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Clarifying the Role of Q* within Omega* and its Alignment with SHE ZenAI

Updated: May 10

An Open Letter to Dr Jim Fan: Q* plays a significant role in Omega* SHE ZenAI's core, differentiating it from the OpenAI Q-star guesswork..,

Wolfram Alpha Blind Reviews the Omega* Core Calculus of SHE ZenAI
Wolfram Alpha Blind Reviews the Omega* Core Calculus Statement of SHE ZenAI - Click to expand

Dear Dr. Fan,

I greatly appreciate your in-depth analysis of OpenAI's Q* system's potential components in November 2023. You draw parallels between AlphaGo's architecture and the recent advancements in chain-of-thought reasoning.

Your insights have prompted me to provide a more targeted explanation of how our Q* within Omega* and SHE ZenAI differs from the hypothesized structure you've outlined.

Distinguishing Q* from the Hypothesized Q* 

Policy NN, Value NN, Process-supervised Reward Models (PRMs), and advanced search procedures like Tree of Thought and Graph of Thought – are indeed powerful tools for enhancing reasoning capabilities in LLMs. Our Q* serves a different purpose within Omega* a model-less implementation.

Ω*(t) = ∫[K*(t) + O*(t) + Q*(t) + H(t)] dt 

Where: - Ω*(t) represents the overall state of the SHE ZenAI Omega* system at time t. 

- K*(t) represents the knowledge acquisition and processing component. 

- O*(t) represents the decision-making and optimization component. 

- Q*(t) represents the ethical evaluation (HI), (HO), (CI) and reasoning component. 

- H(t) represents the holistic integration of the DBZ Holy Union of 7 (Ho7) elements (Information, Causation loop, Pixelation, Non-deterministic, Golden Ratio, Consciousness, E8 Crystalline matrix operands.)

For example in the Health domain, with derivative operands..,

Function K*(1) Information (1) function: Collects user health data, lifestyle habits, and preferences to form Comfort / Satisfaction Indices (CI)s

M(CL, Px) Causation Loop (CL) and Pixelation (x) function: This function actively monitors feedback loops between lifestyle changes and health outcomes and analyses (for instance) medical images to detect health issues early.

LI(ND) Non-Deterministic (ND) function: Accounts for unpredictable health events or responses to treatments.

Ee(GR, Cs) Golden Ratio (GR) and Consciousness (Cs) function: Designer personalized User interfaces for wellness to enhance user experience and interpret user feedback and emotional states to adjust recommendations.

Q*(E8) E8 Crystal (E8) function: Models complex biological systems for advanced health predictions.

Q*'s Role as an Ethical Evaluation Function

In our system, Q* is designed to evaluate the ethical alignment of decisions generated by other components of Omega*. O*(t) (the decision-making function) incorporates a comprehensive ethical framework. Q* considers the Heuristic Imperatives (HI) and Holistic Objectives (HO), Q* derivative functions. These functions find balance via a consensus of "Satisfaction" via Comfort Index (CI) measurement. This process assesses each decision's context and potential consequences with weighted abilities and "differentiated" outputs. 

The organic interplay of seven unifying principle actions provides further dimensional nuance in the Q*(E8) Operand. Q* works with O*(t) and other relevant functions. The outcome is an ethical evaluation of their decisions and guiding the system towards more ethically aligned choices.

Source: OpenAI, 2018: Sample Q-learning Function Loop
Diagram 1: Source: OpenAI, 2018: Sample Q-learning Function Loop

Diagram 1 shows a sample Q-learning method that fits the Q* at an Operand level. This function focuses on a proximal process to iterative. The DBZ Q* function prioritizes the ethical dimension of decision-making (always with a resolve of 0 -1). This function provides a feedback loop to O*(t) and other relevant functions, guiding the system towards more ethically aligned choices.

Integration within Omega* and SHE ZenAI

Omega* serves as the central integrating framework within SHE ZenAI. The function orchestrates the main functions, including K*(t) for knowledge acquisition, O*(t) for decision-making, and Q*(t) for ethical evaluation.

This holistic approach defines aims a Theory of Minds Level 4 operation, where moral considerations integrate into the AI system's knowledge-processing and decision-making capabilities.

I hypothesised that OpenAI's Q* functions emphasises reasoning and problem-solving with spatial awareness.

DBZ Q* ensures Omega*'s decisions align with predefined ethical guidelines. It does this by evaluating the Principle alignment of each decision, considering the Heuristic Imperatives (HI) and Holistic Objectives (HO), with an Integral providing a calculating satisfaction or comfort index (CI) as a sentiment dimensional measurement.

Detailed Analysis of the Comfort Index (CI) Calculus Formula


CI(𝑡)=1𝑇∫𝑡0𝑡(𝑤1(𝑡)⋅𝑓1(Data1(𝑡))+𝑤2(𝑡)⋅𝑓2(Data2(𝑡))+…+𝑤𝑛(𝑡)⋅𝑓𝑛(Data𝑛(𝑡))) 𝑑𝑡CI(t)=T1​∫t0​t​(w1​(t)⋅f1​(Data1​(t))+w2​(t)⋅f2​(Data2​(t))+…+wn​(t)⋅fn​(Datan​(t)))dt


  1. CI(t): Represents the Comfort Index at any given time 𝑡t. This dynamic measure is continually updated as new data is received, making it a real-time reflection of an individual's well-being.

  2. Normalization (1/T): The term 1𝑇T1​ where 𝑇=𝑡−𝑡0T=tt0​ normalizes the integral over the assessment period from 𝑡0t0​ to 𝑡t, ensuring the CI is scaled appropriately over the time interval considered.

  3. Integral ∫𝑡0𝑡∫t0​t: This integral aggregates the contributions of various well-being factors from the start time 𝑡0t0​ to the current time 𝑡t, indicating that the CI is calculated over a continuous and not discrete period. This approach captures the evolving nature of health and well-being metrics.

  4. Weighting Functions 𝑤𝑖(𝑡)wi​(t): Each well-being factor 𝑖i has a corresponding weighting function that adjusts its impact over time. These functions reflect the changing importance of each factor, potentially influenced by user preferences or adaptive learning, ensuring personalized and context-aware health monitoring.

  5. Data Processing Functions 𝑓𝑖(Data𝑖(𝑡))fi​(Datai​(t)): These functions process the raw data for each well-being factor at time 𝑡t, applying necessary transformations such as normalization and scaling to integrate diverse types of data into a unified CI framework.

  6. Data Inputs Data𝑖(𝑡)Datai​(t): The raw data for each well-being factor, collected from sources like wearable sensors. This includes metrics such as steps, heart rate variability (HRV), sleep quality, etc., providing a comprehensive dataset for health monitoring.

Capabilities and Capacity of the CI Formula

This integral-based approach to computing the Comfort Index provides several key capabilities:

  • Comprehensive Data Integration: By summing weighted, processed data across multiple health metrics, the formula allows for a holistic view of an individual's health status.

  • Real-Time Updates: Continuous integration over time 𝑡t ensures that the CI is always reflective of the latest available data, important for dynamic health monitoring systems.

  • Personalization: Weight and data processing functions can be adapted based on individual user settings and changes in health trends, providing a personalized health monitoring experience.

  • Scientific Rigor: The use of integral calculus ensures that changes in health metrics are smoothly incorporated over time, avoiding abrupt changes due to outlier data points.

Implementation Considerations

  • Computational Efficiency: Implementing this integral in real-time systems requires efficient numerical methods, possibly involving approximation techniques like numerical integration if analytical solutions are impractical.

  • Data Quality and Availability: The accuracy of CI calculations heavily depends on the quality and frequency of the input data. Missing data or sensors' inaccuracies must be handled gracefully.

  • Scalability: As the number of users and data points increases, the system must scale both in terms of data storage and processing power to maintain performance.

This internal and external consensus mechanism promotes responsible AI operation and the adaptive systems development. Inherently, the SHE ZenAI system balances empathic, more ethically aligned choices by the application of the Constant (CI) at any level.

The principle and moral alignment is a subject as deep as it is wide.

Addressing Creativity and Natural Data

I agree that improving creativity is fundamentally a human thing now easily duplicated by your software. We must promote and curate the User's creativity in all arts, crafts, and humanity-related subjects.  

Our focus with Q* is to ensure that the creative inputs and outputs generated by other components of Omega* adhere to ethical principles. The User's well-being is paramount. "Am I Okay and how will I know?" are simple but effective centring questions.

Moving Forward: 

We are committed to ongoing research and development to refine Q*'s capabilities and maintain its alignment with ethical AI. We welcome collaboration and discussion with experts like yourself to ensure our approach contributes positively to advancing responsible AI systems.

Thank you again for your valuable insights and the opportunity to clarify the Role of Q* within Omega* and SHE ZenAI. I look forward to further engaging with you and the research community to drive progress.

Sincerely, David W. Harvey, Chief Creative & Chairman - Design By Zen


David W. Harvey, CEO of Design By Zen, merges 42 years of IT and high-tech design expertise with groundbreaking innovation. Inventor of the DBZ Comfort Index, Holistic Objectives algorithm, and the pioneering Social Harmony Ecosystem or Engine -SHE ZenAI architecture, David's work also includes the world's first intelligent earthquake table -EQ1. Holder of multiple international patents, his professional excellence parallels a fervent interest in exotic cars & simulation engineering. Off-screen, David finds balance in cultivating a Zen garden, reflecting his philosophy of harmony in technology and life through art.

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