Morgan | IBM Creates First Movie Trailer by AI [HD]

From YT: Scientists at IBM Research have collaborated with 20th Century Fox to create the first-ever cognitive movie trailer for the movie Morgan.

Utilizing experimental Watson APIs and machine learning techniques, the IBM Research system analyzed hundreds of horror/thriller movie trailers. After learning what keeps audiences on the edge of their seats, the AI system suggested the top 10 best candidate moments for a trailer from the movie Morgan, which an IBM filmmaker then edited and arranged together.

Learn More: http://ibm.biz/BdrJx9

A corporate troubleshooter (Kate Mara) is sent to a remote, top-secret location, where she is to investigate and evaluate a terrifying accident. She learns the event was triggered by a seemingly innocent “human,” who presents a mystery of both infinite promise and incalculable danger.

In Theaters - September 2, 2016
RedSkysays...

The explanation afterwards typifies my skepticism of machine learning and the kind of magical thinking that makes people think that limitless tasks can be automated beyond set domains.

Of course, algorithms with enough data are going to be effective at determining scary, tender or action segments from movies. But just like how they admit, a human touch is required to then piece it together in a way that resonates on an emotional level.

Trailers ultimately are pretty formulaic so they may be automatable but there are bound to be a whole host of areas where either a deterministic result is not practical or the noise of the algorithm response will be high enough to render the prediction meaningless.

Also too bad the movie's getting panned by reviews, I was kind of excited about watching this.

CrushBugsays...

Very true. Take a look at trailers made in the 80s and compare them to now. Very different in how they were created.

RedSkysaid:

The explanation afterwards typifies my skepticism of machine learning and the kind of magical thinking that makes people think that limitless tasks can be automated beyond set domains.

Of course, algorithms with enough data are going to be effective at determining scary, tender or action segments from movies. But just like how they admit, a human touch is required to then piece it together in a way that resonates on an emotional level.

Trailers ultimately are pretty formulaic so they may be automatable but there are bound to be a whole host of areas where either a deterministic result is not practical or the noise of the algorithm response will be high enough to render the prediction meaningless.

Also too bad the movie's getting panned by reviews, I was kind of excited about watching this.

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