Information Units

An analysis of the building blocks that power our intuition.

Picture standing in the middle of a bustling marketplace—a swirl of colors, voices, and movement clamoring for your attention. This is life: a constant flood of sights, sounds, and sensations. Our brains collect this stimulus in the form of electrical impulses and organize it in a way that gives us a sense of the world. We categorize experiences based on how they match with the past: consistent patterns are recognized as ‘things’ and are turned into meaning. As a result, the experience of life is not just a blurred blend of sights and sounds but rather perceived as a world of concrete physical objects set in a shared space.

This process is part of default intuition: there is no intentional thought required when generating these basic assumptions about objective reality. I don’t need to figure out every day what food or danger is—my organism has evolved over millions of years to effortlessly recognize the important stimulus and respond to it automatically. Our bodies have survival instincts engraved in our DNA, and our brains continue to shape our understanding of the world as we learn from new experiences.

To understand and dissect this process, we can use models to categorize and organize the factors that constitute different parts of the world. Different models focus on different parts of reality: scientific models like Newtonian Mechanics are used to simplify and predict physical bodies in motion, or social models like Game Theory are used to understand negotiation, cooperation, and economics. 

In Blob Theory, I use the term ‘default intuitive model’ to describe the sorting algorithm that our brain uses to process and understand reality itself. For example, when you see a chair, you don’t need to analyze its parts to recognize it as a chair—your mind automatically identifies its shape, purpose, and context based on prior experience. This mental shortcut allows you to navigate the world efficiently without constant re-evaluation. It generates the sensation of objective reality by assessing the consistency of patterns, and it does so by using building blocks that I call ‘information units’.

Information Units

An information unit is a mental building block used to perceive, categorize, or reason about the world. It is a distinct and stable conceptual "chunk" that can be used to predict or calculate reality.  Their role is to be a reliable, condensed summary of the external world in order to consciously calculate or predict complex truths. The units themselves, once established, go unquestioned: they are effectively the bedrock upon which further conclusions are made.

As a simple example, consider a “chair” as a unit of information.  It exists as a concrete concept in the mind, even if different chairs look different.  A more abstract example could be “1” in binary code, where “1” and “0” are corresponding to the concepts of presence and absence. 

As a more complex example, consider gravity. It’s the word we have for describing the phenomenon of how things are pulled downwards. As a rule of thumb, the fact that ‘things are pulled downwards’ is extremely consistent and broadly applicable. In an industrial context, this simple truth can be used to sort objects with different properties, relying on the heavier bits to separate from the lighter ones. It can be seen in mining, where heavy metals like gold can be separated from lighter silt, or in agriculture, where grains can be sorted depending on how dense they are relative to the less valuable parts of the plant. It doesn’t matter where you are in the world, the law of gravity will behave the same regardless of your specific conditions.

Gravity is a general example because it is very consistent, representing a physical phenomenon with observable effects. In contrast, information units are an abstract concept — they have no physical form but instead measure attributes like permanence, reliability, and truthfulness within mental or conceptual models.

Clean Units

In Blob Theory, information units have degrees of cleanliness, which is a measurement of how stable and precise the unit behaves.  The default intuitive model relies on using units that are as clean as possible, as to provide conscious thought with a simplified foundation.  The measurement of a unit’s cleanliness uses a system that has its origins in Aristotle’s rules for logic and dates back nearly 2500 years. His 'laws of thought' established fundamental principles for reasoning, which directly align with the criteria for clean information units. By defining rules for consistent identity, non-contradiction, and binary existence, Aristotle’s framework mirrors the qualities that make an information unit 'clean' in Blob Theory. These ancient philosophical principles continue to underpin modern science, mathematics, and computational theory. The laws look something like this:

1. The units have consistent identities that do not change over time.
2. The units cannot contradict themselves.
3. The units either exist or don’t exist, there is no middle option.

If you think about something concrete like a chair, it easily satisfies these conditions.  A chair doesn’t randomly transform over time.  It cannot be simultaneously ‘broken’ and ‘not-broken’.  It either exists in a room or it doesn’t, it can’t partially inhabit a space.

The original purpose of these laws is to measure the degree of something’s logic or reason, but in the context of the default intuitive model, I use the laws to refer to the ‘cleanliness’ of a unit of information. A clean unit is one that follows these laws and can be relied upon for further calculation. It is permanent, consistent, regular, and solid. By comparison, a dirty unit either has an inconsistent identity, it contradicts itself, or it only partially exists.  This isn’t to say that a clean unit is objectively superior to a dirty one!  Clean units have their flaws; nevertheless, they are the basis of the default intuitive model’s operating system. 

The limits of cleanliness

When comparing physics with game theory, it’s clear that physics has higher standards of cleanliness. Clean information is associated with having binary thinking and very strict laws, and it assumes that problems have only one correct solution. Binary thinking involves viewing things in absolute terms (such as true or false, present or absent) with no gray area in between. In the real world, when talking about social models like game theory or economics, there is an implicit messiness or inconsistency in human behavior that muddies the waters.

The hard sciences are cleaner but still imperfect. If you consider the earlier example of gravity, at first glance it seems to fit the criteria. It has a consistent identity that doesn’t change over time: it accelerates objects at a rate of 9.8 m/s². It doesn’t contradict itself: solid objects move down, not up. It clearly exists: there is no place on earth where gravity fails to pull.

That being said, Newtonian gravity is just an approximation of reality.  Perfectly clean units don’t truly reflect how the world works. Newton’s description of clean gravity was upset by Einstein’s magnum opus: his general theory of relativity. His model updated our understanding by pointing out the inaccuracy of calling gravity a force and instead showed it as a condition of spacetime. From this perspective, gravity shouldn’t be seen as having binary existence, but rather as a continuous gradient of varying degrees of spacetime’s curvature. This violates the third law of thought, because under a relativistic model, gravity operates as a ‘middle option’ between concrete existence and nonexistence.  Our modern understanding of gravity isn’t classically “clean”, but it is undeniably a true depiction of the way things work. 

This illustrates a key flaw in our default intuitive model, a concept that relies on dividing reality into clear, binary states. We intuit things to either exist or to not exist, it’s necessary for our most basic conceptualizations of the world. Objective reality is rooted in these terms, and our default assumptions are built on this foundational bedrock. Still, there are a plethora of examples of modern science where this simply doesn’t hold. We exist in a relativistic world, where light and gravity are now known to not exist in absolute terms. It extends far beyond just gravity: at every level of reality—physical, conceptual, and mathematical—our pursuit of clean, stable information units has run into unavoidable limits.
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These facts prompt the need to amend the default intuitive model and to propose an alternative to how we perceive objective reality. To do so requires a deeper understanding of how units of information operate, in order to build and describe an alternate model of the way things work.
Next time, we’ll trace the centuries-long pursuit of clean information, starting with Greek syllogisms and the symbolic logic that followed. But this story is not just about refinement, it's about the limits of refinement itself. The clean, bounded units of classical logic have driven science and computation, but they have also boxed us into a worldview of fixed categories. By revisiting the origins of symbolic reasoning, we’ll lay the groundwork for an alternative approach, one that embraces categorylessness, boundarylessness, and the fluid nature of reality, echoing ideas found in Taoism, Zen Buddhism, and the philosophies of the East. If classical logic gave us order, what lies beyond it?