As artificial intelligence systems grow larger and more capable, researchers face a fundamental challenge: how to increase model capacity without proportionally increasing computational cost. Traditional dense neural networks process every input through every parameter, meaning that doubling the model size roughly doubles the computation required for each inference step. This limitation has driven the search…