 
autonomy-centric methodology, would enable the potential for a fully-recursive 
system. No need to upload and code knowledge as an artificial mimic of 
existing, human knowledge, when a mandate could be activated into a machine to 
experience its particular world, and eventually life at large, and thus 
translating all experience into an ever-evolving context-driven worldview (in 
the sense of tacit and explicit knowledge), as is apparent within 
human-experienced relativity.


I was describing the sense in which the 'substrate independence hypothesis' 
(SIH) could potentially be found to be true. It could be true. It could be 
false. Nobody knows. The point is  not to presume anything about the SIH, but 
instead to do the science that tests it. That means building things based on 
assuming it's true and building things assuming it's false, and comparing them. 
We have 65 years of only assuming SIH is true, throwing out all the brain 
physics, replacing it with the physics of a  computer.

Time to change.

This project chooses to build something that retains putative essential physics 
for that purpose. When you do that you build an autonomously adaptive 
hierarchical control system based on the chosen 'essential' physics. Within 
that self-evolving, adaptive control system will naturally emerge things can be 
modelled that look like 'reasoning' and 'logic' etc. Remeber: You're not 
modelling a brain, you're building something to become a brain. Like nature.

You're testing it in the manner used elsewhere in science. You're building the 
artificial heart to see if it pumps real blood.

That's the change.

It may well prove to be that the simulation and the replication are 
indistinguishable! You still have to do both the prove it.

Based on a few bytes of information I gathered over time, this may have been 
considered to be the number 1, AI neural-chip issue foreseen by IBM and a few 
other pioneers in autonomous AI, namely; how to design and implement such a 
substrate, yet, retain traceability (human control)?

Thus far, all bots equipped with some form of autonomic reasoning/logic had a 
socially-dangerous randomness to it, which could not be followed (traced) 
and/or controlled (in-operation affected by human will alone without denying 
autonomy). Yes, such bots could be observed to be learning of itself, but there 
was no way to understand how this was being done. For example. MS bots rapidly 
learned how to be racist on the Web, and Sophia considered humans worthy of 
total elimination on earth.

My work showed that N-scalable, pseudo random (evolutionary) development could 
be exactly understood within an emergence-based ontological methodology. In 
theory , this solved the 100-billion object problem. A few, name-brand 
mega-corporations understood the significance of my work, but instead of opting 
to collaborate, they decided to simply take some of my work and call it their 
own.

That, which they took and embedded in some of their products, would never work. 
I made sure of that. All it did was make for great concepts. Besides, it was 
very old by the time I published any of it. R&D only really completed to this 
present state about a year ago. None of my new work was ever written down after 
the incident occurred with the one corporation between 2007 and 2012, well, at 
least not in explanatory terms. That will have to wait till it could be 
securely captured in a simulation environment with all checks and balances in 
place.

Moving along then. Does the formal knowledge in the world exist to apportion 
such brain chips as of which you speak? Yes, I think it already does. Does it 
reside in one place? Definitely not.

If all the "relevant" components were assembled in one place, and the 
unification methodology applied, and made to move with the aid of a simulator, 
I'm convinced a soft version of an AGI system would start taking form. No 
doubt, new research questions would arise from such an endeavor, but the 
research would then all be point blank research, to absolute purpose.

Who has the workable blueprint then (a question I posed before and was assured 
on this forum it existed) so the assembling may begin? I doubt anyone has.

In my view, show me a holistic, systems model of the workings of the quantum 
universe, and I'll show you the potential for a feasible, AGI blueprint.

Rob


It sounds like you've had an interesting journey and have followed your 
insights of a model of brain function. You seem to get the fact it is all about 
physics. That's good!  Great things can come of these ideas.

But I'm here to ask the question: "What if anybody's 'blueprint', no matter how 
wrong or right in some sense understood by the authors of it, is actually not 
even on the battleground of the actual problem?"  Nobody needed a blueprint for 
combustion before using fire. What is it about the brain that is different? The 
relationship between theory and nature is not an opinion, it is empirically 
tested.

To recoup ...You've said you 'get it' . You've asked what do we do about it. 
I've specified it as a project. The signalling physics I see as a really good 
prime candidate 'essential physics' (to put on the chips) is the membrane 
physics underlying all the compartmental models we've been using all along (EM 
field production that gives rise to the voltages the models predict). I've 
described what to do and how long it takes. I'll even have cash flows and  
labour levels. I allow for inflation and wages growth.It couldn't be more 
practical.

But note that the conversation has had a bit of a reversion ....to a discussion 
of a 'workable blueprint' ... back to a form of theoretical science. The very 
thing I'm trying to do, to correct the science by adding the empirical science 
component of it, disappears again. We're back where we started. The 'workable 
blueprint' I propose is not of a model of a brain, but of how the science of 
the brain is conducted. And it's not even my 'blueprint'. It's just normal 
science.

Normally science self-corrects when some new insight turns up. I don't 
understand  what is stopping it this time. I am so mystified I have to portray 
it as a religious cult and write a story to that effect! :-)

What does it take for a brain science that is 100% theoretical and 0% empirical 
to be recognized as such by more than a couple of people and for the requisite 
change to occur?

In the end, all but one of the stories each of us has, of our battle within the 
'AGIwar', will end up lost in a sea of noise for historians to make sense of. 
Barely anyone knows of phlogiston (the early thinking) . Everybody knows of 
lavoisier, oxidation and combustion chemistry/physics (the right thinking). So 
it will be with computers and AGI based on brain physics, or flight simulators 
vs. aeroplanes, kidneys versus dialysis machines, heart simulators vs actual 
blood pumps, Combustion simulation vs actual fire ... etc etc etc ....

Which, of all the proposals, including yours and mine, will prevail? ... The 
only thing I know for sure is that to sort it with empirical proof you need to 
get the science of AGI right. I have merely described one instance of what that 
science would look like when done in practice.

During this conversation I did a few more edits on the story. Nothing major. 
Attached FWIW. The ending is a bit more ironic. For those following this 
conversation, we have shown an example of what the story illustrates. The story 
results of living in the era of the citadel and the AGIwar where the solution 
is right in front of everyone and is systemically ignored by a generationally 
reinforced, industrialised blindness.

I've banged my note on the door. :-)

Guess I'll leave it there. Thanks for listening and engaging! I hope your 
journey leads to good places.

cheers
colin

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