E.G. Blee-Goldman

Life is a bad computer. In fact, even the most sophisticated self-replicating systems only use a tiny fraction of their theoretical computational capacity. There is a very good reason for this: anything that self-replicates must sacrifice most of its potential computational power in the service of copying itself. In contrast, the theoretically smartest programs (ones that maximize computational power) inevitably halt. Below I explore some concepts and suggest that self-replicating systems, including life, maximize the mutual information of the present and future rather than maximizing output. The Busy Beaver Limit (BBL) is the theoretical maximum complexity achievable by a terminating, non-replicating, computational process of a given size.[1] Systems operating near this limit are characterized by maximal computational irreducibility: they are exquisitely complex, unpredictable, and inherently fragile. They are, in a sense, maximally "clever." (And rather beautiful!)[2] Conversely, the Von Neumann Threshold (VNT), represents the minimum logical and informational complexity required for a system to become self-replicating. Crossing this threshold marks a transition from a terminal process to an open-ended one. It also requires a fundamentally different strategy; one of complexity directed inward for robustness, redundancy, and error correction, rather than outward for maximal work.[3] These concepts represent distinct "computational teleologies" in the sense of inherent organizational structures that dictate a system's fate. As I will demonstrate, the structural overhead required to cross the VNT imposes a profound cost of persistence, guaranteeing that a self-replicating system cannot simultaneously achieve the productivity defined by the BBL. The trade-off is absolute: to persist, a system must stay far away from the chaotic boundary of the BBL. In a very precise, technical sense, to live forever, a system must be computationally dumber than the theoretical ma