Google+ Uses Machine Learning to Display High Resolution Images at a Third of the Bandwidth

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By Sanket Vijayasarathy | Updated: 12 January 2017 18:23 IST
Highlights
  • The RAISR technique was first shown in November 2016
  • RAISR uses machine learning to retain original shapes and details
  • Google has been applying RAISR to more than 1 billion images per week

Artificial intelligence and machine learning to a significant leap in 2016 with Google launching Assistant for its Pixel and Home products. The company in November also showed off a machine learning technique called RAISR that could be used to enhance low-res and blurry images. 2017 will be no less for Google, which looks to improve the technology further. The RAISR technique is now being used in Google+ which will display high resolution photos using only a third of the bandwidth.

Google in a blog post said that its social networking platform, Google+, will now use the new Rapid and Accurate Image Super-Resolution (RAISR) software which, through machine learning, will allow users to see large high-resolution photos while using 75 percent less bandwidth. This will significantly help those who find themselves with spotty Internet connection and high data costs.

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Essentially, RAISR uses machine learning to retain original shapes and details more accurately so as to provide clearer images. As an example, a 100KB 1000x1500 pixels image is replaced with a 25KB file having retained the original resolution through RAISR.

Google said that it has been applying RAISR "to more than 1 billion images per week, reducing these (Android) users’ total bandwidth by about a third." The company plans to roll out the the technology more broadly in the coming weeks so users.

 

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