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Modeling each neuron in an NN as a process is incredibly computationally wasteful, and we often see this in Neuroevolution implementations where neurons are rep
by guskel 8y ago
Modeling each neuron in an NN as a process is incredibly computationally wasteful, and we often see this in Neuroevolution implementations where neurons are represented as objects. It's clear from advances in DL that neurons and weights should be represented by matrices.
I've never given much credence to Sher's book because of this. Switching to Erlang just isn't necessary given current techniques.
- plainOldText 8y agoHow about using Erlang because it provides fault tolerance, and any faults resulting during the neuroevolutionary process will be contained and won't bring down the whole system? Or evolving groups of neurons in parallel, and across a distributed cluster? These things are much easier in Erlang.