Google's AutoML-Zero Evolves Machine Learning Algorithms Using Basic Math

Algorithms seem to be everywhere nowadays, working their magic behind recommendation engines or helping doctors detect rare genetic disorders. But while machine learning tools are gradually becoming more accessible to non-experts, designing machine learning algorithms themselves typically requires some expert know-how -- and even then, it's no guarantee that AI models will perform correctly, as sometimes their inner workings can be a mystery even to the initiated. So it's little wonder that the field of automated machine learning or AutoML has been garnering interest as of late, allowing non-experts to quickly apply machine learning to real-world problems without having to master its more arcane aspects first. And here's an even more mind-blowing idea: what if machine learning algorithms could be programmed to automatically evolve better versions of themselves? The notion of machine-evolved algorithms could potentially mean more creative solutions -- ones that surpass the ability of human minds to conceive -- in addition to dodging the limits that human bias might place on them.