The purpose of this paper is to present a brief history of the field of cybernetics that is concerned with the simulation of biological brains for the purposes of controlling both machines and industrial processes. This paper will also discuss the current understanding of how biological brains function and learn. It will then discuss the current state of the art in neuromorphic technology design and where it falls short of actually faithfully functioning like a biological brain. It will then discuss how primarily hardware based computational modeling methods can far more rapidly and faithfully model the functionality of biological brains. Finally, it shall conclude with a discussion of the advantages of hardware based computational design over both conventional digital hardware implementation and the ROM-ified code versions of transforming software based ANN&rsquo;s (Attractor Neural Networks) into hardware. It then discusses some hardware examples of each of the analogs to these biological neural systems that have been discussed and concludes with the advantages of this design approach over the conventional approaches used in neuromorphic hardware design.