The explosion in online video streaming is filling up the world's hard drives, saturating its bandwidth, and possibly heading us towards a crisis of storage and pollution. Could the answer be to more effectively shrink the information itself? And what does machine learning models have to do with that? According to a recent study by IDC, the sheer tonnage of global data stored online is set to increase tenfold from current levels to 163 zettabytes—enough data to fill 1630 billion trucks if printed. IBM reports that we generate 2.5 quintillion bits of data every day, with 90% of the data stored on the internet created in the past two years.
This growing tide of data usage has long-term consequences for the sustainability of global energy networks and for the subsequent environmental impact.