This article follows the first piece on machine learning describing how AI interacts with neuroscience, as well as how hardware and chips are getting created and modified to be more efficient for specific AI algorithm
This is a very basic introduction to different techniques currently used in machine learning (artificial neural networks, Particle Swarm Optimization, Evolutionary Algorithms, etc.).
The paper describes the architecture of a simple neural network and offers a useful intuition on how it may be used to solve complex nonlinear problems in an efficient way.
