QIS vs Federated Learning: Why Outcome Routing Wins at Healthcare Scale

QIS vs Federated Learning: Why Outcome Routing Wins at Healthcare Scale In Arizona this week, Christopher Thomas Trevethan — inventor of the Quadratic Intelligence Swarm (QIS) protocol — is presenting to healthcare investors. The question they all ask, once they understand the basic concept: How is this different from federated learning? It is a fair question. Both approaches claim to enable distributed intelligence without centralizing raw data. Both are positioned as solutions to the healthcare data privacy problem. But the mechanism is fundamentally different — and that difference matters enormously at scale. This is a direct technical comparison. The Setup: What Both Approaches Are Trying to Solve Healthcare generates data that, if shared intelligently, could save lives. A rare pediatric presentation in Phoenix might match patterns seen at a hospital in Massachusetts three years ago. A drug interaction discovered in rural Montana could warn a clinic in Miami before the first advers