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Capturing the Mirage: Machine Learning in Media and Entertainment Industries


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These slides were presented by Zecca Lehn, Data Scientist, Earth Advocacy Project for his talk at Data Science Pop Up LA in September 14, 2016.

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Capturing the Mirage: Machine Learning in Media and Entertainment Industries

  1. 1. Machine Learning in Media and Entertainment Industries 1 Sep 14, 2016 Zecca Lehn| Data Scientist Domino Data Science PopUp LA 2016 Underlying Img: DKFindOut!
  2. 2. destination.find(r`deep-water`) Img: Michael Whelen 2005 2 How do we get there?
  3. 3. 3 Img: MySafe:LA
  4. 4. Failures might seem baffling if we follow our intuition and think of artificial intelligence the same way we think about human intelligence. Lukas Biewald What Can we Learn From AI’s Mistakes 4 By 2019, we believe that digital will account for more than 50 percent of the overall total for media. McKinsey The State of Global Media Spending Across media sectors, companies must ramp down traditional offerings, ramp up new revenue streams, and innovate business models. BCG: Seeking Out Opportunities in a Dynamically Evolving Industry
  5. 5. WHERE_WE_ARE: Sources: O’Reilly ‘The New Artificial Intelligence Market’ | Fidelity 5 IT: • 32% AI Spending • 31% SP500 MV MEDIA & ENT: • 2% AI Spending • 5% SP500 MV
  6. 6. WHERE_WE_ARE: Perceptions of AI Value Proposition 6 Source: Accenture The Promise of Artificial Intelligence
  7. 7. WHERE_WE_ARE: The AI bottleneck – Micro 7
  8. 8. WHERE_WE_ARE: DESCRIBE >>SEMANTICS >> CREATIVITY? 8 Source: Accenture The Promise of Artificial Intelligence
  9. 9. WHERE_WE_ARE: Deep Image Recognition (Stanford) Now open source in Python 9 O’Reilly: • 3% of AI spending across all industries...
  10. 10. WHERE_WE_ARE: Deep Natural Language Processing (CNTK Now Open Source Github/MSFT) 10 Source: InformIT O’Reilly: • 3% of AI spending across all industries...
  11. 11. Scene Completion | RNN LSTM| Plot Discovery …getting closer to semantic continuity! 11 SUNSPRING Short| A Sci-Fi Starring Thomas Middleditch
  12. 12. WHAT_WE_SEE: Interactive Dynamic Video: MIT reveals an object’s hidden physical properties 12 Source:
  13. 13. WHAT_WE_SEE: • DataFX integrates statistics and special effects to create new video and digital content. • Los Angeles based startup with NBA and media clients 13
  14. 14. WHAT_WE_SEE: Partnership 14 Accelerator Funded LightStage: Face Scanning Mark Ruffalo for THE HULK
  15. 15. WHAT_WE_SEE: 15 •Presented at Big Data Day LA 2016 •“Prescriptive Analytics” applied through client engagement in feedback loop >> adding to lift through levers •Blending AI w/ econometric models on BIG DATA •Source: / NBA
  16. 16. Film Script NLP AI: predict profitability 16
  17. 17. WHAT_WE_HEAR : 17 Project Magenta @ 2016 MOOG Fest •Open Source Github •Extends ‘live-play’ similar to Markov Chain Next-Work Prediction Engines •Uses Google’s “Deep Dream”
  18. 18. WHAT_WE_HEAR : 18 MetaCreation Lab: ‘Generative Art’  Creative Behavior ‘
  19. 19. WHAT_WE_HEAR : 19
  20. 20. WHAT_WE_HEAR : 20 “Moneyball for Book Publishers” NY Times 2016 Sources: Publishing Perspectives, NPR •Finish Book, Read Fast, Women/Man, Baby Boomer? •Startup from London •Analytics to understand customers through crowd engagement >> prediction >> channel marketing & PR >> publishers •Addresses 20/80 rule – 20% of books are profitable, and 80% not… Disruptor? •Free and sample ebooks offered in return for your behavioral data
  21. 21. WHAT_WE_HEAR : •Match directors and writers in pre- production using NLP •Using writers and directors past projects, experience level, interests, etc. •Takes descriptions of projects shared by studios and production companies •Aim to match equal ratio of men and women directors 21 New LA based startup @DataPony
  22. 22. SUMMARY 22 Img: Zecca Lehn Take a drink, it’s not a mirage… ‘
  23. 23. 23 @Zecca_Lehn Email me for slides and please follow: THANKS!