Tag: philosophy

From Concrescence to Coherence: Whitehead through the Semantic Core (DQM)

Toward a Process-Oriented Architecture of Situated Meaning 1. Introduction The Dynamic Quadranym Model (DQM) project addresses one of the central impasses in artificial intelligence research: the semantic wall—the point at which symbolic or statistical models can manipulate language but cannot inhabit its meaning. While current … Continue reading From Concrescence to Coherence: Whitehead through the Semantic Core (DQM)

The Orienteer and the Literalist: How We Take In Politics (and Why It Matters More Than Facts)

In every political conversation—on the news, in a debate, at the dinner table—you’ll find two kinds of communicators: those who move people, and those who explain things. One reaches into your sense of what matters and redirects it like a compass.The other gives you the … Continue reading The Orienteer and the Literalist: How We Take In Politics (and Why It Matters More Than Facts)

Coherence and Value: Camus, Whitehead, and the DQM

This essay explores the origin of value through three distinct yet converging perspectives: Albert Camus, Alfred North Whitehead, and the Dynamic Quadranym Model (DQM). For Camus, value is claimed in revolt — coherence held by human will against an indifferent universe. For Whitehead, coherence is felt as fundamental to reality itself, intrinsic to each occasion of becoming and preserved in the advance of creativity, even in tragedy. The DQM reframes these insights procedurally, showing coherence as a default, recursive function that grounds both subjective dignity and objective meaning. Together, these perspectives reveal coherence as the generative ground of value — claimed, felt, and expressed.

The Unknowable Engine: Blind Spots as Foundational Features of Situated Cognition

The Unknowable Engine: Blind Spots as Foundational Features of Situated Cognition argues that intelligence does not rest on perfect knowledge but on structural limitations that guarantee perpetual motion. The Dynamic Quadranym Model (DQM) identifies two blind spots of orientation: the epistemological blind spot, rooted in the opacity of perception, and the procedural blind spot, rooted in the opacity of action. These blind spots are not errors but essential design features: they ensure that coherence is never final and that reorientation is always necessary. Distinguishing them from perturbations—situational disruptions that launch new arcs—the essay shows how blind spots are permanent constraints that make process thinking indispensable. Intelligence, in this view, is not the elimination of uncertainty but the art of navigating it, turning the opacity of being into an engine of change.

Orientation Beyond Language and Music: Introducing the DQM’s Semantic Core

Orientation Beyond Language and Music: Introducing the DQM’s Semantic Core” explores how the Dynamic Quadranym Model (DQM) offers a groundbreaking framework for understanding meaning not as fixed content, but as emergent coherence shaped by embodied orientation across systems. Drawing from evolutionary musicology, cognitive science, and AI, the article traces how thinkers like Gary Tomlinson and Elan Barenholtz set the stage for the DQM’s central innovation: the Semantic Core—a procedural engine that tracks, relates, and resolves tensions across linguistic, perceptual, and motor systems. With detailed examples, including the “door” quadranym, and a Q&A that addresses the limitations of traditional models, this piece provides both a conceptual foundation and a practical lens for rethinking orientation, coherence, and intelligent behavior—human or artificial.

Orientation Before Understanding: Rethinking Language, Meaning, and the DQM

“That we cannot understand—or even perceive—anything outside the bounds of our existing language or categories.” This simple yet profound insight reveals one of the most persistent limitations in how we think, speak, and relate. Much of our cognitive process occurs beneath conscious awareness—invisible, unattended, and … Continue reading Orientation Before Understanding: Rethinking Language, Meaning, and the DQM

Linear and Dual Bifurcation

Dual bifurcation not only allows for independent shifts between semantic polarities but also situates an orientation within its context. By enabling two related yet distinct poles to interact dynamically, it maintains both stability and adaptability in the orientation process. Unlike linear bifurcation, which tracks simple, one-dimensional relationships (e.g., more light = less dark), dual bifurcation allows an orientation to emerge from the interaction of two independently adjusting poles, each rooted in a different perspective—expansive (e.g., ambient light), reductive (e.g., dark contrast). This dynamic interplay ensures that the orientation is always situated to the input context.

Situated AI Semantics: The Simple and Powerful DQM

The DQM orientation grammar and scaffolding approach to situated semantics in AI offers a highly effective and elegant framework for understanding how meaning and context can be navigated dynamically. It’s an semantic approach that reflects how humans process the world: dynamically, flexibly, and with a focus on the big picture while attending to immediate details. The overlap between various semantic categories with sensory motor areas suggests that a common mechanism is used by neurons to process action, perception and semantics. Body & environment play important roles in thinking

Orientation Semantics: Layers of Responsiveness

By distinguishing between the dynamic context (external, situational) and the dynamical context (internal, orientation-driven), orientation grammar captures the interplay between meaning and process. This distinction ensures a coherent framework for analyzing how orientation aligns with potential while responding to situational goals and movements. Through this lens, narratives like Jan’s dive reveal how orientation and situation dynamically coalesce to create meaning.

Dynamic Quadranym Model (DQM): Bifurcation

Bifurcation is the dynamic “splitting” of meaning in the Quadranym Model, where expansive (broad exploration) and reductive (focused refinement) orientations diverge along a shared semantic continuum. Like folding a map to reveal two distinct paths, bifurcation creates opposing yet connected perspectives, allowing the AI system to adapt, refine meaning, and navigate complexity. Even at neutral points where exploration and focus balance, bifurcation ensures semantic distinctions remain intact, driving coherence and flexibility.

DQM Summary: Integrating Semantic Structure and Responsiveness for a Situated AI

Summary of original article: The Dynamic Quadranym Model (DQM): Integrating Semantic Structure and Responsiveness for a Situating AI Introduction Language is alive, shifting with context and intention. Yet, AI often treats meaning as static—a pattern to retrieve rather than a process to adapt. Imagine a … Continue reading DQM Summary: Integrating Semantic Structure and Responsiveness for a Situated AI

Understanding the Q Model’s Nested Systems: A Journey Through Scripts

In our exploration of cognitive semantic frameworks, we highlight the significance of harnessing situatedness and its insights and applications for NLP. This approach plays a crucial role in elucidating the complexities of human cognition and communication. The Q model emerges as a sophisticated representation of … Continue reading Understanding the Q Model’s Nested Systems: A Journey Through Scripts

The Q Model: Triadic Semantic Architecture

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A Theoretical Look at the Role of Words for AI

A system summary.

In this framework, we conceptualize the system as analogous to a nervous system, operating through natural language processing. The connections between systems function like neural pathways, facilitating the seamless flow of information and insights. This interconnected structure enables a nuanced understanding of user input, as each system plays a role in interpreting and responding to situational contexts. Serving as the central processor, and guided by Minsky’s six-layer model (The Emotion Machine, 2006), the framework integrates emotional and cognitive dynamics with the situational and dynamical contexts of the Q model.