Arbitrarily fast computation with arbitrarily slow neurons

 Paul Haider, et al, have neurons guess what they will be doing in the future (specifically, use currently available information to forecast the state of its membrane potential after relaxation), predictive processing.* Similarly, each layer of A.s.a. H. predicts its inputs and outputs at future time steps** and can compare these with future observations.*** A prediction engine. On multiple time scales.

Asa's currently active case supplies predictions for the next expected inputs and outputs. If the current observed inputs are found to be close enough to the predictions then the output actions are taken immediately.

* Latent Equilibrium, 35th Conference on Neural Information Processing Systems, Sydney, Australia, 2021, arXiv:2110.14549v1, 27 Oct. 2021.

** See my blogs of  10 Feb. 2011 and 14 May 2012.

*** See my blog of 1 June 2017.

Compression

Each layer in the A.s.a. H. hierarchy typically does a bit more than two orders of magnitude compression.

Another reliability issue

 I typically use USB sticks to transfer case/concept activation from one level in the A.s.a. H. hierarchy to another on another computer. I do this so that I have a record and can study what A.s.a. is thinking in detail. Last week the computer I was using (my desktop at ESU) recognized the drive but would not read the data file. (Previously it had been working normally.) The data is not corrupted. I took the stick home and my Surface Pro (also running Windows 10) read it fine. I may need to make backup copies every time I do such data transfers.