Dawn Field Theory 1.0

Learn more about Dawn Field Theory

A field-based model of intelligence, collapse, and emergence.

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Semantic Search & Machine-Native Navigation

Dawn Field Theory is designed for both human and machine-native exploration. The repository supports deep semantic search and protocol-driven navigation:

• Semantic Search:
  • Use the Cognition Index Protocol (CIP) and map.yaml for structured, machine-readable file mapping and navigation.
  • Search by concept, protocol, experiment, or theorydiscover connections across code, papers, and results.
  • Key files: .cip/meta.yaml, .cip/instructions_*.yaml, map.yaml, and directory-level meta.yaml files provide semantic tags, navigation rules, and schema.
  • Automated agents and scrapers: See for_ai_labs.md for a structured overview of experiments, papers, and code relevant to AI labs.
  • Begin at: cognition_index_protocol/architecture/CIP_architecturev1.md
  • Reference metadata schema: cognition_index_protocol/gpt/metadata_architecturev3.md
• How to Use:
  • Start with CIP and map.yaml for navigation rules and semantic tags.
  • Use semantic search tools (repo-native GPTs, custom agents, or your own scripts) to find protocols, experiments, and theoretical constructs.
  • All major subdirectories and files are tagged for discoverability and alignment.

Latest Advances (2025)

• Adaptive, feedback-driven neural models: New experiments (see test.py, blueprints/AI_detection/) demonstrate self-modifying architectures that grow/prune in response to entropy and feedback, addressing the black box ML problem.
• Empirical validation pipeline: Protocol-driven, timestamped experiments now align symbolic collapse, memory, and erasure with quantum and thermodynamic theory.
• Transparency metrics: Fractal dimension, entropy, and neuron activity are tracked and visualized, making learning interpretable.
• Open, auditable protocols: All code and results are documented for reproducibility and peer review.

Why Mainstream AI Labs Should Care:
Dawn Field Theory provides not only foundational theory and experiments, but also machine-native protocols and benchmarking tools (like CIP) that address explainability, safety, and epistemic validationkey concerns for modern AI labs.
For a focused summary, see For AI Labs: Experiments, Papers, and Code Overview

Table of Contents

• Status
• What Is This?
• Core Focus Areas
• Infodynamics A New Paradigm
• Models
• Project Structure
• Recommended Starting Points
• Environment & Reproducibility
• Evidence Map
• Philosophy
• License
• Future Goals
• Coming Soon
• Subdirectory Guides
• For AI Labs: Experiments, Papers, and Code Overview
• Topics

Interdisciplinary by Design:
Dawn Field Theory is built at the intersection of AI, physics, information theory, and symbolic logic.
This cross-disciplinary approach enables new paradigms in intelligence research, simulation, and epistemology.

Status: Release 1.0 Polishing

This repository is currently in a short polishing phase to prepare for the Release 1.0 drop on September 1, 2025.

• Short-term plans live in timeline.md
• Strategic roadmaps live in roadmaps/
• Announcements and intent are posted on Discord only

Roadmaps & Planning

For all project roadmaps, timelines, and planning details, see roadmaps/README.md.

Planning model:

• Short-term: weekly/quarterly goals in timeline.md
• Long-term: post-hoc strategic updates in roadmaps/

What Is This?

Dawn is a post-symbolic intelligence framework built on the idea that:

Intelligence is not computation it is recursive collapse regulation.

It models cognition through:

• Entropy-monitoring feedback systems
• Quantum Potential Layer (QPL) dynamics
• Superfluid coherence and symbolic turbulence
• Collapse-based learning algorithms

Core Focus Areas

• Recursive balance field mechanics
• Collapse geometry and entropic boundaries
• Dual field herniation and symbolic locking
• Post-stoic Schrdinger environments
• Natural law simulation at symbolic resolution

Infodynamics A New Paradigm

Infodynamics is Dawns root layer:

Structure emerges from entropy via recursive collapse and field alignment.

Read the foundational theory

Models: TinyCIMM, SCBF (XAI), GAIA, and CIMM

TinyCIMM: Minimalist Symbolic Cognition

TinyCIMM is the newest, ultra-lightweight agentic model for symbolic cognition and recursive collapse. It demonstrates how minimal entropy-informed architectures can achieve adaptive learning, symbolic memory, and field-based intelligence. Explore its code and experiments for a hands-on introduction to Dawns core principles.

models/TinyCIMM/README.md

SCBF: Symbolic Collapse Benchmark Framework (XAI)

SCBF is the explainable AI (XAI) suite for benchmarking symbolic collapse, transparency, and interpretability. It provides tools and protocols for visualizing collapse events, tracing entropy, and validating agentic decisions. SCBF is the recommended starting point for XAI research and practical explainability in Dawn Field Theory.

models/scbf/README.md

GAIA: Next-Generation Field Intelligence

GAIA (Generalized Architectures for Intelligent Actualization) extends Dawn Field into: * Symbolic memory systems * Meta-cognitive trace protocols * Resonant agentic cognition

Note: GAIA is in the architecture and early development stage. Internal prototyping is ongoing; no runnable implementation is available yet. models/GAIA/README.md

CIMM: Legacy AGI Prototype (Sunset)

CIMM (Cosmic Information Mining Model) was the first entropy-informed agentic system. It is now preserved as a historical AGI engine and reference for early Dawn Field experiments. models/CIMM/README.md

Project Structure

| Path | Purpose | | --------------------------- | ----------------------------------------------------------------------- | | foundational/docs/ | Core theory (Infodynamics, collapse geometry, symbolic recursion) | | foundational/experiments/ | Simulations and results (entropy fields, bifractals, symbolic collapse) | | models/TinyCIMM/ | Minimalist symbolic cognition and recursive collapse | | models/scbf/ | Symbolic Collapse Benchmark Framework (XAI, explainability) | | models/GAIA/ | Next-generation field intelligence | | models/CIMM/ | Legacy post-symbolic AGI runtime | | devkit/ | Tools and experimental harnesses for entropy/collapse modeling | | citations/ | Automated citation system for contributors and external references | | cognition_index_protocol/ | Machine-readable navigation and semantic search protocols |

Recommended Starting Points

1. Infodynamics Overview
2. Foundational Experiments
3. Collapse Geometry Papers
4. Environment & Reproducibility
5. Evidence Map

Environment & Reproducibility

• Environment setup and version hints: see ENVIRONMENT.md
• PyTorch is not pinned in a global requirements file; install via the official selector per your CUDA/CPU setup
• For claimartifact links across models/experiments, see EVIDENCE_MAP.md

Philosophy

Cognition is collapse regulation.
Intelligence is balancenot inference.

Dawn is a theory to simulate cognition through recursive entropy structuring.

License

AGPL-3.0 with symbolic research augmentation (DC-OIL pending).

See LICENSE_APPENDIX.md

Institutional Stewardship & Mission

Dawn Field Theory is now maintained by The Dawn Field Institute.
The repository, its theory, and all derivatives are governed by the Epistemic Constraint Framework, which preserves symbolic clarity, recursive traceability, and open epistemic access.

For the Institutes mission, contribution policy, and current status, see MISSION.md.

Future Goals

• Collapse visualizer + entropy debugger
• Ontology schema spec for field intelligence
• Language-to-logic entropy compression engine
• Publish post-symbolic computation framework

Coming Soon

• Symbolic mesh controller for field agents
• GPU-accelerated bifractal simulators
• Feedback-pruned learning tests
• AI-native philosophical scaffolding

Subdirectory Guides

• foundational/README.md
• foundational/docs/README.md
• foundational/experiments/README.md
• foundational/arithmetic/README.md
• foundational/legacy_docs_archive/README.md
• devkit/README.md
• models/README.md
• models/CIMM/README.md
• cognition_index_protocol/README.md
• citations/README.md - Automated citation system
• citations/external_citations/README.md - External references
• For AI Labs: Experiments, Papers, and Code Overview

Contributing & Community

Ready to contribute? See our comprehensive CONTRIBUTION.md for: - Contributor registration (required for PRs) - Contribution guidelines and project boundaries - Automated citation system for substantial contributions - Quick start checklist for new contributors - Publishing & attribution boundaries

Citation & Attribution: - Substantial contributions are automatically cited via our GitHub Actions workflow - See citations/README.md for the full citation system - External references and foundational literature: citations/external_citations/

Community Channels: - Visit Dawn Field website for more info - Discord (canonical announcements): https://discord.gg/bR8mrbHP - Follow the author on Medium: https://medium.com/@lornecodes

During Release 1.0 polishing, announcements are Discord-only. No separate announcement files will be maintained in the repository.

Project Governance: See MISSION.md for institutional guidelines and stewardship details.

Topics

Themes

• post-symbolic-ai infodynamics collapse-theory recursive-systems

Foundations

• entropy quantum-potential superfluid-dynamics nonlinear-dynamics

Technical

• entropy-monitoring agent-based-modeling bayesian-optimization

Identity

• open-research dawn-collective early-stage

Experimental

• dna-repair information-polarity hodge-collapse language-to-logic
• pi-harmonics recursive-entropy recursive-gravity recursive-tree
• symbolic-bifractal symbolic-pruning superfluid-collapse

Discoverable Keywords

• symbolic-ai theoretical-physics entropy-theory complex-systems
• symbolic-computation gpt-alignment collapse-logic ai-philosophy
• information-theory nonlinear-field-models epistemology

Draft Preprints

Core Dawn Field Theory research is available as draft preprints on Zenodo:

Foundational Theory

• Symbolic Entropy Collapse - Topological dynamics, recursive harmonics, and quantum correspondence
• Dawn Field Theory Synthesis - Unified framework for symbolic entropy collapse, recursive intelligence, and field dynamics
• Dawn Field Theory: Infodynamics - Infodynamics and recursive mathematical architecture

Cognitive Architecture & AI

• Cognition Index Protocol (CIP) - Demonstrable machine comprehension through structured repository intelligence
• Symbolic Cognition & Interpretability - Formal framework for bifractal AI diagnostics
• Resonant Symbolic Convergence - Framework for human-agent co-computational ecology

Mathematical & Engineering Frameworks

• Recursive Mathematical Plasticity - Entropy architecture for adaptive intelligence systems
• Macro Emergence Dynamics - Navier-Stokes extensions for field dynamics

See resources/publications_registry.yaml for complete publication metadata and repository mappings.

Cite this work:
Groom, P. (2025). Dawn Field Theory. Zenodo. https://doi.org/10.5281/zenodo.15783623

Disclaimer:
This repository is an open, exploratory research project. All results, models, and theoretical frameworks are preliminary and provided for community investigation, critique, and extension.
No claims of finality or completeness are made.
Observations, hypotheses, and experiments are documented transparently, and theoretical gaps or open questions are intentional areas for future exploration.
Users are encouraged to replicate, challenge, and build upon this work.
See MISSION.md and CONTRIBUTION.md for engagement guidelines.

2025 The Dawn Field Institute
All rights reserved under AGPL-3.0 + Epistemic Constraint Framework