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.

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.