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A new method reveals that a single cortical neuron can classify cats vs dogs, recognize spoken words, and solve 10-bit parity, tasks previously thought to require entire networks.
This paper proposes replacing the standard point neuron model in artificial neural networks with a more realistic cortical cell model, claiming improvements in expressivity, robustness, learning speed, and reduced memorization and data requirements.