Unconventional Computing

The Unconventional Computing program investigates whether a single formal criterion can distinguish systems capable of nontrivial information processing from those that are not, regardless of physical implementation. Building on the integration-differentiation balance metric developed in the Existence Threshold program, this work addresses not pattern persistence but the capacity for computation itself. The central hypothesis is that a system computes when its integration-differentiation ratio falls within a bounded regime: sufficiently integrated to propagate signals across the medium, sufficiently differentiated to represent distinct states.

Cross-domain validation

Empirical validation has proceeded across three domains chosen for maximal diversity in physical medium. Neural systems, both biological (EEG recordings) and artificial (transformer attention layers), exhibit integration-differentiation ratios that track computational load. Financial time series display regime transitions between noise-dominated and structure-dominated phases that align with the predicted thresholds. Geomagnetic field data, drawn from solar-terrestrial interaction records, provide a test case for systems whose computational status is genuinely uncertain, offering ground for falsification rather than confirmation.

Medium and expressiveness

The program's longer-term trajectory concerns the relationship between the physical properties of a computing medium and its computational expressiveness. If integration-differentiation balance governs computational capacity, then limits on that balance in a given medium should predict what classes of computation it can and cannot support. This connects the program to questions in unconventional computing, neuromorphic engineering, and the physical limits of non-von-Neumann information processing.