
How Startup Teraki Solves a Too-Much-Data Problem - bootload
http://www.fastcompany.com/3053298/elasticity/how-this-startup-solves-our-too-much-data-problem
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lovboat
Using a server to decide what kind of data has real significance provides a
mean to reduce data. For example if you are in a gym doing hard physical work
the data must be compared with what happen in that circumstances, you can
filter and weigh the data depending of the circumstances. Using AI to classify
contexts in which precision must be increased is the best way to reduce the
too much data problem.

