In 2016 for the first time ever, a “grand master” of the game Go was defeated by a Google created program named AlphaGo. The periodical I read was published in Nature before AlphaGo had even played Lee Sedol. But the program had already beaten the best European player and all other commercial Go programs to date. AlphaGo was employed a deep neural net. Deep neural nets consist of nodes that are all connected together. Each node is designed to analyze the input and give an output that can help the program decide where to go “get the pun?” . One node might determine all the legal moves, one might be for immediate attack, immediate defenses, or analyzing where a position is being contested or held. The AlphaGo programmers were also successful in making the program capable of learning, which it did so magnificently. The program employed tactics into its game play that few, if any, professional players have seen before. The algorithms used are very complex and are different in each node, but when all the nodes communicate together the program is better than any human player can be.