Connectomic AI

     I 've long conjectured that the reason we have an inhibitory network in our brains is to prevent an epileptic burst and it seems that this thought has some truth. In my early simulations of neurons, I found quickly that excitatory networks would get to a tipping point where they would just start firing uncontrollably; i.e. every neuron (node) would be firing as fast as it could and the output would end up being a jumbled mess of motor neurons all firing, all the time. I even continue to experience this sometimes in more true emulations due to the timing or the number of neurons aren't in a correct balance so that the inhibitory neurons aren't in a great enough strength to overcome the excitation.  In AI/Deep Learning (et al), inhibitory networks don't exist. The excitatory network is refined by the error factors and outcomes are created by numeric voting. DL tunes an excitatory network by weighted factors.  There is a delicate balance between the excitatory...

     I feel bad that I didn't write down the scientist that said "AGI must start with the stomach" but he is so right. 99% of AI (ANN/GOFAI/DL/Neurosymbolic/ et al) starts with sensory input and 99.99% attaches the AI to motor activity if it has something to do with robotics, where that motor activity is a direct result of everything sensory. In current AI, motor activity is always secondary to sensory input and most often, AI doesn't even put motor activity as a requisite.  Let me flip the script and instead of starting with sensory input, let me start with motor activity. The reason AGI starts with the stomach is because when we are hungry, we need to move. As an infant, we begin sucking on anything that represents a nipple. As we get older, we grab anything that we know we can eat and put it in our mouths. Even older, we go to the kitchen and make us something to eat. The drive to squash the hunger pain is the reason we learn. To eat in any instance, requires us ...