Google announced today it has acquired machine learning startup Moodstocks in an effort to bolster its work around smartphone image and item recognition. Terms of the deal were not disclosed. See how the cloud is disrupting traditional operating models for IT departments and entire organizations. Moodstocks began developing image recognition technology in 2012 and more recently shifted into object recognition technology. The Paris-based startup said on its website that its "dream has been to give eyes to machines by turning cameras into smart sensors able to make sense of their surroundings."

Open information extraction (open IE) refers to the extraction of structured relation triples from plain text, such that the schema for these relations does not need to be specified in advance. For example, Barack Obama was born in Hawaii would create a triple (Barack Obama; was born in; Hawaii), corresponding to the open domain relation "was born in". The system first splits each sentence into a set of entailed clauses. Each clause is then maximally shortened, producing a set of entailed shorter sentence fragments. These fragments are then segmented into OpenIE triples, and output by the system.

Google has purchased Moodstocks, a French startup that specializes in speedy object recognition from a smartphone, showing (again) the search giant's intense interest in AI. Unlike other products (including Google's own Goggles object recognition app) Moodstocks does most of the crunching on your smartphone, rather than on a server. While Google seemingly has some pretty good image-spotting tech already, like the canny visual categorization in Photos, it says it's just getting started. "There is still a long way to go [with machine learning], and that's where Moodstocks comes in," the company said in a blog post (translated). The deal seems to fall in to the "aqui-hire" category, as Moodstocks will cease its own recognition services, and its team of engineers will join Google at its R&D center in Paris. Google is rumored to be working on a feature that allows Android users to search directly from their photos (below), though the company didn't say if the acquisition is related.

Google announced today that it has acquired Paris-based Moodstocks, a startup that has developed machine learning technology to bolster the image recognition features on smartphones. "We continue to pursue our machine learning and research efforts," wrote Vincent Simonet, head of the research and development team for France Google, "and Moodstocks is the latest proof of our commitment to this area." Today, we're thrilled to announce that we've reached an agreement to join forces with Google in order to deploy our work at scale. We expect the acquisition to be completed in the next few weeks. Our focus will be to build great image recognition tools within Google, but rest assured that current paying Moodstocks customers will be able to use it until the end of their subscription. The terms of the deal were not disclosed.

San Francisco: Google announced a deal to buy Moodstocks, a French startup behind technology that helps smartphones recognise whatever they are aimed at. Moodstocks caught the US technology giant's eye for its work in computer vision and machine learning, as well for accomplishments in enabling smartphones or other mobile devices to recognise images and objects. Google is among Silicon Valley titans investing in ways to get computers to see and understand the world around them the way people do. Machine learning has been woven into an array of Google offerings, such as its free language translation and photo services. "There's a lot more to be done to improve machine vision," Google France tech site lead Vincent Simonet said in a blog post.

Google has acquired Moodstocks, a Paris-based startup that specialises in smartphone image recognition as part of its continued efforts to boost its own artificial intelligence (AI) research, development and capabilities. Announced in a blog post on 6 July, Vincent Simonet, head of Google's research and development (R&D) centre in Paris, says the tech giant's latest purchase is proof of its commitment to the promising sector. "Many Google services use machine learning to make them simpler and more useful in everyday life such as Google Translate, Smart Reply Inbox, or the Google app," Simonet wrote in French. "We have made great strides in terms of visual recognition: Now you can search in Google Pictures such as'party' or'beach' and the application will offer you good pictures without you needing to categorise them manually. But there is still much to do in this area. And this is where Moodstocks comes in."

It's a good time to be a machine learning startup. Two weeks after Twitter bought London-based Magic Pony, Google has purchased French firm Moodstocks. The acquisition was made for an unknown sum, and seems primarily a grab for talent. Moodstocks' engineers and researchers will move to Google's Paris R&D site, and the startup's primary commercial product -- an image recognition API for smartphones -- will be phased out. "Ever since we started Moodstocks, our dream has been to give eyes to machines by turning cameras into smart sensors able to make sense of their surroundings," said Moodstocks in a statement.

Someone at Google really likes sneakers: The company has just bought a French machine learning startup that taught a computer how to recognize 15,000 different types of them. Paris-based Moodstocks builds image and object recognition software using deep learning techniques, and offered an Android app and visual search API that could recognize certain kinds of object. By analyzing video from a smartphone camera, and correlating it with accelerometer readings to determine how the camera is moving around, the software is able to infer information about the three-dimensional shape of objects in the video, facilitating their recognition. In February 2015 the company demonstrated its ability to identify sneakers through its app. Three months later, after training the software using 15,000 photos of shoes from an online retailer's website, Moodstocks claimed to be able to shop online for all the sneakers on sale in a Macy's store. Google has been introducing elements of machine learning into its existing online services, including Google Translate and Inbox, a next-generation interface for Gmail.

Tech giant Google has added to its vast technology services stable by acquiring Paris-based startup Moodstocks, which has developed machine learning based image recognition technology for smartphones. The acquisition by Google will see it add the recognition technology of Moodstocks to its already large number of services it offers which use machine learning, such as Google Translate, Smart Reply in Inbox and the Goggle app. With many of its services already relying on machine learning technologies, Google's acquisition of Moodstocks will help with implementing visual recognition. The Moodstocks team of engineers and researchers, based in Paris, developed new algorithms for Visual pattern recognition and machine learning, as well as a technology for the recognition of images and objects via mobile devices. Head of the R&D Center of Google France, Vincent Simonet, wrote in a blog on July 7 to announce the deal, said that while great steps forward were taken by Google in terms of Visual recognition, there was still much to be done in this area, stating that the company expects that to be where Moodstocks comes into its own.

Google has announced that it had acquired a visual recognition machine learning technology start-up, Moodstocks for an undisclosed amount. Incorporated in 2009, the French start-up originally introduced on-device image recognition in 2012, which enables smartphones to automatically recognize the content their camera detects. With the recent acquisition, Google had made a substantial investment in the machine learning technologies since accurate object recognition is one of the difficult problems for machine learning. For the past 3 years, the small team of researchers and engineers based in Google has taken advantage of deep learning to extend the reach of their object recognition algorithms, licensing machine-readable executable object code including the launch of a software development kit for OEMs to enable them to embed the code into their products. The Moodstocks API, meanwhile, enable users to integrate visual search into their applications in addition to analyzing the images related to color, shape, and texture.