The Duality between Genetic Algorithms and Deep Learning
I claim that it is possible to solve any deep learning problem better using a new technique I have discovered a method that combines back propagation and genetic evolution. It trains faster and more accurate.
http://www.tooltech-software.com/CorTeX/Deep_Genetic_Training.pdf
Published in Members Blogs
Menno Mafait
Anders, what if the theory of evolution is invalid? Nevertheless, good luck.
Anders Modén
In one perspective the evolution theory is just a name on a certain methodology in genetic programming that defines a number of operations that can be made on a population of mathematical solutions that has a unique probability feature. It can find random solutions but its very likely to find solutions near old solutions. Its these features i exploit in my software and that identifies this duality between back propagation and genetic algorithms.
Menno Mafait
Anders, on average, a structured search is faster than a random search. For that reason, genetic programming never used in serious solutions.
A nasty blow for the theory of evolution: I am reverse-engineering the language center of our brain, assuming that the language center of the brain is intelligently designed. And scientists / evolutionists fail to deliver even the simplest of my results: http://mafait.org/challenge/.