Choosing the Optimal AI Algorithm

Automating aspects of deep learning is an obvious next step.   Note also the method described here is an evolutionary method (Aka Genetic Algorithm).    Consider also that the selection and testing of data needs to be addressed.  That's usually harder because there are more choices involved.   See the blog post and paper referred to below ...

IBM’s new system automatically selects the optimal AI algorithm   By Kyle Wiggers  in VentureBeat

Not all deep learning systems — that is to say, systems consisting of layered nodes that ingest data, transform it, output it, and pass it on — are created equal. No algorithm is appropriate for every task, and finding the optimal one can be a long and frustrating exercise. Luckily, there’s hope: IBM developed a system that automates the process.

Martin Wistuba, a data scientist at IBM Research Ireland, described in a recent blog post and accompanying paper the method. He claims it’s 50,000 times faster than other approaches, with only a small increase in error rate.

“At IBM, engineers and scientists select the best architecture for a deep learning model from a large set of possible candidates. Today this is a time-consuming manual process; however, using a more powerful automated AI solution to select the neural network can save time and enable non-experts to apply deep learning faster,” he wrote. “My evolutionary algorithm is designed to reduce the search time for the right deep learning architecture to just hours, making the optimization of deep learning network architecture affordable for everyone.”    ... "