Are neural networks the next marketing creatives?

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If you take comfort in knowing that we’re a long way away from the day when computer systems recognize a beautiful photo, you might want to sit down.

A team from the Warwick Business School at the University of Warwick in England have trained a neural network to recognize beautiful landscapes. Researcher Chanuki Seresinhe told me this is the first time for such an accomplishment, which formed the basis for their academic paper, published by The Royal Society Open Science.

This means that machine learning trained computer systems might — someday soon — help marketers and advertisers pick shots for ads, brochures or presentations. Already, IBM’s Watson has begun down that road, such as his recent job picking shots for a horror movie trailer.

The research team utilized a site called Scenic or Not, which asked 1.5 million visitors to rate about 200,000 landscape photos of UK scenes on a scale of 1 to 10, with 1 representing the ugly side and 10 the beautiful. The team then trained an MIT-based neural network with 80 percent of the photos that had been rated by at least three visitors, employing the average rating. Here’s a selection of most scenic and least scenic scenes selected by humans:

[Read the full article on MarTech Today.]

About The Author

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.


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