Computer scientists view this as a practical application of ensemble theory. No single neural network is perfect. Each has its own training biases, token weights, and mathematical blind spots. By pooling their outputs, we drastically reduce the risk of hallucination. It is the digital equivalent of a medical board. When three world-class experts look at the same data, the truth usually lies in their consensus, while their disagreements point directly to where we must dig deeper.