MIT's automated machine learning works 100x faster than human data scientists

A new automated machine learning system can analyze data and come up with a solution 100x faster than humans, according to a new paper from MIT and Michigan State University. This could potentially help businesses take advantage of machine learning's capabilities in a faster, easier way, while also filling data science talent gaps. The system also potentially marks a tipping point in machine learning adoption in the enterprise, which is expected to double in 2018, as TechRepublic's sister site ZDNet reported. When seeking a solution to a problem, data scientists must wade through huge datasets, and choose the modeling technique they believe will work best. The issue is, there are hundreds of techniques to choose from, including neural networks and support vector machines, and choosing the best one could potentially mean the difference between millions of dollars in ad revenue or none, or catching a flaw in a medical device or not.