neural

Then, they fit a neural network to that description.

A book that explains the core ideas of neural networks and deep learning.

There is a neural net example benchmark in the topaz git repo.

The more you let it happen the faster you'll calm down because you're reworking those neural pathways.

Next to it is a non-neural PCA/Eigenface reconstruction.

Does cold-starting from the same neural network give you the same consciousness or a copy?

Hinton gave backpropagation which is one of the foundational pillars of feed-forward neural net algorithms.

But the exciting thing is that the neural network can start there, and slowly eat its way toward the outer layers, replacing a big stack of hacks with one simple algorithm.

Does consciousness require some form of continuity that's lost if you lower neural activity beyond a certain level?

We tend to work at things we're already good at, and neural nets can be strengthened like any other muscle, especially if there is social encouragement pushing in one direction or the other.

This part is interesting neither scientifically nor mathematically, as we have known for 20 years that neural networks are universal function approximators.

Like we are now forming artificial neural maps through "machine" learning techniques that are accelerated versions of their biological counterparts, I believe that we should develop developmental algorithms into large-scale simulations.