At any given moment, many thousands of new videos are being posted to sites like YouTube, TikTok, and Instagram. An increasing number of those videos are being recorded and streamed live. But tech and media companies still struggle to understand what’s going in all that content.
Now MIT alumnus-founded Netra is using artificial intelligence to improve video analysis at scale. The company’s system can identify activities, objects, emotions, locations, and more to organize and provide context to videos in new ways.
Companies are using Netra’s solution to group similar content into highlight reels or news segments, flag nudity and violence, and improve ad placement. In advertising, Netra is helping ensure videos are paired with relevant ads so brands can move away from tracking individual people, which has led to privacy concerns.
“The industry as a whole is pivoting toward content-based advertising, or what they call affinity advertising, and away from cookie-based, pixel-based tracking, which was always sort of creepy,” Netra co-founder and CTO Shashi Kant SM ’06 says.
Netra also believes it is improving the searchability of video content. Once videos are processed by Netra’s system, users can start a search with a keyword. From there, they can click on results to see similar content and find increasingly specific events.
For instance, Netra’s system can process a baseball season’s worth of video and help users find all the singles. By clicking on certain plays to see more like it, they can also find all the singles that were almost outs and led the fans to boo angrily.
“Video is by far the biggest information resource today,” Kant says. “It dwarfs text by orders of magnitude in terms of information richness and size, yet no one’s even touched it with search. It’s the whitest of white space.”
Pursuing a vision
Internet pioneer and MIT professor Sir Tim Berners-Lee has long worked to improve machines’ ability to make sense of data
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