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Natesh Ganesh: on 4/7/17 at 16:04pm UTC, wrote Dear Rajiv, I appreciate the time you took to provide detailed questions...

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FQXi FORUM
May 30, 2017

CATEGORY: Wandering Towards a Goal Essay Contest (2016-2017) [back]
TOPIC: Intention is Physical by Natesh Ganesh [refresh]
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Author Natesh Ganesh wrote on Feb. 21, 2017 @ 17:18 GMT
Essay Abstract

In this essay, I will present the fundamental relationship between energy dissipation and learning dynamics in physical systems. I will use this relationship to explain how intention is physical, and present recent results from non-equilibrium thermodynamics to unify individual learning with dissipation driven adaptation. I will conclude the essay by establishing the connection between the ideas presented here and the critical brain hypothesis, and it's implications on cognition.

Author Bio

Natesh Ganesh is a PhD student in the Electrical and Computer Engineering Dept. at Umass, Amherst. Research interests include fundamental limits of energy efficiency in computing systems, neuromorphic computing architectures, machine learning algorithms, a physical basis for learning, coherent definitions for information and consciousness, and the philosophy of mind.

Download Essay PDF File




Member George F. R. Ellis wrote on Feb. 22, 2017 @ 07:10 GMT
Dear Natesh

this is an impressive piece of work.

I have not had time to try to work through the details, but for me two things are important. First, you have set a context of predictive estimation. That is a key issue, and I agree whole-heartedly. So there has to be a structure that underlies the existence of this function, and the kay issue is where this structure came from. That cannot be via non-equlibrium thermodynamics alone.

Second, you say Agency is the capacity of a system/entity/agent/organism to act on it’s environment. Is is the Moon an agent n that respect? (after all it causes tides on the Earth). "We will define sense of agency (SA) as the pre-reflective subjective awareness that one is initiating, executing, and controlling one’s own volitional actions in the world." That is already assuming key elements of psychology that do not arise in any simple way from physics.

I will try to reflect more on what you have written in due course. Your principle may well be important at the physical level, when the rest of the context is given.



Best wishes

George

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Author Natesh Ganesh replied on Feb. 22, 2017 @ 14:43 GMT
Professor Ellis,

Thank you for your comments. Since we seem to be dealing with two different conversation threads with different points raised in both, I will try and keep my answers separate to avoid confusion as much as possible.

"Second, you say Agency is the capacity of a system/entity/agent/ organism to act on it’s environment. Is is the Moon an agent n that respect? (after...

view entire post





Lee Bloomquist wrote on Feb. 22, 2017 @ 20:28 GMT
Natesh Ganesh asks, "Can minimal dissipation alone be a sufficient condition for learning?"

Two biological systems might fit this description.

First, in Charles Gallistel's book The Organization of Learning, Chapter 11 tells of foraging experiments. Consider fish (are neurons like fish?). Given probabilistic feeding stations, the school divides itself proportionally— which from the...

view entire post


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Author Natesh Ganesh replied on Feb. 23, 2017 @ 07:33 GMT
Dear Bloomquist,

Thanks for your comments and very interesting links. I will have to look through them in detail as soon as I can. I am hoping we can find many more examples of biological systems that satisfy the idea

presented in this essay. Here are some of my thoughts on your comments-

I have not thought about the behavior of a larger system comprising of many small minimally dissipative parts in detail but if I have to venture a guess, I would think some sort of cooperative behaviour would emerge. Also with respect to the fish example, the fish is a system that can act on its environment and thus its behavior is a tradeoff between 'exploration vs exploitation' under this idea and would not just be a form of predictive learning that we would see in a system that

cannot act on its environment.

While there may be many languages, some providing a more detailed and useful definition of purpose, the language in this paper would explain the emergence of what these other languages describe better.

Thanks again for your comments.

Natesh



Lee Bloomquist replied on Feb. 24, 2017 @ 12:50 GMT
Natesh, thank you for your reply! You wrote:

"Also with respect to the fish example, the fish is a system that can act on its environment and thus its behavior is a tradeoff between 'exploration vs exploitation' under this idea and would not just be a form of predictive learning that we would see in a system that cannot act on its environment."

Is what you wrote, above, about probability-learning foraging fish implied by the definitions of terms in your hypothesis? That is, do the definitions of the terms in your hypothesis (like "open," "constraints," etc.) imply what you have written, above?

Your hypothesis: "Open physical systems with constraints on their finite complexity, that dissipate minimally when driven by external fields, will necessarily exhibit learning and inference dynamics."

Or, is more than this required to understand your hypothesis— more than just the above statement of your hypothesis together with definitions of the terms used in your hypothesis?

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Author Natesh Ganesh replied on Feb. 28, 2017 @ 15:31 GMT
Hi Lee,

Apologies for the late reply. Have been away at a conference to talk about some of the ideas here and how to relate it to computing.

"Or, is more than this required to understand your hypothesis— more than just the above statement of your hypothesis together with definitions of the terms used in your hypothesis?"

--> All that is needed to understand my hypothesis is that statement. I have provided as many definitions as I can there in the essay but due to space limitations I have had to reference some of the other definitions in former papers.

"Is what you wrote, above, about probability-learning foraging fish implied by the definitions of terms in your hypothesis? That is, do the definitions of the terms in your hypothesis (like "open," "constraints," etc.) imply what you have written, above?"

--> Yes. It does.




Joseph Murphy Brisendine wrote on Feb. 22, 2017 @ 22:20 GMT
Hi Natesh,

I think this essay is fantastic and basically completely correct. I love that you took the time to make explicit connections between the Landauer limit, which many biochemical processes ahve been shown to assymptotically approach, and the importance of a predictor circuit and feedback between sensing and acting, and you even bring in the flcutuation theorems at the end in discussing the problem of assigning probabilitites to brain states, I think it's wonderful and very informed with regard to current research in stat mech, neuroscience, and machine learning. You have the diversity of background required to address this question which is at the intersection of so many fields.

I hope you might take the time to peruse my submission, entitled "A sign without meaning." I took a very different approach and went with an equation-free text in the hopes of being as accessible as possible, but I think you'll find that we agree on a great number of issues, and I'm glad that the question is being addressed from multiple perspectives but with the right foundation in statistical mechanics.

Best of luck to you in the competition I think you wrote a hell of an essay!

--Joe Brisendine

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Author Natesh Ganesh replied on Feb. 23, 2017 @ 08:06 GMT
Dear Joe,

Thank you for your very kind and encouraging comments. Inspires me to work harder. I am glad that I managed to communicate the ideas in the essay coherently to you. Yes, the topic of this essay is at a very unique intersection of so many different fields. I wish I wasn't right at the word limit and had more room to discuss a bunch of other things. There is a much needed discussion of semantics, consciousness and the implications of the ideas presented here on the philosophy of the mind that I would have loved to delve into.

The title of your essay is very intriguing. I am caught up at a conference for the next two days but I will definitely read your essay in detail over the weekend and get back to you with questions/comments. I look forward to reading your thoughts on this problem. Thanks a lot again for your encouragement.

Natesh




James Lee Hoover wrote on Feb. 22, 2017 @ 23:18 GMT
Quite interesting, Natesh. The emergence of intention, purpose, goals, and learning are automatically achieved with England's restructuring and replication thesis as dissipation occurs -- but humanly done with purpose and goals? Your emphasis on computer modeling seems to blur the distinction between the human and machine but that is probably my failure to view it after one quick read.

Impressive study.

Jim

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Author Natesh Ganesh replied on Feb. 23, 2017 @ 07:54 GMT
Dear Jim,

I am glad you find it interesting. Yes, while England's ideas have been a big step forward in the right direction, there are some caveats in his hypothesis and I illustrate those points and present a way to unify individual learning and evolutionary processes under the single fluctuation theorems.

"but humanly done with purpose and goals?" I am sorry but I fail to understand your question. Can you help me out here?

I might have used finite state automata/machine which are popular in computer engineering and and being one I am very familiar with them. Their popularity in computer engineering does not reduce their general applicability.

Thanks for your comments. Let me know if there are other things I can clarify if you get a chance to view it in detail.

Natesh




Jeff Yee wrote on Feb. 23, 2017 @ 00:50 GMT
Natesh - You did a good job on your essay and I like how you've been able to incorporate math, which was suggested in the essay rules. Well done! I gave you a good community rating which I hope helps to give your essay the visibility/rating it deserves.

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Author Natesh Ganesh replied on Feb. 23, 2017 @ 07:58 GMT
Dear Jeff,

Thank you for your encouraging comments and kind rating. Gives me greater confidence to carry on and to work harder. Yes, it was tough but after several edits I think I managed to find a good balance of math vs no-math. And the language of math is always beautiful and adds so much to the discussion, wouldnt you agree. I am hoping more people will read this essay.

Natesh




Lee Bloomquist wrote on Feb. 23, 2017 @ 02:16 GMT
Natesh, I can't find an equation that defines "dissipation" in the essay. Is it in the references? I can find "the lower bound on dissipation in this system as it undergoes a state transition..." But that seems specific to finite state machines, which are not equivalent in power to Turing machines. Is it just "delta E"? where E is energy lost from something like a thermodynamic engine?

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Author Natesh Ganesh replied on Feb. 23, 2017 @ 07:46 GMT
Dear Bloomquist,

The dissipation by the system S into the bath B is captured by the \Delta expression of the bath. This would be the change in the average energy of the bath and since only S can exchange energy with B, the increase in energy of the environment would be due to the dissipation by S due to a state transition. A much detailed treatment of the methodology I use is available in the reference as cited in the submission.

Addressing your comment about finite state automata (FSA) vs Turing machines, you are right that Turing machines have greater power but the Markov FSA as I have defined in the essay is still very general and will allow for a wide range of scenarios. Furthermore I have heard arguments that biological organisms need not be Turing machines and capable of computing all functions. Having said that I recognize that the model prescribed here can be vastly improved. I am currently working on something a little more general than the FSA I have prescribed here (still not a Turing machine yet) that will still allow for some insightful takeaways.

I want to note that I substitute the dissipation bound for the actual dissipation, since for the biological processes we would be interested in the bounds are good approximations of the actual dissipation. Furthermore I want to add that, the dissipation bounds though might have a Landauer-like essence to it, it is more rigorously derived and overcomes some of the objections that critics have raised against the hand wavy like calculations in Landauer's original paper. You can view it as energy lost by a very specialized type of thermodynamic engine.

Thank you again for the comments. Please let me know if I missed in address anything else you have brought up.

Natesh




Anonymous wrote on Feb. 23, 2017 @ 13:29 GMT
Thank you for your patience with me, Natesh. I see you are at a nanotechnology lab, so I imagine that "I squared R" dissipates a lot of heat that is of concern. How much dissipation in your hypothesis is from I^(2) R ?

From my work experience in software, implementing a FSM by an array with two indexes, one for current state, one for current input signal, storing at those indexes next...

view entire post


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Lee Bloomquist replied on Feb. 23, 2017 @ 13:31 GMT
Sorry, the previous post was me. Don't know how that happened.

Lee Bloomquist

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Author Natesh Ganesh replied on Feb. 23, 2017 @ 16:20 GMT
Hi Lee,

I am happy to answer all questions. I want to point out again that I use the dissipation bound as a (good) approximation of the actual dissipation in the processes that we are interested in. The dissipation bound expression as entropy \delta S and mutual information terms I. The dissipation bound is fundamental and relates to dissipation associated with irreversible information...

view entire post





Lee Bloomquist wrote on Feb. 23, 2017 @ 22:14 GMT
Natesh. All I can get on the second paper is the abstract and a bit of the intro. The rest is behind a paywall.

You wrote, "When you talk about I^2*R expression for dissipation, you are thinking about wires and charges moving through those wires. So that expression will not hold for spin based architectures." It's Joule heating, as in this...

view entire post


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sridattadev kancharla wrote on Feb. 25, 2017 @ 13:10 GMT
Dear Ganesh,

I wish you all the best with your in depth analysis of how intentions govern reality. I welcome you to read there are no goals as such in which I propose that consciousness is the fundamental basis of existence and that intent is the only true content of reality. Also that we can quantify consciousness using Riemann sphere and achieve artificial consciousness as per the article Representation of qdits on Riemann Sphere. I saw that you are also arriving at study of consciousness in physical systems in the conclusion of your essay. Also please see all the diagrams I have attached in my essay.

Love,

I.

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Author Natesh Ganesh replied on Feb. 28, 2017 @ 16:06 GMT
Hi,

Thanks for reading my essay and your comments. I have read your work and will politely disagree with you on your premise and conclusion though. I do think that starting from consciousness as a fundamental basis of existence is not the right approach. I would argue that consciousness is an emergent property in input mapping that occur in certain systems due to thermodynamic constraints. I think we will just have to agree to disagree. Also you should check out the integrated information theory of consciousness by Tononi and Koch. I think you will enjoy their work. Please rate my work if you enjoyed reading it. Thanks and good luck in the contest.

Cheers

Natesh




Satyavarapu Naga Parameswara Gupta wrote on Feb. 26, 2017 @ 01:13 GMT
Dear Ganesh,

Thank you for the good essay on “Intension is Physical"

You are observations are excellent, like… “fundamental limits on energy efficiency in new computing paradigms using physical information theory as part of my dissertation”

I have some questions here, you mean to say for every external input, our Brain predicts and takes a correction. It wont be acting on directly by its own self….

Probably if we make energy efficient computer, it will become super intelligent, Probably we may require some software also….

Even though my essay (Distances, Locations, Ages and Reproduction of Galaxies in our Dynamic Universe) is not related to Brain functions, It is on COSMOLOGY….

With axioms like… No Isotropy; No Homogeneity; No Space-time continuum; Non-uniform density of matter(Universe is lumpy); No singularities; No collisions between bodies; No Blackholes; No warm holes; No Bigbang; No repulsion between distant Galaxies; Non-empty Universe; No imaginary or negative time axis; No imaginary X, Y, Z axes; No differential and Integral Equations mathematically; No General Relativity and Model does not reduce to General Relativity on any condition; No Creation of matter like Bigbang or steady-state models; No many mini Bigbangs; No Missing Mass; No Dark matter; No Dark energy; No Bigbang generated CMB detected; No Multi-verses etc.

Dynamic Universe Model gave many results otherwise difficult to explain

Have a look at my essay on Dynamic Universe Model and its blog also…

http://vaksdynamicuniversemodel.blogspot.in/

Best wishes…………….

=snp. gupta

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Author Natesh Ganesh replied on Feb. 28, 2017 @ 15:39 GMT
Hi,

Thanks for your comments. Here are my answers to some of the questions you have brought up.

"I have some questions here, you mean to say for every external input, our Brain predicts and takes a correction. It wont be acting on directly by its own self…."

--> If you think of the brain as an hierarchical predictive machine, everything you experience is a result of the continuous prediction-error correction mechanism it is executing. And using terms like "self" is a little loaded and misleading. The sense of self is the result of a physical system that I have described in the essay just evolving under physical law.

"Probably if we make energy efficient computer, it will become super intelligent, Probably we may require some software also…."

--> Yes, it is a very new idea in computing called 'thermodynamic computing'. There is very little work right now but it is gaining momentum. And the point is that there is no fixed algorithm or software. The hardware is set to evolve under larger thermodynamic constraints (as stated in the minimal dissipation hypothesis) for a large set of different environments and it will learn.

I will take a look at your essay but I am an engineer by training and my knowledge in cosmology is very limited, so please forgive me if I cant fully grasp the ideas you express in them. Good luck in the essay contest and please rate if you have enjoyed the work.

Cheers

Natesh




Willy K wrote on Feb. 28, 2017 @ 09:37 GMT
Your work is highly mathematical. Although my math skills are not good enough to understand the details, I think it is a tremendous work. I would love to see your work on consciousness, qualia and meaning, which you hinted at in the essay, primarily because I had considered those areas well-nigh impervious to mathematics. But I am pretty sure you will talk even of those areas using math. Rather impressive, I must say.

I had wanted to evaluate my work on whether it satisfied the mathematical theorems of Ashby and Conant. I am speaking here of the Law of Requisite Variety (Ashby) and the Good Regulator Theorem (Conant). But I could not because my math skills are not good enough for the job. My guess is you would want to evaluate your work as well on its alignment with the basics of those works. Ashby’s work is considered a classic in understanding the functioning of all systems, but on glancing through his works, it is clear that he did his work primarily with the human brain in mind.

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Author Natesh Ganesh replied on Feb. 28, 2017 @ 15:48 GMT
Hi Willy,

Thank you for the kind comments. Yes, I did not have space to treat questions like qualia and meaning in detail but I intend to in the near future. I am an engineer and my immediate focus is to leverage the ideas presented here into actual computing systems. The math was a necessary evil and I will work on making the explanations are lot clearer going forward. I find the ability to address such topics with math very exciting.

I like that you brought up both Ashby and Conant, two people whose work has been very influential on me. The minimal dissipation hypothesis is connected to the Good Regulator Theorem in a straight forward manner, and is something I have thought about and worked on. I will have to think a little bit more about rigorously showing the connection to the law of requisite variety but my initial feeling is that it is not impossible.

Thanks again for your comments. Please rate if you enjoyed the essay. It looks like I could use the help.

Cheers

Natesh




Peter Jackson wrote on Mar. 1, 2017 @ 11:36 GMT
Natesh,

Great essay, well informed and organised analysis of a very interesting hypothesis.

I also like most and agree with much, certainly with the addage that; 'our aims and goals are shaped by our history', and the importance of; efficiency, neuronal avalanches, branching parameters, critical regions and that a 'hierarchical predictive coding' model is possible.

I'm not...

view entire post


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Author Natesh Ganesh replied on Mar. 2, 2017 @ 18:10 GMT
Dear Peter,

Thank you for your kind comments. Much appreciated.

"I also like most and agree with much, certainly with the addage that; 'our aims and goals are shaped by our history', and the importance of; efficiency, neuronal avalanches, branching parameters, critical regions and that a 'hierarchical predictive coding' model is possible."

--> Agreed.

"I'm not yet...

view entire post





Ines Samengo wrote on Mar. 5, 2017 @ 01:29 GMT
Hi, Ganesh, I respond here to a question that you asked in my page:

"I will have to ponder over the idea of ascribing goals to any entropy reduction in a system. I am wondering if that is too narrow a definition. After all, a (conscious) observer should be capable of ascribing a system as performing a computation (and hence the goal of performing that computation,) even with no entropy change(?)"

If the computation is invertible, then the output is equal to the input, except for a change of names. I believe that computations are interesting only when they are non-invertible. But perhaps I am missing something…

I saw your essay as soon as it came out, I was impressed, but did not follow all the details. Today I gave it a second look, and I am still impressed, above all, because this strikes me as an original contribution, which I found only very rarely in this forum. Moreover, within the neural networks theory, I've had enough gradient-descent learning rules that come out of the blue, your proposal is so much physical. I confess I must still give it more proper thought – or perhaps, find the time to do the calculations myself – because I intend to take these ideas very seriously. I hope you publish this work as a paper soon, this essay contest does not seem to be the best environment. The work is probably a bit too technical given the contest rules, the length is too constrained, and the audience can be better targeted. I hope that you will consider presenting these ideas in the computational neuroscience audience. They may not have your same physical-computational background, but they will be surely interested in the conceptual result.

Congratulations!

inés.

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Author Natesh Ganesh replied on Mar. 5, 2017 @ 20:22 GMT
Hi Ines,

Thanks for your kind comments and encouragement. Yes, I have had issues with a wide variety of gradient descent based learning rules, which is why I wanted something more physically grounded. I am working on a more formal paper as we speak, where I will have the space to discuss the details. This is a continuously evolving idea and after receiving some great feedback, I have...

view entire post




Ines Samengo replied on Mar. 5, 2017 @ 21:36 GMT
Hi, Ganesh, I am afraid I do not understand. "the observer will claim that this physical evolution with zero entropy change has achieved the goal of being an AND gate." Why do you say that the evolution has no entropy change, if the observer has made the association A -> 0, and B,C,D -> 1? This association is entropy-reducing, isn't it? I wait for your reply before elaborating more.

Great to know you are on the way to publish! Your essay is new raw material, so the natural evolution is: get it published. As a neuroscientist, I was more surprised by the learning part of your essay, than by the criticality one, but mind you, I am not truly mainstream, so just take it as one opinion out of many. To me, the learning part is thought provoking, I have the impression that new paradigms, and new understanding may come out of that. The criticality claim seems to be everywhere, but I do not gain much from it, apart from classifying the process as critical. Anyway, surely I am missing something...

best!

ines.

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Author Natesh Ganesh replied on Mar. 5, 2017 @ 22:34 GMT
Hi Ines,

Consider the evolution of the system with 4 initial distinguishable states A,B,C and D to 2 orthogonal states 0 and 1, with A evolving to 0, and B,C,D evolving to 1. There is a clearly a reduction in the physical entropy of this system and an observer with access to observe this evolution might decide to associate the AND operation with this evolution. We will call this a faithful...

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Ines Samengo wrote on Mar. 6, 2017 @ 00:46 GMT
Hi Natesh,

sorry about the names! I am a slave of rhymes, and tend to map together all what sounds similar. Actually it's even worse, I also cluster faces together. By all means, I must learn to represent information more injectively...

Yes, sure, as I see it, it may well happen in the brain of the observer. There are many possible settings, which I discuss below. But in all...

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Ines Samengo replied on Mar. 6, 2017 @ 00:51 GMT
Sorry, one more point: when an observer learns a one-to-one mapping, arrogating agency has not much sense, because there is no entropy loss in the mapping. The process of learning the mapping, though, can be arrogated with agency: the observer tends to learn. But here there is a meta-observer observing the first observer, right? It is the learning observer that may be arrogated with agency, not the lower-level system under study. And now yes, I go. Sorry for the long speeches!

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Author Natesh Ganesh replied on Mar. 7, 2017 @ 04:27 GMT
Hi Ines,

Thanks for the long detailed response. You have given me much to think about and definitely introduced me a new point of view.

"Yes, sure, as I see it, it may well happen in the brain of the observer. There are many possible settings, which I discuss below. But in all settings, ascribing agency (as I understand it) requires an entropy-reducing mapping. If the mapping is not...

view entire post





George Kirakosyan wrote on Mar. 22, 2017 @ 08:48 GMT
Hi Dear Ganesh

I have read your article (as we usually speaking this!) and I will simply tell you that I am somewhat skeptical on its possible success. I see that your approach is presented by well logical flow, but I am skeptical as these are based on hypotheses. Maybe you will very right, however who can say you this certainly and definitely for today? Thus, your essay seems to me as the interesting Ideas represented in nice form and by impressing narration. I hope you can understand my point (and maybe somewhat to become agree with me!) if you find time to check my work. Then we can continue talk in my page, if you see we can have somewhat common views.

Best regards

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Author Natesh Ganesh replied on Mar. 23, 2017 @ 22:40 GMT
Hi George,

Thank you for your comments. Skepticism is good and an important quality of a good scientist. I welcome it and your criticism, for it will help me grow as a researcher. As a PhD student with deadlines, I am a little busy but I will have a chance to read your work slowly and in detail over the weekend. I shall get back to you once I have understood what you have to say in your submission. Thanks.

Natesh




Shaikh Raisuddin wrote on Mar. 23, 2017 @ 16:19 GMT
Natesh Ganesh,

How matter learns?

Can we say a cyclone is a goal-directed system?

There is periodicity of want-and-hunt/intentions in every living being, how that can be designed?

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Author Natesh Ganesh replied on Mar. 23, 2017 @ 22:51 GMT
Hi Shaikh,

Thank you for your comments.

"How matter learns?"

--> This is what I address in section 2 of my submission. I think that minimally dissipative systems necessarily learn in an unsupervised manner naturally. There are hints in the derivations on how reinforcement and supervised learning will be covered as well.

"Can we say a cyclone is a goal-directed system?"

--> Good question!We have to differentiate between us ascribing a goal to a cyclone vs whether the cyclone has a goal for itself and a sense of agency? That is an important distinction. We can ofcourse project a goal from us onto a cyclone but unless a cyclone is a minimally dissipative system (having an hierarchical implementation), which it isnt, then the cyclone does not have a sense of its own agency, goal oriented or not. I would recommend reading Dan Bruiger's submission here which makes this distinction between teleology and teleonomy very clearly.

"There is periodicity of want-and-hunt/intentions in every living being, how that can be designed?"

--> I do not know the answer for that yet, on how to make systems like the ones I describe in my submission. I am not even sure if 'design' is the right way to go about it. All the systems that I refer to have been self-organized. Perhaps we should look to creating the conditions/ constraints for such systems to emerge and let physical law do its thing. This is how I would imagine we would achieve a new way of computing, called 'thermodynamic computing' that is being theorized about.

Hope I have satisfactorily answered your questions.

Cheers

Natesh




Edwin Eugene Klingman wrote on Mar. 24, 2017 @ 05:06 GMT
Dear Natesh,

I very much enjoyed reading your most impressive essay. Since you have read mine and commented, I will look at possible correlations, based on the assumption that one of us is actually representative of reality. In fact, even if my essay is correct about the universal nature of awareness, your model may well 'simulate' awareness and may describe realistic governing...

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Author Natesh Ganesh replied on Mar. 26, 2017 @ 19:18 GMT
Dear Edwin,

Sorry for the delayed response. I had a conference paper deadline and finally have some time to myself. Thank you for your detailed response and encouraging comments. It fills me greater confidence to keep working harder at a solution.

I really enjoyed your discussion on the effect of the consciousness field on electrons vs ions. It is an interesting point you make. Some colleagues of mine in the department are working on ion-based memristor devices, which might actually serve as a better substrate to interact with a consciousness field than an electronic device. Furthermore I completely agree with you on the concept of a 3D structure, than the traditional 2D architecture. I too am convinced that any system capable of a comparable consciousness should have some kind of 3D structure. Interestingly I am in discussion with them to possibly constructing 3D array of sorts with these ionic memristors, with the type of constraints that I talk about in my essay (if we figure out how to impose them) and just let it run in an input environment to see what it does. Should be very interesting I think.

I am about 6-7 months from finishing and in full writing mode, but I will definitely take a look at the resources you mentioned (especially the ones on pattern recognition). One can never learn enough and I am sure they will provide some new insight for me. Thanks.

Natesh

PS: I finally got around to rating your essay. I would appreciate it if you rate mine, if you havent already. If you have already, thank you very much!



Edwin Eugene Klingman replied on Mar. 26, 2017 @ 19:44 GMT
Dear Natesh,

I have now rated you (10). Past experience has indicated that there may be turbulence in the final hours, so I had planned to hold off to help you then, but perhaps increased visibility will help now. Some earlier essays that I pushed up for visibility were immediately given '1's by whatever trolls lurk in low places.

The final decisions are made by FQXi judges, and I think they will judge your work well.

I am very glad that you agree about the 3-D structure. What you say about ionic memristors is very interesting! I'm glad to hear this. I hope we stay in touch.

Best,

Edwin Eugene Klingman

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Author Natesh Ganesh replied on Mar. 26, 2017 @ 20:59 GMT
Dear Edwin,

Thank you for your kind rating. Yes, I agree with you on the sad trolling that has been going on, that I fear is hurting the contest overall. I was hit with 5 continuous 1's without any feedback, which sent my essay in freefall and left me disheartened earlier. Hopefully I will have the opportunity to have the work judged by the FQXi panel. Good luck on the contest and I would very much like to stay in touch. Thanks.

Natesh




Robert Groess wrote on Mar. 25, 2017 @ 09:10 GMT
Dear Natesh Ganesh,

Thank you for your beautifully written, and rigorously argued essay. I agree that your "minimal dissipation hypothesis" is a very good indicator of intent and that goal-directed agency emerges from, as you put it, systems that dissipate minimally.

Just as a quick question, have you followed some of Charlie Bennett's work on computational efficiency from thermodynamic considerations? I had the privilege of spending some time with him about a decade ago and found him to be a great source of talent and inspiration in that regard.

Good luck in the contest, I have rated your essay and thoroughly enjoyed reading it.

Regards,

Robert

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Author Natesh Ganesh replied on Mar. 26, 2017 @ 19:37 GMT
Dear Robert,

Thank you for your encouraging reply. I am happy to hear that you liked my submission. Yes, I do think that "minimal dissipation" might provide a sufficient condition for emergence of goal-oriented agency.

Yes, I have across Bennett's work! I think he has been one of the most influential thinkers of our time!! I study the fundamental thermodynamic limits to computing as part of my dissertation and I often use the works of Landauer and Bennett. I also like his work on reversible computing, and am hoping the field will gain more momentum. This is my favorite paper of his "Dissipation-error tradeoff in proofreading." (Apologies for my long winded rant.)

Good luck on the contest. I will definitely take a look at your submission. Thanks.

Natesh

PS: My title is actually a play of words on Landauer's famous paper "Information is Physical".




Simon DeDeo wrote on Mar. 26, 2017 @ 19:50 GMT
Dear Natesh —

Let me ask a very basic question. Say I take a simple Newtonian system, two planets orbiting around each other.

I hit one with a rock, and thereby change the orbital parameters. There's a map from the parameters that describe the incoming rock, and the resulting shift in the system. The system appears to have "learned" something about the environment with minimal (in fact, zero) dissipation.

If I let the rock bounce off elastically, then there is strictly no change in entropy. I could probably arrange the environment in such a way that the system would show decreasing amounts of change to rocks flying at random times in from a particular direction. In general, there will be nice correlations between the two systems.

Why is this open system not an inferential agent?

I suppose I'm trying to get a sense of where the magic enters for you. I think you're cashing out efficiency in terms of KL distance between "predictor" at t and world at time t+1, presumably with some mapping to determine which states are to correspond. This seems to work very well in a lot of situations. But you can also construct cases where it seems to fail. Perhaps because the notion of computation complexity doesn't appear?

Thank you for a stimulating read. It's a pleasure to see the Friston work cited alongside (e.g.) Jeremy England.

Yours,

Simon

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Author Natesh Ganesh replied on Mar. 26, 2017 @ 20:29 GMT
Dear Simon,

Thank you for your comments and questions. This is a nice coincidence. I just finished reading about the Borgesian library and currently on section 2 "the physics of the gap". Great piece of writing and I will reach out on your page once I am done reading and re-reading and digesting it.

"Why is this open system not an inferential agent?"

--> Yes, it technically...

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Simon DeDeo replied on Mar. 26, 2017 @ 21:10 GMT
Dear Natesh — thank you for your very thoughtful response.

You asked me about this remark:

"I think you're cashing out efficiency in terms of KL distance between "predictor" at t and world at time t+1, presumably with some mapping to determine which states are to correspond. This seems to work very well in a lot of situations. But you can also construct cases where it seems to...

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Author Natesh Ganesh replied on Mar. 26, 2017 @ 22:15 GMT
Dear Simon,

I address your comments/questions below:

"So an example would be running two deterministic systems, with identical initial conditions, and with one started a second after the first. The first machine would be a fantastic predictor and learner. There there's correlation, but some kind of causal connection, once initial conditions are fixed, is missing from the pair....

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Don Limuti wrote on Mar. 26, 2017 @ 23:20 GMT
Hi Natesh,

The posts in this blog are as interesting a conversation as are in this contest. In particular your conversation with Ines Samengo is most interesting. More on that in a moment.

The wording of FQXi.org's contest is nebulous, unless you realize it is about the MUH of Tegmark. Tegmark's emphasis is about Mathematics. Landauer's emphasis is about Information. Your emphasis is...

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Author Natesh Ganesh replied on Mar. 27, 2017 @ 18:42 GMT
Hi Don,

Thank you for your very kind comments. I am glad to see that you liked the essay. Ines's work was outstanding and it was very insightful to discuss ideas with her.

"The image your essay triggered in me was Valentino Braitenber's book "Vehicles, Experiments in Synthetic Psychology". It is easy to make the vehicles look as if they had "emergent" goals. "

--> I will check this book out.

"In my essay I hoped to get across how convoluted the language of determinism and freewill is. Don and Lexi each took a side. However, each also used Unconsciously the other viewpoint during the conversation."

--> Ha!! Wonderful. I did not immediately get that but it adds much more to your submission. Thanks.

Cheers

Natesh




Stefan Keppeler wrote on Mar. 28, 2017 @ 15:56 GMT
Dear Natesh,

thanks for your kind comments on my page, which led me to your interesting essay.

I'm afraid, you lose me on page 2. What is
A Hilbert space? What are the
A basis for this Hilbert space? Similarly, what are
and the
What does
mean? Is that some kind of product? The transition mappings
are they unitary, stochastic, or...? You write that some time evolution is governed by a Schrödinger equation, what's the corresponding Hamiltonian? How is this Hamiltonian related to the


Or maybe we can go back one step, away from the technical details: What does it mean that a system has "constraints on its finite complexity"? And can I think of dissipation as energy transfer from the system to the heat bath?

Sorry for so many questions, I just feel I can't get the message, when I don't even understand the terminology on the first few pages.

Cheers, Stefan

PS: Sorry for the rendering - I don't know how to do inline math here. Each equation-tag causes a linebreak. :-(

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Author Natesh Ganesh replied on Mar. 28, 2017 @ 16:28 GMT
Hi Stefan,

No problem at all. I had the same problem and pretty much gave up on using Latex in this forum :D. Given the word limit, I could not get into explaining all the terms you had stated in detail, but here is a paper with all the details- Ganesh, Natesh, and Neal G. Anderson. "Irreversibility and dissipation in finite-state automata." Physics Letters A 45.377 (2013): 3266-3271. Let me know if you are having trouble accessing this.

The paper was written for deterministic automata but the extensions to stochastic mappings hold. The entire universe of referent-system-bath evolve unitarily but the system evolution can be non-unitary (probably is). Shortened version would be S-system in which FSA is instantiated with states \sigma. R=R0R1 is the joint system of past inputs R0 and present input R1, with x being a string in that distribution of inputs (In a classical case, all of these are essentially random variables). L is the transition mapping for which the corresponding Hamiltonian of the global joint system can be constructed so as to achieve the necessary state transition.

"What does it mean that a system has constraints on its finite complexity"?

--> If the complexity of the system can be captured by a mutual information measure, then a finite state automata with finite number of states can only have finite complexity. When we perform optimization of a variable, while keeping another condition constant, we call it constrained optimization and the condition as a constraint.

"And can I think of dissipation as energy transfer from the system to the heat bath?"

---> Yes! Thats exactly what it is. Details are in that paper again.

Thanks for your questions. Wish I had more space to explain all the terms in details. I am working on a more formal paper now and hopefully I can be a lot more detailed in that so as to avoid confusion. Let me know if there any more points to be clarified and I shall be happy to do it.

Cheers

Natesh



Stefan Keppeler replied on Mar. 29, 2017 @ 19:50 GMT
Dear Natesh,

thanks, after reading your Phys. Lett. A article, I think I understand the definitions. I think I also understand roughly how you obtain the bound (3) in your article. There is a similar (but not identical?) bound on page 2 of your essay, which I think is neither derived in your article nor in your essay -- or did I overlook anything?

Cheers, Stefan

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Author Natesh Ganesh replied on Mar. 29, 2017 @ 20:45 GMT
Hi Stefan,

"There is a similar (but not identical?) bound on page 2 of your essay, which I think is neither derived in your article nor in your essay -- or did I overlook anything?"

--> Yes, the bound in the essay was not derived here but is an extension of the bound in the Phys. Lett. paper. The bound in that paper was derived for independent inputs i.e. R0 and R1 are independent. The bound in the essay is derived for correlated R0 and R1, thus generalizing the bound from Phys. Lett. paper (I am writing a new paper on this generalization but it will hold if you follow the same set of steps from the earlier paper). The bound in the essay will reduce to the one in the 2013 paper if you assume R0 and R1 have zero correlations with the last term in equation (3) going to zero. Hope that explains everything. I am glad to see you are being extremely rigorous with the essay. Please keep the questions and comments coming.

Cheers

Natesh




Cristinel Stoica wrote on Mar. 29, 2017 @ 00:26 GMT
Hi Natesh,

Very interesting and well-written essay! I liked the idea of the minimal dissipation hypothesis, and how you used it to learning dynamics and the emergence of goal-oriented agency and the biological evolutionary process.

Best regards,

Cristi

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Author Natesh Ganesh replied on Mar. 29, 2017 @ 20:58 GMT
Hi Cristi,

Thanks for your comments. It is definitely a very interesting idea and I intend to keep working on it. I have read and rated your essay and it was very good piece of work. Good luck in the competition. Thanks.

Cheers

Natesh

PS: Kindly rate my essay if you havent already. If you have, thank you very much for doing so.




Vladimir Nikolaevich Fedorov wrote on Mar. 31, 2017 @ 13:11 GMT
Dear Natesh,

With great interest I read your essay, which of course is worthy of the highest rating.

I'm glad that you have your own position

«I will present the fundamental relationship between energy dissipation and learning dynamics in physical systems. I will use this relationship to explain how intention is physical, and present recent results from non-equilibrium thermodynamics to unify individual learning with dissipation driven adaptation.»

«I will refer to as the minimal dissipation hypothesis»


Your assumptions are very close to me «the phase space characterization of self-organized systems which dissipate minimally, improved understanding of internal control mechanisms to maintain criticality, and detailed formulations of cognitive states as phase transitions in a (non-chaotic strange) attractor.»

You might also like reading my essay , where it is claimed that quantum phenomena occur in the macrocosm due to the dynamism of the phase state of the elements of the medium in the form de Broglie waves of electrons, where parametric resonance and soliton occur, and this mechanism of operation is analogous to the principle of the heat pump. At the same time, «the minimal dissipation hypothesis» is realized.

I wish you success in the contest.

Kind regards,

Vladimir

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Jochen Szangolies wrote on Apr. 3, 2017 @ 14:36 GMT
Dear Natesh,

thanks for an interesting, very densely-packed essay! Your minimal dissipation hypothesis carries some immediate intuitive heft: anything minimizing its dissipation must in some ways adapt to the environment. You then turn traditional reasoning on its head, subverting the expectation that because something learns, it may minimize its dissipation (a good thing for any living system with bounded resources), arguing rather that such minimization itself is simply what constitutes learning.

It's sort of like the thinking that got rid of élan vital: once we've explained the moving around, reproducing, seeking out of food etc. it became clear that we don't need additional magic fairy dust---those sorts of things are just what's meant by the term 'life', they're not the consequence of a life-giving force being present. So in a sense, I see you attempting to do something similar for 'learning': once we've realized minimal dissipation in the agent, we find there's nothing else left over.

I'm a bit puzzled regarding your occasional mentions of quantum systems---it seems to me that essentially the same analysis could be carried out classically; nothing seems to ride on any specifically quantum features, such as superposition, interference, or quantum correlations.

Hope you do well in the contest!

Cheers,

Jochen

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Author Natesh Ganesh replied on Apr. 3, 2017 @ 19:18 GMT
Hi Jochen,

Thank you for your kind comments! The size limitations forced my hand with respect to the denseness. I could not have stated my ideas and thoughts better. I might borrow your comments on 'getting rid of elan vital' to better explain this for future purposes. In retrospect, I should have maybe limited the broad nature and focused with greater details on certain topics.

Yes, you raise a good point. The derivations are done for quantum systems because that is traditionally the regime I often work with for my dissertation in nanoelectronics, classical information stored in quantum systems. No specific quantum features were needed to be invoked in my submission and as I work on updating this submission and on a formal paper, I will make that a lot clearer. Expressions similar to what I have, can conceivably still be derived for classical systems (and I think would be equal to the expressions I have with the classical Shannon entropy terms). But I am interested in obtaining the equivalent quantum operators/mappings for future work and for that the current framework will serve well. Thanks for pointing it out.

Good luck to you in the contest as well!

Cheers

Natesh




Rajiv K Singh wrote on Apr. 3, 2017 @ 15:18 GMT
Dear Ganesh,

I suppose, you like critical examination of your essay. I must confess that I really could not follow the mathematical derivation entirely, may be due to my own limitation. But, I will grant the concluding remarks by you based on those mathematical expressions. I read this essay twice over a fortnight.

I take the following statement as your motivation. "Open physical...

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Author Natesh Ganesh replied on Apr. 3, 2017 @ 20:10 GMT
Hi Rajiv,

Lots to unpack here but I will do my best to answer all queries. To save space, I will paste a few lines from your comments while I try to address the entire paragraph.

"A prediction from higher level cannot be compared with the prediction error that took place at the lower level, it would make no sense. A predictive estimator must receive appropriate modular value derived...

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Rajiv K Singh replied on Apr. 4, 2017 @ 08:05 GMT
Dear Ganesh,

It would not be wise to attempt to repeat my arguments to emphasize the differences in understanding. But I should still make two points --

1. Consider this that you may have missed the central themes in each of the points that I made, you may be able to discover paths to strengthen your ideas and make them robust. For example, "As I said about your system that goals and purposes would not arise unless especially coded in the system, the same applies to all systems. In a system like brain, such a coding is achieved by the process of natural evolution in the Darwinian sense." If it so happened that you realized later sometime in future the truth of this statement, you may see suddenly a different meaning in each of my statements.

2. When I called you a magician, it was not meant to call you a 'scientific conman', many scientists believe that using the right descriptive words is needed to bring about the understanding of mental processes in physical terms. Often they believe, there isn't anything more than just a reframing of terms. And I meant, that you did a good job of that. Moreover, as you can understand that I would know the meaning of your names, therefore, I thought, you would understand the pun, and therefore, the fun in calling you with a similarly meaning word that goes well with your success. Looks like humor was lost !

By the way, it is not easy being a 'scientific conman' and succeed. Except for a tiny few, most cannot succeed in being so. So, from that perspective also, even if not intended, it is a complement.

Rajiv

P.S. At least you would have noticed the amount of time that I must have spent on your essay !

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Rajiv K Singh replied on Apr. 4, 2017 @ 08:46 GMT
Dear Ganesh,

I reread my own earlier comment. And then I realized, that several statements I wrote that could open a young PhD student mind. For example,

1. The association of an awareness of an action being performed to the system SA is in your/our mind. I do not see where and how exactly this sense of awareness is represented in SA.

So, that you can easily see that we have a tendency to assign the logical interpretation of our own mind into the processing systems so very easily -- a learning, what to be wary of in our thinking.

2. I am going to consider a stone as a system S embedded in surrounding heat bath, the air in thermal equilibrium.

So that next time, you will peruse your own statements with greater scrutiny to observe that your statements can be interpreted from very general or very narrow perspective.

3. "Thanks for a delightful exchange. I am enjoying myself!!" I consider you a system like SA, so which component of S and A is referring to itself as an enjoyer, and which component is being enjoyed? And why would both be claimed to be as oneself?

Placing you in a logical dilemma, so that you can ponder and get the deeper meanings of your objectives. It is also to demonstrate that there is always certain deeper implications that one should be careful about. And to open a mind that our understanding of nature must apply to our routine reflections, otherwise, you will not see the universality of applications of scientific thoughts.

I am sure, you will see that such confrontations with rationality could open minds of a budding scientist.

Rajiv

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Torsten Asselmeyer-Maluga wrote on Apr. 3, 2017 @ 20:59 GMT
Dear Natesh,

what a wonderful essay, full of new ideas. In particular I like your approach using finite automta (most argumentation using statistical physics need infinte systems). Very interesting for me was the criticality hypothesis. If the collective dynamics of the brain is close to a phase transition then this dynamics must be close to chaotic dynamics (like the cascade of harmonics for the logistic map). But at this point the underlying dynamics has a fractal state space.

You use a more statistical physics point of view but in my opinion we got similar results. Maybe you are also interested to read my essay? I considered a model for the brain network with a phase transition to a tree (so having a goal). Here the transition happens at the topology of the network.

All the best for you and for the contest (with a strong upvoting from my side)

Torsten

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Author Natesh Ganesh replied on Apr. 4, 2017 @ 15:23 GMT
Dear Torsten,

Thank you for the encouraging comments and the rating. I agree that Markov finite automata could be a very powerful and useful tool in studying the brain. Yes, I had read about the criticality hypothesis in neuroscience a few years ago and was not very convinced of it back then. It was surprising to me that the minimal dissipation hypothesis could be framed to predict this idea and the results look promising.

I will definitely have a close look at your work and reply on your page in detail later today.

"But at this point the underlying dynamics has a fractal state space."

--> Agreed. I am beginning to study attractors, chaotic dynamics, etc. in more detail now. My knowledge at this moment is very limited, but the idea I am most interested in that area are strange non-chaotic attractors.

"I considered a model for the brain network with a phase transition to a tree (so having a goal). Here the transition happens at the topology of the network."

--> This sounds very interesting and promising. I will reach out to you on your page.

Thanks and good luck on the contest.

Cheers

Natesh




Dizhechko Boris Semyonovich wrote on Apr. 5, 2017 @ 10:03 GMT
Meet up the New Cartesian Physic, based on the identity of space and matter. You need it, because it showed that the formula of mass-energy equivalence comes from the pressure of the Universe, the flow of force which on the corpuscle is equal to the product of Planck's constant to the speed of light.

New Cartesian Physics has enormous potential in understanding the world. To show this potential I ventured to give "materialistic explanations of the paranormal and supernatural" is the title of my essay.

Visit my essay, you will find there the New Cartesian Physic. After you give a post in my topic, I have to do the same in your theme



sincerely,

Dizhechko Boris

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Author Natesh Ganesh replied on Apr. 7, 2017 @ 15:01 GMT
Hi Boris,

I do not have the knowledge expertise to understand or critically judge your essay, so I am going to not comment or rate it to be fair. Thanks and good luck.

Natesh




Gary D. Simpson wrote on Apr. 6, 2017 @ 23:58 GMT
Natesh,

I'm glad to see another engineer in the contest. I won't pretend to understand fully what you have presented. My comprehension of your work is at most 50%. Having said that, it is clear to me that you have presented a break-through concept that connects the physical to the mental. You have quantified the ability to learn and done so in a manner that is not human-centric or even life-centric.

I can offer one observation from Chemical Engineering that might be useful to you. We have an area of study called Process Control. This is dedicated to controlling flow rates and temperatures and pressures and all such variables associated with chemical operations. In this field, we use concepts such as critically-damped, under-damped, and over-damped. These concepts are very similar to what you present near the end of your essay. There are also a host of methods available for what type of control to select and how to tune the control loops. If your university has a Department of Chemical Engineering, it might be worth spending a few hours discussing these items with some of the ChE faculty.

Best Regards and Good Luck,

Gary Simpson

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Author Natesh Ganesh replied on Apr. 7, 2017 @ 14:51 GMT
Dear Gary,

Thank you for your kind comments. Yes, I did not find many other engineer submissions here as well, so its good to meet another one. I do think the ideas presented here are potentially very useful and perhaps I need to do a better job of explaining myself better that everyone understands the work completely.

"You have quantified the ability to learn and done so in a manner that is not human-centric or even life-centric."

--> Could not have phrased it better myself. That was the goal (pardon the pun, couldnt help myself).

And your comments on over/critical/under damping is very interesting. I would be very interested in the control mechanisms especially and I will follow your advice and reach out to the Chem. Engineering department to better acquaint myself with ideas they have. The level I have presented is too high level and I will need the detailed mechanisms associated at the chemical levels to make further progress. Which as a computer engineer is to figure out how to build one of these systems :)

Cheers

Natesh




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