A Roadmap for Reverse-Architecting the Brain’s Neocortex

This course provides a roadmap for reverse-architecting the brain's neocortex, aiming to understand and replicate its computing paradigms. The learning outcomes include exploring natural layers of abstraction, developing feedforward neural networks for unsupervised learning, and reverse-architecting higher-level cognitive functions. The course teaches skills such as abstraction from biological electronics to computational primitives, building functional blocks for neural networks, and implementing neural network taxonomy. The teaching method is a methodical, bottom-up approach based on years of study and experimentation. The intended audience for this course includes computer architecture researchers, neuroscience enthusiasts, and individuals interested in exploring unconventional approaches to computational paradigms.