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Curating the Next Blockbuster with IBM Watson

The ushering in of autumn means pumpkin spice everything, counting down to the holiday season, and classic movies on the silver screen. While summer is full of action flicks and superheroes, the latter half of the year is a mix of horror, feel-good, and holiday movies.

One such film making its debut for the fall is Morgan, a science fiction film featuring an ensemble cast with the likes of Kate Mara (House of Cards), Ana Taylor Joy, Michelle Yeoh, Jason Leigh, and Paul Giametti. Filmed in Northern Ireland, the plot follows the creation of an intelligent laboratory being named Morgan and the subsequent ethical issues surrounding her release into the world.

One of the alluring factors with movies are their trailers, seen on television and before other movies within a theater. For me personally, trailers are as entertaining as the movies themselves, offering just enough to keep me on the edge of my seats while staying interested to watch the movie in full. Sometimes it’s enough for me to purchase the ticket right there and get my calendar ready for the showing.

Creating good movie trailers is also on the minds of IBM Watson Research Teams. Utilizing Watson APIs and machine learning techniques, the team analyzed hundreds of similar horror and thriller films. After learning what keeps audiences intrigued, the developed system suggested the top 10 moments from Morgan, which was then arranged and edited by an IBM video editor.

The results are as shown:

While creative professionals are nowhere near from being replaced anytime soon, the eerie video suggests that even media-driven behavior can be duplicated by artificial intelligence. This got me thinking, where else can this be applied? Some thoughts:

  • Sporting events: Based on how the ebb and flow of a game goes, AI can be in charge of changing the music or encouraging the crowd to stand up and cheer.
  • Transportation: Traffic in many cities including Southern California is horrendous during rush hour. If radios and mobile phones could respond with the right types of music and podcasting content in correlation with traffic conditions, drives could be more pleasant.
  • Food: Food consumption is always an interesting topic of discussion. At the very end of the day, we value variety and want to eat a bit of everything. What if Watson could optimize what gets featured in our fridges?

In any case, the ideas are endless. What do you think Watson could be capable of?

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Albert Qian

Albert Qian is a Marketing Manager at Perficient for our IBM PCS, DevOps, and Enterprise Solutions Partners focused on cloud computing technologies.

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