Hi Trevor,
The gradient concept is great. From my understanding, the reason why neuromorphic hardware is so computational efficient is that it only need to do “addition” operations if the outputs of neuros are binary spike events. Event a three-bit neuron can not have that operation advantage (I might be wrong here, not much knowledge on the hardware side). It’s definetely useful to have nengo as a tool to optimize 32-bit neural networks to smaller bit number. But I suppose it will not use any of nengo’s spiking neuron type. If I understand it correcly, the implementation of gradient concept will make nengo similar to exiting frameworks like tensorflow with additional optimization algorithms designed for lower bit neurons. Please correct me if I’m wrong here. Thannk you.