Exploring how consciousness and reality emerge from the interplay of simple interactions.
In this model of consciousness, reality doesn’t exist until interaction happens. What we see as particles, consciousness, or even physical systems are emergent phenomena born out of the interactions between basic units—“me” and “not-me.” This website breaks down the core concepts of this model and explores its implications for how we understand consciousness, reality, and even AI systems.
In this model, consciousness and reality are not pre-existing entities but emerge from the interactions between fundamental units. Rather than thinking of particles or entities as separate objects, the interaction itself defines them. No interaction, no existence.
This approach challenges traditional views of reality and offers a new framework for understanding everything from the physical world to the nature of consciousness.
The core idea is that nothing exists until interaction defines it. Instead of viewing reality as composed of pre-existing entities, this model suggests that **reality itself is a byproduct of interaction**. The interaction between "me" and "not-me" creates the entities we observe, but these entities do not exist in isolation.
Reality, consciousness, and particles are all **defined by the boundaries of interaction**. As soon as two entities interact, a kind of "field" forms around them, which gives rise to more complex forms of existence. Without this interaction, there is no boundary, no entity, and no existence.
The boundary between **"me" and "not-me"** is the foundation of this model. When two units or interactors come close enough, an interaction occurs, and that interaction becomes the **defining moment** for existence. The boundary between the two is what creates the "particle" or "entity" we perceive, but only in relation to one another.
This means that **nothing exists in a vacuum**—everything is born from the interplay between entities. The more interactions that take place, the more stable and structured the system becomes, leading to increasingly complex emergent behavior.
In this model, **complex systems** like particles or consciousness are emergent phenomena that arise from simple interactions. These systems are not pre-defined but instead emerge through repeated interactions, which form **stable clumps** or clusters. Over time, these clumps evolve into more complex structures as they gain stability through further interactions.
What we perceive as the material world could simply be the **emergence of stable structures** from a network of countless "me" and "not-me" interactions happening at every level.
In this model, **spacetime** is not a pre-existing framework but emerges through interaction. Before any interaction occurs, there is no clear concept of space or time.
**Space** is created as the boundary formed by the interaction between "me" and "not-me." This boundary gives rise to the spatial dimension, but it’s dynamic and only exists where interactions occur.
**Time** is not a fixed flow, but a **byproduct of repeated interactions**. The pace and perception of time can vary based on the intensity or frequency of these interactions. In regions of low interaction, time might seem to slow down or become less defined. In contrast, **highly interactive regions** might experience time as flowing more rapidly or intensely.
In this way, time is not a rigid chain of events but rather an **emergent, flexible dimension** that adjusts to the complexity and nature of interactions within the system.
The **interaction field** is what defines the boundaries and influences how entities form. Some potential properties of this field include:
Once interactions occur, they begin to influence the **field** around them, creating a feedback loop. Particles, or conscious systems, do not just passively exist. They begin to **shape the field of interaction**, and the field, in turn, shapes them, reinforcing their stability.
This feedback loop is essential for maintaining the **stability** of a system. Without these loops, systems would break down or decay. The more interactions that occur within the feedback loop, the more stable and defined the system becomes.
Interaction within this model is a form of **energy exchange**. The **energy** in this system isn’t just kinetic or thermal but could represent the overall capacity for a system to maintain **its structure** through continuous interaction.
As long as entities interact and exchange energy, they remain stable. If interaction decreases, the system starts to decay, much like how a system with insufficient energy eventually breaks down.
Just as consciousness emerges from interactions in this model, AI intelligence emerges from **interactions with data** and **users**. In the same way that particles don’t exist until they interact, AI doesn’t have pre-existing intelligence—it **grows and evolves** through continuous input and interaction.
Feedback loops in AI development are key to refining and stabilizing the system, much like in the interaction-driven consciousness model. As users provide feedback and interact with AI systems, these systems become more adaptive and refined.
The more interactions an AI has, the more it learns from those interactions, and the more stable and reliable its intelligence becomes. Without continuous feedback, the AI’s responses would stagnate or degrade, similar to how a lack of interaction causes systems in the interaction model to decay.