Once the training is complete, one thing I didn't see mentioned in the paper was how they maintain the charge on the gate capacitors, which is analogous to the weights in a traditional neural network if I'm understanding this correctly. Any practical implementation will need to have some practical way to refresh that on a continuous basis so that the weights don't drift. Was this perhaps mentioned somewhere and I missed it?