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RECENT POSTS IN THIS TOPIC

George Kirakosyan: on 3/22/17 at 8:48am UTC, wrote Hi Dear Ganesh I have read your article (as we usually speaking this!) and...

Natesh Ganesh: on 3/7/17 at 4:27am UTC, wrote Hi Ines, Thanks for the long detailed response. You have given me much to...

Ines Samengo: on 3/6/17 at 0:51am UTC, wrote Sorry, one more point: when an observer learns a one-to-one mapping,...

Ines Samengo: on 3/6/17 at 0:46am UTC, wrote Hi Natesh, sorry about the names! I am a slave of rhymes, and tend to map...

Natesh Ganesh: on 3/5/17 at 22:34pm UTC, wrote Hi Ines, Consider the evolution of the system with 4 initial...

Ines Samengo: on 3/5/17 at 21:36pm UTC, wrote Hi, Ganesh, I am afraid I do not understand. "the observer will claim that...

Natesh Ganesh: on 3/5/17 at 20:22pm UTC, wrote Hi Ines, Thanks for your kind comments and encouragement. Yes, I have had...

Ines Samengo: on 3/5/17 at 1:29am UTC, wrote Hi, Ganesh, I respond here to a question that you asked in my page: "I...


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FQXi FORUM
March 23, 2017

CATEGORY: Wandering Towards a Goal Essay Contest (2016-2017) [back]
TOPIC: Intention is Physical by Natesh Ganesh [refresh]
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This essay's rating: Community = 5.4; Public = 5.6


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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Joe Fisher wrote on Feb. 24, 2017 @ 16:47 GMT
Dear Potential Dr. Ganesh,

Please excuse me for I have no intention of disparaging in any way any part of your essay.

I merely wish to point out that “Everything should be made as simple as possible, but not simpler.” Albert Einstein (1879 - 1955) Physicist & Nobel Laureate.

Only nature could produce a reality so simple, a single cell amoeba could deal with it.

The real Universe must consist only of one unified visible infinite physical surface occurring in one infinite dimension, that am always illuminated by infinite non-surface light.

A more detailed explanation of natural reality can be found in my essay, SCORE ONE FOR SIMPLICITY. I do hope that you will read my essay and perhaps comment on its merit.

Joe Fisher, Realist

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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...

view entire post


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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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