UPDATED 11:13 EDT / JULY 06 2016

NEWS

Google acquires image recognition startup Moodstocks to bolster machine learning efforts

A month after launching a machine learning research center in Zurich, Google is expanding its European artificial intelligence operations once again with the acquisition of Moodstocks SAS. The Paris-based startup has developed an image recognition tool specifically optimized to process media captured via mobile devices.

The software started its life two years and a half ago as an offline scanner and was later turned into an iOS application for finding products from physical catalogs online. Eventually, Moodstocks pivoted to the developer market with a cloud-based implementation that allowed third party app makers to incorporate its technology into their services. The startup then suddenly found itself competing with Google in December 2015 after the search giant launched a rivaling image recognition offering called Cloud Vision API.

By acquiring Moodstocks, the Alphabet Inc. subsidiary is removing a competitor and strengthening its market position in the process. Google didn’t specify what it’s planning to do with the French outfit after the transaction completes, but the available information allows for some educated guesses. For starters, it’s safe to assume that the startup’s engineers will contribute to Cloud Vision API given their related work experience. And a post that was published on the Google France Blog today indicates that the team can also expect to become involved with some of the company’s consumer-focused image recognition projects.

The French-language entry revealed that Moodstocks will be integrated into the company’s Paris R&D facility, which develops features for Google Photos, YouTube and several other key Alphabet services. Regardless of exactly what the startup’s team will end up doing, however, the acquisition marks a major milestone for everyone involved. And seeing how essential machine learning is to the search giant’s operations, many more such deals can be expected to follow in the future. The company is also investing in internal projects like its recently revealed effort to develop a homegrown chip optimized for running artificial intelligence algorithms.

Image via Pixabay

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