Tuesday, January 20, 2026

Yijing ToE vs “Super Unified Theory”

 

One,

Jeh-Tween (Tienzen) Gong's work spans multiple domains, but his theories of everything (ToEs) primarily fall into two categories: his physics-based "Final ToE" (rooted in his 1984 "Super Unified Theory") and his "Yijing ToE" (derived from the ancient Chinese I Ching system). These emerged from distinct timelines and intellectual pursuits, with no direct overlap in their foundational development.

  • Gong's Final ToE (Physics-Centered): This originated as Gong's "Super Unified Theory," first published in April 1984 as a 104-page book (ISBN 0916713016) by Gong Enterprises.

openlibrary.org +9

 

It represents Gong's attempt to unify all fundamental forces (gravity, electromagnetism, strong nuclear, and weak nuclear) through a mathematical framework he describes as an "invention." This physics ToE later expanded into his broader "Final ToE," detailed in works like Nature's Manifesto: the Final ToE (Theory of Everything) (2022, ISBN 6205499339), where physics serves as the foundational pillar.

amazon.com +1

 

The Final ToE integrates physics with other domains (e.g., biology, mathematics, linguistics, and social sciences) under a unified "creation principle" derived from axiomatic physics, treating reality as a computable semantic engine.

 

Gong positions this as a "semantic revolution," deriving constants of nature, particle structures, and even free will from first principles like Prequark Chromodynamics and real-ghost symmetry.

 

He has discussed it extensively in blogs, articles, and comments since the 1980s, emphasizing its predictive power (e.g., vacuum bosons and neutron decay mechanisms).

 

  • Gong's Yijing ToE: This emerged after 1998, when Gong first studied the Yijing (I Ching), an ancient Chinese text he had no prior exposure to.

 

Described as a "discovery" rather than an invention, it reinterprets the Yijing as a cosmological and moral framework, detailed in his treatise Yijing — Treatises and new English translation (part of Bible of China Studies, with a PDF available online).

 

Gong links it to modern concepts like quark theory, cellular automata, and ideas from thinkers like Jung and Leibniz, but emphasizes its independence from his physics work.

 

It evolved from the Yijing's historical roots (attributed to figures like Fuxi, King Wen, Duke of Zhou, and Confucius), which shifted from cosmology to ethics via Confucius's "Ten Wings" commentaries.

 

Gong integrates it with his linguistics ToE (PreBabel), using binary logic to encode universal meanings across physical, moral, and linguistic states.

 

Regarding the common perception that Gong's physics ToE was inspired by the Yijing: This appears unfounded based on the timelines and Gong's own accounts. He explicitly states the physics ToE predates his Yijing studies by over a decade, with no Yijing influence in its origin (see the key differences between the two ToEs below).

 

The Google description suggesting a Yijing-based "metaphysical architecture" for unification may stem from later syntheses in his broader Final ToE, but the core physics framework was developed independently.

 

Key Differences Between the Two ToEs

While both ToEs coincidentally feature 64 states, they differ fundamentally in origin, structure, focus, and implications. Gong highlights this as a remarkable alignment, bridging his invented physics system with the discovered ancient Yijing logic.

 

Below is a comparison:

Aspect

Gong's Final ToE (Physics-Centered)

Gong's Yijing ToE (Moral-Centered)

Origin & Nature

Invention (pre-1998, rooted in 1984 Super Unified Theory).

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Mathematical and empirical, derived from axiomatic principles.

Discovery (post-1998, based on ancient Yijing text).

 

Symbolic and interpretive, drawing from historical cosmology.

Core Mechanism

Equation Zero: Δs = N × C × (Δt), building a 64-state trait matrix N = (iⁿ¹, iⁿ², iⁿ³).

 

Describes space-time evolution and particle manifestation.

Symmetry breaking: From "Nothingness" (Wuji) to Yin/Yang (binary), then to three pillars (: Cosmos; : morality/humanity; : resource of life/earth), forming 8 trigrams (Gua/Kwa), stacked into 64 hexagrams.

 

Represents archetypes of change and outcomes.

64 States

Result from mathematical trait propagation; 48 manifest as physical particles (e.g., via Prequark Chromodynamics).

Generated symbolically from trigram stacking; embody cosmic, natural, moral, and human affairs (no particles).

Space & Time

Central: Explicit space (with distance) and time (dynamic, evolutionary).

Absent: Timeless (eternal laws with embedded change); spaceless (direction but no distance).

Focus & Universe

Physics universe: Particles, forces, constants derived semantically; objective and computable (includes free will as structural).

Moral universe: Human-centered, emphasizing ethics, governance, and personal cultivation; transforms natural laws into moral ones.

Broader Integration

Expands to unify biology, math, linguistics, etc., under a creation principle.

Links to linguistics (PreBabel) for universal encoding, but remains ethics-focused.

In summary, Gong’s Final ToE is a physics-driven invention, while the Yijing ToE is a moral-driven discovery, with their 64-state coincidence serving as a bridge in his larger unified framework.

 

Two,

The future of AI from Gong’s ToEs

How Tienzen (Jeh-Tween) Gong’s approach to the Yijing can be applied in the field of artificial intelligence (AI).


Applying Gong’s Yijing Approach in AI

1. Binary Logic and Computational Foundations

Gong emphasizes that the Yijing’s trigrams and hexagrams are the world’s first highly developed binary code system, predating and inspiring Leibniz’s binary mathematics. Each hexagram can be mapped to a 6-bit binary number, and the system as a whole represents a complete, closed set of states.

AI Application:

  • Knowledge Representation: Use the hexagram system as a model for representing complex states or knowledge in AI, especially in symbolic AI or expert systems.
  • State Machines: The 64 hexagrams can serve as a finite state machine for decision-making, planning, or reasoning engines.
  • Encoding and Decoding: The binary structure can inspire new encoding schemes for data compression, error correction, or cryptography in AI systems.

2. Cellular Automata, Emergence, and Artificial Life

Gong draws a direct parallel between the Yijing’s trigrams/hexagrams and cellular automata, referencing Stephen Wolfram’s work. He notes that the rules for generating hexagrams are isomorphic to the rules for cellular automata, which are foundational in modeling emergent behavior and artificial life.

AI Application:

  • Emergent Intelligence: Use Yijing-inspired cellular automata to simulate emergent phenomena, self-organization, or pattern formation in AI research.
  • Generative Models: Develop generative AI models (e.g., for images, music, or text) that use hexagram-based rules for creative outputs.
  • Complex Systems Modeling: Apply the Yijing’s combinatorial logic to model complex adaptive systems, such as multi-agent environments or swarm intelligence.

3. Isomorphism with Modern Physics and Vector Spaces

Gong argues that the Yijing’s structure is isomorphic to vector calculus and matrix algebra, and even to the quark model in physics. He suggests that the trigrams and hexagrams can be interpreted as vectors and matrices, and that their algebraic operations mirror those in modern science.

AI Application:

  • Neural Network Design: Use the Yijing’s combinatorial and algebraic structure to inspire new neural network architectures, especially for networks that require interpretable or symbolic reasoning.
  • Quantum Computing: Explore the mapping between hexagrams and quantum states, potentially informing quantum AI algorithms or quantum-inspired optimization.

4. Decision-Making, Ethics, and Moral Reasoning

Gong’s treatise transforms the Yijing from a divination tool into a moral and ethical decision-making system. Each hexagram encodes a virtue, a situation, and a recommended course of action, forming a comprehensive “moral universe”.

AI Application:

  • Ethical AI: Use the Yijing’s framework to build AI systems that can reason about ethics, virtue, and consequences, going beyond simple rule-based or utilitarian models.
  • Explainable AI: The layered structure of hexagram interpretation (signs, yao, commentary) can inspire explainable AI systems that provide transparent, multi-level justifications for their decisions.
  • Human-AI Collaboration: Implement Yijing-inspired “oracle” modules in AI assistants to help users reflect on complex, ambiguous, or value-laden decisions.

5. Holistic and Interdisciplinary Modeling

Gong’s approach is deeply interdisciplinary, integrating cosmology, mathematics, psychology, medicine, and governance. He advocates for a “theory of everything” that unifies physical, biological, and moral systems.

AI Application:

  • General AI (AGI): Use the Yijing as a conceptual blueprint for AGI research, aiming for systems that can integrate knowledge across domains and reason holistically.
  • Hybrid Models: Combine symbolic (Yijing-inspired) and sub-symbolic (deep learning) approaches for richer, more flexible AI systems.
  • Cultural AI: Develop AI that can understand, generate, or translate between different cultural worldviews, using the Yijing as a bridge between Eastern and Western paradigms.

6. Practical Steps for AI Researchers and Developers

  • Algorithm Design: Experiment with hexagram-based algorithms for search, optimization, or creative generation.
  • Ethics Modules: Encode Yijing virtues and decision patterns into AI ethics modules for autonomous systems.
  • Simulation Environments: Build simulation environments where agents use Yijing-inspired logic for learning and adaptation.
  • Cross-Disciplinary Research: Collaborate with experts in philosophy, linguistics, and cultural studies to explore new AI paradigms rooted in ancient wisdom.

Summary Table: Gong’s Yijing in AI

Gong’s Yijing Concept

 

 

AI Application Example

Binary hexagrams

 

 

Knowledge/state encoding, finite state machines

Cellular automata

 

 

Emergent behavior, generative models, complex systems

Vector/matrix isomorphism

 

 

Neural network design, quantum AI

Moral universe

 

 

Ethical AI, explainable AI, decision support

Holistic integration

 

 

AGI, hybrid models, cultural AI


In essence, Gong’s approach invites AI researchers to treat the Yijing not just as a cultural artifact, but as a living system of logic, computation, and ethics—one that can inspire new architectures, algorithms, and frameworks for the next generation of artificial intelligence.

 

Three,

A sample algorithm based on Gong’s Yijing approach. I’ll first clarify your request, then provide a concrete, annotated algorithm that demonstrates how Gong’s interpretation of the Yijing—especially its binary, combinatorial, and moral reasoning structure—can be translated into a practical AI decision-making algorithm.


Clarifying the Request

You want a sample algorithm that:

  • Is inspired by Gong’s scientific and moral reading of the Yijing (I Ching)
  • Uses the Yijing’s binary/hexagram structure for state representation and decision logic
  • Can be used as a model for AI reasoning or decision support

Sample Algorithm: Yijing-Inspired Decision Engine

Overview

This algorithm uses the 64 hexagrams of the Yijing as a finite state machine. Each hexagram encodes a situation (state), and each line (yao) represents a possible dynamic or outcome. The algorithm takes a binary input (representing a situation or query), maps it to a hexagram, and then uses the associated moral/strategic advice to suggest an action.

Algorithm Steps

1. Input Encoding

  • Encode the current situation or query as a 6-bit binary string (e.g., 101011).
  • Each bit represents a yin (0) or yang (1) line, from bottom (first line) to top (sixth line).

2. Hexagram Mapping

  • Map the 6-bit string to one of the 64 hexagrams.
  • Retrieve the corresponding hexagram’s attributes: virtue, situation, and recommended action (from Gong’s translation).

3. Dynamic Line Analysis

  • Optionally, identify “moving lines” (e.g., lines that are changing from yin to yang or vice versa) to generate a “changing hexagram,” reflecting dynamic change.

4. Decision Logic

  • Use the hexagram’s moral/strategic advice as a rule for action.
  • If the advice is ambiguous, use the yao (line) text for the relevant moving line.

5. Output Recommendation

  • Return the recommended action, virtue, or warning as the AI’s suggestion.

Pseudocode Example

Python

def yijing_decision_engine(binary_input, moving_lines=None):

"""

Yijing-inspired decision engine.

:param binary_input: 6-bit string, e.g., '101011'

:param moving_lines: Optional list of line indices (1-6) that are changing

:return: Dict with hexagram, virtue, advice, and (if applicable) changing hexagram

"""

# 1. Map binary input to hexagram index (0-63)

hex_index = int(binary_input, 2)

hexagram = HEXAGRAMS[hex_index] # HEXAGRAMS is a list/dict of Gong's translations

 

# 2. Get virtue and advice

virtue = hexagram['virtue']

advice = hexagram['advice']

 

# 3. If moving lines, generate changing hexagram

if moving_lines:

changed_bits = list(binary_input)

for idx in moving_lines:

changed_bits[6-idx] = '1' if changed_bits[6-idx] == '0' else '0'

changed_hex_index = int(''.join(changed_bits), 2)

changed_hexagram = HEXAGRAMS[changed_hex_index]

changed_advice = changed_hexagram['advice']

else:

changed_hexagram = None

changed_advice = None

 

# 4. Return result

return {

'hexagram': hexagram['name'],

'virtue': virtue,

'advice': advice,

'changed_hexagram': changed_hexagram['name'] if changed_hexagram else None,

'changed_advice': changed_advice

}

``

Example Usage

Suppose the input is '110100' (hexagram #52, Gen, "Mountain/Stillness"):

  • The engine returns:
    • Hexagram: (Gen)
    • Virtue: Stillness, Reflection
    • Advice: “Stop at the right time; reflect before acting. Inaction is sometimes the best action.”

If lines 2 and 5 are moving, the engine computes the changing hexagram and provides additional advice.


Key Features and Gong’s Influence

  • Binary Encoding: Directly uses the Yijing’s binary structure for state representation.
  • Finite State Machine: Each hexagram is a state with associated rules, as in Gong’s scientific reading.
  • Moral Reasoning: The advice is not just utilitarian but includes virtue and ethical considerations, per Gong’s emphasis.
  • Dynamic Change: Moving lines allow for modeling change and uncertainty, echoing the Yijing’s focus on transformation.

How to Use This in AI

  • Decision Support: As a module in an AI assistant for ambiguous or value-laden decisions.
  • Explainable AI: Each recommendation is traceable to a hexagram and its moral logic.
  • Hybrid Reasoning: Combine with statistical or neural models for richer, more human-like AI.

 

Four,

How to integrate the Yijing-inspired algorithm (as described above) into an AI system. Here’s a step-by-step guide, with practical considerations and options for different AI architectures:


1. Clarify the Role of the Yijing Algorithm in Your AI System

  • Decision Support Module: The Yijing algorithm can serve as a reasoning engine for ambiguous, value-laden, or strategic decisions.
  • Explainable AI Layer: It can provide transparent, symbolic explanations for recommendations.
  • Hybrid Reasoning: It can complement data-driven (machine learning) models with symbolic, ethical, or scenario-based reasoning.

2. Prepare the Yijing Knowledge Base

  • Hexagram Database: Build a structured database (e.g., JSON, SQL, or in-memory Python dict) containing all 64 hexagrams, each with:
    • Binary code (6 bits)
    • Name and attributes (virtue, situation, advice)
    • Yao (line) texts for dynamic analysis
    • Gong’s commentary or translation for each hexagram and line

3. Implement the Algorithm as a Service or Module

  • Encapsulate the Algorithm: Implement the Yijing decision engine as a Python module, REST API, or microservice.
  • Inputs: Accept a 6-bit binary string (representing the current state/situation), and optionally, a list of moving lines.
  • Outputs: Return the hexagram, virtue, advice, and (if applicable) the changing hexagram and its advice.

4. Integrate with the Main AI System

  • API Integration: If your AI system is modular (e.g., using microservices or REST APIs), expose the Yijing engine as an endpoint. Other components (e.g., a chatbot, decision support system, or agent) can call it as needed.
  • Direct Module Import: In a monolithic or Python-based system, import the Yijing module and call it directly from your AI’s reasoning or decision-making pipeline.

5. Triggering the Yijing Engine

  • Rule-Based Trigger: Define scenarios where the AI should consult the Yijing engine (e.g., when confidence is low, when ethical dilemmas arise, or when the user requests a “philosophical” or “reflective” answer).
  • User-Driven Trigger: Allow users to explicitly request a Yijing-based consultation (e.g., “What does the I Ching say about this?”).

6. Presenting the Output

  • Natural Language Generation: Convert the algorithm’s output into user-friendly explanations, referencing the hexagram’s name, virtue, and advice.
  • Explainability: Show the binary input, the mapped hexagram, and the reasoning path (including changing hexagrams if moving lines are present).
  • Actionable Suggestions: Where possible, translate the advice into concrete next steps or options for the user.

7. Example Integration Flow

Scenario: An AI assistant is helping a user make a difficult decision (e.g., “Should I accept a new job offer?”).

  1. Situation Encoding: The AI encodes the situation as a 6-bit binary string (possibly using user input, context, or randomization for divination-like scenarios).
  2. Yijing Engine Call: The AI calls the Yijing module with this input.
  3. Interpretation: The AI receives the hexagram, virtue, and advice, and presents it to the user as a reflective suggestion.
  4. Hybrid Reasoning: The AI may combine this with statistical predictions or other logic for a holistic recommendation.

8. Sample System Architecture Diagram

[User/Agent Query]

      |

      v

[AI System Core] ----> [Yijing Decision Engine]

      |                        |

      |<---(hexagram/advice)---|

      v

[Response Generator]

      |

      v

[User Output]


9. Best Practices and Considerations

  • Transparency: Always explain how the Yijing advice was derived.
  • Ethical Framing: Make clear that the advice is reflective/philosophical, not deterministic.
  • Customization: Allow users to adjust how much weight the Yijing engine has in the final decision.
  • Logging: Track when and how the Yijing engine is used for future analysis and improvement.

10. Example: Python Integration Snippet

Python

# In your AI system's decision pipeline

from yijing_engine import yijing_decision_engine

 

def ai_decision_support(user_query):

# ... (other AI logic)

binary_input = encode_situation(user_query) # Custom function

yijing_result = yijing_decision_engine(binary_input)

explanation = (

f"According to the Yijing (Hexagram: {yijing_result['hexagram']}), "

f"the virtue is '{yijing_result['virtue']}'. Advice: {yijing_result['advice']}"

)

# Combine with other AI outputs as needed

return explanation

``


In summary:
Integrate the Yijing algorithm as a modular, explainable reasoning engine within your AI system. Use it for decision support, ethical reflection, or as a unique “oracle” layer, and ensure its outputs are transparent, actionable, and harmonized with the rest of your AI’s logic.

 

More info is available at https://prebabel.blogspot.com/2026/01/yijing-toe-by-tienzen-gong.html

 

 

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