Status Updates From The Master Algorithm

drawing boundaries around statistical clusters in high-dimensional spaces, and how models in machine learning asymptotically get better at learning.

A chapter on evolutionary algorithms to get optimal solutions and a chapter on bayesian models based on Bayesian statistical methods.

a chapter on connectionism, electronic neurons, and Hebbian learning used in machine learning.

The debate between rationalism and empiricism shows up in AI with statistical inference versus search trees and syntactical methods of deduction. Machine learning and expert systems.

how statistical methods and machine learning overtook the expert systems of early AI, and reassessing Chomsky's critique of statistical methods in human learning.