Spiking / time-domain models are definitely an answer to the efficiency problem. I think neuromorphic hardware is putting the cart before the horse. We should

Spiking / time-domain models are definitely an answer to the efficiency problem. I think neuromorphic hardware is putting the cart before the horse. We should start with neuro evolution experiments that seek to discover effective recurrent spiking topologies. There are non-linear networks that are so efficient that we wouldn't need specialized hardware to run them. The trade off is that they're incredibly hard to find. I think we might have enough compute on hand now. Assuming a generalist online learning model exists, we'd only have to find it one time. This isn't like back propagation. Activation = learning when techniques like spike timing dependent plasticity are used.