Google Research: Machine Learning System

Google's effort to scale massive data set, an approach to design a highly scalable learning system statistically on a small training set, solving what it called a 'hard predictions problem' which idea it conceived several years ago is back-in-project according to it official Google Research blog post on Tuesday.

The project is code-named 'Seti' on the notion that it searches for signal in a large space. It's set to scale massive data, which helps in information retrieval and machine translation - improving translation algorithms and semantic understanding.

The system is typically employed in places where machine learning will provide significant improvement in accuracy over the existing system.

It is perhaps less academically interesting to design an algorithm that is slightly worse in accuracy, but that has greater ease of use and system reliability stated Google. However, it's useful in places where there is a good chance of significantly improving predictive accuracy over the incumbent system.

Machine learning on the other hand remains an interesting area of research, as it can be applied to several real world problems comparable to modern classifiers.
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