A Druid's Pier

Practical Machine Sentience 4: Causality

The article explores machine sentience, focusing on how machines can process and associate sensory inputs to understand causality. It categorizes noumenal tokens and emphasizes the significance of functional output in distinguishing important sensory inputs from irrelevant noise. The piece includes definitions of association and causation as foundational to developing machine sentience.

It’s quite simple, straightforward, and easy to understand causality, friend. All you need to do is connect the dots. – DruidPeter

In the previous 3 articles, we went over basic definitions of Machine Sentience. We discussed foundational architecture needed to implement said definition, and we discussed what could be considered layer 1 processing of integrated sensory field devices on said architecture. As a result, we currently have a machine that is capable of associating sensory inputs with noumenal tokens, which were defined in the previous articles as well. For those who wish a very quick refresher on what noumenal tokens are, simply remove the word noumenal and just take the word token at face value: A thing that stands for something else.

Having traveled through these prerequisites, we now discuss the last prerequisite needed for the development of a machine understanding of causality.

System Functional Output as Group Operation

The key thing to take away here is that the machine treats its collection of and assortment of noumenal tokens as members of a civilization of mathematical groups. The definition and full understanding of a mathematical group is well beyond the scope of this article. Nonetheless, in layman’s terms, one can think of a mathematical group as a collection of objects that have certain properties, and some sort of action/operation that affects the properties of the collection.

To put it another way, our machine does not simply recognize and record sense impressions into sense tokens. But rather, it organizes and changes how it organizes and/or represents these tokens over time. The exact specification for how our machine does this is not of absolute importance for our purposes of creating a sentient machine, and in fact, according to how we defined machine sentience in the first article, can vary quite considerably.

Hence, let us for now simply construct a simple baseline classification system for our immediate purposes.

Baseline Classification of Noumenal Tokens

Let us first divide the collection of Noumenal Tokens into three groups:

Current Active Tokens

Current Active Tokens are simply tokens which can be said to correspond to currently recognized sensory input that is actively being sensed.

Non-current Active Tokens

These are tokens which are recognizable to the system, but which are not currently active within the sensory input system.

Current Associative Tokens

These are non-current tokens that are nonetheless associated with current active tokens. For example, if we see a bird from behind, then we may not see its beak. Nonetheless, we often associate beaks with birds, and as such, the token for a beak might be in this group.

Now, regarding current associative tokens, it is important to note that the exact mechanism for deciding what tokens are considered associated with current tokens is not important now. And indeed, at any given time, the collection of current associative tokens may be determined by algorithm and/or circumstance. Overall, this is a very simple system, but it will serve our purposes nicely.

The Role of Functional Output

In mathematical groups, there is often defined one or more operations, which, when applied to the group, affect either its properties or the properties of elements of the group. An integrated sensory field device is limited in its ability to provide means for recognizing such an operation outside of artificial means. This is because there is no natural dividing point between one sense impression and another. Between any two sense impressions, there exists only a continuum of other potential sense impressions.

We argue, then, that functional output of the system creates the natural boundary that is needed. Recall that functional output is simply some output from the system that, as a side effect of its operation, is capable of changing the sense impressions impressed upon the integrated sensory field device. Again, a very simple example would be that of muscular movement in the case of human beings. If you move your head, light will enter your retinas in a different way and produce different visual impressions upon you.

Why Functional Output is so Important

We choose functional output because of how it plays a role in determining what subsets of sensory inputs are functionally important to the system, and what are irrelevant and considered noise. Functional output, by definition of the term “function” is a function of input. And the input comes from none other than the integrated sensory field device.

Consider, then, for example, the sensory input of a threat, say, a bear, alongside additional sensory input of something nonthreatening, say, a tree. Upon first impression, the machine might associate both the bear and the tree together as a noumenal token serving as a functional input, associated with the interpretation of “threat”.

But let the machine now encounter the same threat, a bear, next to something else decided un-tree-like. After repeated exposure, the machine learns to interpret precisely what subset of the sensory integrated field, ‘e.g. the bear’ is actually to be associated with what functional output is chosen, ‘e.g. running away’.

We will for the time being ignore the process of how functional outputs are, over time, consistently chosen from functional inputs, as that is a complex subject in itself. All we need to know is that over time, the machine learns to associate significance from functional input, and map such significance to a consistent behavioral (e.g. ‘functional’) output.

Association, and then Finally, Causation

Under the current system as we have described it, we have a machine capable of recognizing subsets of sense impression, and consistently reacting in some manner upon encountering said aforementioned sense impressions. We now define a very important concept, Association, as the following:

Association := Some subset of the integrated sensory field input, operating as a functional input, which may be consistently encountered as a result of some consistent functional input or output of the machine.

For example, consider that we see a bird from behind. By consistent behavioral output, we may also encounter the bird’s beak, either because we move around to get a better look, or perhaps because the bird chose to move around on its own.

But this is what association is in a nutshell. Where we find sense impression ‘a’, we will also find not too far removed sense impression ‘b’, somewhere.

This leads us almost immediately and definitely to our practical definition of machine causality:

Causality := An association of associations; A group of subsets of the integrated sensory field input, recognized as an association, which may be consistently encountered as a result of some consistent set of functional inputs (an association) or set of functional outputs (the resulting functional inputs of which becoming an association), or some combination of the two.

If the hand lets go of the ball, the ball will fall.
First associative group: Hand, Ball, letting go.
Second associative group: Ball, falling through space.

What the machine interprets as a causal connected event, is in reality a very large number of nested sense impressions, any number or combination of which may be utilized as a functional input for any number of the machine’s systems and resultant functional outputs.

Think of the totality of the sense impression of letting go of the ball as a very deeply nested JSON data structure, encoding all manner of aspectual data regarding the situation, from the texture of the ball to it’s weight to the color of the sky on the day of its release, and everything in-between. Likewise, the effect of the cause is another JSON data structure that encodes for all aspective properties of the effect.

Machine understanding of causality, then, is simply an association of a specific path within the first JSON data structure with a well-defined path within a possible future JSON data structure, in this analogy. And if one association may lead to another, we now have a machine capable of forming sequences of causal chains, albeit still unable to form branching causal logical reasoning. But such capabilities are currently outside the scope of our discussion, as we still have to formally construct the special causal sequence that leads to the development of machine sentience.

But we are close. In the next article, we will build upon everything we have built so far, and will finally illustrate the mechanism that leads our machine finally becoming, by prior definition, sentient.

Musings on Rebuilding the American and Global Economy

The blog post provides an overview of the current global economic fragility, highlighting the disconnect between corporate profits and individual wealth. It argues that disillusionment with work leads to civil unrest and addresses the flaws in economic theories that assume selfishness. The post suggests the need for legislative reform to address the economic damage caused since the 1980s.

A topic such as this can hardly be treated exhaustively within the confines of a single blog post. Hence, this first post might be better treated as a general overview that briefly surveys various associated topics, with posts delving into more detail to follow.

The Current State of Decay

There seems to be a general state of economic fragility over the current global economy. Large corporations continue to do business as usual, but there is a growing awareness that more and more citizens of America and other countries around the world have less and less money to fuel corporate growth. Economies overall are still trying to grow their GDP, but it has long been accepted that growth is becoming harder and more difficult over time.

This has led to many individuals becoming disillusioned with the world of work in their home countries. This disillusionment has fueled a rising malaise of despair, meaninglessness, and cynical resentment towards individuals and groups/organizations that are believed to be unfairly benefiting over society as a whole. This in turn creates a whole cascade of effects that generally lead to unfocused and undirected civil unrest and increasing violence rising throughout society as a whole. We need not delve into what happens past this point, as I think most people know exactly where this state of affairs leads.

This article isn’t really about establishing the validity of any resentment on one side of the economic divide over another. Wars are fought and chaos is unleashed since time immemorial over who is to blame. Who is right, and who is wrong. I am more interested in exploring the necessary changes that will be required to bring society back onto a more preferable path, revolution or war in the meantime or not. (Though, admittedly, I would very much prefer to avoid revolution. I don’t have the patience for such things.)

And in any case, the blame can not truly be distributed in one direction.

The sophistication of international trade and manufacturing pipelines is far more advanced and technical than most American citizens, I feel, are capable of even understanding or comprehending. That is to say, there seems to be a disconnect between most American’s intuitive internal beliefs about what is involved in producing the vast majority of modern goods and services, and what is actually involved in supplying them.

Likewise, and I could be displaying a particularly American bias in this following observation, but civic participation and understanding in my country, for the vast majority of American citizens, is simply nonexistent. There is little point to living in a Democracy if, for most individuals, there is no real difference in their lives from living within a Dictatorship. And no, it is NOT the responsibility of any government to ensure the civic education of its citizenry. And even if it was, human nature will ensure that no government would do so unless forced.

So, with these preliminary points out of the way, let us discuss the primary assumptions about the foundational components of American Global Capitalism.

The Axioms of Contemporary Economic and Political Theory

The fundamental assumptions of modern economics may be summed up quite succinctly:

People are selfish. Everyone wants everything for themselves, and they will act to do so.
Resources are essentially zero sum game. One man’s fortune is another man’s impoverishment.

Taken together to the most logical extreme, our current underpinning assumptions about economic functioning would seem to imply that the only way forward is war of all against all, and the economic winners are simply the ones who outmaneuver others according to the rules of the game.

Taken together to the most logical extreme, our current underpinning assumptions about economic functioning would seem to imply that the only way forward is war of all against all, and the economic winners are simply the ones who outmaneuver others according to the rules of the game. – No one particularly important.

We may, find some issues with this basic assumption:

Economic rules are superseded by legal rules, which are in turn are superseded by laws of human nature. If the game becomes rigged in the favor of a class of economic winners, then those winners of the economic dance at the expense of others will face lawsuits to overthrow them. If the legal system is rigged in the favor of those economic winners, then the winners of those lawsuits will face violence.

Of course, any society which comes to this point will have a government that has a monopoly on violence. So the economic winners will be able to use the government to inflict greater violence on the poor than the poor are able to inflict on the rich. At least until the government’s resources run out, which nonetheless can be quite a long time.

Having said that, a system such as that just pointed out is no democracy, but rather is a totalitarian state engaged in a constant war of surveillance and suspicion of its own citizens.

Democracy as a concept was invented at the very least as a preferable alternative to such an environment. In the west, many of us at the very least pay lip service to the idea that living in a Democracy is better than living in a Dictatorship.

Behaviorally, however, Democracies tend to fall into dictatorship when individuals of the upper class come to the belief that they can escape the fate of all prior dictatorships perpetually, as well as when the upper classes enjoy a prolonged period of peace long enough for them to forget how utterly miserable it is and impossible to enjoy their material wealth in opposition of endless hordes of resentful everymen.

Another issue with that basic assumption is that it is treated as an absolute, but it is trivial to point to the existence of attitudes of selflessness and non-zero sum behavior in other individuals, as well as idealism and more noble thinking and behavior amongst our fellow kind. Economic theory has no reply to such aberrations, and its own systems work well enough that the existence of such exceptions doesn’t really bother too many. We still get the benefits of industry without being forced to contend with such tricky philosophical questions.

Though, one might be pressed to wonder why anyone would really endorse such an economic theory as bleak and condemning of humanity’s moral character such as what has been brought forth. It doesn’t take much to realize that the basic foundations of our economic systems are built upon, ultimately, the most cynical and misanthropic view of human nature to date.

Though, one might be pressed to wonder why anyone would really endorse such an economic theory as bleak and condemning of humanity’s moral character such as what has been brought forth. It doesn’t take much to realize that the basic foundations of our economic systems are built upon, ultimately, the most cynical and misanthropic view of human nature to date.

So what is Actually Good about All of this?

As much as I hate to admit it, the benefit of this system seems to be only that, when one looks at the alternative systems available to us, it simply becomes a choice of “Eventual Dictatorship” vs “Dictatorship right now”.

I think that there is one other fundamental assumption about modern economic theory that many of us in the past did subscribe to without realizing it. The assumption is that, “It’s okay to believe everyone is a selfish miscreant, because in doing so, in forcing everyone to fight in the arena of economic competition, all of the competing forces will balance each other out, and we will have a system that perpetually abstains from the descent into tyranny and class warfare.

The problem is that this assumption is not only unfounded. It’s easily observable to be false. Economic competition obviously favors entrenched interests over new competitors. But even if we ignore that point, there is an obvious imbalance in power between producers and consumers. The corporation that builds and supplies all of the things we use has an obvious advantage in market price negotiation.

Business firms have the overwhelming advantage in applying constant upwards price pressure on goods and services. Consumers have only an intermittent and moderate advantage in applying downwards price pressure on the same, and only under great organizational and logistical burden, at that.

Business firms have the overwhelming advantage in applying constant upwards price pressure on goods and services. Consumers have only an intermittent and moderate advantage in applying downwards price pressure on the same, and only under great organizational and logistical burden, at that.

Unfairness, while lessened under this system, is not abolished.

How the System was Cheesed

I could write quite a bit in an effort to make this section more impressive and complex sounding that it really is. But in truth, the current state of the American economy as a result of the cheesing of the system isn’t that difficult to figure out:

Starting in the early 80s, executive leadership of corporations was permitted to merge with oversight committees, the investor class, and advisory boards of the same corporations. The executive CEO of one corporation was permitted to sit on the board of Directors of another Corporation. Alternatively, one individual is permitted to fill multiple advisory slots of an advisory organization, thus having complete control over the corporation. This also allowed executives AND the investor class to benefit financially from running corporations into the ground deliberately.

This is different from before, as no executive would willing run a corporation into the ground before, since they would be punished financially for it.
Corporations replaced pensions and strict pension regulation with 401k plans and very loose regulation on investment of 401k funds, as well as greatly reduced funding matching requirements.
Free trade allows corporations to circumvent labor laws and minimum wage price increases, as well as general labor protections down to the lowest bidder.
Any public goods or infrastructure outside of the most minimal, already established and provided goods and infrastructure was and still is demonized as communist in nature. Any sort of government funded housing, transportation, utilities, healthcare, infrastructure, in excess of what was already provided was cancelled or blocked with accusations of totalitarian government overreach. Many services that ARE currently provided have been reduced or are in the processes of being reduced/eliminated. Accusations of communism and government overreach are no longer as effective as they once were, but there are other approaches being considered.
Legislation originally intended to limit corporate consolidation, public good contamination, and predatory business practices has been largely repealed.

Much can be made of the details, and certainly other policy changes have made things worse, but I think these 5 large policies changes can be directly attributed as causing the large bulk of the economic damage from 1980 through to the present day.

All Right. So that’s what’s Wrong. How do we Fix it?

One possible way of fixing this problem is through getting legislation passed that undoes the previous harms that have occurred. This is admittedly, no easy feat. The process of getting any sort of legislation passed, especially within the current suffocating strictures of our current political environment… is difficult. Effort could be made to more properly describe how difficult, but honestly, hyperbole fails to be a limiting factor in circumstances such as these.

Having said that, perhaps this is a topic for another day, and another blog post that treats this matter in a much more general sense. “How” to get any bill passed in the halls of congress might be quite valuable as a post in itself, to say nothing of a bill that treats the specific items mentioned above.

And so, somewhat anti-climatically, my own musings on this subject are going to come to a close, for now. But this is a topic I plan to return to. That much, is for certain.

Ah Yes… the Return

The last few posts I’ve made on this blog were… they had a style that was almost completely devoid of any personality. The reason for that, I like to think, would be the nature of the subject matter which they covered, namely, my theory of machine sentience. It might have been easy for the astute observer to jump to the conclusion that all of my posts would be written in such crisp, blunt, no-rounded corners style.

Fortunately, that is not actually the case, and I am returning to this blog after a hiatus because I do not intend to let all of my hard work go to waste. It has been quite the ordeal, this website of mine. I’ve been wrangling together all of the necessary technologies and hosting everything completely myself without using any of the hyper modern technologies that most startups utilize these days. Everything has been implemented using pre-node.js technology, I suppose one might say. I have my reasons for doing things like this, but now is not the time to go into that, I suppose.

I think that, for a long time, I struggled with the issues that were inevitably going to crop up: How do I juggle managing content between this website, it’s various components, and at the same time also meeting the requirements of the unholy algorithm that demands endless volumes of content? I struggled for quite a while, searching for a more elegant solution than the one I have decided to implement: Namely, for those of you who might be reading this post on DeviantArt or another platform, just know that this blog post was originally written for and showcased on my website, https://www.druidpier.com.

Yes, that’s right. I’ve decided to simply create content for my blog first, and mirror the content elsewhere on other social media platforms. Not innovative at all, haha, but a solid and reliable method, I suppose.

So Where have I Been?

At the beginning of 2025, I moved into an apartment with a roommate of mine in a different location in the city. One month after doing so, I dislocated my kneecap. Oops. Well, that meant about 1 month of recuperation, and then I had only one month left of living with my roommate before we *both* were going to have to move back in with my parents while we waited for the lease of a 3rd friend to expire. The idea was that afterwards, the three of us( me, my friend, and my other friend) would then move in right and proper together to another apartment and split the rent three ways.

Living with my parents is not as, erm… *distraction free* as I would have liked, and my productivity took a hit. Still, the months rolled by, and finally I moved back out around June 21st… just in time for me to apparently have contracted a… uh… pretty nasty mystery sickness. Respiratory infection. Mild fever. But plenty of fatigue, headaches, sore throat, bloodshot eyes, hacking cough, ear pain, vertigo… blech. Stubbord, too.

And so now I’m waiting for this respiratory condition to clear before I start ramping up my production schedule again. What a year so far, huh?

What have I Been Up to?

My videogame, Duinvoorde, has been slowly making progress in spite of all the other things that have been getting in the way, haha. Since I’m still sick and it hasn’t been even a week since I’ve moved in to the new place, I haven’t quite settled into my routine. Still, I want to start sharing updates regularly on the game’s progress. One thing that was really keeping me from participating a lot on social media et al is that I had a self-imposed moratorium on talking or sharing updates about the game. Considering that for a while, working on the game was the large bulk of what I was up to, that meant that it was really quite hard to have much to talk about.

Of course, that’s only the situation at the personal level. Truth is… DeviantArt, which was my former primary platform, is currently a hollowed out husk of its former self. And the situation doesn’t just apply to DeviantArt, either. It seems like the whole world is collapsing at the seams at times. And here I am, so ill-prepared to weather the torrential storm of chaos that seems to be bearing down upon the western world… I guess trying to grow my follower count has seemed less and less of importance these days…

What is needed, I think, is a better, more organized, more holistic approach to the generation of content. Hence, I’m choosing to go back to posting most of my content on my own platforms first, while worrying about the algorithm has taken backseat in my list of priorities.

It seems like Social Media has become such a cess-pool that it no longer, I think, seems to me to be a question of having to choose between gaming the algorithm vs struggling out on one’s own. It seems that both options these days are so equally abysmal that I might as well take the path that seems more interesting to me.

What’s Next?

Good Question.

In addition to my video game, I’ve got a medley of other projects. But I think it would best if, instead of detailing what they are in every single “welcome back post,” I simply should focus on actually getting stuff from various projects out the door.

So we shall see. 😀

Practical Machine Sentience 3: Truth Values & Noumenality

Having defined machine sentience in practical terms based on integrated sensory systems as a natural starting point, this article expands into machine concepts of truth and noumenality. The machine must recognize clusters of sense data and transform them into uri descriptor-like data structures called noumenal tokens, which is a foundational step leading to causality, deduction, inference, and ultimately, sentience.

In the previous 2 articles, I discussed a basic, foundational definition of machine sentience and elaborated upon how integrated sensory systems allow practical implementations of sentient systems to arise. The definition aimed to provide a hard-boiled, nuts-and-bolts definition with immediate accessibility being of primary concern. I do believe the definition as given succeeded. However, the cost of practicality strips the basic definition of much of the more mystical elements that are commonly associated with sentience. We try to rectify this discrepancy in this article, whereby we reintroduce concepts that traditionally have been considered part & parcel of any sentient organism’s repertoire: An understanding of truth and falsehood, and the beginnings of Noumenality.

What is Truth?

What is Truth?
Pontius Pilate, in questioning of the Nazarene

For our purposes, we define truth as the result of a look-up operation between some formal system and an integrated sensory field device. As discussed in a previous article, a sensory field device is simply a mechanism that reflects some aspect of reality in a uniquely identifying way. The human eye, for example, will ostensibly recreate (more-or-less) the same internal image given reasonably identical light inputs. The same goes for the human auditory system, olfactory system, sense of balance, touch, and so on and so forth. Each of these systems interact with the world in some consistent manner. e.g. identical interactions will produce identical sense impressions upon the human “sense system”.

We choose this definition of truth for the simple reason that integrated sensory field devices can not upon themselves generate their own data. All input into sensory field devices is impressed upon them from en external source beyond the sensing system itself. (For simplicity sake, let us ignore for now the possibility of loop-back inputs, whereby the system generates models that are then fed back into the sensing circuitry) Furthermore, it is currently outside the known laws of physics for anyone to build any sort of sensory field devices that produce materially different sense impressions from identical interactions with physical phenomena.

Or rather, to put it another way: Even though all eyes, ears, noses, cameras, microphones, etc, produce slightly different variations of any given phenomena, all sense devices nevertheless still produce a sense-impression that is identifiably and physically consistent with all other sense impressions of the same phenomena.

We do not have the ability or understanding to create any sensor devices that operates on the same principles as all other similar sensor devices, yet produces materially different sense impressions, and this lack of ability appears to be, at least to the knowledge of all humans, universal.

Hence, in order to avoid delving too deeply into the muck of philosophy, this definition of “truth” will have to suffice.

However…

This definition of truth has some advantages. First, we are trying to build a machine that operates at the same level of human sentience. Hence, absolute rigor is not something that is necessarily needed. Furthermore, much of the sophistication of human behavior is actually predicated on the fact that different people “see” the world slightly differently. Building a system that takes this slight incongruency into consideration allows us to create mitigation algorithms that are inherently much more practical and usable than if we were trying to find and utilize some definition of absolute truth.

Now then. Let us turn from perception to conceptualization.

A Foundational Definition of Noumenality as Association

So far, let us assume that we have constructed the following components of our soon to be sentient machine:

An integrated sensory field device.
A frame and housing for the various components of said integrated sensory field device.
Various other components attached to the housing and frame which are necessary for continuous functioning of the sensory field device, and also necessary for some output operation of the mechanism.
An “output operation” of the mechanism. This must be something which at the very least alters the input from the external world into the sensory field device. For example, movement of the human neck muscles may produce a change in what light may enter through the retina. This produces a change in vision.

Given all of this, the machine must then enter into a process of interacting with the input from the sensory field device. In so doing, various processes are to be undertaken:

Sense Discrimination

Subsets of the sensory field input must be recognized as naturally associating with other subsets of the same sensory field input throughout a given timestamp duration.

Consider, for example, visual input of a bird. No visual input is going to ever provide solely the input data of the bird and nothing else. Instead, there will always be the sense data of the bird embedded within the sense data of some other external environment.

Our machine does not yet know what the concept of a bird is. However, it is capable of, over time, recognizing that certain sense data tends to cluster with other sense data in groups. The color of the beak of a bird, for example, also shows up in the sense data every time the color of, say, the feathers of a bird, is also in view.

This would make sense. After all, every time we look at the same picture of the same bird from the same angle, we should see a similar cluster of sense data in our visual field. This must occur, not just for the sense data of a single bird, but for the sense data of countless other things.

Over time, our machine must learn to recognize what collections of similar sense data clusters exist within its integrated sensory field.

Time Out: A Rationale for Simplification

Our machine is capable of some output which changes its sensory input. Say, motion. e.g. moving it's body will change the orientation of its cameras. In so doing, the machine is co-performing another process which is necessary for boot-strapping the process of deduction. However, we will not be discussing this process quite yet, as we have a complicated enough road ahead of us at the moment. Bare with us, dear reader.

From Association to Noumenation

After our mechanism has created an internal catalog of sense impressions which are recognized as clustering together, the machine is now capable of transforming these sense impression entries into what might be considered “Noumenal Tokens,” or rather, “Object Concepts”. It should be stressed that this is not an automatic process. The actual mechanism for how this occurs, and why, requires more knowledge of the mechanism’s use of its functional output. e.g. The ability of the machine to produce some output which alters the input from the integrated sensory field device.

We will not be discussing this processes in this article, as it would take us quite off the route of the current topic of discussion. For simplicity’s sake, assume that the machine has created a Noumenal Token from the myriad sense impressions in its sense impression catalog. What is the precise form of a Noumenal Token?

Practical Definition of a Noumenal Token

For our purposes, a Noumenal Token is simply some data structure which allows our machine to identify some subset of the integrated sensory field device, along with the state values of the sensory field device within and outside of that subset.

So what do we mean by this? Consider a computer monitor that is showing a picture of an apple on screen. A noumenal token would simply be some URI Descriptor data structure that is capable of rebuilding the apple in some meaningful sense, even when the apple is not actually on the screen. It is important to understand that a Noumenal Token is not simply a label which is assigned to the image data. It actually is a kind of encapsulating data structure that references and contains the image data itself, along with the addresses of the pixels on the screen where it was displayed. It is, essentially, “Sense Data” + “Sense Context”. e.g. What was sensed, and what parts of the sense faculties actually did the sensing, and to what degree, etc.

I so far have made reference to the “sense data” because I wanted to impress upon the reader that the data is actually being recorded and stored somewhere in the mechanism’s own internal memory. However, when it comes to the precise form of said “sense data”, it must be stressed that the actual data format of a noumenal token on disk is going to be very different than a raw recording of sense states from specific sense receptor sites. The “concept” of an apple, internally, is going to end up containing a very compressed representation of the original sense data. Much like with human beings, we do not record perfect sense impressions within ourselves(Generally speaking). And indeed, humans often do not store much more than vague generalities of the sense impressions which ultimately form our conceptualized internal representations of what we behold.

Nonetheless and to Summarize:

Our mechanism has attached to it sensory devices which form unified sense impressions. The machine records a catalog of clumps of sensory data which tends to co-occur. These clumps of sensory data are transformed into Noumenal Tokens via a process which is not automatic, but which nonetheless will be discussed in greater detail in another article.

At last, we are now ready to take our first steps towards a machine conception of causality, which will lead us to deduction, inference, and finally, self-referential conceptualization. e.g. Sentience… the next step of which we shall resume in the next article.

Practical Machine Sentience Part 2: Integrated Sensory Field Design and Implementation

The post discusses the creation of sentient machines, outlining the importance of integrated sensory fields over static data sets for self-awareness. It describes a potential design including visual, auditory, and proprioception sensory devices. The hardware and software specifications are detailed, emphasizing real-time data and interaction for forming a self-referential concept necessary for machine sentience.

ATTENTION: I began this blog post way back when I was intending to develop an actual proof-of-concept along with the publish points of the articles in this series. I have since come to realize that I simply do not have the time, resources, energy, et al, to accomplish such a thing, as I am a broke Mexican who was raised very much in isolation from the greater tech community.

In lieu of re-writing this article from scratch, I have decided merely to edit and continue, but please note that no actual implementation will be developed alongside these articles.

Having said that, I am going to be writing these articles with the intention that any reasonably seasoned developer may understand and verify the concepts these articles introduce with implementations of their own.

In a previous post, I introduced a practical definition of machine sentience, and went over some basic implications of such definition on the implementation of living sentient machines, as well as implications regarding how such machines might fit within the greater legal zeitgeist of humanity. In this post, I will begin outlining the process of creating a practical implementation of a sentient + ancillary functional systems. We start with the design of an integrated sensor field input mechanism.

Why Integrated Sensory Fields Matter

Analogous implementations of integrated sensory fields would correspond to the standard Artificial Intelligence Training Set. ChatGPT and similar systems are trained on passive data sets of data in one or another specific format. The datasets may be considered as halfway removed already from the direct experience of reality that humans undergo. These data sets are unusable for two primary reasons:

Static Data sets are unchanging, which means that there is no need to create a machine that constantly parses new data. Once the dataset has been trained according to whatever algorithm process is used for the AI, the machine is functionally passive, and de facto dead for all practical purposes.
Static Data sets are inherently unable to contain self-referential data. The machine is artificially divorced from the training data, and hence no concept from the data may be formed which refers to the learning entity itself. Hence, it is impossible for a machine created to study a static passive set to construct any conceptualization of the “learner” from within the data itself, which is a critically vital component of any sentience mechanism.

As per the definition given in the previous post, it is necessary for the machine to form a self-concept from the training data. The only training data set capable of providing this is direct sensor information itself.

Organization of an Integrated Sensory Field

A specific sensory device may be defined in 3 components:

A shell, or separation between external sense data and internal sense processing of said data.
An interior component that is capable of taking some sort of structure or organization, and that retains said structure or organization over a meaningful and useful time span.
An aperture, membrane, interface, et al, that permits outside interaction between the interior organizing component in such a way that the organization of the interior records/reflects the outside interaction in a reproducible and uniquely identifying (relatively speaking) manner.

An integrated sensory field, then, may be defined as follows:

1 or more sensory devices which are time/input-synchronized. They each record data such that sensory input on one device can be treated as belonging to the same overall sensory data impression as every other device over uniquely determined units or ranges of time.
The phenomena that each device interacts with is continuous in the mathematical sense, either ideally, or for all practical purposes of the machine. In other words, the phenomena perceived may be partitioned into infinitely many 2-member sets of 1 open, bounded disk (wikipedia link on bounded sets) and 1 unbounded universe (wikipedia link on universal compliments) comprising of the phenomenal field itself.

The 2nd definition only applies in the ideal sense, as any real digital sensory device will have a limited resolution with which to process any field phenomena. Digital Cameras are limited by their megapixel resolution, et al. And analog devices, while capable of perfect field capture, have a practical limit of usability. 35mm analog film captures perfectly continuous data, but we are only able to extract usable continuous data above a certain size threshold on the film.

For the purposes of creating a sentient machine, there is one more additional requirement to our Integrated Sensory Field:

Some SUBSET of the sensory data provided by the integrated sensory field must be vulnerable to mechanism manipulation: Operations carried out by the machine must be capable of affecting uniquely identifiable and reproducible changes within the input data collected from the integrated sensory field.

The reason why this is necessary is because no sensory device can provide direct sense interaction with itself. Sensor components within the shell can not be recorded by sensor components within the shell, which can only record data from outside the shell.

In order to form a self referential concept, then, it is necessary that the system do so through inference. The inferential mechanism is established through a very basic and straightforward logical deduction:

There exists entities within the sensory field which may be considered disparate from the sensory field and other entities which also may be considered disparate from the sensory field.
Certain entities appear to have votive mechanism for action. They interact with and respond to stimuli through some interface.
Some stimuli the entity receives appears to be dependent on some output the entity is capable of producing.
Some stimuli “I receive” appears to be dependent on some output “I produce” (the primary output in the case of humans is muscular contraction).
Some component of the stimuli “I receive” appears to indivisibly and consistently reveal aspects, of which when combined may produce a mental model of an “entity” which:
Exists within the sensory field and yet may be considered disparate from the sensory field and other “entities” recognizable within said field.
Since this component is indivisible from the stimuli received from some output, the source of said output must come from said component.
Produced output is directly actuated. “I” produce output that affects some subset of the sensory field. The response sensory stimuli contains a “component” which must be the source of said affected subset of the sensory field.
Therefore “I” must be that “component” which I recognize.
Hence, “I exist”.
To conclude: “There is a world. I exist within it. Yet I am also apart from it. I live.”

Any system sophisticated enough to to form the above deductive inference is capable of sentience and sentient motivation.

Our Implementation Specification

I have opted to leave this part of the article undeleted. I, sadly, do not have the time nor energy nor financial resources to develop the proof of concept necessary to validate the claims discussed in this series of articles. 

I likely will refer back to this once the series of articles is done in order to create a possible reference implementation of a sentience machine architecture. For now, interested readers should simply understand that moving forward, no "actual" proof-of-concept implementation of a sentient machine will be developed in tandem with this article series.

Let us now proceed towards an actual technical implementation of a real world sensory integrated sensory field device with a specification. We shall keep things simple. Our device shall survey 3 + 1 sense domains:

The visual domain. Two digital cameras shall be mounted on a controlling frame. The cameras shall be independently controllable.
The Auditory domain. Likewise, we shall have two dynamics microphones mounted on a controlling frame.
The Kinematic resistance domain. The frame shall also contain Pule-Width-Modulation servo motors capable of moving limbs of the mechanism. Software shall keep track of the PWM signals and resultant limb orientations from control software signals.

It is possible to calculate the resulting limb configuration from PWM signals sent to the motors under ideal circumstances. Real life mechanical resistances and loads, however, produce errors in actual real world resultant limb configuration. The error between the calculated ideal limb configuration and the actual recorded limb configuration can be used to determine continuous sensory data of the force loads on the various motor components at all time.

This allows us to form a rudimentary proprioception sensory device.

Finally, we have our last sensory domain:

Standard Voltage, Wattage, Thermal, Gyroscope sensors. These components shall be integrated into the system software and API because of their easy availability and ubiquity on most modern chip-sets and computer hardware.

The Software Specification

Now that we have our hardware specification, we need only proceed to the creation of a software and api specification. The specification for our purposes will be accomplished via ARM64 Linux Kernel Modules. We shall need to re-implement specific modules for the sensory devices themselves, and also implement a kernel module to perform inter-device module communication and also generate a user-space accessible memory mapped data region in ram. Finally, we will need a user space daemon to structure, organize, and provide a transparent high level access api to other processes. This will be tackled in a future blog post.

Next Up

The next article in this series will discuss Machine conceptualization, understanding, and manipulation of the concepts of truth, falsehood, and causality, and their relationship and potential implementation within any sentient processing architecture.

Resuming Work on this Website

Just a quick post. Getting shit back together. I was originally thinking that I would space out my more serious technical blog posts, such as my “Machine Sentience” series, between less ground-breaking stuff such as posts about exercise/fitness, etc.

I have come to think that that’s just a really bad idea. I’m really bad at multi-tasking as it is. If I were to try and space things out like that, I would likely find it difficult to complete any one series, let alone all the others I have in my head. So, for this point forward, I will be working on series sequentially, and will only punctuate them with other blog posts as necessary and as the need arises.

Cheers,
DruidPeter 😀

Fundamentals of Exercise & Fitness

The article provides valuable fitness advice for beginners, emphasizing that the primary challenge is building a consistent exercise habit. It suggests a 30-day challenge, exercising every day to establish routine momentum. Strength, aerobic, and flexibility training should not be mixed at this phase; instead, focus on one type during the challenge. The primary goal is establishing consistency rather than quick gains. Proper breathing techniques for strength training are also detailed. In essence, momentum and commitment outshine optimization in early fitness journeys.

The most difficult aspect of physical fitness for those who are not currently in shape is the giant morass of anxieties, mental health issues, fears, excuses, and rationalizations that stop one from starting. This article is for the individual who has a lot of fear and anxiety about moving forward, and perhaps may find themselves overwhelmed or at the mercy of all the noise online about what is the best way to get fit, the benefits of doing so, how to exercise, etc. This is for the ones who want to be in shape, but who may be fighting against a whole range of things that could be hurting their progress.

So let’s start with two simple things: Exercise regimen, and type of exercise.

DISCLAIMER: While I personally take care to provide information that is helpful, correct, and useful, I do so with absolutely no warranty. I am not a licensed medical professional, and nothing I write should be taken as medical advice. You are solely responsible for the actions you take/perform in all things regarding all things. I accept zero legal liability for any decisions you make as a result of reading anything I write. Think before you act. Your decisions are your own.

Exercise Frequency

One common misconception about strength training exercises is that a person has to exercise every day, and that the individual has to be sore every day. This is wrong. Regardless of whether you are training for muscle growth or just to increase practical strength, all the gains you will make after exercise will only occur after exercise. In other words, during the rest period of your training.

Despite this, I actually do not recommend a proper work-rest-retrain cycle if you are just starting out with fitness, or if you have been out of shape for a long time. If you are just starting out on your fitness journey, then I recommend you do a full 1-month challenge where you exercise every single day for 30 days.

At this stage, momentum is far more important than proper technique. Unless you are already highly disciplined, it’s going to be very difficult for you to stick to an exercise schedule long term unless you’ve built your exercise into a habit. In order to do this, you want to reach a point where your body notices not when you exercise, but instead your body notices when you haven’t exercised for the day.

You want to reach a point where your body notices when you haven’t exercised for the day.
DruidPeter

If you don’t do this when you first start out, your body will notice when a day is an exercise day, and you will have to exert energy to overcome that resistance. But if every day is an exercise day, then so long as you don’t stop for the duration of the challenge, your body doesn’t have to notice. If you don’t stop, then there’s no chance you want start-up again. At least for the first 30 days.

Furthermore, you absolutely should not train your muscles till failure at this stage. Proper gains require muscles to be worked till fatigue and failure to see results. But at this point, that is not what you should be trying to do. You’re trying to form a habit, so you need to eliminate resistance as much as you can.

To this end, there are two rules of thumb you can use when starting out:

Stop 5-10 minutes after you break a sweat. If you don’t break a sweat, do more repetitions or decrease the time you wait between sets. If you can’t complete a set of a certain number of repetitions, then do more sets of less repetitions.
If you are sore the day after you exercise, then do half as many total repetitions as you did the last the day. If you are note sore the day after you exercise, then do at least as many repetitions as you did the day before.

Again, when first starting out, your goal should be to stick with the regimen through till the end. No one achieves massive gains in strength or appearance over the span of a single month. This is especially true for those who are out of shape or who are just starting out. So put your thoughts of gains or your physical fitness goals out of your head for now. You have one objective, and one objective only: Reach the finish line.

Only after you’ve successfully exercised every day for 30 days should you start thinking about lowering your frequency of training. But before then, you shouldn’t even be considering it. To that end, I won’t be discussing a more appropriate long-term strength training regimen in this article. We’ll get to the more advanced stuff later. I promise.

The Big 3 Types of Exercise

I am referring, of course, to:

Strength Training – Exercises consisting of sets of repetitions of specific duration per repetition, using weights or just body weight.
Aerobic Training – Exercises that require you to work your lungs and your heart. Running, rope skipping, dancing, etc.
Flexibility Training – Stretching. Not as a warm-up, but as an exercise in itself. Treating stretches as exercises in and of themselves involves a commitment to gradually increase your maximum flexible range of motion for each stretch. It implies over time being able to stretch farther and farther for each specific exercise done, and not simply stretching as a warm-up before resistance or cardio training.

When doing your first 30-day startup challenge, I recommend not trying to do all 3 types of exercise. Do not mix-and-match different types of exercises on different days, either. Rather, do 1 type of training, and only perform that type of training for the duration of the challenge. For the purposes of these challenges, you can and should consider each type of training as a completely separate activity that requires a completely separate habit to be formed.

Hence, only after you have done a separate 30-day challenge for each type of training should you then switch over to a more appropriate training regimen for each type.

Now then, operating under the assumption that strength training will be the first type of exercise that you will be performing, here are some basic fundamental tips regarding that type of exercise. Tips on cardio and/or flexibility training will come in future articles.

Strength Training

Breathe During Exercise

One of the basic principles of any sort of resistance exercise is breath. When you do launch into any sort of exercise, be it a push-up, a sit-up, a pull-up, or something else, you must remember to breathe. If you hold your breath when you start the exercise, your muscles will be starved of oxygen before they even get a chance to do any work.

The boundaries of your breath should be aligned with the boundaries of your repetitions. To give an example, let’s say that you start a push up as you exhale from your last breath. You may do as many push-ups as you wish while you are exhaling. When you begin to inhale, however, you should be either at the top of your next rep, or at the bottom of your current rep. Thus, when you start to go down on your next push-up, you are doing so as you are starting to inhale. Or, as you start to go up after your last push up, you are also starting to inhale.

Your breath should be aligned with the starts and stops of each repetition. This is a good habit to practice when you are exercising.

In Summary

If you’re just starting out or have been out of shape for a while, then momentum is your greatest friend. Being able to build up that momentum is the best way to keep going long term, and going long term is going to get you results that last you the rest of your life.

There are many, many other things that you can/could consider when starting out your fitness regimen. However, if you stress out about optimizing or maximizing results this early in the game, then you’ve already lost.

You are just starting out. There is absolutely no combination of factors or regimen that will make any significant difference from any other. When you are an elite athlete, then small changes make big differences. But you have a long way to go before you reach that bridge. So don’t worry about crossing it just yet.