# Startups needs scale to use algorithms

The algorithms work in a proficient way only if the scale is large or when the data collected is large. Startups like GraphLab and Prediction IO are working on scaling these algorithms up on huge data, where as of now only simple algorithms could be applied.

Much like an election exit poll survey, exactness improves as scale of data becomes big, running into terabytes to a certain extent than gigabytes.

According to Varun Banka, co-founder, socialcops, a Delhi based startup, "We are getting base data ready in three areas -- education, healthcare and public information. But our scale is small -- about two million data points. The more data you have the better output will it give."

# Man-machine play

Although algorithms play a vital role in managing scale very well that includes sending news feeds to 1.4 billion Facebook users or providing suggestions based on user profiles to shoppers online, but does that thing work every time? At times there are some first time visitors to a site or there are products that are launched for the very first time on the websites. In such situations machine has no clue how to deal with it.

 According to Nishant Rao, managing director, LinkedIn India, “An algorithm will send content, say an article only to people it believes might be interested in it. But someone interested in healthcare might also be interested in cameras and cars. We can't leave everything to algorithms.”

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