The machine learning problem of the next decade

A few months ago, my company, CrowdFlower, ran a machine learning competition on Kaggle. It perfectly highlighted the biggest opportunity (and challenge) with machine learning: What do you do with an 80% accurate algorithm? We uploaded data collected on our platform and Kaggle sent it out to over 1,000 data scientists, who competed to see who could build the best search model. The simplest approach gave a baseline accuracy of 32%. By the next morning, one team already had a 53% accurate model.