> Now, what wrong with TrueNorth? My main criticism is that TrueNorth implements networks of integrate-and-fire spiking neurons. This type of neural net that has never been shown to yield accuracy anywhere close to state of the art on any task of interest (like, say recognizing objects from the ImageNet dataset). Spiking neurons have binary outputs (like neurons in the brain). The advantage of spiking neurons is that you don't need multipliers (since the neuron states are binary). But to get good results on a task like ImageNet you need about 8 bit of precision on the neuron states. To get this kind of precision with spiking neurons requires to wait multiple cycles so the spikes "average out". This slows down the overall computation.
Surely you can do this in the spatial domain instead of time? That is, each neuron is one bit, so you have 8 each computing one of the 8 bits he says are necessary? Perhaps the problem is using that value afterwards, I guess.
Surely you can do this in the spatial domain instead of time? That is, each neuron is one bit, so you have 8 each computing one of the 8 bits he says are necessary? Perhaps the problem is using that value afterwards, I guess.