Working Papers
I’ve developed an integrated framework exploring how evolutionary principles can inform artificial intelligence architecture and how AI systems can be designed to augment rather than replace human intelligence.
The Framework
These papers form a cohesive argument across four domains:
1. Beyond FLOPS: The Evolutionary Processing Unit and the Roadmap to AGI
October 2025
The prevailing AI paradigm assumes that scaling computational resources will lead to artificial general intelligence. This paper challenges that view through a thought experiment: the Evolutionary Processing Unit (EPU) represents ~5.5 × 10³⁸ brain-equivalent FLOPS of cumulative computational effort over four billion years. Rather than attempting to replicate this through brute force, we should understand the architectural principles evolution discovered: modularity, plasticity, causal grounding, and efficient attention allocation.
2. Beyond Scale: A Modular Architecture for Adaptive AI
October 2025
This paper proposes a concrete alternative to pure scaling: a modular AI architecture with specialized components coordinated by a dynamic executive function, inspired by the biological brain’s distributed intelligence. The framework emphasizes continuous plasticity, explicit bias correction, causal reasoning capabilities, and built-in value alignment—offering a more efficient and interpretable path toward Augmented Human Intelligence (AHI).
3. Attention Is All We Have: What AI’s Greatest Breakthrough Can Teach Us About Being Human
October 2025
The 2017 Transformer paper demonstrated that attention mechanisms—selective focus on relevant information—are sufficient for remarkable AI performance. This paper argues that attention is not merely a technical mechanism but a fundamental principle governing both artificial and biological intelligence. Understanding attention as a resource allocation strategy reveals insights for building better AI systems and for living more deliberately as humans.
4. The Mastery of Life: A Framework for Living with Clarity, Intention, and Adaptation
October 2025
Modern life offers endless options but limited clarity about what actually matters. This paper introduces a practical framework for identifying priorities, tracking progress, and adapting to change. Grounded in behavioral science and cognitive architecture, the Mastery of Life (MOL) framework treats human flourishing as an attention allocation problem—demonstrating how principles from AI and evolutionary biology can be deliberately applied to enhance how we live.
The Integration
These papers connect through a central thesis: attention—the selective allocation of limited resources—is the fundamental mechanism enabling intelligence in both biological and artificial systems. By understanding how evolution optimized this mechanism in the human brain, we can build AI that augments rather than replaces human capability, and we can apply these same principles to living more deliberately.
The framework bridges theory and practice, offering both architectural principles for AI development and actionable frameworks for human decision-making.
These working papers represent my current thinking and are intended to stimulate discussion rather than present definitive conclusions. I welcome feedback, critique, and collaboration.