Brands see visual intelligence as key part of AI strategy
Ever since neural networks began their renewed renaissance in 2012, computer vision has been a ripe field of study and innovation for AI researchers and a fruitful area of applied AI for enterprises. Deep learning enables incredible feats of machine vision, such as classifying image subjects at human parity and dynamically generating completely new imagery.
Brands have quickly recognized this technology as a commercial asset. Clarifai, a leading computer vision company with a popular visual intelligence API, was recently used to analyze hundreds of photos of fans during baseball games to identify when they have caught a ball. The insight was then overlaid over stadium seating maps to show the highest probability seats for fans hoping to bring home a souvenir catch. From a business perspective, such data can drive more effective tiered pricing.
The same technology was equally adept playing Hearthstone, a popular card game produced by Blizzard Entertainment. By watching many rounds of play, the AI learned the cards and strategies of the game and could offer play-by-play commentary. During a hackathon, developers used Clarifai’s visual APIs for yet another purpose: Tinder swiping. The algorithms learned the preferences of one of the developers and took over the laborious act of swiping for him.
“The common theme here is customization,” explains Clarifai founder and CEO Matthew Zeiler. “You can teach the platform whatever you want to recognize, and that applies all the way up to the biggest companies.” Indeed, many large corporations in search of faster methods of photo searching and sorting are taking notice. Digital media juggernaut Buzzfeed adopted visual intelligence in order to assist editors in finding relevant photos for articles. Another one of Clarifai’s customers, a proponent of “natural beauty”, used visual intelligence to identify examples from social media of fashionable women not wearing makeup who embodied their brand message.
Zeiler and his team at Clarifai are not the only ones who are banking on the potential of visual intelligence. Major players like Google, IBM, Salesforce, Microsoft as well as smaller entities such as GumGum and Ditto all offer computer vision solutions. The Google Cloud Vision API, for example, enables user to easily organize stored photos. Amazon’s version, Rekognition, is marketed towards developers who want to add facial recognition security to apps or record the demographics of their viewers. GumGum’s offer is directed at companies interested in using social media posts to monitor brand representation online or calculate earned media from videos of sporting events.
