Google's SETI

Google has developed a new large scale machine learning system called SETI (Since it's searching for signals in a large space). In the article Simon Tong from Google research talks about how they sacrificed accuracy by a bit to achieve ease of use and system reliability. He says
"Seti is typically used in places where a machine learning system will provide a significant improvement in accuracy over the existing system. The gains are usually large enough that most teams do not care about the small differences in accuracy between different flavors of algorithms. And, in practice, the small differences are often washed out by other effects such as better data filtering, adding another useful feature, parameter tuning, etc. "

The last point has been true in our own work of developing classifiers for Kindle Content Ingestion. Data cleaning, feature selection, parameter tuning and post processing have yielded the largest improvements of accuracy.