[retrofrost]

There's a lot of really interesting work in neuroevolution that has the potential to make some really interesting unsupervised training regimes. I think theres some really interesting possibilities for unique encoding schemes like ACE encoding to speed up training and provide much smarter behavior out the other end. Especially, if "genes" can form reusable elements of neural topology that makes scaling networks faster. Reusing components all over body is how we fit such complexity in the relatively little unique DNA we have. The other interesting thing about using genetic algorithms for a portion of training/network mapping is that allows you to have heterogenous networks, so you can have simulations or representations of astrocyte/glial behaivor easily get integrated with neural networks. With traditional training methods it's a massive fucking pain to train a non-feed forward network.

I do think that languages like Elixir and other cpu concurrent strong tools can really be leveraged to make some dynamite libraries.