Neuromorphic Computing: Concepts and Hardware Implementations

This lecture introduces the concept of neuromorphic computing, which involves using electronic analog circuits to mimic neuro-biological architectures present in the nervous system. The instructor explains the need for novel neuromorphic compute architectures and hardware to efficiently execute new algorithms at large scales. The lecture also covers the challenges faced in ternary computing and successful binary computing cases, such as Moore's Law and the advancements in transistor count on microchips. Hardware simulations of the brain, including Boolean simulations and the comparison of neurons to CPUs, are discussed. Additionally, the lecture delves into the potential of new materials for artificial brain cells and the compatibility requirements for implementing synaptic functionality in memristors.