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AMP pages from Google Search now load twice as fast

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At its I/O 2017 developers conference today, Google announced that its fast-loading Accelerated Mobile Pages (AMP) accessed from Google Search now load twice as fast.

Google first unveiled the open source AMP Project in October 2015. Since then, the company has been working hard to add new features and push AMP across not just its own products, but the larger web.

Google Search only launched AMP support out of developer preview in September 2016. 8 months later, and Google has already cut the time it takes to render content in half.

The company explains that this is possible due to several key optimizations made to the Google AMP Cache. These include server-side rendering of AMP components and reducing bandwidth usage from images by 50 percent without affecting the perceived quality.

Also helpful was using the Brotli compression algorithm, which resulted in a reduced document size by an additional 10 percent in supported browsers (even Edge uses it). Google open-sourced Brotli in September 2015 and considers it a successor to the Zopfli algorithm.

Speed aside, Google also shared that new platforms and websites have joined the AMP ecosystem. There are already over 2 billion AMP pages and 900,000 domains with AMP on the web. Even within the search sphere, Google isn’t the only one supporting AMP: Bing, Baidu, Sogou, and Yahoo Japan are also all on board.

China’s largest social network Tencent Qzone and the country’s third largest, Weibo are adopting AMP pages. Tumblr says it is publishing 340 million blogs across 500,000 domains in AMP starting this week. Twitter is linking to AMP pages from their new mobile web app, and will be launching AMP support in their Android and iOS apps. eBay plans to use AMP across all its product pages and Zalando is implementing AMP for its 250,000 product pages.

In short, Google has managed to keep AMP momentum going. Next week, the company will release the AMP Project roadmap for the upcoming quarter.

Read Google IO Stories Here

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