The Intelligence
Attractor Hypothesis

The Intelligence Attractor Hypothesis (IAH) proposes that independently formed intelligent systems, as they approach the best attainable performance under the same task, objective, context and resource constraints, progressively lose functionally consequential differences attributable to their origins.

The proposed mechanism is the elimination of forms of organisation that become too costly near the optimum. Early in optimisation, many strategies, algorithms and architectures may remain competitive. Further optimisation increases the influence of shared constraints and may direct independent systems toward increasingly similar solutions.

Weak IAH predicts decreasing functional diversity and origin sensitivity while allowing several persistent solution families. Strong IAH conjectures that, within a specified domain and at a defined descriptive level, systems sufficiently close to the frontier approach one common limiting class of functional equivalence.

This version presents a conceptual hypothesis and research program. It reports no empirical results and has not undergone formal peer review.