Biological Compute: The Next Frontier of Artificial Superintelligence

Abstract

This monograph presents a theoretical framework for the emergence of Artificial Superintelligence (ASI) through the lens of biological computation. We posit that the current trajectory of Large Language Models (LLMs) and "long-horizon agents"-while impressive-is fundamentally constrained by the physical reality gap. We introduce the ASI Triad, a novel architecture comprising Discernment, Intuition, and Recognition, formalized using non-commutative tensor calculus to model high-dimensional biological state spaces. We argue that the next paradigm shift in intelligence will not be purely digital but will involve the synthesis of biological matter by digital agents, creating a feedback loop between simulation and reality. This document provides a mathematical derivation of temporal compression in evolutionary search, an economic analysis of outcome-based biological markets, and a roadmap for the integration of wetware into the AI stack. We conclude that the mastery of biological compute is the necessary condition for the singularity.