Differentiable logic gate networks run EEG classification with no floating point.

Dharia, Smith and Valderrama replace floating-point networks with differentiable logic gate networks for real-time EEG on microcontroller-class hardware. Logic gate networks compile to boolean circuits, so inference is effectively free relative to matmul. Concrete evidence for the thesis that edge inference won't be quantized transformers, it'll be something structurally different.