The past seven days has seen Google bugged with security flaws and threats to Android and its Drive cloud storage.
But the firm did have a couple of positive moments with the news that San Antonio will receive Google Fibre, and that a partnership with MIT has created an algorithm that removes obstacles from pictures.
Google and Samsung promise monthly Android security fixes after Stagefright scare
Google joined Samsung in promising to fast track monthly Android security updates following Stagefright, a major security vulnerability that left up to 95 percent of all Android devices at risk.
Google revealed plans to start rolling out monthly security updates to its Nexus product range to address concerns raised by the malware. The fixes will be released to the public at the same time via the Android Open Source Project.
Major cloud services such as Google Drive and Dropbox at risk from 'man-in-the-cloud' attacks
Google Drive, along with Box, Dropbox and Microsoft OneDrive, are at risk of ‘man-in-the-cloud' cyber attacks, according to a research paper by Imperva.
The firm said that cloud-based businesses are vulnerable to exploitation by hackers, and even claimed that data can be accessed without needing usernames or passwords.
Google plans Fibre fitting in San Antonio
On the other side of the Atlantic, Google revealed that it will roll out its high-speed Google Fibre internet service to San Antonio.
Google's blog said that the Texas city is the sixth area in the US to be slated for Google Fibre access, and will be the largest to receive Google's high-speed broadband so far.
Google and MIT work on algorithm to remove obstructions from pictures
Popular Science reported that Google and MIT have created an algorithm to remove reflections and obstructions from pictures taken by smartphone cameras.
Picture editing can fabricate this process, but the algorithm allows the obstruction to be removed without doctoring the image directly. It works by taking an input of five images from a short video where the camera is slightly panning.
The algorithm then detects the obstruction in the foreground, and tracks it throughout the five frames. When the foreground and background are separated, the algorithm fills in what would be missing space with pixels from the other frames, meaning that obstructions are edited out without marring the realism of the image.
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