‘…deep learning is less adept at interpreting video. Analyzing a video frame won’t reveal what’s happening unless that frame is compared with the ones that come before and after—a person holding a door may be opening it or closing it’

A group from MIT and IBM think they’ve found a way to adapt deep learning algorithms to analyze videos. The issues are:

  • Context: is it in the air? on land? in water?
  • Compute-intensity: can it be done without a big carbon footprint?
  • Volume: 500 hours a minute, every day, is uploaded to YouTube as of May 2019, translating to 720,000 hours of new video posted daily.
  • Potential uses: range from monitoring offensive material to selling ads.


This Technique Can Make It Easier for AI to Understand Videos
WIRED | October 15, 2019 | by Will Knight