Neuromorphic Computing

This course explores neuromorphic computing, focusing on a machine that works like the brain. The learning outcomes include understanding the end of the Turing-von Neumann paradigm, computation limits, energy vs. time considerations, and the operational temperature range. The course teaches about ATI vs. cognitive ability (EQ), global energy consumption, and general characteristics of neuromorphic computing. The teaching method is a lecture delivered by Ivan Schuller. The intended audience for this course is individuals interested in the intersection of neuroscience and computing.