#Pinterest active users software#

#Pinterest active users software#

The software then finds pins that are visually similar to whatever is in the rectangle. You just click or tap the magnifying glass in the top corner of a pin, and it will let you adjust the size and location of a rectangle superimposed over the image. The way Pinterest uses this technology in visual search is certainly compelling. Apple, Facebook, Google, Microsoft, and other companies are using this approach more and more, now that more data and economical computing power is available than ever before. The visual search system depends on a hot type of artificial intelligence called deep learning, which involves training artificial neural networks on lots of data - such as, you guessed it, photos in pins! - and then getting the neural networks to make inferences about new data. Today happens to be the one-year anniversary of the launch of the fourth of those. Machine learning is at work across all four key parts of Pinterest: home feed, search, related pins, and visual search. “With a lot of the focus that we’ve had going international, you can imagine why visual signals would be really valuable there,” Mohammad Shahangian, Pinterest’s lead data science engineer, told VentureBeat in an interview at Pinterest’s San Francisco headquarters. In the past two years, Pinterest has taken steps to do smarter things with all the images, and it looks like that’s paying off. Pinterest stands out thanks to its large, image-heavy data collection that users themselves organize. Of course, other up-and-coming companies, like Airbnb and Spotify, are also personalizing and localizing their content to accumulate more users and keep them around. Join today’s leading executives at the Low-Code/No-Code Summit virtually on November 9.