While our existing model is two-dimensional, we hope it is obvious how the model scales to higher dimensions. This would defeat the purpose of using a local model in the first place. If a three-dimensional model were to be used it would make sense to strongly restrict the size of one of the dimensions. However for the moment, FPGAs are thoroughly two-dimensional.
Neural nets appear to be in fashion.
While it would be possible to use cellular neural nets as a target substrate for HAL, and it is possible to use HAL as a genetic substrate for breeding neural nets in a separate medium, neural nets do not appear to be appropriate for most of the target problems we're considering. In particular, although the best players of the Game of Go in the world use neural nets, a pure neural net approach seems to have very severe weaknesses when it comes to reading out tactical sequences. We doubt an intelligent Go player design would be purely neural-net based. Neural nets do not appear to be a particularly good match for the target hardware either - which typically resembles a network of boolean logic gates more than a network of neurons. HAL constitutes an attempt to develop computational devices by mimicing the fundamental processes of living organisms.