Neon Labs Inc. software predicts your pick to click-Center for Innovation and Entrepreneurship - Carnegie Mellon University

Tuesday, October 15, 2013

Neon Labs Inc. software predicts your pick to click

Editors know that images help draw consumers to news and social media websites.

Sophie Lebrecht, CEO and co-founder of Neon Labs Inc., a Carnegie Mellon University spinoff company, says using powerful images as thumbnails — the small photos that link to video or text — improves the frequency of clicks on them and leads to advertising revenue.

Neon developed technology that automatically selects the best frame in a video to become a thumbnail. That's important, because online video viewership is booming.

Market researcher GfK said last month that more than half of those ages 13 to 54, the core TV viewing population in the United States, watches streaming video in a given week. GfK said 51 percent watch TV programs or movies using streaming video, up from 37 percent three years ago. Tablets and smartphones have aided in that growth.

“Images are a great way to draw people into the story, whether it's a video or other content, and thumbnails will change the number of people that click to view that content — so the image you use for a thumbnail is incredibly powerful,” Lebrecht said.

Neon Labs is testing its software and intends to release a final version for sale this fall, said Lebrecht, who moved last year to Carnegie Mellon's Silicon Valley campus in Moffett Field, Calif. Co-founder and senior technical adviser Michael Tarr, a professor of cognitive neuroscience and co-director of the Center for the Neural Basis of Cognition, works in Pittsburgh. The center is a joint program between Carnegie Mellon and the University of Pittsburgh.

To determine what people are likely to watch, researchers in Pittsburgh and at Brown University in Providence, R.I., studied how people process information — “how people see the world ... how the brain generates a choice, that was our initial research question,” Lebrecht said. “Then we asked, can we build a computer model of the human brain that predicts how people will respond to..Read more»

By: John D. Oravecz