DQM: Dynamic Sense

Written by DS
1. The Gap Between Static and Dynamic Understanding

Imagine stepping into a craft studio. The scent of sawdust mingles with lavender, and you’re handed a block of wood and a chisel. Your task? To create a hand-carved box. At first, your cuts are hesitant, clumsy—but then your hands find a rhythm, guided by the grain of the wood. This moment isn’t just about carving—it’s about adapting, learning, and refining as you go.

When we read a story like this, our understanding goes far beyond fixed definitions of words like “chisel” or “box.” Human thought flows like a river—connecting ideas, generalizing experiences, and finding meaning in complexity. To a person, every experience is like something else. It’s this dynamic sense of lived experience that enables us to make sense of the world in real time.

Static language models, by contrast, resemble canals: rigid, efficient, but confined to predefined paths. They process text, but they don’t participate in meaning. This gap—between adaptability and rigidity—is an under-explored frontier of semantic AI research and a vast opportunity for innovation.

Now, imagine a system that doesn’t just process text but dynamically tracks overarching themes, emotional undertones, and evolving contexts in real time. That’s the vision behind the Dynamic Quadranym Model (DQM): a framework designed to give AI the fluidity of thought that humans take for granted.

2. Dynamic Sense: The Equilibrium of Thought

Human thought thrives on balancing opposites—possibility and precision, subjective feelings and objective realities. This dynamic equilibrium is a natural response to change, a way for biological systems to orient themselves in shifting environments. Think of it as a compass, a tool that helps us navigate the evolving landscape of thought conjured by the stories we read.

The quadranym acts as this compass. It’s a semantic framework that bridges fixed meaning with dynamic change. Structured into four facets, it captures how meaning evolves:

  • Open exploration contrasts with narrowing focus.
  • Internal perspectives interact with external realities.

Return to the craft studio. As you carve the wood, expansive exploration drives your creative vision, while reductive precision sharpens each cut. Subjectively, you feel the grain of the wood; objectively, you see the box taking shape. A quadranym maps this interplay, adapting dynamically as the situation unfolds.

This balance isn’t static. It shifts, responds, and evolves in real time, enabling the DQM to replicate the fluidity of human thought within AI.

3. Layers of Thought: Scaling Meaning Dynamically

When carving a hand-crafted box, your mind seamlessly shifts between layers of focus. One moment, you’re carefully guiding the chisel along the grain of the wood, responding to the immediate challenge of avoiding a splinter. The next, you’re envisioning the overall design—how the edges will meet and how the box will look when complete. These layers of thought—balancing big-picture awareness with real-time precision—are a hallmark of human cognition.

Human thought operates hierarchically, effortlessly balancing multiple levels of meaning. While your hands focus on a single detail, your mind maintains an awareness of overarching goals and adapts to unexpected changes. The DQM system models this dynamic layering by structuring meaning into hierarchical orientations:

  • Broad Orientations: Goals like mastering the craft of woodworking provide a steady anchor, connecting each action to a larger purpose.
  • Focused Tasks: Attention narrows to carving specific patterns, translating broad goals into actionable steps.
  • Immediate Actions: Real-time adjustments, like changing the chisel angle to avoid splinters, respond to the fine details of the moment.
  • Adaptive Adjustments: Unforeseen challenges, such as a knot in the wood, require instant recalibration without losing sight of the overall vision.

These layers flow into one another, creating a dynamic system where each action contributes to the broader purpose. The DQM reflects this adaptability, balancing complexity with immediacy and ensuring that both overarching goals and immediate tasks remain aligned. It captures the very essence of human thought: a seamless interplay between vision and action, structure and flexibility.

4. The Power of Sequences: Navigating Orientation

Meaning doesn’t just exist—it unfolds. Like carving a box, every act of understanding is a journey between where you are and where you want to be. The DQM doesn’t just observe these journeys; it maps how they happen, step by step.

Imagine the moment you press the chisel to the wood:

  • The actual state is the act of carving—the feel of the grain under your hand, the resistance of the material.
  • The potential state is the box you envision—the smooth surface, the intricate patterns you hope to create.

These aren’t just steps; they are transitions. The DQM understands that meaning evolves not from isolated states but from the interplay between them:

  • Potential becomes Actual: Your expansive imagination (what could be) sharpens into reductive precision (what is).
  • Actual leads to Potential: Each cut creates new possibilities, setting the stage for what comes next.

Orientation as a Process, Purpose as a Goal

Here’s the key: orientation starts as a process, a flow without fixed direction. It’s the moment when you pick up the chisel—not yet knowing how the grain will guide you. Purpose, by contrast, is what emerges through interaction. The block of wood becomes meaningful only when it aligns with your goal: carving the box.

The DQM represents this duality through two core elements:

  • Modes: The expansive search for possibilities (Potential) versus the reductive focus on specifics (Actual).
  • States: The subjective sense of being immersed in the process (Actual) versus the objective goal driving action forward (Potential).

How Sequences Shape Understanding:

Human thought thrives on sequences. Each state flows into the next, creating a rhythm of action and reflection:

  1. Expansive (Potential): You imagine the design, letting your mind wander.
  2. Reductive (Actual): You focus on the details, bringing the design to life.

This interplay between modes and states isn’t arbitrary—it’s how humans naturally make sense of the world. The DQM captures this flow, enabling AI to replicate the same intuitive shifts.

For instance:

  • States: [Actual (Carving) → Potential (Box)].
  • Modes: [Potential (Exploration) → Actual (Precision)].

These sequences don’t just tell a story; they build meaning. By tracking how actual states transition into potential outcomes, the DQM ensures that AI can adapt to the evolving nature of real-world tasks.

The Beauty of Sequences in AI:

This isn’t just theory—it’s the foundation for dynamic adaptability. In the craft studio, sequences would help AI:

  • Identify the initial orientation (the feel of the wood).
  • Transition to the potential goal (creating the box).
  • Adjust dynamically as the situation changes (avoiding a knot in the grain).

The result is an AI that doesn’t just respond to static inputs but evolves alongside the task, capturing the fluidity of human thought.

5. Tools for Dynamic Understanding: The Scaffold Matrix

Like the ocean shifts and bends, adapting to meaning is a current—an invisible flow beneath the surface of our thoughts. Sometimes the current is calm, carrying our focus gently toward understanding. Other times, it surges and swirls, demanding effort to navigate and reposition. Orientation within the Dynamic Quadranym Model (DQM) mirrors this current: not the meaning itself, but the force that targets meaning, guiding the process of engagement and interpretation.

Each layer of the DQM represents a distinct level of orientation, all operating simultaneously. These layers—general goals, relevant tasks, immediate actions, and dynamic adjustments—flow together, creating a seamless system. To manage this interplay effectively, the model introduces a “zoom lens” to focus on each level as needed. This tool, the Scaffold Matrix (SM), allows the system to adjust its focus dynamically across layers of meaning.

The Scaffold Matrix: A Zoom Lens for Meaning:

The SM enables the DQM to track the flow of meaning across layers, adapting to both the broad strokes and the finer details of a situation. In the woodworking class, the SM operates like this:

  • Zooming Out: The SM captures the overarching goal—transforming a block of wood into a hand-carved box.
  • Zooming In: It fine-tunes focus to the precise angle and pressure of the chisel.

By seamlessly shifting focus, the SM ensures that each layer contributes to the larger process without losing its unique role. When the wood reveals an unexpected knot, the SM recalibrates the system. The overarching goal remains intact, but the immediate approach adapts to the new challenge.

Complementing the SM: Phrase Templates (PTs)

To further refine this process, the DQM employs Phrase Templates (PTs). These templates break down text into quadranyms, structuring meaning into manageable components. For instance:

“For the [state of potential] in [topic], [expansive mode] depends on [reductive mode] to achieve [state of actual].”

Together, the SM and PTs create a cohesive system, capable of balancing complexity with adaptability. By maintaining a dynamic interplay between layers, the DQM ensures that AI can respond with the same fluidity and precision as human thought—keeping the broader goal in mind while navigating the intricacies of the moment.

6. Folding and Shifting: The Dynamics of Orientation

Orientation isn’t static; it’s alive, flowing like the currents of an ocean. At times it folds inward, concentrating on a single point, while at others it shifts outward, opening to new possibilities. This constant interplay between expansive exploration and reductive focus is the heartbeat of the Dynamic Quadranym Model (DQM).

When carving a wooden box, for instance, your orientation shifts moment by moment. You might start with a broad sense of what the box should look like, an expansive view of its potential. As you carve, your focus narrows to the immediate cut, a reductive action grounded in precision. Once that cut is complete, your perspective shifts again, reconnecting with the broader design before the next focused action. This folding and shifting is how meaning evolves—fluidly adapting to context.

The Role of Neutral Points:

To manage these transitions, the DQM introduces neutral points—moments of balance where expansive and reductive forces meet. Think of these as waypoints in the flow of orientation, stabilizing the process before it shifts direction.

Neutral points allow the system to:

  • Pause and recalibrate without losing momentum.
  • Balance broad possibilities with specific actions.
  • Maintain alignment across layers of meaning.

For example, in the woodworking class, a neutral point might occur when you pause to examine the progress of your carving. This moment isn’t about action but about reflection—a brief equilibrium that informs your next move.

Bifurcation: The Pivot Between States:

Every transition in the DQM involves a bifurcation—a split where the system pivots between opposites. When you carve the box, bifurcation occurs as you move from imagining the design (expansive) to executing a precise cut (reductive). These splits aren’t disruptions; they’re opportunities for refinement, allowing the system to recalibrate and align with the evolving situation.

Bifurcation in the DQM operates on two levels:

  1. Semantic Shifts: Moving between states like [actual → potential] or [subjective → objective].
  2. Procedural Adjustments: Recalibrating modes like Potential → Actual or Expansive → Reductive.

Orientation as a Living Process:

By integrating neutral points and bifurcation into its framework, the DQM transforms orientation into a living process—responsive, adaptable, and dynamic. Each shift is purposeful, guiding the system toward clarity without rigidly defining what that clarity must look like.

Whether it’s carving a wooden box, navigating a conversation, or interpreting a story, the DQM’s folding and shifting dynamics enable it to engage with complexity in a way that feels natural and intuitive. This is more than just a model for meaning—it’s a blueprint for adaptability itself.

The Quadranym: Modes & States

create-a-highly-detailed-high-resolution-image-capturing-a-craft-studio

In the Dynamic Quadranym Model (DQM), the concepts of modes and states are closely intertwined but serve distinct roles in representing how meaning evolves and adapts over time.

Modes:

Modes represent the directional processes or approaches that guide how meaning is approached in a dynamic context. They capture the flow between expansive and reductive thinking, which guide the system’s exploration of possibilities versus its focus on specific details.

  • Expansive Mode (Potential): This mode is about exploring possibilities, envisioning outcomes, and generating ideas. It’s the phase of broad thinking, where you imagine what could be, such as the design of the box in the woodworking example.
  • Reductive Mode (Actual): This mode represents focusing on specifics, narrowing in on what’s immediately required to achieve the goal. It’s about precision, focusing attention on the immediate task at hand, like carving specific details of the box.

Modes are action-oriented, representing the overarching approaches (expansion vs. reduction) that influence how meaning is constructed in real-time.

States:

States, on the other hand, reflect the current condition or mental state a person or system is in at any given moment. States are more about the subjective experience (actual) or the objective goal (potential) at a specific point in the process.

  • Actual State: This is the current experience of being immersed in the process. It’s the real-time interaction with the world—like the tactile experience of carving the wood or making precise movements.
  • Potential State: This is the future-oriented goal or vision of what is to be achieved. It’s the idea or goal that guides the current actions, like the envisioned final design of the box that directs your carving efforts.

States are about where the system is at any given moment—either in the subjective (actual) or objective (potential) realms—and are more about being than about doing.

Key Differences:

  1. Focus:
    • Modes focus on how we approach the task (broad vs. specific).
    • States focus on where we are in the process (actual vs. potential).
  2. Temporal Aspect:
    • Modes are more about the processes that guide action in real-time, switching between expansive and reductive thinking.
    • States are more about the condition or position the system is in, either immersed in the present (actual) or oriented towards the future (potential).
  3. Nature:
    • Modes are directional and related to how meaning evolves (searching vs. focusing).
    • States are descriptive of the present condition of understanding or action (subjective experience vs. goal-driven).

Example in the Woodworking Scenario:

  • Mode: As you carve, you might switch between the expansive mode (imagining the whole box, letting your ideas flow) and the reductive mode (focusing on the specifics of carving the next detail).
  • State: The actual state is when you’re physically carving and experiencing the present task. The potential state is the envisioned completed box, which guides your actions.

In summary, modes are the directional forces that shape how meaning is explored (expansive vs. reductive), while states describe where the system is in its flow of meaning (subjective experience vs. future-oriented goal).