Clarifai image recognition API can train algorithms to be able to search for photos

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Clarifai provides advanced image recognition systems for customers to detect near-duplicates and visual searches. Clarifai’s image recognition systems recognize various categories, objects, and tags in images, as well as find similar images. The company’s image recognition systems allow its users to find similar images in large uncategorized repositories

Clarifai gives developers tools for tagging metadata to photos and enable the company to algorithmically learn what kinds of objects are in those photos. With that data, developers are able to train algorithms to search for those objects in photos or video or input their own content to search for objects. The company raised $30 million in October last year in a round led by Menlo Ventures, with Union Square Ventures, Lux Capital and others participating, and has raised a total of $41.25 million in financing.

These are problems that larger companies like Pinterest and Google are working on, but for the time being those companies are keeping the tools in-house. Clarifai instead is trying to build a set of products that opens up the kinds of visual search tools those companies have to any startup or larger partner. Clarifai, too, is trying to be a neutral player — giving companies a set of tools they can use without feeling pressure that data is being shared with competitors or forcing companies to duct tape themselves to an experience powered by something like Google in order to have access to visual search.

From Tecrunch,

Clarifai, a New York-based startup that offers developers the ability to tag metadata to photos in such a way that the company algorithmically learns what kinds of objects are in photos. With that, Clarifai developers can train algorithms to be able to search for those objects, or input their own photos in order to find similar objects. The company said today that it has raised $30 million. The round was led by Menlo Ventures, with Union Square Ventures, Lux Capital and others participating. In total. Clarifai has $41.25 million in financing.

While Google, Pinterest and other companies build visual search technology, Clarifai is looking to do the same but focus on giving third-party applications and developers access to that kind of technology. Zeiler says Clarifai only needs a few images’ worth of data to start building out a model for determining what kinds of objects are in an image. Developers can teach algorithms with their own kinds of tagging to build new classes of “objects” within those images and videos.

“Our number one entry point into our customer is a developer,” Zeiler said. “Think of Twilio, they were very much developer first and API platform company for communications. We are the same thing for AI, we like to going to meet-ups and hosting events at our office, going to hackathons. We want to get every developer talking about and using Clarifai, building their next app on Clarifai, so one day someone is building the next Snapchat in their garage and we want to grow wit their growth.”

Clarifai makes its tools available in the form of APIs that start off as easy-to-implement lines of code — geared even toward first-time developers or programmers, in the same fashion that Twilio does — to more in-depth tools that allow greater levels of customization. If it were able to tap into the same developer zeitgeist that Twilio has, there may be a similar path to a strong business in the same way Twilio built.

 For now, Clarifai focuses on and continues to work on image and video search capabilities. But the ability to build an understanding of data structures could theoretically extend to other mediums. Zeiler wouldn’t say what other kinds of tools that Clarifai is working on, but it’s pretty easy to guess where it could extend, to things like audio and text.

Clarifai’s goal is to essentially give the same tools that the Googles and Pinterests have, and point them downstream to developers and other companies like retailers. For example, Walmart might want to use something like this, or Macy’s, but in working with a company like Google those retailers could end up giving retail data to competitors. They then may end up giving those companies a way to build something competitive.