"DePo": a "delayed pointer" neural net model with superior evolvabilities for implementation in a second generation brain building machine BM2

For nearly a decade, the author has been planning of building artificial brains by evolving neural net circuits at electronic speeds in dedicated evolvable hardware and assembling tens of thousands of such individually evolved circuits into humanly defined artificial brain architectures. However, this approach will only work if the individual neural net modules have high evolvabilities (i.e. the capacity to evolve desired functionalities, both qualitative and quantitative). This paper introduces a new neural net model with superior evolvabilities compared to the model implemented in the first generation brain building machine CBM. This model may be implemented in a second generation brain building machine BM2