Artificial intelligence that can evolve on its own is being tested by Google scientists

"Innovation is also limited by having fewer options: you cannot discover what you cannot search for." The analysis, which was published last month on arXiv, is titled "Evolving Machine Learning Algorithms From Scratch" and is credited to a team working for Google Brain division. "The nice thing about this kind of AI is that it can be left to its own devices without any pre-defined parameters, and is able to plug away 24/7 working on developing new algorithms," Ray Walsh, a computer expert and digital researcher at ProPrivacy, told Newsweek. As noted by ScienceMag, AutoML-Zero is designed to create a population of 100 "candidate algorithms" by combining basic random math, then testing the results on simple tasks such as image differentiation. The best performing algorithms then "evolve" by randomly changing their code. The results--which will be variants of the most successful algorithms--then get added to the general population, as older and less successful algorithms get left behind, and the process continues to repeat. The network grows significantly, in turn giving the system more natural algorithms to work with. Fun AutoML-Zero experiments: Evolutionary search discovers fundamental ML algorithms from scratch, e.g., small neural nets with backprop. Can evolution be the â Master Algorithmâ?