Facebook Refocusing on Web Access Over App Access
Facebook today announced the forthcoming re-launch of m.facebook.com, which will represent a new direction for the company's mobile efforts. The wholly re-realized web site is said to be accessible from a much wider range of handsets and mobile browsers, and offers a simpler tool set to users. Facebook says that moving forward, it will focus more on how users access its services from mobile web browsers rather than dedicated mobile applications. "We are internalizing our own strategies around HTML5 to prove out that this emphasis on the mobile Web can actually work," said Erick Tseng, Facebook's head of mobile. "Yes, there is going to be a day when the majority of folks have something that looks more like an Android, but I don't believe that's going to happen in the next year, probably not the next two years." The revised web site is going to be rolled out to all of Facebook's 250 million mobile users over the coming weeks.
Facebook Testing Video Services
Facebook today said it is looking to increase the number of ways people can consume video on its platform. The company is testing a revised version of its suggested videos function on the iPhone, which purports to ease the discovery process for related strings of videos.
Facebook Aims to Simplify Connecting with Others Via Messenger
Facebook is adding several tools to its Messenger service with the the goal of making it easier to begin conversations with others. To start, the company is rolling out Messenger Codes, which allows people to scan one another's code and begin chatting.
Facebook Makes It Easier to Report Abusive Messenger Conversations
Facebook has rolled out a change to Messenger that simplifies the process of reporting abusive conversations. Before today, the process involved using Facebook or Messenger on the web.
Facebook Relying On AI for Its Own Artistic Filters
Facebook today announced Caffe2go, an artificial intelligence client that it is adding to its mobile applications for Android and iOS. Caffe2go is able to condense computations by a factor of 100, allowing it to efficiently perform neural network and machine learning tasks on mobile devices.
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