When the Art of Entertainment ties the knot with Science
summary
Builds AI models that predict a screenplay’s success probability and recommended production spend and casting tradeoffs, uses Microsoft/Google/Amazon video APIs to auto-tag scenes and faces, and maps digital minute-level dropoffs to TV viewing to create a common currency. Finds 23% uplift after re-editing three drop points in an episode, measures that 40% binge-watch at midnight while another segment (80% male) watches across afternoons, and prototypes per-user highlight cuts from 50-camera feeds.
AI-written summary · about
chapters (14)
- 0:00Intro
- 3:21Abuse of Science
- 4:52Data Science in Media Industry
- 5:36Ad Optimization
- 6:31Greenlighting
- 8:25Dialogue
- 9:40Talent Management
- 10:52Content Editing
- 13:20Content Publishing
- 14:09Analytics
- 19:58Hit map
- 20:49Breaking down videos
- 22:57Digital and TV data
- 23:45Hero and heroine
related talks
27mBeing Smart with Art
37mHow we generate 130,000 shorts per month using AI
41mDigital Dystopia or Artistic Utopia? The AI Creative Quandary
14mLeveraging Artificial Intelligence for Scene Detection in Broadcast Video
42mSmart Testing: The Impact of AI on the Entertainment Industry
41mUnlocking Profit: How AI-Driven Budget Optimization Elevates Marketing Performance
30mWhich episode? Using AI to streamline media content operations
29mBuilding Netflix - from movie magic to ML reality
