A startup called Emerald Logic claims it uses an evolutionary process to discover the best algorithm for predicting outcomes from any dataset. It might sound to good to be true, but the company claims successes already and is one of several startups trying something similar.
Think about being a hospital that wants to improve survival rates for patients. You have lots of data about patients — their medical histories, EKG readings, room numbers, doctors, billing information and much more — and you certainly know whether they leave alive or dead. Somewhere in all that data, the current thinking goes, there must be a formula that can predict what’s going to happen.
It’s not so much a big data problem as much as it’s a complex data problem. According to Patrick Lilley, co-founder and CEO of an Aliso Viejo, Calif., startup called Emerald Logic, the real world runs on systems where there are inputs and outcomes, only the complexity of the data we’re generating makes it very difficult to find the inputs that will lead to the best outcomes. He equates it to sticking a marble in a black box, eventually getting it out the other side, and then having to diagram what you think the inside looks like.