The Technology Review published an article on Jetpac, a new travel app that uses image identifying technology to rate and recommend restaurants and other travel destinations. Whereas most recommendation apps rely on user reviews, Jetpac applies image analysis algorithms based on deep learning to crowdsourced images–in this case photos on Instagram–to make determinations about a venue.
How does this work? When it comes to restaurants, the machine algorithm analyzes Instagram photos and tries to identify specific objects. For example, if it picks up a prevalence of martini glasses or wine glasses, the program makes the assumption that the restaurant is higher class. if it finds more plastic cups or beer bottles, it assumes a lower-end establishment. The program can also determine whether the restaurant is pet friendly by counting the number of pets at outdoor tables in photos.
To get a sense for how well people like the restaurant, or whether it’s a fun place to hang out, the program looks at how many people are smiling or laughing in the photos. By observing what people are wearing, the app can also try to make judgments about the general type of clientele that frequent the place (apparently chunky glasses are indicative of hipster types).
Can intelligent assistants leverage this kind of machine learning to help pick out the best places to recommend? Right now, most assistants are limited to Yelp ratings to rank the restaurant results they return. But what if a super powerful intelligent assistant could scan hundreds of Instagram photos when you ask about the best local coffee shop? And what if it knew you well enough to know you’ll probably like the place with outdoor tables and flower boxes? It could use that knowledge to tailor its recommendations just for you.
Though this type of photo analysis technology is in the early stages, apps like Jetpac give a hint of the future possibilities. At some point, they’re sure to be integrated into the smart assistants that serve us.