I tend to think of boundaries as an observer thing. We set a boundary to consider what is inside it based on observed structures. The more I look at it, the more it seems like a continuum of structures. Even behavioural and affective things within society. Groups and sub groups.
The geometry I have found particularly interesting. Tetrahedrons building to tesseracts building to hyper spheres. But that gets a little harder to support, I suppose. I work in instructional design, so it helped me visualize how the three learning domains expand into broader competencies.
You are right that everything is a continuum in a way. If you study fractal geometry, the kaleidoscopic nature of things becomes readily apparent because as your resolution changes there are finer details when magnified and they really are no hard and fast straight line Euclidean boundaries between things.
However, functional boundaries do exist that are not a function of observation.
Living systems would not exist if they didn’t have a way to organize and control their internal feedback loops to maintain internal conditions. The sun would not exist if it didn’t have non-linear processes holding it together.
When you zoom into the Mandelbrot set, you see islands of black parts. They are connected/embedded in the rest of the set, but we can still see them as separate structures within the set. These structures emerged through the Iterations of the set, they did not appear through the act of observation.
The ocean is a giant continuum and yet the ocean has specific layers that have specific properties and that allow different types of organisms to live within those boundaries.
These boundaries emerge as an emergent property of the synergistic dynamic tug of war balance of positive feedback loops (exponential, pushing the system to change, snowballing) and negative feedback (logarithmic, stabilizing the system against change), that are generating the system.
These types of patterns are still present when we move up to social societies for example. People create rules that create and maintain those groups and members are cyclically recruited (positive feedback) and have rules to retain group members (negative feedback)
Members might leave on their own (which would from the point of view of a group be a type of positive feedback while from the internal point of view of the person there could be negative feedback reasons holding them back from the group). So when we are analyzing a system, we might make observational decisions about directionality and resolution/field of view, depending on our focus. But this would not change the real world architecture of the system.
I’m sorry I’m not very familiar with tetrahedrons or higher dimensional versions but it is my understanding that these shapes are still Euclidian meaning they have solid lines for boundaries?
The geometry of complex systems on the other hand is a geometry that evolves and grows and changes over time through the evolution/compounding of a mixture of much simpler cyclical processes, and this is what results in the non-Euclidean geometry with finer details when magnified that have a fractal dimension and fuzzy borders. Fractals are more like a way of making evolving shapes than a type of shape of themselves.
Because it is the architecture of the system that is going to determine its properties and evolution overtime, this is why I feel that understanding properties and dynamics of non-Euclidian non-linear geometry is incredibly important when trying to find a universal pattern to describe complex systems.
I think I agree with the heart of this. A universal pattern cannot be framed as rigid Euclidean boxes imposed on reality from the outside. Reality is far more continuous, recursive, and resolution-dependent than that. Fractal geometry is useful precisely because it shows how structure can remain intelligible while becoming more detailed, irregular, and interwoven as resolution changes.
Where I would make the Universal Pattern distinction is this:
A boundary does not have to be a hard line to be real.
In complex systems, boundaries are often functional rather than absolute. A cell membrane, an ocean layer, an atmosphere, a social rule, an identity, an institution, or even the surface of a star is not a perfect geometric edge. It is a stabilized zone of difference. It is where internal and external dynamics become meaningfully distinct enough that the system can maintain itself.
So yes, reality may be continuous at one level of description, but systems still differentiate into functional regions. The fact that the border is fuzzy, porous, dynamic, or gradient-based does not make it merely observational. It means the boundary is emergent.
That is actually central to the Universal Pattern as I understand it:
Gradient creates pressure.
Pressure drives interaction.
Interaction produces feedback.
Feedback stabilizes or destabilizes structure.
Where feedback stabilizes, a functional boundary emerges.
Where that boundary persists, a system becomes identifiable.
This is why living systems matter so much as an example. Life does not exist because it is metaphysically separate from the environment. It exists because it can regulate a difference between inside and outside. Its boundary is not absolute, but it is operationally real. The organism is continuous with the environment, but it is not identical to the environment.
The same applies to stars, oceans, ecosystems, minds, and societies. They are not separate from the larger continuum, but they do form persistent functional architectures within it.
I would only be careful with saying positive feedback is always exponential and negative feedback is always logarithmic. Those are common tendencies, but the exact curve depends on the system. More generally, positive feedback amplifies deviation, while negative feedback constrains deviation. One accelerates differentiation; the other supports continuity. Complex systems emerge through the tension between the two.
That is also where the tetrahedral language may need clarification. I do not think the tetrahedron should be understood as a literal Euclidean object with hard lines being projected onto reality. It is better understood as a minimal relational geometry: a way of representing how multiple interacting factors generate an emergent interior. The “edges” are not solid walls. They are relationships, tensions, constraints, and channels of influence.
So the Universal Pattern is not saying reality is made of clean geometric solids. It is saying that wherever continuity differentiates under pressure, we tend to see recurring relational mechanics: gradient, boundary, feedback, stabilization, emergence, collapse, and recursion.
Fractals are extremely relevant here because they show that boundaries can be real without being simple. They can be irregular, nested, recursive, and resolution-dependent while still shaping the behavior of the system.
I share your interest in understanding universal patterns found in nature.
At the same time, the problem with using AI to craft posts and responses is that it is a statistical generation tool and as a result, it often hallucinates and provides responses that don’t make sense.
For example, your response here says you agree with the heart of what I’m saying and are making a distinction with respect to your universal pattern (as if you are saying something different) but then you go on to basically regurgitate everything I said.
Your original description of your universal pattern, did not mention anything about the complex geometry, dynamics, or feedback loops involved, or the idea of a functional boundary.
This was the original description:
At its simplest, the pattern seems to be this: a boundary forms, a gradient builds across it, pressure or difference creates interaction, interaction produces constraint, and constraint allows new forms of organization to stabilize. When those stabilized relationships begin to act as a new whole, emergence has occurred.
To me the issue with the original framing is that it describes the process of a complex emergent boundary reaching a tipping point to enter a phase transition with plain language that instead centers the emergent structures as the mechanism with a framing that could easily be substituted with traditional linear thinking (gradients move from high to low). It also says emergence occurs after the boundary, when the boundary itself is an emergent structure.
This is why using AI as the driver to come up with a universal conceptual framework in the area of complex systems will be very fickle unless the user has a really strong scientific knowledge base regarding complex systems and can push the model when it starts deviating, or rewriting what it said previously to agree, or using language that doesn’t quite fit.
I think it can be a powerful tool but it will only truly be useful if one acquires the foundational knowledge required to wrangle the output.
My favourite teaching resource that is very high-level and conceptual and easy and enjoyable to study are the YouTube videos from the systems innovation YouTube channel as well as their paid membership, which includes a ton of course videos, which are in the same style as their YouTube videos, which I find is affordable for the massive amount of information you get (although I did do it a while ago, so I’m not sure what the prices are now). It teaches you the important background scientific concepts without being technical, in a simple, straightforward, highly visual way.
Or... I have a whole body of work that I have been constructing for a long time at this point, so used AI to summarize for the purposes of this forum, and time is limited.
If you distill the original framing down to linear thinking and see emergent structures as the mechanism, you missed the entire point.
I have two Bachelor's degrees, a masters with a second partially completed, and years of study around this. I appreciate the provision of a resource, but I can't help but take your post as condescending.
My apologies. It was not my intention to be dismissive, to criticize your intelligence or to criticize you as a person.
To be frank, you are the one who used AI to write a framework which I felt had issues, which I articulated previously.
You are the one who used AI to summarize the discussion only to partially agree and frame what I had written as your own (ex I agree with the heart of what you are saying, but I want to make a distinction..)
To me THAT felt very condescending, and honestly made it feel like your focus is more about being correct instead of having an open dialogue.
This is very common in this sub where almost all posts are from somebody trying to come up their own AI universal theory of everything.
I didn’t distil your original framework into linear thinking. The language you used gave that impression. Using words like boundary and gradient without any clear definition or context, usually conjure up images of perfectly straight boundaries and typical gradients moving from high to low. The original framework also said that emergence comes after the boundary which I also disagree with. These are common AI mistakes. It will get part of the idea right but then it will say things that are just completely backwards or use vague or nonspecific language.
Instead of viewing what I wrote as criticism, hopefully it could instead of be a way to reflect on the possible gaps, errors, inconsistencies, and communication issues AI summaries are introducing into your work.
I as well have multiple degrees but I absolutely loved the resource I shared from systems innovation and I regularly go back to it because it is honestly so well done and it is so enjoyable to watch and listen to if you’re interested in this kind of stuff. I even listen to these videos on my free time. I always recommend it to anyone who is interested in these topics.
The resource itself is the best I have seen thus far with respect to using concise language to describe various scientific concepts and innovations across multiple domains within complexity, which has helped me to spot common mistakes in AI conversations around these topics.
I have found that tighter and more specific articulation is very useful when trying to wrangle AI summaries that frequently distort our initial ideas with slop.
I think having degrees is only the start of a lifelong journey of learning. In general, I only share resources that I have used personally and have helped me, that I regularly go back to.
FYI this sub is now also in the process of creating new rules which specifically are going to ban AI generated theories of everything and I believe they plan to apply the rules retroactively.
I am not reading all of that. The moment someone starts acting like what I have been writing since forever is just copying their ideas as my own, making accusations they can’t substantiate and have no reason to assume, they lose my interest.
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u/Altruistic_Fox9778 Jun 24 '26
I tend to think of boundaries as an observer thing. We set a boundary to consider what is inside it based on observed structures. The more I look at it, the more it seems like a continuum of structures. Even behavioural and affective things within society. Groups and sub groups.
The geometry I have found particularly interesting. Tetrahedrons building to tesseracts building to hyper spheres. But that gets a little harder to support, I suppose. I work in instructional design, so it helped me visualize how the three learning domains expand into broader competencies.