Project summary

This project proposes a radical departure from digital matrix computation toward Analog Wave Interference as the foundation for Artificial General Intelligence (AGI). By modeling neurons as entities interacting through constructive and destructive interference—rather than discrete numerical weights—this research aims to create an AGI that is natively energy-efficient, inherently interpretable (per-neuron), and capable of continuous biological learning. Below are my current theories

Definitions and Core Postulates

Definition: The Entity An "Entity" is any concept, object, or phenomenon that can be represented through symbols/language or directly experienced.

Theory 1: Universal Uniqueness, Every entity in existence is intrinsically unique. This uniqueness serves as the fundamental basis for identity and differentiation.

Theory 2: Infinite Dimensionality, True uniqueness implies that every entity possesses an unlimited number of dimensions. To be truly distinct from all other things, an entity must have infinite depth that cannot be fully captured by a finite set of parameters.

Philosophical and Causal Implications

Theory 3: The Argument for Design, The existence of unique entities with infinite dimensionality suggests intentional creation. From a probabilistic standpoint, the likelihood of achieving infinite-dimensional uniqueness through random chance is zero; therefore, this uniqueness points to a divine origin.

Theory 4: Uniqueness as the Root of Logic, Uniqueness is the prerequisite for causality and reason. We can only engage in logical deduction and argumentation because entities are distinct and identifiable; without uniqueness, logic would collapse into a homogenous void.

The Limitations of Current AI

Theory 5: The Failure of Data-Grounded Models, Generative AI and traditional Machine Learning models are fundamentally incapable of reaching AGI. Because these models rely on finite datasets to represent entities of infinite dimensionality, they inevitably succumb to the Curse of Dimensionality. Consequently, they cannot truly generalize to the universal world, leading instead to overfitting and rote memorization rather than genuine understanding.

The Path to True AGI

Theory 6: The Analog Imperative, To achieve AGI, we must move beyond digital architectures. AGI requires a model that mirrors the inherent uniqueness of the physical world. This is only achievable through analog systems, which naturally reflect the continuous and unique state of reality without the need for discrete classifiers or digital approximation.

What are this project's goals? How will you achieve them?

The goal is to prove that wave mechanics can represent complex concepts more effectively than discrete digital bits.

• Phase 1: Formalize the mathematics of "symbol modeling" and build a functional single-neuron analog prototype to demonstrate interference-based activation.

• Phase 2: Iterate to multi-neuron clusters while building a team dedicated to AGI education, lowering the "entrance knowledge" barrier for this new science.

• Phase 3: Develop an Analog Internet Collective System, moving toward a distributed, biological-style network that learns and infers globally in real-time.
  

How will this funding be used?

The funding will be used strictly for personal subsistence and "buying time." * Living Expenses: $500/month to cover housing, food, and high-speed internet in Palembang, Indonesia.

• Research Infrastructure: $0. I already possess a laptop and paper. I utilize upcycled waste materials for physical prototyping to keep costs near zero. The grant allows me to work full-time as an independent researcher without the cognitive strain of a traditional 9-to-5, which is necessary due to my health circumstances.
  

Who is on your team? What's your track record on similar projects?

I am currently a solo researcher.

• Background: I hold a BS in Pure Mathematics and an MS in Plant Science (University of Missouri), where I specialized in AI residue modeling in agriculture.

• Relevant Experience: I spent two years as a Data Analyst at Oishii Farm Corporation, working at the intersection of data and biological systems.

• Unique Perspective: For the past six years, I have navigated schizoaffective disorder and schizophrenia. While this precludes a traditional PhD path, it has provided me with a "perceptual pivot"—the ability to see cracks in digital discretization and model the "uniqueness" of the analog world from a first-principles perspective. I have been developing these AGI axioms independently since 2020.
  

What are the most likely causes and outcomes if this project fails?

• Based on the mathematical axioms I have developed since 2020, I do not view the fundamental theory of Analog Wave Interference as a "risk" of failure, but rather a matter of temporal execution.

  • The Nature of the Challenge: The primary challenge is not the validity of the science, but the variable timeline required to translate these complex analog symmetries into a prototype while managing the cognitive fluctuations associated with schizophrenia. Because I operate outside traditional academic pressures, the "risk" is simply that the formalization may take longer than a standard quarterly cycle.

  • Outcome and Mitigation: This project is designed for maximum resilience. Because the overhead is near zero and the theory is grounded in fixed mathematical truths of wave mechanics, the work continues until the prototype is achieved.

  • The "Zero-Loss" Guarantee: Even during periods of slower cognitive pace, the research generates unique insights into low-power analog computing and interpretable AI architecture. The outcome is a guaranteed contribution to the field of "AGI" providing a roadmap for others to move beyond the digital ceiling of matrix-based AI.
    

How much money have you raised in the last 12 months, and from where?

$0. I have been self-funding my research through personal savings and the support of my family while refining the theoretical framework. This is my first formal application for research grant funding.